diff --git a/.github/workflows/bench.yml b/.github/workflows/bench.yml new file mode 100644 index 0000000000000..7587966320c81 --- /dev/null +++ b/.github/workflows/bench.yml @@ -0,0 +1,300 @@ +# Benchmark +name: Benchmark + +on: + workflow_dispatch: + inputs: + gpu-series: + description: 'Azure GPU series to run with' + required: true + type: choice + options: + - Standard_NC4as_T4_v3 + - Standard_NC24ads_A100_v4 + - Standard_NC80adis_H100_v5 + sha: + description: 'Commit SHA1 to build' + required: false + type: string + duration: + description: 'Duration of the bench' + type: string + default: 10m + + push: + branches: + - master + paths: ['llama.cpp', 'ggml.c', 'ggml-backend.c', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp'] + pull_request_target: + types: [opened, synchronize, reopened] + paths: ['llama.cpp', 'ggml.c', 'ggml-backend.c', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp'] + schedule: + - cron: '04 2 * * *' + +concurrency: + group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}-${{ github.event.inputs.sha }} + cancel-in-progress: true + +jobs: + bench-server-baseline: + runs-on: Standard_NC4as_T4_v3 + env: + RUNNER_LABEL: Standard_NC4as_T4_v3 # FIXME Do not find a way to not duplicate it + N_USERS: 8 + DURATION: 10m + + strategy: + matrix: + model: [phi-2] + ftype: [q4_0, q8_0, f16] + include: + - model: phi-2 + ftype: q4_0 + pr_comment_enabled: "true" + + if: ${{ github.event.inputs.gpu-series == 'Standard_NC4as_T4_v3' || github.event.schedule || github.event.pull_request || github.head_ref == 'master' || github.ref_name == 'master' || github.event.push.ref == 'refs/heads/master' }} + steps: + - name: Clone + id: checkout + uses: actions/checkout@v4 + with: + fetch-depth: 0 + ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }} + + - name: Install python env + id: pipenv + run: | + cd examples/server/bench + python3 -m venv venv + source venv/bin/activate + pip install -r requirements.txt + + - name: Prometheus + id: install_prometheus + run: | + wget --quiet https://github.com/prometheus/prometheus/releases/download/v2.51.0/prometheus-2.51.0.linux-amd64.tar.gz + tar xzf prometheus*.tar.gz --strip-components=1 + ./prometheus --config.file=examples/server/bench/prometheus.yml & + while ! nc -z localhost 9090; do + sleep 0.1 + done + + - name: Set up Go + uses: actions/setup-go@v5 + with: + go-version: '1.21' + + - name: Install k6 and xk6-sse + id: k6_installation + run: | + cd examples/server/bench + go install go.k6.io/xk6/cmd/xk6@latest + xk6 build master \ + --with github.com/phymbert/xk6-sse + + - name: Build + id: cmake_build + run: | + set -eux + mkdir build + cd build + cmake .. \ + -DLLAMA_NATIVE=OFF \ + -DLLAMA_BUILD_SERVER=ON \ + -DLLAMA_CURL=ON \ + -DLLAMA_CUBLAS=ON \ + -DCUDAToolkit_ROOT=/usr/local/cuda \ + -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \ + -DCMAKE_CUDA_ARCHITECTURES=75 \ + -DLLAMA_FATAL_WARNINGS=OFF \ + -DLLAMA_ALL_WARNINGS=OFF \ + -DCMAKE_BUILD_TYPE=Release; + cmake --build . --config Release -j $(nproc) --target server + + - name: Download the dataset + id: download_dataset + run: | + cd examples/server/bench + wget --quiet https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json + + - name: Server bench + id: server_bench + run: | + set -eux + + cd examples/server/bench + source venv/bin/activate + python bench.py \ + --runner-label ${{ env.RUNNER_LABEL }} \ + --name ${{ github.job }} \ + --branch ${{ github.head_ref || github.ref_name }} \ + --commit ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha }} \ + --scenario script.js \ + --duration ${{ github.event.inputs.duration || env.DURATION }} \ + --hf-repo ggml-org/models \ + --hf-file ${{ matrix.model }}/ggml-model-${{ matrix.ftype }}.gguf \ + --model-path-prefix /models \ + --parallel ${{ env.N_USERS }} \ + -ngl 33 \ + --batch-size 2048 \ + --ubatch-size 256 \ + --ctx-size 16384 \ + --n-prompts 1000 \ + --max-prompt-tokens 1024 \ + --max-tokens 2048 + + cat results.github.env >> $GITHUB_ENV + + # Remove dataset as we do not want it in the artefact + rm ShareGPT_V3_unfiltered_cleaned_split.json + + - uses: actions/upload-artifact@v4 + with: + name: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }} + compression-level: 9 + path: | + examples/server/bench/*.jpg + examples/server/bench/*.json + examples/server/bench/*.log + + - name: Commit status + uses: Sibz/github-status-action@v1 + with: + authToken: ${{secrets.GITHUB_TOKEN}} + sha: ${{ inputs.sha || github.event.pull_request.head.sha || github.sha }} + context: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }} + description: | + ${{ env.BENCH_RESULTS }} + state: 'success' + + - name: Upload benchmark images + uses: devicons/public-upload-to-imgur@v2.2.2 + continue-on-error: true # Important as it looks unstable: 503 + id: imgur_step + with: + client_id: ${{secrets.IMGUR_CLIENT_ID}} + path: | + examples/server/bench/prompt_tokens_seconds.jpg + examples/server/bench/predicted_tokens_seconds.jpg + examples/server/bench/kv_cache_usage_ratio.jpg + examples/server/bench/requests_processing.jpg + + - name: Extract mermaid + id: set_mermaid + run: | + set -eux + + cd examples/server/bench + PROMPT_TOKENS_SECONDS=$(cat prompt_tokens_seconds.mermaid) + echo "PROMPT_TOKENS_SECONDS<> $GITHUB_ENV + echo "$PROMPT_TOKENS_SECONDS" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + + PREDICTED_TOKENS_SECONDS=$(cat predicted_tokens_seconds.mermaid) + echo "PREDICTED_TOKENS_SECONDS<> $GITHUB_ENV + echo "$PREDICTED_TOKENS_SECONDS" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + + KV_CACHE_USAGE_RATIO=$(cat kv_cache_usage_ratio.mermaid) + echo "KV_CACHE_USAGE_RATIO<> $GITHUB_ENV + echo "$KV_CACHE_USAGE_RATIO" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + + REQUESTS_PROCESSING=$(cat requests_processing.mermaid) + echo "REQUESTS_PROCESSING<> $GITHUB_ENV + echo "$REQUESTS_PROCESSING" >> $GITHUB_ENV + echo "EOF" >> $GITHUB_ENV + + - name: Extract image url + id: extract_image_url + continue-on-error: true + run: | + set -eux + + echo "IMAGE_O=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[0] }}" >> $GITHUB_ENV + echo "IMAGE_1=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[1] }}" >> $GITHUB_ENV + echo "IMAGE_2=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[2] }}" >> $GITHUB_ENV + echo "IMAGE_3=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[3] }}" >> $GITHUB_ENV + + - name: Comment PR + uses: mshick/add-pr-comment@v2 + id: comment_pr + if: ${{ github.event.pull_request != '' && matrix.pr_comment_enabled == 'true' }} + with: + message-id: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }} + message: | +

+ + 📈 **llama.cpp server** for _${{ github.job }}_ on _${{ env.RUNNER_LABEL }}_ for `${{ matrix.model }}`-`${{ matrix.ftype }}`: **${{ env.BENCH_ITERATIONS}} iterations** 🚀 + +

+ +
+ + Expand details for performance related PR only + + - Concurrent users: ${{ env.N_USERS }}, duration: ${{ github.event.inputs.duration || env.DURATION }} + - HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(95)=${{ env.HTTP_REQ_DURATION_P_95_ }}ms fails=${{ env.HTTP_REQ_FAILED_PASSES }}, finish reason: stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }} truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }} + - Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_P_95_ }}tk/s + - Token generation (tg): avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_TOKENS_SECOND_P_95_ }}tk/s + - ${{ env.BENCH_GRAPH_XLABEL }} + + +

+ + prompt_tokens_seconds + +

+ + More + + ```mermaid + ${{ env.PROMPT_TOKENS_SECONDS }} + ``` + +
+ + predicted_tokens_seconds + +
+ More + + ```mermaid + ${{ env.PREDICTED_TOKENS_SECONDS }} + ``` + +
+ +

+ +
+ + Details + +

+ + kv_cache_usage_ratio + +

+ More + + ```mermaid + ${{ env.KV_CACHE_USAGE_RATIO }} + ``` + +
+ + requests_processing + +
+ More + + ```mermaid + ${{ env.REQUESTS_PROCESSING }} + ``` + +
+ +

+
+
diff --git a/.github/workflows/server.yml b/.github/workflows/server.yml deleted file mode 100644 index e385e03f3a245..0000000000000 --- a/.github/workflows/server.yml +++ /dev/null @@ -1,136 +0,0 @@ -# Server build and tests -name: Server - -on: - workflow_dispatch: # allows manual triggering - inputs: - slow_tests: - description: 'Run slow tests' - required: true - type: boolean - push: - branches: - - master - paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/tests/**.*'] - pull_request: - types: [opened, synchronize, reopened] - paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/tests/**.*'] - schedule: - - cron: '0 0 * * *' - -jobs: - server: - runs-on: ubuntu-latest - - strategy: - matrix: - sanitizer: [ADDRESS, THREAD, UNDEFINED] - build_type: [Debug, Release] - include: - - build_type: Release - sanitizer: "" - exclude: - - build_type: Release - sanitizer: ADDRESS - - build_type: Release - sanitizer: THREAD - - build_type: Release - sanitizer: UNDEFINED - - container: - image: ubuntu:latest - ports: - - 8888 - options: --cpus 4 - - steps: - - name: Clone - id: checkout - uses: actions/checkout@v3 - with: - fetch-depth: 0 - - - name: Dependencies - id: depends - run: | - apt-get update - apt-get -y install \ - build-essential \ - git \ - cmake \ - python3-pip \ - wget \ - language-pack-en - - - name: Build - id: cmake_build - run: | - mkdir build - cd build - cmake .. \ - -DLLAMA_NATIVE=OFF \ - -DLLAMA_BUILD_SERVER=ON \ - -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ - -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ; - cmake --build . --config ${{ matrix.build_type }} -j $(nproc) --target server - - - name: Tests dependencies - id: test_dependencies - run: | - pip install -r examples/server/tests/requirements.txt - - - name: Tests - id: server_integration_tests - run: | - cd examples/server/tests - PORT=8888 ./tests.sh - - - name: Slow tests - id: server_integration_tests_slow - if: ${{ github.event.schedule != '' && matrix.build_type == 'Release' || github.event.inputs.slow_tests == 'true' }} - run: | - cd examples/server/tests - PORT=8888 ./tests.sh --stop --no-skipped --no-capture --tags slow - - - server-windows: - runs-on: windows-latest - - steps: - - name: Clone - id: checkout - uses: actions/checkout@v3 - with: - fetch-depth: 0 - - - name: Build - id: cmake_build - run: | - mkdir build - cd build - cmake .. -DLLAMA_BUILD_SERVER=ON -DCMAKE_BUILD_TYPE=Release ; - cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server - - - name: Python setup - id: setup_python - uses: actions/setup-python@v5 - with: - python-version: '3.11' - - - name: Tests dependencies - id: test_dependencies - run: | - pip install -r examples/server/tests/requirements.txt - - - name: Tests - id: server_integration_tests - run: | - cd examples/server/tests - behave.exe --summary --stop --no-capture --exclude 'issues|wrong_usages|passkey' --tags llama.cpp - - - name: Slow tests - id: server_integration_tests_slow - if: ${{ github.event.schedule != '' || github.event.inputs.slow_tests == 'true' }} - run: | - cd examples/server/tests - behave.exe --stop --no-skipped --no-capture --tags slow diff --git a/.gitignore b/.gitignore index 1a45e7c082058..c5b0ba4585177 100644 --- a/.gitignore +++ b/.gitignore @@ -13,6 +13,8 @@ .vs/ .vscode/ +ggml-metal-embed.metal + lcov-report/ gcovr-report/ diff --git a/AUTHORS b/AUTHORS new file mode 100644 index 0000000000000..b029f13da3b56 --- /dev/null +++ b/AUTHORS @@ -0,0 +1,655 @@ +# date: Tue Apr 9 09:17:14 EEST 2024 +# this file is auto-generated by scripts/gen-authors.sh + +0cc4m +0xspringtime <110655352+0xspringtime@users.noreply.github.com> +2f38b454 +3ooabkhxtn <31479382+3ooabkhxtn@users.noreply.github.com> +44670 <44670@users.noreply.github.com> +AN Long +AT +Aarni Koskela +Aaron Miller +Aaryaman Vasishta +Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com> +Abhishek Gopinath K <31348521+overtunned@users.noreply.github.com> +Adithya Balaji +AdithyanI +Adrian +Adrian Hesketh +AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com> +Aisuko +Alberto <57916483+albbus-stack@users.noreply.github.com> +Alex +Alex Azarov +Alex Azarov +Alex Klinkhamer +Alex Klinkhamer +Alex Nguyen +Alex Petenchea +Alex Renda +Alex von Gluck IV +Alexey Parfenov +Ali Chraghi <63465728+alichraghi@users.noreply.github.com> +Ali Nehzat +Ali Tariq +Alon +AlpinDale <52078762+AlpinDale@users.noreply.github.com> +AmirAli Mirian <37371367+amiralimi@users.noreply.github.com> +Ananta Bastola +Anas Ahouzi <112881240+aahouzi@users.noreply.github.com> +András Salamon +Andrei +Andrew Canis +Andrew Duffy +Andrew Godfrey +Arik Poznanski +Artem +Artyom Lebedev +Asbjørn Olling +Ásgeir Bjarni Ingvarsson +Ashok Gelal <401055+ashokgelal@users.noreply.github.com> +Ashraful Islam +Atsushi Tatsuma +Austin <77757836+teleprint-me@users.noreply.github.com> +AustinMroz +BADR +Bach Le +Bailey Chittle <39804642+bachittle@users.noreply.github.com> +BarfingLemurs <128182951+BarfingLemurs@users.noreply.github.com> +Behnam M <58621210+ibehnam@users.noreply.github.com> +Ben Garney +Ben Siraphob +Ben Williams +Benjamin Lecaillon <84293038+blecaillon@users.noreply.github.com> +Bernat Vadell +Bodo Graumann +Bono Lv +Borislav Stanimirov +Branden Butler +Brian +Bruce MacDonald +CJ Pais +CRD716 +Cameron +Cameron Kaiser +Casey Primozic +Casey Primozic +CausalLM <148736309+CausalLM@users.noreply.github.com> +Cebtenzzre +Chad Brewbaker +Cheng Shao +Chris Kuehl +Christian Demsar +Christian Demsar +Christian Falch <875252+chrfalch@users.noreply.github.com> +Christian Kögler +Clark Saben <76020733+csaben@users.noreply.github.com> +Clint Herron +Cuong Trinh Manh +DAN™ +Damian Stewart +Dane Madsen +DaniAndTheWeb <57776841+DaniAndTheWeb@users.noreply.github.com> +Daniel Bevenius +Daniel Drake +Daniel Hiltgen +Daniel Illescas Romero +DannyDaemonic +Dat Quoc Nguyen <2412555+datquocnguyen@users.noreply.github.com> +Dave Della Costa +David Friehs +David Kennedy +David Pflug +David Renshaw +David Sommers <12738+databyte@users.noreply.github.com> +David Yang +Dawid Wysocki <62249621+TortillaZHawaii@users.noreply.github.com> +Dean +Deins +Didzis Gosko +Don Mahurin +DooWoong Lee (David) +Doomsdayrs <38189170+Doomsdayrs@users.noreply.github.com> +Douglas Hanley +Dr. Tom Murphy VII Ph.D <499244+tom7@users.noreply.github.com> +Ebey Abraham +Ed Lee +Ed Lepedus +Edward Taylor +Elbios <141279586+Elbios@users.noreply.github.com> +Engininja2 <139037756+Engininja2@users.noreply.github.com> +Equim +Eric Sommerlade +Eric Zhang <34133756+EZForever@users.noreply.github.com> +Erik Garrison +Erik Scholz +Ettore Di Giacinto +Evan Jones +Evan Miller +Eve <139727413+netrunnereve@users.noreply.github.com> +Evgeny Kurnevsky +Ewout ter Hoeven +ExtReMLapin <3909752+ExtReMLapin@users.noreply.github.com> +FK +Fabian +Fabio R. 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+sjinzh +slaren <2141330+slaren@users.noreply.github.com> +slaren +snadampal <87143774+snadampal@users.noreply.github.com> +staviq +stduhpf +swittk +takov751 <40316768+takov751@users.noreply.github.com> +tarcey +texmex76 <40733439+texmex76@users.noreply.github.com> +thement <40525767+thement@users.noreply.github.com> +tjohnman +tslmy +ubik2 +uint256_t +uint256_t +unbounded +valiray <133289098+valiray@users.noreply.github.com> +vodkaslime <646329483@qq.com> +vvhg1 <94630311+vvhg1@users.noreply.github.com> +vxiiduu <73044267+vxiiduu@users.noreply.github.com> +wbpxre150 <100937007+wbpxre150@users.noreply.github.com> +whoreson <139810751+whoreson@users.noreply.github.com> +wonjun Jang +wzy <32936898+Freed-Wu@users.noreply.github.com> +xaedes +xaedes +xloem <0xloem@gmail.com> +yangli2 +yuiseki +zakkor +zhouwg <6889919+zhouwg@users.noreply.github.com> +zrm +源文雨 <41315874+fumiama@users.noreply.github.com> +Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com> diff --git a/CMakeLists.txt b/CMakeLists.txt index abb2d5bbacb26..a40ef8db8c567 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -65,7 +65,8 @@ find_package(Threads REQUIRED) add_compile_definitions(LOG_DISABLE_LOGS) -set(GGML_SOURCES_CUDA ggml-cuda.cu ggml-cuda.h) +file(GLOB GGML_SOURCES_CUDA "ggml-cuda/*.cu") +list(APPEND GGML_SOURCES_CUDA "ggml-cuda.cu") set(GGML_V3_CUDA_SOURCES otherarch/ggml_v3-cuda.cu otherarch/ggml_v3-cuda.h) set(GGML_V2_CUDA_SOURCES otherarch/ggml_v2-cuda.cu otherarch/ggml_v2-cuda.h) set(GGML_V2_LEGACY_CUDA_SOURCES otherarch/ggml_v2-cuda-legacy.cu otherarch/ggml_v2-cuda-legacy.h) @@ -79,7 +80,7 @@ if (LLAMA_CUBLAS) enable_language(CUDA) - add_compile_definitions(GGML_USE_CUBLAS) + add_compile_definitions(GGML_USE_CUDA) add_compile_definitions(SD_USE_CUBLAS) add_compile_definitions(GGML_CUDA_MMQ_Y=${LLAMA_CUDA_MMQ_Y}) @@ -155,7 +156,9 @@ if (LLAMA_HIPBLAS) if (${hipblas_FOUND} AND ${hip_FOUND}) message(STATUS "HIP and hipBLAS found") - add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUBLAS SD_USE_CUBLAS) + file(GLOB GGML_SOURCES_ROCM "ggml-cuda/*.cu") + list(APPEND GGML_SOURCES_ROCM "ggml-cuda.cu") + add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUDA SD_USE_CUBLAS) add_library(ggml-rocm OBJECT ${GGML_SOURCES_CUDA}) if (LLAMA_CUDA_FORCE_DMMV) target_compile_definitions(ggml-rocm PUBLIC GGML_CUDA_FORCE_DMMV) @@ -163,7 +166,7 @@ if (LLAMA_HIPBLAS) target_compile_definitions(ggml-rocm PUBLIC GGML_CUDA_DMMV_X=${LLAMA_CUDA_DMMV_X}) target_compile_definitions(ggml-rocm PUBLIC GGML_CUDA_MMV_Y=${LLAMA_CUDA_MMV_Y}) target_compile_definitions(ggml-rocm PUBLIC K_QUANTS_PER_ITERATION=${LLAMA_CUDA_KQUANTS_ITER}) - set_source_files_properties(ggml-cuda.cu PROPERTIES LANGUAGE CXX) + set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE CXX) target_link_libraries(ggml-rocm PUBLIC hip::device hip::host roc::rocblas roc::hipblas) @@ -433,7 +436,8 @@ add_library(common2 examples/llava/clip.cpp examples/llava/clip.h unicode.h - unicode.cpp) + unicode.cpp + unicode-data.cpp) target_include_directories(common2 PUBLIC . ./otherarch ./otherarch/tools ./otherarch/sdcpp ./otherarch/sdcpp/thirdparty ./examples ./common) target_compile_features(common2 PUBLIC cxx_std_11) # don't bump target_link_libraries(common2 PRIVATE ggml ${LLAMA_EXTRA_LIBS}) diff --git a/Makefile b/Makefile index e1af9d2869c1f..e136be2144568 100644 --- a/Makefile +++ b/Makefile @@ -57,7 +57,7 @@ CLBLAST_FLAGS = -DGGML_USE_CLBLAST FAILSAFE_FLAGS = -DUSE_FAILSAFE VULKAN_FLAGS = -DGGML_USE_VULKAN ifdef LLAMA_CUBLAS - CUBLAS_FLAGS = -DGGML_USE_CUBLAS -DSD_USE_CUBLAS + CUBLAS_FLAGS = -DGGML_USE_CUDA -DSD_USE_CUBLAS else CUBLAS_FLAGS = endif @@ -79,7 +79,7 @@ ifeq ($(UNAME_S),Darwin) CFLAGS += -pthread CXXFLAGS += -pthread CLANG_VER = $(shell clang -v 2>&1 | head -n 1 | awk 'BEGIN {FS="[. ]"};{print $$1 $$2 $$4}') - ifeq ($(CLANG_VER),Appleclang15) + ifeq ($(CLANG_VER),Appleclang15) LDFLAGS += -ld_classic endif endif @@ -111,7 +111,7 @@ endif # Architecture specific # TODO: probably these flags need to be tweaked on some architectures -# feel free to update the Makefile for your architecture and send a pull request or issue +# feel free to update the Makefile for your architecture and send a pull request or issue ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686)) # Use all CPU extensions that are available: # old library NEEDS mf16c to work. so we must build with it. new one doesnt @@ -144,9 +144,10 @@ endif # it is recommended to use the CMAKE file to build for cublas if you can - will likely work better ifdef LLAMA_CUBLAS - CUBLAS_FLAGS = -DGGML_USE_CUBLAS -DSD_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include + CUBLAS_FLAGS = -DGGML_USE_CUDA -DSD_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include CUBLASLD_FLAGS = -lcuda -lcublas -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/x86_64-linux/lib -L/usr/local/cuda/targets/aarch64-linux/lib -L/usr/local/cuda/targets/sbsa-linux/lib -L/usr/lib/wsl/lib CUBLAS_OBJS = ggml-cuda.o ggml_v3-cuda.o ggml_v2-cuda.o ggml_v2-cuda-legacy.o + CUBLAS_OBJS += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu)) NVCC = nvcc NVCCFLAGS = --forward-unknown-to-host-compiler -use_fast_math @@ -203,7 +204,9 @@ ifdef LLAMA_CUDA_CCBIN NVCCFLAGS += -ccbin $(LLAMA_CUDA_CCBIN) endif -ggml-cuda.o: ggml-cuda.cu ggml-cuda.h +ggml-cuda/%.o: ggml-cuda/%.cu ggml-cuda/%.cuh ggml.h ggml-common.h ggml-cuda/common.cuh + $(NVCC) $(NVCCFLAGS) $(subst -Ofast,-O3,$(CXXFLAGS)) $(CUBLAS_FLAGS) $(CUBLAS_CXXFLAGS) -Wno-pedantic -c $< -o $@ +ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh) $(NVCC) $(NVCCFLAGS) $(subst -Ofast,-O3,$(CXXFLAGS)) $(CUBLAS_FLAGS) $(CUBLAS_CXXFLAGS) -Wno-pedantic -c $< -o $@ ggml_v2-cuda.o: otherarch/ggml_v2-cuda.cu otherarch/ggml_v2-cuda.h $(NVCC) $(NVCCFLAGS) $(subst -Ofast,-O3,$(CXXFLAGS)) $(CUBLAS_FLAGS) $(CUBLAS_CXXFLAGS) -Wno-pedantic -c $< -o $@ @@ -228,33 +231,26 @@ ifdef LLAMA_HIPBLAS LLAMA_CUDA_DMMV_X ?= 32 LLAMA_CUDA_MMV_Y ?= 1 LLAMA_CUDA_KQUANTS_ITER ?= 2 - HIPFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUBLAS -DSD_USE_CUBLAS $(shell $(ROCM_PATH)/bin/hipconfig -C) + HIPFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUDA -DSD_USE_CUBLAS $(shell $(ROCM_PATH)/bin/hipconfig -C) HIPLDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib -lhipblas -lamdhip64 -lrocblas - HIP_OBJS += ggml-cuda.o ggml_v3-cuda.o ggml_v2-cuda.o ggml_v2-cuda-legacy.o -ggml-cuda.o: HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS)) \ - -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) \ - -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) \ - -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) -ggml_v2-cuda.o: HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS)) \ - -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) \ - -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) \ - -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) -ggml_v2-cuda-legacy.o: HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS)) \ - -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) \ - -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) \ - -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) -ggml_v3-cuda.o: HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS)) \ - -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) \ - -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) \ - -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) -ggml-cuda.o: ggml-cuda.cu ggml-cuda.h - $(HCXX) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< + HIP_OBJS += ggml-cuda.o ggml_v3-cuda.o ggml_v2-cuda.o ggml_v2-cuda-legacy.o + HIP_OBJS += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu)) + + HIPFLAGS2 += $(addprefix --offload-arch=,$(GPU_TARGETS)) + HIPFLAGS2 += -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X) + HIPFLAGS2 += -DGGML_CUDA_MMV_Y=$(LLAMA_CUDA_MMV_Y) + HIPFLAGS2 += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) + +ggml-cuda/%.o: ggml-cuda/%.cu ggml-cuda/%.cuh ggml.h ggml-common.h ggml-cuda/common.cuh + $(HCXX) $(CXXFLAGS) $(HIPFLAGS) $(HIPFLAGS2) -x hip -c -o $@ $< +ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh) + $(HCXX) $(CXXFLAGS) $(HIPFLAGS) $(HIPFLAGS2) -x hip -c -o $@ $< ggml_v2-cuda.o: otherarch/ggml_v2-cuda.cu otherarch/ggml_v2-cuda.h - $(HCXX) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< + $(HCXX) $(CXXFLAGS) $(HIPFLAGS) $(HIPFLAGS2) -x hip -c -o $@ $< ggml_v2-cuda-legacy.o: otherarch/ggml_v2-cuda-legacy.cu otherarch/ggml_v2-cuda-legacy.h - $(HCXX) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< + $(HCXX) $(CXXFLAGS) $(HIPFLAGS) $(HIPFLAGS2) -x hip -c -o $@ $< ggml_v3-cuda.o: otherarch/ggml_v3-cuda.cu otherarch/ggml_v3-cuda.h - $(HCXX) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< + $(HCXX) $(CXXFLAGS) $(HIPFLAGS) $(HIPFLAGS2) -x hip -c -o $@ $< endif # LLAMA_HIPBLAS @@ -424,6 +420,8 @@ llavaclip.o: examples/llava/clip.cpp examples/llava/clip.h $(CXX) $(CXXFLAGS) -c $< -o $@ unicode.o: unicode.cpp unicode.h $(CXX) $(CXXFLAGS) -c $< -o $@ +unicode-data.o: unicode-data.cpp unicode-data.h + $(CXX) $(CXXFLAGS) -c $< -o $@ #version 3 libs ggml_v3.o: otherarch/ggml_v3.c otherarch/ggml_v3.h @@ -514,25 +512,26 @@ gpttype_adapter_vulkan_noavx2.o: $(GPTTYPE_ADAPTER) clean: rm -vf *.o main sdmain quantize_gguf quantize_clip quantize_gpt2 quantize_gptj quantize_neox quantize_mpt quantize-stats perplexity embedding benchmark-matmult save-load-state gguf imatrix imatrix.exe gguf.exe main.exe quantize_clip.exe quantize_gguf.exe quantize_gptj.exe quantize_gpt2.exe quantize_neox.exe quantize_mpt.exe koboldcpp_default.dll koboldcpp_openblas.dll koboldcpp_failsafe.dll koboldcpp_noavx2.dll koboldcpp_clblast.dll koboldcpp_clblast_noavx2.dll koboldcpp_cublas.dll koboldcpp_hipblas.dll koboldcpp_vulkan.dll koboldcpp_vulkan_noavx2.dll koboldcpp_default.so koboldcpp_openblas.so koboldcpp_failsafe.so koboldcpp_noavx2.so koboldcpp_clblast.so koboldcpp_clblast_noavx2.so koboldcpp_cublas.so koboldcpp_hipblas.so koboldcpp_vulkan.so koboldcpp_vulkan_noavx2.so + rm -vrf ggml-cuda/*.o # useful tools -main: examples/main/main.cpp common/sampling.cpp build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) +main: examples/main/main.cpp common/sampling.cpp build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o unicode-data.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) @echo '==== Run ./main -h for help. ====' -sdmain: otherarch/sdcpp/util.cpp otherarch/sdcpp/main.cpp otherarch/sdcpp/stable-diffusion.cpp otherarch/sdcpp/upscaler.cpp otherarch/sdcpp/model.cpp otherarch/sdcpp/thirdparty/zip.c build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) +sdmain: otherarch/sdcpp/util.cpp otherarch/sdcpp/main.cpp otherarch/sdcpp/stable-diffusion.cpp otherarch/sdcpp/upscaler.cpp otherarch/sdcpp/model.cpp otherarch/sdcpp/thirdparty/zip.c build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o unicode-data.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) -imatrix: examples/imatrix/imatrix.cpp common/sampling.cpp build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) +imatrix: examples/imatrix/imatrix.cpp common/sampling.cpp build-info.h ggml.o ggml-quants.o ggml-alloc.o unicode.o unicode-data.o ggml-backend.o llama.o common.o console.o grammar-parser.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) -gguf: examples/gguf/gguf.cpp build-info.h ggml.o llama.o unicode.o $(OBJS) +gguf: examples/gguf/gguf.cpp build-info.h ggml.o llama.o unicode.o unicode-data.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) #generated libraries -koboldcpp_default: ggml.o ggml_v3.o ggml_v2.o ggml_v1.o expose.o common.o gpttype_adapter.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_default: ggml.o ggml_v3.o ggml_v2.o ggml_v1.o expose.o common.o gpttype_adapter.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(DEFAULT_BUILD) ifdef OPENBLAS_BUILD -koboldcpp_openblas: ggml_v4_openblas.o ggml_v3_openblas.o ggml_v2_openblas.o ggml_v1.o expose.o common.o gpttype_adapter.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_openblas: ggml_v4_openblas.o ggml_v3_openblas.o ggml_v2_openblas.o ggml_v1.o expose.o common.o gpttype_adapter.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(OPENBLAS_BUILD) else koboldcpp_openblas: @@ -540,7 +539,7 @@ koboldcpp_openblas: endif ifdef FAILSAFE_BUILD -koboldcpp_failsafe: ggml_v4_failsafe.o ggml_v3_failsafe.o ggml_v2_failsafe.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_failsafe.o ggml-quants_failsafe.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_failsafe: ggml_v4_failsafe.o ggml_v3_failsafe.o ggml_v2_failsafe.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_failsafe.o ggml-quants_failsafe.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(FAILSAFE_BUILD) else koboldcpp_failsafe: @@ -548,7 +547,7 @@ koboldcpp_failsafe: endif ifdef NOAVX2_BUILD -koboldcpp_noavx2: ggml_v4_noavx2.o ggml_v3_noavx2.o ggml_v2_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_failsafe.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_noavx2: ggml_v4_noavx2.o ggml_v3_noavx2.o ggml_v2_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_failsafe.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(NOAVX2_BUILD) else koboldcpp_noavx2: @@ -556,10 +555,10 @@ koboldcpp_noavx2: endif ifdef CLBLAST_BUILD -koboldcpp_clblast: ggml_v4_clblast.o ggml_v3_clblast.o ggml_v2_clblast.o ggml_v1.o expose.o common.o gpttype_adapter_clblast.o ggml-opencl.o ggml_v3-opencl.o ggml_v2-opencl.o ggml_v2-opencl-legacy.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_clblast: ggml_v4_clblast.o ggml_v3_clblast.o ggml_v2_clblast.o ggml_v1.o expose.o common.o gpttype_adapter_clblast.o ggml-opencl.o ggml_v3-opencl.o ggml_v2-opencl.o ggml_v2-opencl-legacy.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(CLBLAST_BUILD) ifdef NOAVX2_BUILD -koboldcpp_clblast_noavx2: ggml_v4_clblast_noavx2.o ggml_v3_clblast_noavx2.o ggml_v2_clblast_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_clblast_noavx2.o ggml-opencl.o ggml_v3-opencl.o ggml_v2-opencl.o ggml_v2-opencl-legacy.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_clblast_noavx2: ggml_v4_clblast_noavx2.o ggml_v3_clblast_noavx2.o ggml_v2_clblast_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_clblast_noavx2.o ggml-opencl.o ggml_v3-opencl.o ggml_v2-opencl.o ggml_v2-opencl-legacy.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(CLBLAST_BUILD) else koboldcpp_clblast_noavx2: @@ -573,7 +572,7 @@ koboldcpp_clblast_noavx2: endif ifdef CUBLAS_BUILD -koboldcpp_cublas: ggml_v4_cublas.o ggml_v3_cublas.o ggml_v2_cublas.o ggml_v1.o expose.o common.o gpttype_adapter_cublas.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_cublas.o $(CUBLAS_OBJS) $(OBJS) +koboldcpp_cublas: ggml_v4_cublas.o ggml_v3_cublas.o ggml_v2_cublas.o ggml_v1.o expose.o common.o gpttype_adapter_cublas.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_cublas.o $(CUBLAS_OBJS) $(OBJS) $(CUBLAS_BUILD) else koboldcpp_cublas: @@ -581,7 +580,7 @@ koboldcpp_cublas: endif ifdef HIPBLAS_BUILD -koboldcpp_hipblas: ggml_v4_cublas.o ggml_v3_cublas.o ggml_v2_cublas.o ggml_v1.o expose.o common.o gpttype_adapter_cublas.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_cublas.o $(HIP_OBJS) $(OBJS) +koboldcpp_hipblas: ggml_v4_cublas.o ggml_v3_cublas.o ggml_v2_cublas.o ggml_v1.o expose.o common.o gpttype_adapter_cublas.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_cublas.o $(HIP_OBJS) $(OBJS) $(HIPBLAS_BUILD) else koboldcpp_hipblas: @@ -589,10 +588,10 @@ koboldcpp_hipblas: endif ifdef VULKAN_BUILD -koboldcpp_vulkan: ggml_v4_vulkan.o ggml_v3.o ggml_v2.o ggml_v1.o expose.o common.o gpttype_adapter_vulkan.o ggml-vulkan.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_vulkan: ggml_v4_vulkan.o ggml_v3.o ggml_v2.o ggml_v1.o expose.o common.o gpttype_adapter_vulkan.o ggml-vulkan.o ggml-quants.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(VULKAN_BUILD) ifdef NOAVX2_BUILD -koboldcpp_vulkan_noavx2: ggml_v4_vulkan_noavx2.o ggml_v3_noavx2.o ggml_v2_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_vulkan_noavx2.o ggml-vulkan.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o grammar-parser.o sdcpp_default.o $(OBJS) +koboldcpp_vulkan_noavx2: ggml_v4_vulkan_noavx2.o ggml_v3_noavx2.o ggml_v2_noavx2.o ggml_v1_failsafe.o expose.o common.o gpttype_adapter_vulkan_noavx2.o ggml-vulkan.o ggml-quants_noavx2.o ggml-alloc.o ggml-backend.o llava.o llavaclip.o unicode.o unicode-data.o grammar-parser.o sdcpp_default.o $(OBJS) $(VULKAN_BUILD) else koboldcpp_vulkan_noavx2: @@ -606,17 +605,17 @@ koboldcpp_vulkan_noavx2: endif # tools -quantize_gguf: examples/quantize/quantize.cpp ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o +quantize_gguf: examples/quantize/quantize.cpp ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -quantize_gptj: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o otherarch/tools/gptj_quantize.cpp otherarch/tools/common-ggml.cpp +quantize_gptj: ggml_v3.o ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o otherarch/tools/gptj_quantize.cpp otherarch/tools/common-ggml.cpp $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -quantize_gpt2: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o otherarch/tools/gpt2_quantize.cpp otherarch/tools/common-ggml.cpp +quantize_gpt2: ggml_v3.o ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o otherarch/tools/gpt2_quantize.cpp otherarch/tools/common-ggml.cpp $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -quantize_neox: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o otherarch/tools/neox_quantize.cpp otherarch/tools/common-ggml.cpp +quantize_neox: ggml_v3.o ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o otherarch/tools/neox_quantize.cpp otherarch/tools/common-ggml.cpp $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -quantize_mpt: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o otherarch/tools/mpt_quantize.cpp otherarch/tools/common-ggml.cpp +quantize_mpt: ggml_v3.o ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o otherarch/tools/mpt_quantize.cpp otherarch/tools/common-ggml.cpp $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -quantize_clip: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o examples/llava/clip.cpp examples/llava/clip.h examples/llava/quantclip.cpp +quantize_clip: ggml_v3.o ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o unicode.o unicode-data.o examples/llava/clip.cpp examples/llava/clip.h examples/llava/quantclip.cpp $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) perplexity: examples/perplexity/perplexity.cpp build-info.h ggml_cublas.o ggml_v2_cublas.o ggml_v1.o expose.o common.o gpttype_adapter_cublas.o k_quants.o ggml-alloc.o $(CUBLAS_OBJS) $(HIP_OBJS) $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) $(HIPLDFLAGS) diff --git a/README.md b/README.md index adb2eb849c5b7..9d8f2f1f9379d 100644 --- a/README.md +++ b/README.md @@ -79,10 +79,6 @@ My typical start command looks like this: ``python koboldcpp.py --threads 6 --bl - You can attempt a CuBLAS build with using the provided CMake file with visual studio. If you use the CMake file to build, copy the `koboldcpp_cublas.dll` generated into the same directory as the `koboldcpp.py` file. If you are bundling executables, you may need to include CUDA dynamic libraries (such as `cublasLt64_11.dll` and `cublas64_11.dll`) in order for the executable to work correctly on a different PC. - Make the KoboldCPP project using the instructions above. - -## Docker -- KoboldCpp has a few unofficial third-party community created docker images. Feel free to try them out, but do not expect up-to-date support: - - https://github.com/korewaChino/koboldCppDocker - - https://github.com/noneabove1182/koboldcpp-docker ## Arch Linux Packages There are 4 community made AUR packages (Maintained by @AlpinDale) available: [CPU-only](https://aur.archlinux.org/packages/koboldcpp-cpu), [CLBlast](https://aur.archlinux.org/packages/koboldcpp-clblast), [CUBLAS](https://aur.archlinux.org/packages/koboldcpp-cuda), and [HIPBLAS](https://aur.archlinux.org/packages/koboldcpp-hipblas). They are, respectively, for users with no GPU, users with a GPU (vendor-agnostic), users with NVIDIA GPUs, and users with a supported AMD GPU. @@ -138,6 +134,12 @@ For more information, be sure to run the program with the `--help` flag, or [che - KoboldCpp now has an **official Colab GPU Notebook**! This is an easy way to get started without installing anything in a minute or two. [Try it here!](https://colab.research.google.com/github/LostRuins/koboldcpp/blob/concedo/colab.ipynb). - Note that KoboldCpp is not responsible for your usage of this Colab Notebook, you should ensure that your own usage complies with Google Colab's terms of use. +## Docker +- The official docker can be found at https://hub.docker.com/r/koboldai/koboldcpp +- KoboldCpp also has a few unofficial third-party community created docker images. Feel free to try them out, but do not expect up-to-date support: + - https://github.com/korewaChino/koboldCppDocker + - https://github.com/noneabove1182/koboldcpp-docker +- If you're building your own docker, remember to set CUDA_DOCKER_ARCH or enable LLAMA_PORTABLE ## Questions and Help - **First, please check out [The KoboldCpp FAQ and Knowledgebase](https://github.com/LostRuins/koboldcpp/wiki) which may already have answers to your questions! Also please search through past issues and discussions.** diff --git a/SECURITY.md b/SECURITY.md new file mode 100644 index 0000000000000..14504b1bfff39 --- /dev/null +++ b/SECURITY.md @@ -0,0 +1,67 @@ +# Security Policy + + - [**Using llama.cpp securely**](#using-llamacpp-securely) + - [Untrusted models](#untrusted-models) + - [Untrusted inputs](#untrusted-inputs) + - [Data privacy](#data-privacy) + - [Untrusted environments or networks](#untrusted-environments-or-networks) + - [Multi-Tenant environments](#multi-tenant-environments) + - [**Reporting a vulnerability**](#reporting-a-vulnerability) + +## Using llama.cpp securely + +### Untrusted models +Be careful when running untrusted models. This classification includes models created by unknown developers or utilizing data obtained from unknown sources. + +*Always execute untrusted models within a secure, isolated environment such as a sandbox* (e.g., containers, virtual machines). This helps protect your system from potentially malicious code. + +> [!NOTE] +> The trustworthiness of a model is not binary. You must always determine the proper level of caution depending on the specific model and how it matches your use case and risk tolerance. + +### Untrusted inputs + +Some models accept various input formats (text, images, audio, etc.). The libraries converting these inputs have varying security levels, so it's crucial to isolate the model and carefully pre-process inputs to mitigate script injection risks. + +For maximum security when handling untrusted inputs, you may need to employ the following: + +* Sandboxing: Isolate the environment where the inference happens. +* Pre-analysis: Check how the model performs by default when exposed to prompt injection (e.g. using [fuzzing for prompt injection](https://github.com/FonduAI/awesome-prompt-injection?tab=readme-ov-file#tools)). This will give you leads on how hard you will have to work on the next topics. +* Updates: Keep both LLaMA C++ and your libraries updated with the latest security patches. +* Input Sanitation: Before feeding data to the model, sanitize inputs rigorously. This involves techniques such as: + * Validation: Enforce strict rules on allowed characters and data types. + * Filtering: Remove potentially malicious scripts or code fragments. + * Encoding: Convert special characters into safe representations. + * Verification: Run tooling that identifies potential script injections (e.g. [models that detect prompt injection attempts](https://python.langchain.com/docs/guides/safety/hugging_face_prompt_injection)). + +### Data privacy + +To protect sensitive data from potential leaks or unauthorized access, it is crucial to sandbox the model execution. This means running the model in a secure, isolated environment, which helps mitigate many attack vectors. + +### Untrusted environments or networks + +If you can't run your models in a secure and isolated environment or if it must be exposed to an untrusted network, make sure to take the following security precautions: +* Confirm the hash of any downloaded artifact (e.g. pre-trained model weights) matches a known-good value +* Encrypt your data if sending it over the network. + +### Multi-Tenant environments + +If you intend to run multiple models in parallel with shared memory, it is your responsibility to ensure the models do not interact or access each other's data. The primary areas of concern are tenant isolation, resource allocation, model sharing and hardware attacks. + +1. Tenant Isolation: Models should run separately with strong isolation methods to prevent unwanted data access. Separating networks is crucial for isolation, as it prevents unauthorized access to data or models and malicious users from sending graphs to execute under another tenant's identity. + +1. Resource Allocation: A denial of service caused by one model can impact the overall system health. Implement safeguards like rate limits, access controls, and health monitoring. + +1. Model Sharing: In a multitenant model sharing design, tenants and users must understand the security risks of running code provided by others. Since there are no reliable methods to detect malicious models, sandboxing the model execution is the recommended approach to mitigate the risk. + +1. Hardware Attacks: GPUs or TPUs can also be attacked. [Researches](https://scholar.google.com/scholar?q=gpu+side+channel) has shown that side channel attacks on GPUs are possible, which can make data leak from other models or processes running on the same system at the same time. + +## Reporting a vulnerability + +Beware that none of the topics under [Using llama.cpp securely](#using-llamacpp-securely) are considered vulnerabilities of LLaMA C++. + + +However, If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released. + +Please disclose it as a private [security advisory](https://github.com/ggerganov/llama.cpp/security/advisories/new). + +A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure. diff --git a/class.py b/class.py index c1cd4a81ae0bf..0478bef5b91c9 100644 --- a/class.py +++ b/class.py @@ -273,7 +273,8 @@ def _load(self, save_model: bool, initial_load: bool) -> None: unbantokens=False, bantokens=None, usemirostat=None, forceversion=0, nommap=self.kcpp_nommap, usemlock=False, noavx2=self.kcpp_noavx2, debugmode=self.kcpp_debugmode, skiplauncher=True, hordeconfig=None, noblas=self.kcpp_noblas, useclblast=self.kcpp_useclblast, usecublas=self.kcpp_usecublas, usevulkan=self.kcpp_usevulkan, gpulayers=self.kcpp_gpulayers, tensor_split=self.kcpp_tensor_split, config=None, - onready='', multiuser=False, foreground=False, preloadstory=None, noshift=False, remotetunnel=False, ssl=False, benchmark=None, nocertify=False, sdconfig=None, mmproj=None, password=None) + onready='', multiuser=False, foreground=False, preloadstory=None, noshift=False, remotetunnel=False, ssl=False, benchmark=None, nocertify=False, sdconfig=None, mmproj=None, + password=None, chatcompletionsadapter=None) #koboldcpp.main(kcppargs,False) #initialize library without enabling Lite http server diff --git a/colab.ipynb b/colab.ipynb index cc9d608a156fa..e29081a7bebd6 100644 --- a/colab.ipynb +++ b/colab.ipynb @@ -58,7 +58,7 @@ "VCommand = \"\"\r\n", "#@markdown
\r\n", "LoadImgModel = False #@param {type:\"boolean\"}\r\n", - "ImgModel = \"https://huggingface.co/koboldcpp/imgmodel/resolve/main/imgmodel_older_q4_0.gguf\" #@param [\"https://huggingface.co/koboldcpp/imgmodel/resolve/main/imgmodel_older_q4_0.gguf\"]{allow-input: true}\r\n", + "ImgModel = \"https://huggingface.co/koboldcpp/imgmodel/resolve/main/imgmodel_ftuned_q4_0.gguf\" #@param [\"https://huggingface.co/koboldcpp/imgmodel/resolve/main/imgmodel_ftuned_q4_0.gguf\"]{allow-input: true}\r\n", "SCommand = \"\"\r\n", "\r\n", "import os\r\n", diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt deleted file mode 100644 index 350bbdf7f7b1b..0000000000000 --- a/common/CMakeLists.txt +++ /dev/null @@ -1,73 +0,0 @@ -# common - - -# Build info header -# - -if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/../.git") - set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../.git") - - # Is git submodule - if(NOT IS_DIRECTORY "${GIT_DIR}") - file(READ ${GIT_DIR} REAL_GIT_DIR_LINK) - string(REGEX REPLACE "gitdir: (.*)\n$" "\\1" REAL_GIT_DIR ${REAL_GIT_DIR_LINK}) - string(FIND "${REAL_GIT_DIR}" "/" SLASH_POS) - if (SLASH_POS EQUAL 0) - set(GIT_DIR "${REAL_GIT_DIR}") - else() - set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../${REAL_GIT_DIR}") - endif() - endif() - - if(EXISTS "${GIT_DIR}/index") - set(GIT_INDEX "${GIT_DIR}/index") - else() - message(WARNING "Git index not found in git repository.") - set(GIT_INDEX "") - endif() -else() - message(WARNING "Git repository not found; to enable automatic generation of build info, make sure Git is installed and the project is a Git repository.") - set(GIT_INDEX "") -endif() - -# Add a custom command to rebuild build-info.cpp when .git/index changes -add_custom_command( - OUTPUT "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp" - COMMENT "Generating build details from Git" - COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION} - -DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME} - -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/../scripts/gen-build-info-cpp.cmake" - WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.." - DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX} - VERBATIM -) -set(TARGET build_info) -add_library(${TARGET} OBJECT build-info.cpp) -if (BUILD_SHARED_LIBS) - set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) -endif() - - -set(TARGET common) - -add_library(${TARGET} STATIC - base64.hpp - common.h - common.cpp - sampling.h - sampling.cpp - console.h - console.cpp - grammar-parser.h - grammar-parser.cpp - train.h - train.cpp - ) - -if (BUILD_SHARED_LIBS) - set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) -endif() - -target_include_directories(${TARGET} PUBLIC .) -target_compile_features(${TARGET} PUBLIC cxx_std_11) -target_link_libraries(${TARGET} PRIVATE build_info PUBLIC llama) diff --git a/common/common.cpp b/common/common.cpp index ec92fa02e15da..0a3d281ccbf63 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -17,6 +17,7 @@ #include #include #include +#include #if defined(__APPLE__) && defined(__MACH__) #include @@ -28,7 +29,6 @@ #ifndef NOMINMAX # define NOMINMAX #endif -#include #include #include #include @@ -38,18 +38,36 @@ #include #include #endif +#if defined(LLAMA_USE_CURL) +#include +#include +#include +#include +#endif #if defined(_MSC_VER) #pragma warning(disable: 4244 4267) // possible loss of data #endif -#if (defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)) -#define GGML_USE_CUBLAS_SYCL +#if (defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)) +#define GGML_USE_CUDA_SYCL +#endif + +#if (defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)) || defined(GGML_USE_VULKAN) +#define GGML_USE_CUDA_SYCL_VULKAN #endif -#if (defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)) || defined(GGML_USE_VULKAN) -#define GGML_USE_CUBLAS_SYCL_VULKAN +#if defined(LLAMA_USE_CURL) +#ifdef __linux__ +#include +#elif defined(_WIN32) +#define PATH_MAX MAX_PATH +#else +#include #endif +#define LLAMA_CURL_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083 +#define LLAMA_CURL_MAX_HEADER_LENGTH 256 +#endif // LLAMA_USE_CURL int32_t get_num_physical_cores() { #ifdef __linux__ @@ -87,7 +105,7 @@ int32_t get_num_physical_cores() { return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4; } -void process_escapes(std::string& input) { +void process_escapes(std::string & input) { std::size_t input_len = input.length(); std::size_t output_idx = 0; @@ -140,774 +158,1093 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { return result; } -bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) { - bool invalid_param = false; - std::string arg; - const std::string arg_prefix = "--"; - llama_sampling_params & sparams = params.sparams; +bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param) { + llama_sampling_params& sparams = params.sparams; - for (int i = 1; i < argc; i++) { - arg = argv[i]; - if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) { - std::replace(arg.begin(), arg.end(), '_', '-'); + if (arg == "-s" || arg == "--seed") { + if (++i >= argc) { + invalid_param = true; + return true; } - - if (arg == "-s" || arg == "--seed") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.seed = std::stoul(argv[i]); - } else if (arg == "-t" || arg == "--threads") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_threads = std::stoi(argv[i]); - if (params.n_threads <= 0) { - params.n_threads = std::thread::hardware_concurrency(); - } - } else if (arg == "-tb" || arg == "--threads-batch") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_threads_batch = std::stoi(argv[i]); - if (params.n_threads_batch <= 0) { - params.n_threads_batch = std::thread::hardware_concurrency(); - } - } else if (arg == "-td" || arg == "--threads-draft") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_threads_draft = std::stoi(argv[i]); - if (params.n_threads_draft <= 0) { - params.n_threads_draft = std::thread::hardware_concurrency(); - } - } else if (arg == "-tbd" || arg == "--threads-batch-draft") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_threads_batch_draft = std::stoi(argv[i]); - if (params.n_threads_batch_draft <= 0) { - params.n_threads_batch_draft = std::thread::hardware_concurrency(); - } - } else if (arg == "-p" || arg == "--prompt") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.prompt = argv[i]; - } else if (arg == "-e" || arg == "--escape") { - params.escape = true; - } else if (arg == "--prompt-cache") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.path_prompt_cache = argv[i]; - } else if (arg == "--prompt-cache-all") { - params.prompt_cache_all = true; - } else if (arg == "--prompt-cache-ro") { - params.prompt_cache_ro = true; - } else if (arg == "-bf" || arg == "--binary-file") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::ifstream file(argv[i], std::ios::binary); - if (!file) { - fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); - invalid_param = true; - break; - } - // store the external file name in params - params.prompt_file = argv[i]; - std::ostringstream ss; - ss << file.rdbuf(); - params.prompt = ss.str(); - fprintf(stderr, "Read %zu bytes from binary file %s\n", params.prompt.size(), argv[i]); - } else if (arg == "-f" || arg == "--file") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::ifstream file(argv[i]); - if (!file) { - fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); - invalid_param = true; - break; - } - // store the external file name in params - params.prompt_file = argv[i]; - std::copy(std::istreambuf_iterator(file), std::istreambuf_iterator(), back_inserter(params.prompt)); - if (!params.prompt.empty() && params.prompt.back() == '\n') { - params.prompt.pop_back(); - } - } else if (arg == "-n" || arg == "--n-predict") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_predict = std::stoi(argv[i]); - } else if (arg == "--top-k") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.top_k = std::stoi(argv[i]); - } else if (arg == "-c" || arg == "--ctx-size") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_ctx = std::stoi(argv[i]); - } else if (arg == "--grp-attn-n" || arg == "-gan") { - if (++i >= argc) { - invalid_param = true; - break; - } - - params.grp_attn_n = std::stoi(argv[i]); - } else if (arg == "--grp-attn-w" || arg == "-gaw") { - if (++i >= argc) { - invalid_param = true; - break; - } - - params.grp_attn_w = std::stoi(argv[i]); - } else if (arg == "--rope-freq-base") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.rope_freq_base = std::stof(argv[i]); - } else if (arg == "--rope-freq-scale") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.rope_freq_scale = std::stof(argv[i]); - } else if (arg == "--rope-scaling") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::string value(argv[i]); - /**/ if (value == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_NONE; } - else if (value == "linear") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_LINEAR; } - else if (value == "yarn") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_YARN; } - else { invalid_param = true; break; } - } else if (arg == "--rope-scale") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.rope_freq_scale = 1.0f/std::stof(argv[i]); - } else if (arg == "--yarn-orig-ctx") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.yarn_orig_ctx = std::stoi(argv[i]); - } else if (arg == "--yarn-ext-factor") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.yarn_ext_factor = std::stof(argv[i]); - } else if (arg == "--yarn-attn-factor") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.yarn_attn_factor = std::stof(argv[i]); - } else if (arg == "--yarn-beta-fast") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.yarn_beta_fast = std::stof(argv[i]); - } else if (arg == "--yarn-beta-slow") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.yarn_beta_slow = std::stof(argv[i]); - } else if (arg == "--pooling") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::string value(argv[i]); - /**/ if (value == "none") { params.pooling_type = LLAMA_POOLING_TYPE_NONE; } - else if (value == "mean") { params.pooling_type = LLAMA_POOLING_TYPE_MEAN; } - else if (value == "cls") { params.pooling_type = LLAMA_POOLING_TYPE_CLS; } - else { invalid_param = true; break; } - } else if (arg == "--defrag-thold" || arg == "-dt") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.defrag_thold = std::stof(argv[i]); - } else if (arg == "--samplers") { - if (++i >= argc) { - invalid_param = true; - break; - } - const auto sampler_names = string_split(argv[i], ';'); - sparams.samplers_sequence = sampler_types_from_names(sampler_names, true); - } else if (arg == "--sampling-seq") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.samplers_sequence = sampler_types_from_chars(argv[i]); - } else if (arg == "--top-p") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.top_p = std::stof(argv[i]); - } else if (arg == "--min-p") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.min_p = std::stof(argv[i]); - } else if (arg == "--temp") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.temp = std::stof(argv[i]); - sparams.temp = std::max(sparams.temp, 0.0f); - } else if (arg == "--tfs") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.tfs_z = std::stof(argv[i]); - } else if (arg == "--typical") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.typical_p = std::stof(argv[i]); - } else if (arg == "--repeat-last-n") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.penalty_last_n = std::stoi(argv[i]); - sparams.n_prev = std::max(sparams.n_prev, sparams.penalty_last_n); - } else if (arg == "--repeat-penalty") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.penalty_repeat = std::stof(argv[i]); - } else if (arg == "--frequency-penalty") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.penalty_freq = std::stof(argv[i]); - } else if (arg == "--presence-penalty") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.penalty_present = std::stof(argv[i]); - } else if (arg == "--dynatemp-range") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.dynatemp_range = std::stof(argv[i]); - } else if (arg == "--dynatemp-exp") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.dynatemp_exponent = std::stof(argv[i]); - } else if (arg == "--mirostat") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.mirostat = std::stoi(argv[i]); - } else if (arg == "--mirostat-lr") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.mirostat_eta = std::stof(argv[i]); - } else if (arg == "--mirostat-ent") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.mirostat_tau = std::stof(argv[i]); - } else if (arg == "--cfg-negative-prompt") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.cfg_negative_prompt = argv[i]; - } else if (arg == "--cfg-negative-prompt-file") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::ifstream file(argv[i]); - if (!file) { - fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); - invalid_param = true; - break; - } - std::copy(std::istreambuf_iterator(file), std::istreambuf_iterator(), back_inserter(sparams.cfg_negative_prompt)); - if (!sparams.cfg_negative_prompt.empty() && sparams.cfg_negative_prompt.back() == '\n') { - sparams.cfg_negative_prompt.pop_back(); - } - } else if (arg == "--cfg-scale") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.cfg_scale = std::stof(argv[i]); - } else if (arg == "-b" || arg == "--batch-size") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_batch = std::stoi(argv[i]); - } else if (arg == "-ub" || arg == "--ubatch-size") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_ubatch = std::stoi(argv[i]); - } else if (arg == "--keep") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_keep = std::stoi(argv[i]); - } else if (arg == "--draft") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_draft = std::stoi(argv[i]); - } else if (arg == "--chunks") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_chunks = std::stoi(argv[i]); - } else if (arg == "-np" || arg == "--parallel") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_parallel = std::stoi(argv[i]); - } else if (arg == "-ns" || arg == "--sequences") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_sequences = std::stoi(argv[i]); - } else if (arg == "--p-split" || arg == "-ps") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.p_split = std::stof(argv[i]); - } else if (arg == "-m" || arg == "--model") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.model = argv[i]; - } else if (arg == "-md" || arg == "--model-draft") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.model_draft = argv[i]; - } else if (arg == "-a" || arg == "--alias") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.model_alias = argv[i]; - } else if (arg == "--lora") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.lora_adapter.emplace_back(argv[i], 1.0f); - params.use_mmap = false; - } else if (arg == "--lora-scaled") { - if (++i >= argc) { - invalid_param = true; - break; - } - const char * lora_adapter = argv[i]; - if (++i >= argc) { - invalid_param = true; - break; - } - params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i])); - params.use_mmap = false; - } else if (arg == "--lora-base") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.lora_base = argv[i]; - } else if (arg == "--mmproj") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.mmproj = argv[i]; - } else if (arg == "--image") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.image = argv[i]; - } else if (arg == "-i" || arg == "--interactive") { - params.interactive = true; - } else if (arg == "--embedding") { - params.embedding = true; - } else if (arg == "--interactive-first") { - params.interactive_first = true; - } else if (arg == "-ins" || arg == "--instruct") { - params.instruct = true; - } else if (arg == "-cml" || arg == "--chatml") { - params.chatml = true; - } else if (arg == "--infill") { - params.infill = true; - } else if (arg == "-dkvc" || arg == "--dump-kv-cache") { - params.dump_kv_cache = true; - } else if (arg == "-nkvo" || arg == "--no-kv-offload") { - params.no_kv_offload = true; - } else if (arg == "-ctk" || arg == "--cache-type-k") { - params.cache_type_k = argv[++i]; - } else if (arg == "-ctv" || arg == "--cache-type-v") { - params.cache_type_v = argv[++i]; - } else if (arg == "--multiline-input") { - params.multiline_input = true; - } else if (arg == "--simple-io") { - params.simple_io = true; - } else if (arg == "-cb" || arg == "--cont-batching") { - params.cont_batching = true; - } else if (arg == "--color") { - params.use_color = true; - } else if (arg == "--mlock") { - params.use_mlock = true; - } else if (arg == "--gpu-layers" || arg == "-ngl" || arg == "--n-gpu-layers") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_gpu_layers = std::stoi(argv[i]); - if (!llama_supports_gpu_offload()) { - fprintf(stderr, "warning: not compiled with GPU offload support, --n-gpu-layers option will be ignored\n"); - fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n"); - } - } else if (arg == "--gpu-layers-draft" || arg == "-ngld" || arg == "--n-gpu-layers-draft") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_gpu_layers_draft = std::stoi(argv[i]); - if (!llama_supports_gpu_offload()) { - fprintf(stderr, "warning: not compiled with GPU offload support, --n-gpu-layers-draft option will be ignored\n"); - fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n"); - } - } else if (arg == "--main-gpu" || arg == "-mg") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.main_gpu = std::stoi(argv[i]); -#ifndef GGML_USE_CUBLAS_SYCL - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS/SYCL. Setting the main GPU has no effect.\n"); -#endif // GGML_USE_CUBLAS_SYCL - } else if (arg == "--split-mode" || arg == "-sm") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::string arg_next = argv[i]; - if (arg_next == "none") { - params.split_mode = LLAMA_SPLIT_MODE_NONE; - } else if (arg_next == "layer") { - params.split_mode = LLAMA_SPLIT_MODE_LAYER; - } else if (arg_next == "row") { -#ifdef GGML_USE_SYCL - fprintf(stderr, "warning: The split mode value:[row] is not supported by llama.cpp with SYCL. It's developing.\nExit!\n"); - exit(1); -#endif // GGML_USE_SYCL - params.split_mode = LLAMA_SPLIT_MODE_ROW; - } else { - invalid_param = true; - break; - } -#ifndef GGML_USE_CUBLAS_SYCL - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS/SYCL. Setting the split mode has no effect.\n"); -#endif // GGML_USE_CUBLAS_SYCL - - } else if (arg == "--tensor-split" || arg == "-ts") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::string arg_next = argv[i]; - - // split string by , and / - const std::regex regex{R"([,/]+)"}; - std::sregex_token_iterator it{arg_next.begin(), arg_next.end(), regex, -1}; - std::vector split_arg{it, {}}; - if (split_arg.size() >= llama_max_devices()) { - invalid_param = true; - break; - } - for (size_t i = 0; i < llama_max_devices(); ++i) { - if (i < split_arg.size()) { - params.tensor_split[i] = std::stof(split_arg[i]); - } else { - params.tensor_split[i] = 0.0f; - } - } -#ifndef GGML_USE_CUBLAS_SYCL_VULKAN - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS/SYCL/Vulkan. Setting a tensor split has no effect.\n"); -#endif // GGML_USE_CUBLAS_SYCL - } else if (arg == "--no-mmap") { - params.use_mmap = false; - } else if (arg == "--numa") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::string value(argv[i]); - /**/ if (value == "distribute" || value == "") { params.numa = GGML_NUMA_STRATEGY_DISTRIBUTE; } - else if (value == "isolate") { params.numa = GGML_NUMA_STRATEGY_ISOLATE; } - else if (value == "numactl") { params.numa = GGML_NUMA_STRATEGY_NUMACTL; } - else { invalid_param = true; break; } - } else if (arg == "--verbose-prompt") { - params.verbose_prompt = true; - } else if (arg == "--no-display-prompt") { - params.display_prompt = false; - } else if (arg == "-r" || arg == "--reverse-prompt") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.antiprompt.emplace_back(argv[i]); - } else if (arg == "-ld" || arg == "--logdir") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.logdir = argv[i]; - - if (params.logdir.back() != DIRECTORY_SEPARATOR) { - params.logdir += DIRECTORY_SEPARATOR; - } - } else if (arg == "--save-all-logits" || arg == "--kl-divergence-base") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.logits_file = argv[i]; - } else if (arg == "--perplexity" || arg == "--all-logits") { - params.logits_all = true; - } else if (arg == "--ppl-stride") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.ppl_stride = std::stoi(argv[i]); - } else if (arg == "-ptc" || arg == "--print-token-count") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.n_print = std::stoi(argv[i]); - } else if (arg == "--ppl-output-type") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.ppl_output_type = std::stoi(argv[i]); - } else if (arg == "--hellaswag") { - params.hellaswag = true; - } else if (arg == "--hellaswag-tasks") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.hellaswag_tasks = std::stoi(argv[i]); - } else if (arg == "--winogrande") { - params.winogrande = true; - } else if (arg == "--winogrande-tasks") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.winogrande_tasks = std::stoi(argv[i]); - } else if (arg == "--multiple-choice") { - params.multiple_choice = true; - } else if (arg == "--multiple-choice-tasks") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.multiple_choice_tasks = std::stoi(argv[i]); - } else if (arg == "--kl-divergence") { - params.kl_divergence = true; - } else if (arg == "--ignore-eos") { - params.ignore_eos = true; - } else if (arg == "--no-penalize-nl") { - sparams.penalize_nl = false; - } else if (arg == "-l" || arg == "--logit-bias") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::stringstream ss(argv[i]); - llama_token key; - char sign; - std::string value_str; - try { - if (ss >> key && ss >> sign && std::getline(ss, value_str) && (sign == '+' || sign == '-')) { - sparams.logit_bias[key] = std::stof(value_str) * ((sign == '-') ? -1.0f : 1.0f); - } else { - throw std::exception(); - } - } catch (const std::exception&) { - invalid_param = true; - break; - } - } else if (arg == "-h" || arg == "--help") { - return false; - - } else if (arg == "--version") { - fprintf(stderr, "version: %d (%s)\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT); - fprintf(stderr, "built with %s for %s\n", LLAMA_COMPILER, LLAMA_BUILD_TARGET); - exit(0); - } else if (arg == "--random-prompt") { - params.random_prompt = true; - } else if (arg == "--in-prefix-bos") { - params.input_prefix_bos = true; - } else if (arg == "--in-prefix") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.input_prefix = argv[i]; - } else if (arg == "--in-suffix") { - if (++i >= argc) { - invalid_param = true; - break; - } - params.input_suffix = argv[i]; - } else if (arg == "--grammar") { - if (++i >= argc) { - invalid_param = true; - break; - } - sparams.grammar = argv[i]; - } else if (arg == "--grammar-file") { - if (++i >= argc) { - invalid_param = true; - break; - } - std::ifstream file(argv[i]); - if (!file) { - fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); - invalid_param = true; - break; - } - std::copy( - std::istreambuf_iterator(file), - std::istreambuf_iterator(), - std::back_inserter(sparams.grammar) - ); - } else if (arg == "--override-kv") { - if (++i >= argc) { - invalid_param = true; - break; + params.seed = std::stoul(argv[i]); + return true; + } + if (arg == "-t" || arg == "--threads") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_threads = std::stoi(argv[i]); + if (params.n_threads <= 0) { + params.n_threads = std::thread::hardware_concurrency(); + } + return true; + } + if (arg == "-tb" || arg == "--threads-batch") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_threads_batch = std::stoi(argv[i]); + if (params.n_threads_batch <= 0) { + params.n_threads_batch = std::thread::hardware_concurrency(); + } + return true; + } + if (arg == "-td" || arg == "--threads-draft") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_threads_draft = std::stoi(argv[i]); + if (params.n_threads_draft <= 0) { + params.n_threads_draft = std::thread::hardware_concurrency(); + } + return true; + } + if (arg == "-tbd" || arg == "--threads-batch-draft") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_threads_batch_draft = std::stoi(argv[i]); + if (params.n_threads_batch_draft <= 0) { + params.n_threads_batch_draft = std::thread::hardware_concurrency(); + } + return true; + } + if (arg == "-p" || arg == "--prompt") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.prompt = argv[i]; + return true; + } + if (arg == "-e" || arg == "--escape") { + params.escape = true; + return true; + } + if (arg == "--prompt-cache") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.path_prompt_cache = argv[i]; + return true; + } + if (arg == "--prompt-cache-all") { + params.prompt_cache_all = true; + return true; + } + if (arg == "--prompt-cache-ro") { + params.prompt_cache_ro = true; + return true; + } + if (arg == "-bf" || arg == "--binary-file") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::ifstream file(argv[i], std::ios::binary); + if (!file) { + fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); + invalid_param = true; + return true; + } + // store the external file name in params + params.prompt_file = argv[i]; + std::ostringstream ss; + ss << file.rdbuf(); + params.prompt = ss.str(); + fprintf(stderr, "Read %zu bytes from binary file %s\n", params.prompt.size(), argv[i]); + return true; + } + if (arg == "-f" || arg == "--file") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::ifstream file(argv[i]); + if (!file) { + fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); + invalid_param = true; + return true; + } + // store the external file name in params + params.prompt_file = argv[i]; + std::copy(std::istreambuf_iterator(file), std::istreambuf_iterator(), back_inserter(params.prompt)); + if (!params.prompt.empty() && params.prompt.back() == '\n') { + params.prompt.pop_back(); + } + return true; + } + if (arg == "-n" || arg == "--n-predict") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_predict = std::stoi(argv[i]); + return true; + } + if (arg == "--top-k") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.top_k = std::stoi(argv[i]); + return true; + } + if (arg == "-c" || arg == "--ctx-size") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_ctx = std::stoi(argv[i]); + return true; + } + if (arg == "--grp-attn-n" || arg == "-gan") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.grp_attn_n = std::stoi(argv[i]); + return true; + } + if (arg == "--grp-attn-w" || arg == "-gaw") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.grp_attn_w = std::stoi(argv[i]); + return true; + } + if (arg == "--rope-freq-base") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.rope_freq_base = std::stof(argv[i]); + return true; + } + if (arg == "--rope-freq-scale") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.rope_freq_scale = std::stof(argv[i]); + return true; + } + if (arg == "--rope-scaling") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::string value(argv[i]); + /**/ if (value == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_NONE; } + else if (value == "linear") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_LINEAR; } + else if (value == "yarn") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_YARN; } + else { invalid_param = true; } + return true; + } + if (arg == "--rope-scale") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.rope_freq_scale = 1.0f / std::stof(argv[i]); + return true; + } + if (arg == "--yarn-orig-ctx") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.yarn_orig_ctx = std::stoi(argv[i]); + return true; + } + if (arg == "--yarn-ext-factor") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.yarn_ext_factor = std::stof(argv[i]); + return true; + } + if (arg == "--yarn-attn-factor") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.yarn_attn_factor = std::stof(argv[i]); + return true; + } + if (arg == "--yarn-beta-fast") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.yarn_beta_fast = std::stof(argv[i]); + return true; + } + if (arg == "--yarn-beta-slow") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.yarn_beta_slow = std::stof(argv[i]); + return true; + } + if (arg == "--pooling") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::string value(argv[i]); + /**/ if (value == "none") { params.pooling_type = LLAMA_POOLING_TYPE_NONE; } + else if (value == "mean") { params.pooling_type = LLAMA_POOLING_TYPE_MEAN; } + else if (value == "cls") { params.pooling_type = LLAMA_POOLING_TYPE_CLS; } + else { invalid_param = true; } + return true; + } + if (arg == "--defrag-thold" || arg == "-dt") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.defrag_thold = std::stof(argv[i]); + return true; + } + if (arg == "--samplers") { + if (++i >= argc) { + invalid_param = true; + return true; + } + const auto sampler_names = string_split(argv[i], ';'); + sparams.samplers_sequence = sampler_types_from_names(sampler_names, true); + return true; + } + if (arg == "--sampling-seq") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.samplers_sequence = sampler_types_from_chars(argv[i]); + return true; + } + if (arg == "--top-p") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.top_p = std::stof(argv[i]); + return true; + } + if (arg == "--min-p") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.min_p = std::stof(argv[i]); + return true; + } + if (arg == "--temp") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.temp = std::stof(argv[i]); + sparams.temp = std::max(sparams.temp, 0.0f); + return true; + } + if (arg == "--tfs") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.tfs_z = std::stof(argv[i]); + return true; + } + if (arg == "--typical") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.typical_p = std::stof(argv[i]); + return true; + } + if (arg == "--repeat-last-n") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.penalty_last_n = std::stoi(argv[i]); + sparams.n_prev = std::max(sparams.n_prev, sparams.penalty_last_n); + return true; + } + if (arg == "--repeat-penalty") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.penalty_repeat = std::stof(argv[i]); + return true; + } + if (arg == "--frequency-penalty") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.penalty_freq = std::stof(argv[i]); + return true; + } + if (arg == "--presence-penalty") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.penalty_present = std::stof(argv[i]); + return true; + } + if (arg == "--dynatemp-range") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.dynatemp_range = std::stof(argv[i]); + return true; + } + if (arg == "--dynatemp-exp") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.dynatemp_exponent = std::stof(argv[i]); + return true; + } + if (arg == "--mirostat") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.mirostat = std::stoi(argv[i]); + return true; + } + if (arg == "--mirostat-lr") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.mirostat_eta = std::stof(argv[i]); + return true; + } + if (arg == "--mirostat-ent") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.mirostat_tau = std::stof(argv[i]); + return true; + } + if (arg == "--cfg-negative-prompt") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.cfg_negative_prompt = argv[i]; + return true; + } + if (arg == "--cfg-negative-prompt-file") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::ifstream file(argv[i]); + if (!file) { + fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); + invalid_param = true; + return true; + } + std::copy(std::istreambuf_iterator(file), std::istreambuf_iterator(), back_inserter(sparams.cfg_negative_prompt)); + if (!sparams.cfg_negative_prompt.empty() && sparams.cfg_negative_prompt.back() == '\n') { + sparams.cfg_negative_prompt.pop_back(); + } + return true; + } + if (arg == "--cfg-scale") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.cfg_scale = std::stof(argv[i]); + return true; + } + if (arg == "-b" || arg == "--batch-size") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_batch = std::stoi(argv[i]); + return true; + } + if (arg == "-ub" || arg == "--ubatch-size") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_ubatch = std::stoi(argv[i]); + return true; + } + if (arg == "--keep") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_keep = std::stoi(argv[i]); + return true; + } + if (arg == "--draft") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_draft = std::stoi(argv[i]); + return true; + } + if (arg == "--chunks") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_chunks = std::stoi(argv[i]); + return true; + } + if (arg == "-np" || arg == "--parallel") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_parallel = std::stoi(argv[i]); + return true; + } + if (arg == "-ns" || arg == "--sequences") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_sequences = std::stoi(argv[i]); + return true; + } + if (arg == "--p-split" || arg == "-ps") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.p_split = std::stof(argv[i]); + return true; + } + if (arg == "-m" || arg == "--model") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.model = argv[i]; + return true; + } + if (arg == "-md" || arg == "--model-draft") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.model_draft = argv[i]; + return true; + } + if (arg == "-a" || arg == "--alias") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.model_alias = argv[i]; + return true; + } + if (arg == "-mu" || arg == "--model-url") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.model_url = argv[i]; + return true; + } + if (arg == "-hfr" || arg == "--hf-repo") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.hf_repo = argv[i]; + return true; + } + if (arg == "-hff" || arg == "--hf-file") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.hf_file = argv[i]; + return true; + } + if (arg == "--lora") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.lora_adapter.emplace_back(argv[i], 1.0f); + params.use_mmap = false; + return true; + } + if (arg == "--lora-scaled") { + if (++i >= argc) { + invalid_param = true; + return true; + } + const char* lora_adapter = argv[i]; + if (++i >= argc) { + invalid_param = true; + return true; + } + params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i])); + params.use_mmap = false; + return true; + } + if (arg == "--lora-base") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.lora_base = argv[i]; + return true; + } + if (arg == "--control-vector") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.control_vectors.push_back({ 1.0f, argv[i], }); + return true; + } + if (arg == "--control-vector-scaled") { + if (++i >= argc) { + invalid_param = true; + return true; + } + const char* fname = argv[i]; + if (++i >= argc) { + invalid_param = true; + return true; + } + params.control_vectors.push_back({ std::stof(argv[i]), fname, }); + return true; + } + if (arg == "--control-vector-layer-range") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.control_vector_layer_start = std::stoi(argv[i]); + if (++i >= argc) { + invalid_param = true; + return true; + } + params.control_vector_layer_end = std::stoi(argv[i]); + return true; + } + if (arg == "--mmproj") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.mmproj = argv[i]; + return true; + } + if (arg == "--image") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.image = argv[i]; + return true; + } + if (arg == "-i" || arg == "--interactive") { + params.interactive = true; + return true; + } + if (arg == "--embedding") { + params.embedding = true; + return true; + } + if (arg == "--interactive-first") { + params.interactive_first = true; + return true; + } + if (arg == "-ins" || arg == "--instruct") { + params.instruct = true; + return true; + } + if (arg == "-cml" || arg == "--chatml") { + params.chatml = true; + return true; + } + if (arg == "--infill") { + params.infill = true; + return true; + } + if (arg == "-dkvc" || arg == "--dump-kv-cache") { + params.dump_kv_cache = true; + return true; + } + if (arg == "-nkvo" || arg == "--no-kv-offload") { + params.no_kv_offload = true; + return true; + } + if (arg == "-ctk" || arg == "--cache-type-k") { + params.cache_type_k = argv[++i]; + return true; + } + if (arg == "-ctv" || arg == "--cache-type-v") { + params.cache_type_v = argv[++i]; + return true; + } + if (arg == "--multiline-input") { + params.multiline_input = true; + return true; + } + if (arg == "--simple-io") { + params.simple_io = true; + return true; + } + if (arg == "-cb" || arg == "--cont-batching") { + params.cont_batching = true; + return true; + } + if (arg == "--color") { + params.use_color = true; + return true; + } + if (arg == "--mlock") { + params.use_mlock = true; + return true; + } + if (arg == "--gpu-layers" || arg == "-ngl" || arg == "--n-gpu-layers") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_gpu_layers = std::stoi(argv[i]); + if (!llama_supports_gpu_offload()) { + fprintf(stderr, "warning: not compiled with GPU offload support, --n-gpu-layers option will be ignored\n"); + fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n"); + } + return true; + } + if (arg == "--gpu-layers-draft" || arg == "-ngld" || arg == "--n-gpu-layers-draft") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_gpu_layers_draft = std::stoi(argv[i]); + if (!llama_supports_gpu_offload()) { + fprintf(stderr, "warning: not compiled with GPU offload support, --n-gpu-layers-draft option will be ignored\n"); + fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n"); + } + return true; + } + if (arg == "--main-gpu" || arg == "-mg") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.main_gpu = std::stoi(argv[i]); +#ifndef GGML_USE_CUDA_SYCL + fprintf(stderr, "warning: llama.cpp was compiled without CUDA/SYCL. Setting the main GPU has no effect.\n"); +#endif // GGML_USE_CUDA_SYCL + return true; + } + if (arg == "--split-mode" || arg == "-sm") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::string arg_next = argv[i]; + if (arg_next == "none") { + params.split_mode = LLAMA_SPLIT_MODE_NONE; + } + else if (arg_next == "layer") { + params.split_mode = LLAMA_SPLIT_MODE_LAYER; + } + else if (arg_next == "row") { +#ifdef GGML_USE_SYCL + fprintf(stderr, "warning: The split mode value:[row] is not supported by llama.cpp with SYCL. It's developing.\nExit!\n"); + exit(1); +#endif // GGML_USE_SYCL + params.split_mode = LLAMA_SPLIT_MODE_ROW; + } + else { + invalid_param = true; + return true; + } +#ifndef GGML_USE_CUDA_SYCL + fprintf(stderr, "warning: llama.cpp was compiled without CUDA/SYCL. Setting the split mode has no effect.\n"); +#endif // GGML_USE_CUDA_SYCL + return true; + } + if (arg == "--tensor-split" || arg == "-ts") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::string arg_next = argv[i]; + + // split string by , and / + const std::regex regex{ R"([,/]+)" }; + std::sregex_token_iterator it{ arg_next.begin(), arg_next.end(), regex, -1 }; + std::vector split_arg{ it, {} }; + if (split_arg.size() >= llama_max_devices()) { + invalid_param = true; + return true; + } + for (size_t i = 0; i < llama_max_devices(); ++i) { + if (i < split_arg.size()) { + params.tensor_split[i] = std::stof(split_arg[i]); + } + else { + params.tensor_split[i] = 0.0f; + } + } +#ifndef GGML_USE_CUDA_SYCL_VULKAN + fprintf(stderr, "warning: llama.cpp was compiled without CUDA/SYCL/Vulkan. Setting a tensor split has no effect.\n"); +#endif // GGML_USE_CUDA_SYCL_VULKAN + return true; + } + if (arg == "--no-mmap") { + params.use_mmap = false; + return true; + } + if (arg == "--numa") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::string value(argv[i]); + /**/ if (value == "distribute" || value == "") { params.numa = GGML_NUMA_STRATEGY_DISTRIBUTE; } + else if (value == "isolate") { params.numa = GGML_NUMA_STRATEGY_ISOLATE; } + else if (value == "numactl") { params.numa = GGML_NUMA_STRATEGY_NUMACTL; } + else { invalid_param = true; } + return true; + } + if (arg == "--verbose-prompt") { + params.verbose_prompt = true; + return true; + } + if (arg == "--no-display-prompt") { + params.display_prompt = false; + return true; + } + if (arg == "-r" || arg == "--reverse-prompt") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.antiprompt.emplace_back(argv[i]); + return true; + } + if (arg == "-ld" || arg == "--logdir") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.logdir = argv[i]; + + if (params.logdir.back() != DIRECTORY_SEPARATOR) { + params.logdir += DIRECTORY_SEPARATOR; + } + return true; + } + if (arg == "-lcs" || arg == "--lookup-cache-static") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.lookup_cache_static = argv[i]; + return true; + } + if (arg == "-lcd" || arg == "--lookup-cache-dynamic") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.lookup_cache_dynamic = argv[i]; + return true; + } + if (arg == "--save-all-logits" || arg == "--kl-divergence-base") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.logits_file = argv[i]; + return true; + } + if (arg == "--perplexity" || arg == "--all-logits") { + params.logits_all = true; + return true; + } + if (arg == "--ppl-stride") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.ppl_stride = std::stoi(argv[i]); + return true; + } + if (arg == "-ptc" || arg == "--print-token-count") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.n_print = std::stoi(argv[i]); + return true; + } + if (arg == "--ppl-output-type") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.ppl_output_type = std::stoi(argv[i]); + return true; + } + if (arg == "--hellaswag") { + params.hellaswag = true; + return true; + } + if (arg == "--hellaswag-tasks") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.hellaswag_tasks = std::stoi(argv[i]); + return true; + } + if (arg == "--winogrande") { + params.winogrande = true; + return true; + } + if (arg == "--winogrande-tasks") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.winogrande_tasks = std::stoi(argv[i]); + return true; + } + if (arg == "--multiple-choice") { + params.multiple_choice = true; + return true; + } + if (arg == "--multiple-choice-tasks") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.multiple_choice_tasks = std::stoi(argv[i]); + return true; + } + if (arg == "--kl-divergence") { + params.kl_divergence = true; + return true; + } + if (arg == "--ignore-eos") { + params.ignore_eos = true; + return true; + } + if (arg == "--penalize-nl") { + sparams.penalize_nl = true; + return true; + } + if (arg == "-l" || arg == "--logit-bias") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::stringstream ss(argv[i]); + llama_token key; + char sign; + std::string value_str; + try { + if (ss >> key && ss >> sign && std::getline(ss, value_str) && (sign == '+' || sign == '-')) { + sparams.logit_bias[key] = std::stof(value_str) * ((sign == '-') ? -1.0f : 1.0f); + } + else { + throw std::exception(); + } + } + catch (const std::exception&) { + invalid_param = true; + return true; + } + return true; + } + if (arg == "-h" || arg == "--help") { + gpt_print_usage(argc, argv, gpt_params()); + exit(0); + } + if (arg == "--version") { + fprintf(stderr, "version: %d (%s)\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT); + fprintf(stderr, "built with %s for %s\n", LLAMA_COMPILER, LLAMA_BUILD_TARGET); + exit(0); + } + if (arg == "--random-prompt") { + params.random_prompt = true; + return true; + } + if (arg == "--in-prefix-bos") { + params.input_prefix_bos = true; + return true; + } + if (arg == "--in-prefix") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.input_prefix = argv[i]; + return true; + } + if (arg == "--in-suffix") { + if (++i >= argc) { + invalid_param = true; + return true; + } + params.input_suffix = argv[i]; + return true; + } + if (arg == "--grammar") { + if (++i >= argc) { + invalid_param = true; + return true; + } + sparams.grammar = argv[i]; + return true; + } + if (arg == "--grammar-file") { + if (++i >= argc) { + invalid_param = true; + return true; + } + std::ifstream file(argv[i]); + if (!file) { + fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); + invalid_param = true; + return true; + } + std::copy( + std::istreambuf_iterator(file), + std::istreambuf_iterator(), + std::back_inserter(sparams.grammar) + ); + return true; + } + if (arg == "--override-kv") { + if (++i >= argc) { + invalid_param = true; + return true; + } + char* sep = strchr(argv[i], '='); + if (sep == nullptr || sep - argv[i] >= 128) { + fprintf(stderr, "error: Malformed KV override: %s\n", argv[i]); + invalid_param = true; + return true; + } + struct llama_model_kv_override kvo; + std::strncpy(kvo.key, argv[i], sep - argv[i]); + kvo.key[sep - argv[i]] = 0; + sep++; + if (strncmp(sep, "int:", 4) == 0) { + sep += 4; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; + kvo.int_value = std::atol(sep); + } + else if (strncmp(sep, "float:", 6) == 0) { + sep += 6; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; + kvo.float_value = std::atof(sep); + } + else if (strncmp(sep, "bool:", 5) == 0) { + sep += 5; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; + if (std::strcmp(sep, "true") == 0) { + kvo.bool_value = true; } - char * sep = strchr(argv[i], '='); - if (sep == nullptr || sep - argv[i] >= 128) { - fprintf(stderr, "error: Malformed KV override: %s\n", argv[i]); - invalid_param = true; - break; + else if (std::strcmp(sep, "false") == 0) { + kvo.bool_value = false; } - struct llama_model_kv_override kvo; - std::strncpy(kvo.key, argv[i], sep - argv[i]); - kvo.key[sep - argv[i]] = 0; - sep++; - if (strncmp(sep, "int:", 4) == 0) { - sep += 4; - kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; - kvo.int_value = std::atol(sep); - } else if (strncmp(sep, "float:", 6) == 0) { - sep += 6; - kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; - kvo.float_value = std::atof(sep); - } else if (strncmp(sep, "bool:", 5) == 0) { - sep += 5; - kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; - if (std::strcmp(sep, "true") == 0) { - kvo.bool_value = true; - } else if (std::strcmp(sep, "false") == 0) { - kvo.bool_value = false; - } else { - fprintf(stderr, "error: Invalid boolean value for KV override: %s\n", argv[i]); - invalid_param = true; - break; - } - } else { - fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]); + else { + fprintf(stderr, "error: Invalid boolean value for KV override: %s\n", argv[i]); invalid_param = true; - break; + return true; } - params.kv_overrides.push_back(kvo); + } + else { + fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]); + invalid_param = true; + return true; + } + params.kv_overrides.push_back(kvo); + return true; + } #ifndef LOG_DISABLE_LOGS - // Parse args for logging parameters - } else if ( log_param_single_parse( argv[i] ) ) { - // Do nothing, log_param_single_parse automatically does it's thing - // and returns if a match was found and parsed. - } else if ( log_param_pair_parse( /*check_but_dont_parse*/ true, argv[i] ) ) { - // We have a matching known parameter requiring an argument, - // now we need to check if there is anything after this argv - // and flag invalid_param or parse it. - if (++i >= argc) { - invalid_param = true; - break; - } - if( !log_param_pair_parse( /*check_but_dont_parse*/ false, argv[i-1], argv[i]) ) { - invalid_param = true; - break; - } - // End of Parse args for logging parameters + // Parse args for logging parameters + if (log_param_single_parse(argv[i])) { + // Do nothing, log_param_single_parse automatically does it's thing + // and returns if a match was found and parsed. + return true; + } + if (log_param_pair_parse( /*check_but_dont_parse*/ true, argv[i])) { + // We have a matching known parameter requiring an argument, + // now we need to check if there is anything after this argv + // and flag invalid_param or parse it. + if (++i >= argc) { + invalid_param = true; + return true; + } + if (!log_param_pair_parse( /*check_but_dont_parse*/ false, argv[i - 1], argv[i])) { + invalid_param = true; + return true; + } + return true; + } + // End of Parse args for logging parameters #endif // LOG_DISABLE_LOGS - } else { + + return false; +} + +bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) { + bool invalid_param = false; + std::string arg; + const std::string arg_prefix = "--"; + llama_sampling_params & sparams = params.sparams; + + for (int i = 1; i < argc; i++) { + arg = argv[i]; + if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) { + std::replace(arg.begin(), arg.end(), '_', '-'); + } + + if (!gpt_params_find_arg(argc, argv, arg, params, i, invalid_param)) { throw std::invalid_argument("error: unknown argument: " + arg); } } + if (invalid_param) { throw std::invalid_argument("error: invalid parameter for argument: " + arg); } + if (params.prompt_cache_all && (params.interactive || params.interactive_first || params.instruct)) { @@ -915,6 +1252,11 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) { throw std::invalid_argument("error: --prompt-cache-all not supported in interactive mode yet\n"); } + // short-hand to avoid specifying --hf-file -> default it to --model + if (!params.hf_repo.empty() && params.hf_file.empty()) { + params.hf_file = params.model; + } + if (params.escape) { process_escapes(params.prompt); process_escapes(params.input_prefix); @@ -1032,7 +1374,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { printf(" -dt N, --defrag-thold N\n"); printf(" KV cache defragmentation threshold (default: %.1f, < 0 - disabled)\n", params.defrag_thold); printf(" --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n"); - printf(" --no-penalize-nl do not penalize newline token\n"); + printf(" --penalize-nl penalize newline tokens\n"); printf(" --temp N temperature (default: %.1f)\n", (double)sparams.temp); printf(" --all-logits return logits for all tokens in the batch (default: disabled)\n"); printf(" --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n"); @@ -1096,12 +1438,28 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { printf(" --lora FNAME apply LoRA adapter (implies --no-mmap)\n"); printf(" --lora-scaled FNAME S apply LoRA adapter with user defined scaling S (implies --no-mmap)\n"); printf(" --lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter\n"); + printf(" --control-vector FNAME\n"); + printf(" add a control vector\n"); + printf(" --control-vector-scaled FNAME S\n"); + printf(" add a control vector with user defined scaling S\n"); + printf(" --control-vector-layer-range START END\n"); + printf(" layer range to apply the control vector(s) to, start and end inclusive\n"); printf(" -m FNAME, --model FNAME\n"); printf(" model path (default: %s)\n", params.model.c_str()); printf(" -md FNAME, --model-draft FNAME\n"); - printf(" draft model for speculative decoding\n"); + printf(" draft model for speculative decoding (default: unused)\n"); + printf(" -mu MODEL_URL, --model-url MODEL_URL\n"); + printf(" model download url (default: unused)\n"); + printf(" -hfr REPO, --hf-repo REPO\n"); + printf(" Hugging Face model repository (default: unused)\n"); + printf(" -hff FILE, --hf-file FILE\n"); + printf(" Hugging Face model file (default: unused)\n"); printf(" -ld LOGDIR, --logdir LOGDIR\n"); printf(" path under which to save YAML logs (no logging if unset)\n"); + printf(" -lcs FNAME, --lookup-cache-static FNAME\n"); + printf(" path to static lookup cache to use for lookup decoding (not updated by generation)\n"); + printf(" -lcd FNAME, --lookup-cache-dynamic FNAME\n"); + printf(" path to dynamic lookup cache to use for lookup decoding (updated by generation)\n"); printf(" --override-kv KEY=TYPE:VALUE\n"); printf(" advanced option to override model metadata by key. may be specified multiple times.\n"); printf(" types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false\n"); @@ -1143,6 +1501,77 @@ std::string gpt_random_prompt(std::mt19937 & rng) { GGML_UNREACHABLE(); } +// Validate if a filename is safe to use +// To validate a full path, split the path by the OS-specific path separator, and validate each part with this function +bool validate_file_name(const std::string & filename) { + if (!filename.length()) { + // Empty filename invalid + return false; + } + if (filename.length() > 255) { + // Limit at common largest possible filename on Linux filesystems + // to avoid unnecessary further validation + // (On systems with smaller limits it will be caught by the OS) + return false; + } + + std::u32string filename_utf32; + try { + std::wstring_convert, char32_t> converter; + filename_utf32 = converter.from_bytes(filename); + + // If the reverse conversion mismatches, it means overlong UTF-8 sequences were used, + // or invalid encodings were encountered. Reject such attempts + std::string filename_reencoded = converter.to_bytes(filename_utf32); + if (filename_reencoded != filename) { + return false; + } + } catch (const std::exception &) { + return false; + } + + // Check for forbidden codepoints: + // - Control characters + // - Unicode equivalents of illegal characters + // - UTF-16 surrogate pairs + // - UTF-8 replacement character + // - Byte order mark (BOM) + // - Illegal characters: / \ : * ? " < > | + for (char32_t c : filename_utf32) { + if (c <= 0x1F // Control characters (C0) + || c == 0x7F // Control characters (DEL) + || (c >= 0x80 && c <= 0x9F) // Control characters (C1) + || c == 0xFF0E // Fullwidth Full Stop (period equivalent) + || c == 0x2215 // Division Slash (forward slash equivalent) + || c == 0x2216 // Set Minus (backslash equivalent) + || (c >= 0xD800 && c <= 0xDFFF) // UTF-16 surrogate pairs + || c == 0xFFFD // Replacement Character (UTF-8) + || c == 0xFEFF // Byte Order Mark (BOM) + || c == '/' || c == '\\' || c == ':' || c == '*' // Illegal characters + || c == '?' || c == '"' || c == '<' || c == '>' || c == '|') { + return false; + } + } + + // Reject any leading or trailing ' ', or any trailing '.', these are stripped on Windows and will cause a different filename + // Unicode and other whitespace is not affected, only 0x20 space + if (filename.front() == ' ' || filename.back() == ' ' || filename.back() == '.') { + return false; + } + + // Reject any ".." (currently stricter than necessary, it should be fine to just check for == ".." instead) + if (filename.find("..") != std::string::npos) { + return false; + } + + // Reject "." + if (filename == ".") { + return false; + } + + return true; +} + // // String utils // @@ -1282,6 +1711,9 @@ static ggml_type kv_cache_type_from_str(const std::string & s) { if (s == "q4_1") { return GGML_TYPE_Q4_1; } + if (s == "iq4_nl") { + return GGML_TYPE_IQ4_NL; + } if (s == "q5_0") { return GGML_TYPE_Q5_0; } @@ -1343,10 +1775,364 @@ void llama_batch_add( batch.n_tokens++; } +#ifdef LLAMA_USE_CURL + +static bool llama_download_file(CURL * curl, const char * url, const char * path) { + bool force_download = false; + + // Set the URL, allow to follow http redirection + curl_easy_setopt(curl, CURLOPT_URL, url); + curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L); + +#if defined(_WIN32) + // CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of + // operating system. Currently implemented under MS-Windows. + curl_easy_setopt(curl, CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); +#endif + + // Check if the file already exists locally + struct stat model_file_info; + auto file_exists = (stat(path, &model_file_info) == 0); + + // If the file exists, check for ${path_model}.etag or ${path_model}.lastModified files + char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0}; + char etag_path[PATH_MAX] = {0}; + snprintf(etag_path, sizeof(etag_path), "%s.etag", path); + + char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0}; + char last_modified_path[PATH_MAX] = {0}; + snprintf(last_modified_path, sizeof(last_modified_path), "%s.lastModified", path); + + if (file_exists) { + auto * f_etag = fopen(etag_path, "r"); + if (f_etag) { + if (!fgets(etag, sizeof(etag), f_etag)) { + fprintf(stderr, "%s: unable to read file %s\n", __func__, etag_path); + } else { + fprintf(stderr, "%s: previous file found %s: %s\n", __func__, etag_path, etag); + } + fclose(f_etag); + } + + auto * f_last_modified = fopen(last_modified_path, "r"); + if (f_last_modified) { + if (!fgets(last_modified, sizeof(last_modified), f_last_modified)) { + fprintf(stderr, "%s: unable to read file %s\n", __func__, last_modified_path); + } else { + fprintf(stderr, "%s: previous file found %s: %s\n", __func__, last_modified_path, + last_modified); + } + fclose(f_last_modified); + } + } + + // Send a HEAD request to retrieve the etag and last-modified headers + struct llama_load_model_from_url_headers { + char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0}; + char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0}; + }; + llama_load_model_from_url_headers headers; + { + typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *); + auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t { + llama_load_model_from_url_headers *headers = (llama_load_model_from_url_headers *) userdata; + + // Convert header field name to lowercase + for (size_t i = 0; i < n_items && buffer[i] != ':'; ++i) { + buffer[i] = tolower(buffer[i]); + } + + const char * etag_prefix = "etag: "; + if (strncmp(buffer, etag_prefix, strlen(etag_prefix)) == 0) { + strncpy(headers->etag, buffer + strlen(etag_prefix), n_items - strlen(etag_prefix) - 2); // Remove CRLF + } + + const char * last_modified_prefix = "last-modified: "; + if (strncmp(buffer, last_modified_prefix, strlen(last_modified_prefix)) == 0) { + strncpy(headers->last_modified, buffer + strlen(last_modified_prefix), + n_items - strlen(last_modified_prefix) - 2); // Remove CRLF + } + return n_items; + }; + + curl_easy_setopt(curl, CURLOPT_NOBODY, 1L); // will trigger the HEAD verb + curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 1L); // hide head request progress + curl_easy_setopt(curl, CURLOPT_HEADERFUNCTION, static_cast(header_callback)); + curl_easy_setopt(curl, CURLOPT_HEADERDATA, &headers); + + CURLcode res = curl_easy_perform(curl); + if (res != CURLE_OK) { + curl_easy_cleanup(curl); + fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res)); + return false; + } + + long http_code = 0; + curl_easy_getinfo(curl, CURLINFO_RESPONSE_CODE, &http_code); + if (http_code != 200) { + // HEAD not supported, we don't know if the file has changed + // force trigger downloading + force_download = true; + fprintf(stderr, "%s: HEAD invalid http status code received: %ld\n", __func__, http_code); + } + } + + // If the ETag or the Last-Modified headers are different: trigger a new download + bool should_download = !file_exists + || force_download + || (strlen(headers.etag) > 0 && strcmp(etag, headers.etag) != 0) + || (strlen(headers.last_modified) > 0 && strcmp(last_modified, headers.last_modified) != 0); + if (should_download) { + char path_temporary[PATH_MAX] = {0}; + snprintf(path_temporary, sizeof(path_temporary), "%s.downloadInProgress", path); + if (file_exists) { + fprintf(stderr, "%s: deleting previous downloaded file: %s\n", __func__, path); + if (remove(path) != 0) { + curl_easy_cleanup(curl); + fprintf(stderr, "%s: unable to delete file: %s\n", __func__, path); + return false; + } + } + + // Set the output file + auto * outfile = fopen(path_temporary, "wb"); + if (!outfile) { + curl_easy_cleanup(curl); + fprintf(stderr, "%s: error opening local file for writing: %s\n", __func__, path); + return false; + } + + typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * data, size_t size, size_t nmemb, void * fd); + auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t { + return fwrite(data, size, nmemb, (FILE *)fd); + }; + curl_easy_setopt(curl, CURLOPT_NOBODY, 0L); + curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, static_cast(write_callback)); + curl_easy_setopt(curl, CURLOPT_WRITEDATA, outfile); + + // display download progress + curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L); + + // helper function to hide password in URL + auto llama_download_hide_password_in_url = [](const std::string & url) -> std::string { + std::size_t protocol_pos = url.find("://"); + if (protocol_pos == std::string::npos) { + return url; // Malformed URL + } + + std::size_t at_pos = url.find('@', protocol_pos + 3); + if (at_pos == std::string::npos) { + return url; // No password in URL + } + + return url.substr(0, protocol_pos + 3) + "********" + url.substr(at_pos); + }; + + // start the download + fprintf(stderr, "%s: downloading from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__, + llama_download_hide_password_in_url(url).c_str(), path, headers.etag, headers.last_modified); + auto res = curl_easy_perform(curl); + if (res != CURLE_OK) { + fclose(outfile); + curl_easy_cleanup(curl); + fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res)); + return false; + } + + long http_code = 0; + curl_easy_getinfo (curl, CURLINFO_RESPONSE_CODE, &http_code); + if (http_code < 200 || http_code >= 400) { + fclose(outfile); + curl_easy_cleanup(curl); + fprintf(stderr, "%s: invalid http status code received: %ld\n", __func__, http_code); + return false; + } + + // Clean up + fclose(outfile); + + // Write the new ETag to the .etag file + if (strlen(headers.etag) > 0) { + auto * etag_file = fopen(etag_path, "w"); + if (etag_file) { + fputs(headers.etag, etag_file); + fclose(etag_file); + fprintf(stderr, "%s: file etag saved %s: %s\n", __func__, etag_path, headers.etag); + } + } + + // Write the new lastModified to the .etag file + if (strlen(headers.last_modified) > 0) { + auto * last_modified_file = fopen(last_modified_path, "w"); + if (last_modified_file) { + fputs(headers.last_modified, last_modified_file); + fclose(last_modified_file); + fprintf(stderr, "%s: file last modified saved %s: %s\n", __func__, last_modified_path, + headers.last_modified); + } + } + + if (rename(path_temporary, path) != 0) { + curl_easy_cleanup(curl); + fprintf(stderr, "%s: unable to rename file: %s to %s\n", __func__, path_temporary, path); + return false; + } + } + + return true; +} + +struct llama_model * llama_load_model_from_url( + const char * model_url, + const char * path_model, + const struct llama_model_params & params) { + // Basic validation of the model_url + if (!model_url || strlen(model_url) == 0) { + fprintf(stderr, "%s: invalid model_url\n", __func__); + return NULL; + } + + // Initialize libcurl + auto * curl = curl_easy_init(); + + if (!curl) { + fprintf(stderr, "%s: error initializing libcurl\n", __func__); + return NULL; + } + + if (!llama_download_file(curl, model_url, path_model)) { + return NULL; + } + + // check for additional GGUFs split to download + int n_split = 0; + { + struct gguf_init_params gguf_params = { + /*.no_alloc = */ true, + /*.ctx = */ NULL, + }; + auto * ctx_gguf = gguf_init_from_file(path_model, gguf_params); + if (!ctx_gguf) { + fprintf(stderr, "\n%s: failed to load input GGUF from %s\n", __func__, path_model); + curl_easy_cleanup(curl); + return NULL; + } + + auto key_n_split = gguf_find_key(ctx_gguf, LLM_KV_SPLIT_COUNT_STR); + if (key_n_split >= 0) { + n_split = gguf_get_val_u16(ctx_gguf, key_n_split); + } + + gguf_free(ctx_gguf); + } + + curl_easy_cleanup(curl); + + if (n_split > 1) { + char split_prefix[PATH_MAX] = {0}; + char split_url_prefix[LLAMA_CURL_MAX_URL_LENGTH] = {0}; + + // Verify the first split file format + // and extract split URL and PATH prefixes + { + if (!llama_split_prefix(split_prefix, sizeof(split_prefix), path_model, 0, n_split)) { + fprintf(stderr, "\n%s: unexpected model file name: %s" + " n_split=%d\n", __func__, path_model, n_split); + return NULL; + } + + if (!llama_split_prefix(split_url_prefix, sizeof(split_url_prefix), model_url, 0, n_split)) { + fprintf(stderr, "\n%s: unexpected model url: %s" + " n_split=%d\n", __func__, model_url, n_split); + return NULL; + } + } + + // Prepare download in parallel + std::vector> futures_download; + for (int idx = 1; idx < n_split; idx++) { + futures_download.push_back(std::async(std::launch::async, [&split_prefix, &split_url_prefix, &n_split](int download_idx) -> bool { + char split_path[PATH_MAX] = {0}; + llama_split_path(split_path, sizeof(split_path), split_prefix, download_idx, n_split); + + char split_url[LLAMA_CURL_MAX_URL_LENGTH] = {0}; + llama_split_path(split_url, sizeof(split_url), split_url_prefix, download_idx, n_split); + + auto * curl = curl_easy_init(); + bool res = llama_download_file(curl, split_url, split_path); + curl_easy_cleanup(curl); + + return res; + }, idx)); + } + + // Wait for all downloads to complete + for (auto & f : futures_download) { + if (!f.get()) { + return NULL; + } + } + } + + return llama_load_model_from_file(path_model, params); +} + +struct llama_model * llama_load_model_from_hf( + const char * repo, + const char * model, + const char * path_model, + const struct llama_model_params & params) { + // construct hugging face model url: + // + // --repo ggml-org/models --file tinyllama-1.1b/ggml-model-f16.gguf + // https://huggingface.co/ggml-org/models/resolve/main/tinyllama-1.1b/ggml-model-f16.gguf + // + // --repo TheBloke/Mixtral-8x7B-v0.1-GGUF --file mixtral-8x7b-v0.1.Q4_K_M.gguf + // https://huggingface.co/TheBloke/Mixtral-8x7B-v0.1-GGUF/resolve/main/mixtral-8x7b-v0.1.Q4_K_M.gguf + // + + std::string model_url = "https://huggingface.co/"; + model_url += repo; + model_url += "/resolve/main/"; + model_url += model; + + return llama_load_model_from_url(model_url.c_str(), path_model, params); +} + +#else + +struct llama_model * llama_load_model_from_url( + const char * /*model_url*/, + const char * /*path_model*/, + const struct llama_model_params & /*params*/) { + fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__); + return nullptr; +} + +struct llama_model * llama_load_model_from_hf( + const char * /*repo*/, + const char * /*model*/, + const char * /*path_model*/, + const struct llama_model_params & /*params*/) { + fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__); + return nullptr; +} + +#endif // LLAMA_USE_CURL + std::tuple llama_init_from_gpt_params(gpt_params & params) { auto mparams = llama_model_params_from_gpt_params(params); - llama_model * model = llama_load_model_from_file(params.model.c_str(), mparams); + llama_model * model = nullptr; + + if (!params.hf_repo.empty() && !params.hf_file.empty()) { + model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), mparams); + } else if (!params.model_url.empty()) { + model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams); + } else { + model = llama_load_model_from_file(params.model.c_str(), mparams); + } + if (model == NULL) { fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str()); return std::make_tuple(nullptr, nullptr); @@ -1361,8 +2147,32 @@ std::tuple llama_init_from_gpt_par return std::make_tuple(nullptr, nullptr); } + if (!params.control_vectors.empty()) { + if (params.control_vector_layer_start <= 0) params.control_vector_layer_start = 1; + if (params.control_vector_layer_end <= 0) params.control_vector_layer_end = llama_n_layer(model); + + const auto cvec = llama_control_vector_load(params.control_vectors); + if (cvec.n_embd == -1) { + llama_free(lctx); + llama_free_model(model); + return std::make_tuple(nullptr, nullptr); + } + + int err = llama_control_vector_apply(lctx, + cvec.data.data(), + cvec.data.size(), + cvec.n_embd, + params.control_vector_layer_start, + params.control_vector_layer_end); + if (err) { + llama_free(lctx); + llama_free_model(model); + return std::make_tuple(nullptr, nullptr); + } + } + for (unsigned int i = 0; i < params.lora_adapter.size(); ++i) { - const std::string& lora_adapter = std::get<0>(params.lora_adapter[i]); + const std::string & lora_adapter = std::get<0>(params.lora_adapter[i]); float lora_scale = std::get<1>(params.lora_adapter[i]); int err = llama_model_apply_lora_from_file(model, lora_adapter.c_str(), @@ -1644,7 +2454,7 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l fprintf(stream, "cpu_has_avx512: %s\n", ggml_cpu_has_avx512() ? "true" : "false"); fprintf(stream, "cpu_has_avx512_vbmi: %s\n", ggml_cpu_has_avx512_vbmi() ? "true" : "false"); fprintf(stream, "cpu_has_avx512_vnni: %s\n", ggml_cpu_has_avx512_vnni() ? "true" : "false"); - fprintf(stream, "cpu_has_cublas: %s\n", ggml_cpu_has_cublas() ? "true" : "false"); + fprintf(stream, "cpu_has_cuda: %s\n", ggml_cpu_has_cuda() ? "true" : "false"); fprintf(stream, "cpu_has_vulkan: %s\n", ggml_cpu_has_vulkan() ? "true" : "false"); fprintf(stream, "cpu_has_clblast: %s\n", ggml_cpu_has_clblast() ? "true" : "false"); fprintf(stream, "cpu_has_kompute: %s\n", ggml_cpu_has_kompute() ? "true" : "false"); @@ -1746,7 +2556,7 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l fprintf(stream, "n_predict: %d # default: -1 (unlimited)\n", params.n_predict); fprintf(stream, "n_probs: %d # only used by server binary, default: 0\n", sparams.n_probs); fprintf(stream, "no_mmap: %s # default: false\n", !params.use_mmap ? "true" : "false"); - fprintf(stream, "no_penalize_nl: %s # default: false\n", !sparams.penalize_nl ? "true" : "false"); + fprintf(stream, "penalize_nl: %s # default: false\n", sparams.penalize_nl ? "true" : "false"); fprintf(stream, "ppl_output_type: %d # default: 0\n", params.ppl_output_type); fprintf(stream, "ppl_stride: %d # default: 0\n", params.ppl_stride); fprintf(stream, "presence_penalty: %f # default: 0.0\n", sparams.penalty_present); @@ -1878,3 +2688,173 @@ void llama_embd_normalize(const float * inp, float * out, int n) { } } +float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n){ + double sum = 0.0; + double sum1 = 0.0; + double sum2 = 0.0; + + for (int i = 0; i < n; i++) { + sum += embd1[i] * embd2[i]; + sum1 += embd1[i] * embd1[i]; + sum2 += embd2[i] * embd2[i]; + } + + return sum / (sqrt(sum1) * sqrt(sum2)); +} + +// +// Control vector utils +// + +static llama_control_vector_data llama_control_vector_load_one(const llama_control_vector_load_info & load_info) { + int32_t n_tensors; + + size_t n_bytes = 0; + + uint32_t max_direction_layer = 0; + + llama_control_vector_data result = { -1, {} }; + + // calculate size of ctx needed for tensors, ensure tensors are f32, and find max layer + { + struct ggml_init_params meta_params = { + /* .mem_size = */ ggml_tensor_overhead() * 128 + ggml_graph_overhead(), + /* .mem_buffer = */ nullptr, + /* .no_alloc = */ true, + }; + ggml_context * meta_ctx = ggml_init(meta_params); + struct gguf_init_params meta_gguf_params = { + /* .no_alloc = */ true, + /* .ctx = */ &meta_ctx, + }; + struct gguf_context * meta_ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), meta_gguf_params); + if (!meta_ctx_gguf) { + fprintf(stderr, "%s: failed to load control vector from %s\n", __func__, load_info.fname.c_str()); + ggml_free(meta_ctx); + return result; + } + + n_tensors = gguf_get_n_tensors(meta_ctx_gguf); + for (int i = 0; i < n_tensors; i++) { + std::string name = gguf_get_tensor_name(meta_ctx_gguf, i); + + // split on '.' + size_t dotpos = name.find('.'); + if (dotpos != std::string::npos && name.substr(0, dotpos) == "direction") { + try { + uint32_t layer = std::stoi(name.substr(dotpos + 1)); + if (layer == 0) { + fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str()); + ggml_free(meta_ctx); + gguf_free(meta_ctx_gguf); + return result; + } + if (layer > max_direction_layer) { + max_direction_layer = layer; + } + } catch (...) { + fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str()); + ggml_free(meta_ctx); + gguf_free(meta_ctx_gguf); + return result; + } + } + + struct ggml_tensor * tensor_meta = ggml_get_tensor(meta_ctx, name.c_str()); + if (tensor_meta->type != GGML_TYPE_F32 || ggml_n_dims(tensor_meta) != 1) { + fprintf(stderr, "%s: direction tensor invalid in %s\n", __func__, load_info.fname.c_str()); + ggml_free(meta_ctx); + gguf_free(meta_ctx_gguf); + return result; + } + if (result.n_embd == -1) { + result.n_embd = ggml_nelements(tensor_meta); + } else if (ggml_nelements(tensor_meta) != result.n_embd) { + fprintf(stderr, "%s: direction tensor sizes mismatched in %s\n", __func__, load_info.fname.c_str()); + ggml_free(meta_ctx); + gguf_free(meta_ctx_gguf); + return result; + } + n_bytes += ggml_nbytes(tensor_meta); + } + ggml_free(meta_ctx); + gguf_free(meta_ctx_gguf); + } + + if (n_tensors == 0) { + fprintf(stderr, "%s: no direction tensors found in %s\n", __func__, load_info.fname.c_str()); + return result; + } + + // load and scale tensors into final control vector context + struct ggml_init_params ggml_params = { + /* .mem_size = */ ggml_tensor_overhead() * n_tensors + n_bytes, + /* .mem_buffer = */ nullptr, + /* .no_alloc = */ false, + }; + struct ggml_context * ctx = ggml_init(ggml_params); + + struct gguf_init_params params = { + /*.no_alloc = */ false, + /*.ctx = */ &ctx, + }; + struct gguf_context * ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), params); + if (!ctx_gguf) { + fprintf(stderr, "%s: failed to load control vector from %s\n", __func__, load_info.fname.c_str()); + ggml_free(ctx); + return result; + } + + // do not store data for layer 0 (it's not used) + result.data.resize(result.n_embd * max_direction_layer); + + for (uint32_t il = 1; il <= max_direction_layer; il++) { + const std::string name = "direction." + std::to_string(il); + const ggml_tensor * tensor = ggml_get_tensor(ctx, name.c_str()); + + float * dst = result.data.data() + result.n_embd * (il - 1); + + if (tensor) { + const float * src = (const float *) tensor->data; + for (int j = 0; j < result.n_embd; j++) { + dst[j] = src[j] * load_info.strength; + } + } else { + for (int j = 0; j < result.n_embd; j++) { + dst[j] = 0.0f; + } + } + } + + return result; +} + +llama_control_vector_data llama_control_vector_load(const std::vector & load_infos) { + llama_control_vector_data result = { -1, {} }; + + for (const auto & info : load_infos) { + auto cur = llama_control_vector_load_one(info); + + if (cur.n_embd == -1) { + return result; + } + if (result.n_embd != -1 && (result.n_embd != cur.n_embd || result.data.size() != cur.data.size())) { + fprintf(stderr, "%s: control vector in %s does not match previous vector dimensions\n", __func__, info.fname.c_str()); + return result; + } + + if (result.n_embd == -1) { + result = std::move(cur); + } else { + for (size_t i = 0; i < cur.data.size(); i++) { + result.data[i] += cur.data[i]; + } + } + } + + if (result.n_embd == -1) { + fprintf(stderr, "%s: no vectors passed\n", __func__); + } + + return result; +} diff --git a/common/common.h b/common/common.h index 6dc9395a41c45..e023b503dbd30 100644 --- a/common/common.h +++ b/common/common.h @@ -31,10 +31,15 @@ fprintf(stderr, "%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET); \ } while(0) +// build info + +struct llama_control_vector_load_info; + +int32_t get_num_physical_cores(); + // // CLI argument parsing // -int32_t get_num_physical_cores(); struct gpt_params { uint32_t seed = LLAMA_DEFAULT_SEED; // RNG seed @@ -99,17 +104,22 @@ struct gpt_params { // // sampling parameters struct llama_sampling_params sparams; - std::string model = "models/7B/ggml-model-f16.gguf"; // model path - std::string model_draft = ""; // draft model for speculative decoding - std::string model_alias = "unknown"; // model alias - std::string prompt = ""; - std::string prompt_file = ""; // store the external prompt file name - std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state - std::string input_prefix = ""; // string to prefix user inputs with - std::string input_suffix = ""; // string to suffix user inputs with + std::string model = "models/7B/ggml-model-f16.gguf"; // model path + std::string model_draft = ""; // draft model for speculative decoding + std::string model_alias = "unknown"; // model alias + std::string model_url = ""; // model url to download + std::string hf_repo = ""; // HF repo + std::string hf_file = ""; // HF file + std::string prompt = ""; + std::string prompt_file = ""; // store the external prompt file name + std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state + std::string input_prefix = ""; // string to prefix user inputs with + std::string input_suffix = ""; // string to suffix user inputs with std::vector antiprompt; // string upon seeing which more user input is prompted - std::string logdir = ""; // directory in which to save YAML log files - std::string logits_file = ""; // file for saving *all* logits + std::string logdir = ""; // directory in which to save YAML log files + std::string lookup_cache_static = ""; // path of static ngram cache file for lookup decoding + std::string lookup_cache_dynamic = ""; // path of dynamic ngram cache file for lookup decoding + std::string logits_file = ""; // file for saving *all* logits std::vector kv_overrides; @@ -117,6 +127,11 @@ struct gpt_params { std::vector> lora_adapter; // lora adapter path with user defined scale std::string lora_base = ""; // base model path for the lora adapter + std::vector control_vectors; // control vector with user defined scale + + int32_t control_vector_layer_start = -1; // layer range for control vector + int32_t control_vector_layer_end = -1; // layer range for control vector + int ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. int ppl_output_type = 0; // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line // (which is more convenient to use for plotting) @@ -144,7 +159,7 @@ struct gpt_params { bool interactive_first = false; // wait for user input immediately bool multiline_input = false; // reverse the usage of `\` bool simple_io = false; // improves compatibility with subprocesses and limited consoles - bool cont_batching = false; // insert new sequences for decoding on-the-fly + bool cont_batching = true; // insert new sequences for decoding on-the-fly bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix bool ignore_eos = false; // ignore generated EOS tokens @@ -172,12 +187,16 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params); void gpt_print_usage(int argc, char ** argv, const gpt_params & params); +bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param); + std::string get_system_info(const gpt_params & params); std::string gpt_random_prompt(std::mt19937 & rng); void process_escapes(std::string& input); +bool validate_file_name(const std::string & filename); + // // String utils // @@ -197,6 +216,9 @@ std::tuple llama_init_from_gpt_par struct llama_model_params llama_model_params_from_gpt_params (const gpt_params & params); struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params); +struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model, const struct llama_model_params & params); +struct llama_model * llama_load_model_from_hf(const char * repo, const char * file, const char * path_model, const struct llama_model_params & params); + // Batch utils void llama_batch_clear(struct llama_batch & batch); @@ -282,3 +304,32 @@ void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40 void llama_embd_normalize(const float * inp, float * out, int n); +float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n); + +// +// Control vector utils +// + +struct llama_control_vector_data { + int n_embd; + + // stores data for layers [1, n_layer] where n_layer = data.size() / n_embd + std::vector data; +}; + +struct llama_control_vector_load_info { + float strength; + + std::string fname; +}; + +// Load control vectors, scale each by strength, and add them together. +// On error, returns {-1, empty} +llama_control_vector_data llama_control_vector_load(const std::vector & load_infos); + +// +// Split utils +// +static const char * const LLM_KV_SPLIT_NO_STR = "split.no"; +static const char * const LLM_KV_SPLIT_COUNT_STR = "split.count"; +static const char * const LLM_KV_SPLIT_TENSORS_COUNT_STR = "split.tensors.count"; diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp new file mode 100644 index 0000000000000..0e468034642f7 --- /dev/null +++ b/common/json-schema-to-grammar.cpp @@ -0,0 +1,721 @@ +#include "json-schema-to-grammar.h" +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using json = nlohmann::ordered_json; + +const std::string SPACE_RULE = "\" \"?"; + +std::unordered_map PRIMITIVE_RULES = { + {"boolean", "(\"true\" | \"false\") space"}, + {"number", "(\"-\"? ([0-9] | [1-9] [0-9]*)) (\".\" [0-9]+)? ([eE] [-+]? [0-9]+)? space"}, + {"integer", "(\"-\"? ([0-9] | [1-9] [0-9]*)) space"}, + {"value", "object | array | string | number | boolean"}, + {"object", "\"{\" space ( string \":\" space value (\",\" space string \":\" space value)* )? \"}\" space"}, + {"array", "\"[\" space ( value (\",\" space value)* )? \"]\" space"}, + {"uuid", "\"\\\"\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] " + "\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] " + "\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] " + "\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] " + "\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] \"\\\"\" space"}, + {"string", " \"\\\"\" (\n" + " [^\"\\\\] |\n" + " \"\\\\\" ([\"\\\\/bfnrt] | \"u\" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F])\n" + " )* \"\\\"\" space"}, + {"null", "\"null\" space"} +}; +std::vector OBJECT_RULE_NAMES = {"object", "array", "string", "number", "boolean", "null", "value"}; + +std::unordered_map DATE_RULES = { + {"date", "[0-9] [0-9] [0-9] [0-9] \"-\" ( \"0\" [1-9] | \"1\" [0-2] ) \"-\" ( \"0\" [1-9] | [1-2] [0-9] | \"3\" [0-1] )"}, + {"time", "([01] [0-9] | \"2\" [0-3]) \":\" [0-5] [0-9] \":\" [0-5] [0-9] ( \".\" [0-9] [0-9] [0-9] )? ( \"Z\" | ( \"+\" | \"-\" ) ( [01] [0-9] | \"2\" [0-3] ) \":\" [0-5] [0-9] )"}, + {"date-time", "date \"T\" time"}, + {"date-string", "\"\\\"\" date \"\\\"\" space"}, + {"time-string", "\"\\\"\" time \"\\\"\" space"}, + {"date-time-string", "\"\\\"\" date-time \"\\\"\" space"} +}; + +static bool is_reserved_name(const std::string & name) { + static std::unordered_set RESERVED_NAMES; + if (RESERVED_NAMES.empty()) { + RESERVED_NAMES.insert("root"); + for (const auto &p : PRIMITIVE_RULES) RESERVED_NAMES.insert(p.first); + for (const auto &p : DATE_RULES) RESERVED_NAMES.insert(p.first); + } + return RESERVED_NAMES.find(name) != RESERVED_NAMES.end(); +} + +std::regex INVALID_RULE_CHARS_RE("[^a-zA-Z0-9-]+"); +std::regex GRAMMAR_LITERAL_ESCAPE_RE("[\r\n\"]"); +std::regex GRAMMAR_RANGE_LITERAL_ESCAPE_RE("[\r\n\"\\]\\-\\\\]"); +std::unordered_map GRAMMAR_LITERAL_ESCAPES = { + {'\r', "\\r"}, {'\n', "\\n"}, {'"', "\\\""}, {'-', "\\-"}, {']', "\\]"} +}; + +std::unordered_set NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'}; +std::unordered_set ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'[', ']', '(', ')', '|', '{', '}', '*', '+', '?'}; + +template +std::string join(Iterator begin, Iterator end, const std::string & separator) { + std::ostringstream result; + if (begin != end) { + result << *begin; + for (Iterator it = begin + 1; it != end; ++it) { + result << separator << *it; + } + } + return result.str(); +} + +static std::vector split(const std::string & str, const std::string & delimiter) { + std::vector tokens; + size_t start = 0; + size_t end = str.find(delimiter); + + while (end != std::string::npos) { + tokens.push_back(str.substr(start, end - start)); + start = end + delimiter.length(); + end = str.find(delimiter, start); + } + + tokens.push_back(str.substr(start)); + + return tokens; +} + +static std::string repeat(const std::string & str, size_t n) { + if (n == 0) { + return ""; + } + + std::string result; + result.reserve(str.length() * n); + + for (size_t i = 0; i < n; ++i) { + result += str; + } + + return result; +} + +static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function & replacement) { + std::smatch match; + std::string result; + + std::string::const_iterator searchStart(input.cbegin()); + std::string::const_iterator searchEnd(input.cend()); + + while (std::regex_search(searchStart, searchEnd, match, regex)) { + result.append(searchStart, searchStart + match.position()); + result.append(replacement(match)); + searchStart = match.suffix().first; + } + + result.append(searchStart, searchEnd); + + return result; +} + +static std::string format_literal(const std::string & literal) { + std::string escaped = replacePattern(literal, GRAMMAR_LITERAL_ESCAPE_RE, [&](const std::smatch & match) { + char c = match.str()[0]; + return GRAMMAR_LITERAL_ESCAPES.at(c); + }); + return "\"" + escaped + "\""; +} + + +class SchemaConverter { +private: + std::function _fetch_json; + bool _dotall; + std::map _rules; + std::unordered_map _refs; + std::unordered_set _refs_being_resolved; + std::vector _errors; + std::vector _warnings; + + std::string _add_rule(const std::string & name, const std::string & rule) { + std::string esc_name = regex_replace(name, INVALID_RULE_CHARS_RE, "-"); + if (_rules.find(esc_name) == _rules.end() || _rules[esc_name] == rule) { + _rules[esc_name] = rule; + return esc_name; + } else { + int i = 0; + while (_rules.find(esc_name + std::to_string(i)) != _rules.end() && _rules[esc_name + std::to_string(i)] != rule) { + i++; + } + std::string key = esc_name + std::to_string(i); + _rules[key] = rule; + return key; + } + } + + std::string _generate_union_rule(const std::string & name, const std::vector & alt_schemas) { + std::vector rules; + for (size_t i = 0; i < alt_schemas.size(); i++) { + rules.push_back(visit(alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i))); + } + return join(rules.begin(), rules.end(), " | "); + } + + std::string _visit_pattern(const std::string & pattern, const std::string & name) { + if (!(pattern.front() == '^' && pattern.back() == '$')) { + _errors.push_back("Pattern must start with '^' and end with '$'"); + return ""; + } + std::string sub_pattern = pattern.substr(1, pattern.length() - 2); + std::unordered_map sub_rule_ids; + + size_t i = 0; + size_t length = sub_pattern.length(); + + using literal_or_rule = std::pair; + auto to_rule = [&](const literal_or_rule & ls) { + auto is_literal = ls.second; + auto s = ls.first; + return is_literal ? "\"" + s + "\"" : s; + }; + std::function transform = [&]() -> literal_or_rule { + size_t start = i; + std::vector seq; + + auto get_dot = [&]() { + std::string rule; + if (_dotall) { + rule = "[\\U00000000-\\U0010FFFF]"; + } else { + rule = "[\\U00000000-\\x09\\x0B\\x0C\\x0E-\\U0010FFFF]"; + } + return _add_rule("dot", rule); + }; + + // Joins the sequence, merging consecutive literals together. + auto join_seq = [&]() { + std::vector ret; + + std::string literal; + auto flush_literal = [&]() { + if (literal.empty()) { + return false; + } + ret.push_back(std::make_pair(literal, true)); + literal.clear(); + return true; + }; + + for (const auto & item : seq) { + auto is_literal = item.second; + if (is_literal) { + literal += item.first; + } else { + flush_literal(); + ret.push_back(item); + } + } + flush_literal(); + + std::vector results; + for (const auto & item : ret) { + results.push_back(to_rule(item)); + } + return std::make_pair(join(results.begin(), results.end(), " "), false); + }; + + while (i < length) { + char c = sub_pattern[i]; + if (c == '.') { + seq.push_back(std::make_pair(get_dot(), false)); + i++; + } else if (c == '(') { + i++; + if (i < length) { + if (sub_pattern[i] == '?') { + _warnings.push_back("Unsupported pattern syntax"); + } + } + seq.push_back(std::make_pair("(" + to_rule(transform()) + ")", false)); + } else if (c == ')') { + i++; + if (start > 0 && sub_pattern[start - 1] != '(') { + _errors.push_back("Unbalanced parentheses"); + } + return join_seq(); + } else if (c == '[') { + std::string square_brackets = std::string(1, c); + i++; + while (i < length && sub_pattern[i] != ']') { + if (sub_pattern[i] == '\\') { + square_brackets += sub_pattern.substr(i, 2); + i += 2; + } else { + square_brackets += sub_pattern[i]; + i++; + } + } + if (i >= length) { + _errors.push_back("Unbalanced square brackets"); + } + square_brackets += ']'; + i++; + seq.push_back(std::make_pair(square_brackets, false)); + } else if (c == '|') { + seq.push_back(std::make_pair("|", false)); + i++; + } else if (c == '*' || c == '+' || c == '?') { + seq.back() = std::make_pair(to_rule(seq.back()) + c, false); + i++; + } else if (c == '{') { + std::string curly_brackets = std::string(1, c); + i++; + while (i < length && sub_pattern[i] != '}') { + curly_brackets += sub_pattern[i]; + i++; + } + if (i >= length) { + _errors.push_back("Unbalanced curly brackets"); + } + curly_brackets += '}'; + i++; + auto nums = split(curly_brackets.substr(1, curly_brackets.length() - 2), ","); + int min_times = 0; + int max_times = std::numeric_limits::max(); + try { + if (nums.size() == 1) { + min_times = max_times = std::stoi(nums[0]); + } else if (nums.size() != 2) { + _errors.push_back("Wrong number of values in curly brackets"); + } else { + if (!nums[0].empty()) { + min_times = std::stoi(nums[0]); + } + if (!nums[1].empty()) { + max_times = std::stoi(nums[1]); + } + } + } catch (const std::invalid_argument & e) { + _errors.push_back("Invalid number in curly brackets"); + return std::make_pair("", false); + } + auto &last = seq.back(); + auto &sub = last.first; + auto sub_is_literal = last.second; + + if (min_times == 0 && max_times == std::numeric_limits::max()) { + sub += "*"; + } else if (min_times == 0 && max_times == 1) { + sub += "?"; + } else if (min_times == 1 && max_times == std::numeric_limits::max()) { + sub += "+"; + } else { + if (!sub_is_literal) { + std::string & sub_id = sub_rule_ids[sub]; + if (sub_id.empty()) { + sub_id = _add_rule(name + "-" + std::to_string(sub_rule_ids.size()), sub); + } + sub = sub_id; + } + std::string result; + if (sub_is_literal && min_times > 0) { + result = "\"" + repeat(sub.substr(1, sub.length() - 2), min_times) + "\""; + } else { + for (int j = 0; j < min_times; j++) { + if (j > 0) { + result += " "; + } + result += sub; + } + } + if (min_times > 0 && min_times < max_times) { + result += " "; + } + if (max_times == std::numeric_limits::max()) { + result += sub + "*"; + } else { + for (int j = min_times; j < max_times; j++) { + if (j > min_times) { + result += " "; + } + result += sub + "?"; + } + } + seq.back().first = result; + seq.back().second = false; + } + } else { + std::string literal; + auto is_non_literal = [&](char c) { + return NON_LITERAL_SET.find(c) != NON_LITERAL_SET.end(); + }; + while (i < length) { + if (sub_pattern[i] == '\\' && i < length - 1) { + char next = sub_pattern[i + 1]; + if (ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.find(next) != ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.end()) { + i++; + literal += sub_pattern[i]; + i++; + } else { + literal += sub_pattern.substr(i, 2); + i += 2; + } + } else if (sub_pattern[i] == '"') { + literal += "\\\""; + i++; + } else if (!is_non_literal(sub_pattern[i]) && + (i == length - 1 || literal.empty() || sub_pattern[i + 1] == '.' || !is_non_literal(sub_pattern[i + 1]))) { + literal += sub_pattern[i]; + i++; + } else { + break; + } + } + if (!literal.empty()) { + seq.push_back(std::make_pair(literal, true)); + } + } + } + return join_seq(); + }; + return _add_rule(name, "\"\\\"\" " + to_rule(transform()) + " \"\\\"\" space"); + } + + std::string _resolve_ref(const std::string & ref) { + std::string ref_name = ref.substr(ref.find_last_of('/') + 1); + if (_rules.find(ref_name) == _rules.end() && _refs_being_resolved.find(ref) == _refs_being_resolved.end()) { + _refs_being_resolved.insert(ref); + json resolved = _refs[ref]; + ref_name = visit(resolved, ref_name); + _refs_being_resolved.erase(ref); + } + return ref_name; + } + + std::string _build_object_rule( + const std::vector> & properties, + const std::unordered_set & required, + const std::string & name, + const json & additional_properties) + { + std::vector required_props; + std::vector optional_props; + std::unordered_map prop_kv_rule_names; + for (const auto & kv : properties) { + const auto &prop_name = kv.first; + const auto &prop_schema = kv.second; + + std::string prop_rule_name = visit(prop_schema, name + (name.empty() ? "" : "-") + prop_name); + prop_kv_rule_names[prop_name] = _add_rule( + name + (name.empty() ? "" : "-") + prop_name + "-kv", + format_literal(json(prop_name).dump()) + " space \":\" space " + prop_rule_name + ); + if (required.find(prop_name) != required.end()) { + required_props.push_back(prop_name); + } else { + optional_props.push_back(prop_name); + } + } + if (additional_properties.is_object() || (additional_properties.is_boolean() && additional_properties.get())) { + std::string sub_name = name + (name.empty() ? "" : "-") + "additional"; + std::string value_rule = visit(additional_properties.is_object() ? additional_properties : json::object(), sub_name + "-value"); + std::string kv_rule = _add_rule(sub_name + "-kv", _add_rule("string", PRIMITIVE_RULES.at("string")) + " \":\" space " + value_rule); + prop_kv_rule_names["*"] = kv_rule; + optional_props.push_back("*"); + } + + std::string rule = "\"{\" space "; + for (size_t i = 0; i < required_props.size(); i++) { + if (i > 0) { + rule += " \",\" space "; + } + rule += prop_kv_rule_names[required_props[i]]; + } + + if (!optional_props.empty()) { + rule += " ("; + if (!required_props.empty()) { + rule += " \",\" space ( "; + } + + std::function &, bool)> get_recursive_refs = [&](const std::vector & ks, bool first_is_optional) { + std::string res; + if (ks.empty()) { + return res; + } + std::string k = ks[0]; + std::string kv_rule_name = prop_kv_rule_names[k]; + if (k == "*") { + res = _add_rule( + name + (name.empty() ? "" : "-") + "additional-kvs", + kv_rule_name + " ( \",\" space " + kv_rule_name + " )*" + ); + } else if (first_is_optional) { + res = "( \",\" space " + kv_rule_name + " )?"; + } else { + res = kv_rule_name; + } + if (ks.size() > 1) { + res += " " + _add_rule( + name + (name.empty() ? "" : "-") + k + "-rest", + get_recursive_refs(std::vector(ks.begin() + 1, ks.end()), true) + ); + } + return res; + }; + + for (size_t i = 0; i < optional_props.size(); i++) { + if (i > 0) { + rule += " | "; + } + rule += get_recursive_refs(std::vector(optional_props.begin() + i, optional_props.end()), false); + } + if (!required_props.empty()) { + rule += " )"; + } + rule += " )?"; + } + + rule += " \"}\" space"; + + return rule; + } + +public: + SchemaConverter( + const std::function & fetch_json, + bool dotall) + : _fetch_json(fetch_json), _dotall(dotall) + { + _rules["space"] = SPACE_RULE; + } + + void resolve_refs(json & schema, const std::string & url) { + /* + * Resolves all $ref fields in the given schema, fetching any remote schemas, + * replacing each $ref with absolute reference URL and populates _refs with the + * respective referenced (sub)schema dictionaries. + */ + std::function visit_refs = [&](json & n) { + if (n.is_array()) { + for (auto & x : n) { + visit_refs(x); + } + } else if (n.is_object()) { + if (n.contains("$ref")) { + std::string ref = n["$ref"]; + if (_refs.find(ref) == _refs.end()) { + json target; + if (ref.find("https://") == 0) { + std::string base_url = ref.substr(0, ref.find('#')); + auto it = _refs.find(base_url); + if (it != _refs.end()) { + target = it->second; + } else { + // Fetch the referenced schema and resolve its refs + auto referenced = _fetch_json(ref); + resolve_refs(referenced, base_url); + _refs[base_url] = referenced; + } + if (ref.find('#') == std::string::npos || ref.substr(ref.find('#') + 1).empty()) { + return; + } + } else if (ref.find("#/") == 0) { + target = schema; + n["$ref"] = url + ref; + ref = url + ref; + } else { + _errors.push_back("Unsupported ref: " + ref); + return; + } + std::string pointer = ref.substr(ref.find('#') + 1); + std::vector tokens = split(pointer, "/"); + for (size_t i = 1; i < tokens.size(); ++i) { + std::string sel = tokens[i]; + if (target.is_null() || !target.contains(sel)) { + _errors.push_back("Error resolving ref " + ref + ": " + sel + " not in " + target.dump()); + return; + } + target = target[sel]; + } + _refs[ref] = target; + } + } else { + for (auto & kv : n.items()) { + visit_refs(kv.value()); + } + } + } + }; + + visit_refs(schema); + } + + std::string _generate_constant_rule(const json & value) { + return format_literal(value.dump()); + } + + std::string visit(const json & schema, const std::string & name) { + json schema_type = schema.contains("type") ? schema["type"] : json(); + std::string schema_format = schema.contains("format") ? schema["format"].get() : ""; + std::string rule_name = is_reserved_name(name) ? name + "-" : name.empty() ? "root" : name; + + if (schema.contains("$ref")) { + return _add_rule(rule_name, _resolve_ref(schema["$ref"])); + } else if (schema.contains("oneOf") || schema.contains("anyOf")) { + std::vector alt_schemas = schema.contains("oneOf") ? schema["oneOf"].get>() : schema["anyOf"].get>(); + return _add_rule(rule_name, _generate_union_rule(name, alt_schemas)); + } else if (schema_type.is_array()) { + std::vector schema_types; + for (const auto & t : schema_type) { + schema_types.push_back({{"type", t}}); + } + return _add_rule(rule_name, _generate_union_rule(name, schema_types)); + } else if (schema.contains("const")) { + return _add_rule(rule_name, _generate_constant_rule(schema["const"])); + } else if (schema.contains("enum")) { + std::vector enum_values; + for (const auto & v : schema["enum"]) { + enum_values.push_back(_generate_constant_rule(v)); + } + return _add_rule(rule_name, join(enum_values.begin(), enum_values.end(), " | ")); + } else if ((schema_type.is_null() || schema_type == "object") + && (schema.contains("properties") || + (schema.contains("additionalProperties") && schema["additionalProperties"] != true))) { + std::unordered_set required; + if (schema.contains("required") && schema["required"].is_array()) { + for (const auto & item : schema["required"]) { + if (item.is_string()) { + required.insert(item.get()); + } + } + } + std::vector> properties; + if (schema.contains("properties")) { + for (const auto & prop : schema["properties"].items()) { + properties.emplace_back(prop.key(), prop.value()); + } + } + return _add_rule(rule_name, + _build_object_rule( + properties, required, name, + schema.contains("additionalProperties") ? schema["additionalProperties"] : json())); + } else if ((schema_type.is_null() || schema_type == "object") && schema.contains("allOf")) { + std::unordered_set required; + std::vector> properties; + std::string hybrid_name = name; + std::function add_component = [&](const json & comp_schema, bool is_required) { + if (comp_schema.contains("$ref")) { + add_component(_refs[comp_schema["$ref"]], is_required); + } else if (comp_schema.contains("properties")) { + for (const auto & prop : comp_schema["properties"].items()) { + properties.emplace_back(prop.key(), prop.value()); + if (is_required) { + required.insert(prop.key()); + } + } + } else { + // todo warning + } + }; + for (auto & t : schema["allOf"]) { + if (t.contains("anyOf")) { + for (auto & tt : t["anyOf"]) { + add_component(tt, false); + } + } else { + add_component(t, true); + } + } + return _add_rule(rule_name, _build_object_rule(properties, required, hybrid_name, json())); + } else if ((schema_type.is_null() || schema_type == "array") && (schema.contains("items") || schema.contains("prefixItems"))) { + json items = schema.contains("items") ? schema["items"] : schema["prefixItems"]; + if (items.is_array()) { + std::string rule = "\"[\" space "; + for (size_t i = 0; i < items.size(); i++) { + if (i > 0) { + rule += " \",\" space "; + } + rule += visit(items[i], name + (name.empty() ? "" : "-") + "tuple-" + std::to_string(i)); + } + rule += " \"]\" space"; + return _add_rule(rule_name, rule); + } else { + std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item"); + std::string list_item_operator = "( \",\" space " + item_rule_name + " )"; + std::string successive_items; + int min_items = schema.contains("minItems") ? schema["minItems"].get() : 0; + json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json(); + int max_items = max_items_json.is_number_integer() ? max_items_json.get() : -1; + if (min_items > 0) { + successive_items += repeat(list_item_operator, min_items - 1); + min_items--; + } + if (max_items >= 0 && max_items > min_items) { + successive_items += repeat(list_item_operator + "?", max_items - min_items - 1); + } else { + successive_items += list_item_operator + "*"; + } + std::string rule; + if (min_items == 0) { + rule = "\"[\" space ( " + item_rule_name + " " + successive_items + " )? \"]\" space"; + } else { + rule = "\"[\" space " + item_rule_name + " " + successive_items + " \"]\" space"; + } + return _add_rule(rule_name, rule); + } + } else if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) { + return _visit_pattern(schema["pattern"], rule_name); + } else if ((schema_type.is_null() || schema_type == "string") && std::regex_match(schema_format, std::regex("^uuid[1-5]?$"))) { + return _add_rule(rule_name == "root" ? "root" : schema_format, PRIMITIVE_RULES.at("uuid")); + } else if ((schema_type.is_null() || schema_type == "string") && DATE_RULES.find(schema_format) != DATE_RULES.end()) { + for (const auto & kv : DATE_RULES) { + _add_rule(kv.first, kv.second); + } + return schema_format + "-string"; + } else if (schema.empty() || schema_type == "object") { + for (const auto & n : OBJECT_RULE_NAMES) { + _add_rule(n, PRIMITIVE_RULES.at(n)); + } + return _add_rule(rule_name, "object"); + } else { + if (!schema_type.is_string() || PRIMITIVE_RULES.find(schema_type.get()) == PRIMITIVE_RULES.end()) { + _errors.push_back("Unrecognized schema: " + schema.dump()); + return ""; + } + // TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero + return _add_rule(rule_name == "root" ? "root" : schema_type.get(), PRIMITIVE_RULES.at(schema_type.get())); + } + } + + void check_errors() { + if (!_errors.empty()) { + throw std::runtime_error("JSON schema conversion failed:\n" + join(_errors.begin(), _errors.end(), "\n")); + } + if (!_warnings.empty()) { + fprintf(stderr, "WARNING: JSON schema conversion was incomplete: %s\n", join(_warnings.begin(), _warnings.end(), "; ").c_str()); + } + } + + std::string format_grammar() { + std::stringstream ss; + for (const auto & kv : _rules) { + ss << kv.first << " ::= " << kv.second << std::endl; + } + return ss.str(); + } +}; + +std::string json_schema_to_grammar(const json & schema) { + SchemaConverter converter([](const std::string &) { return json::object(); }, /* dotall= */ false); + auto copy = schema; + converter.resolve_refs(copy, "input"); + converter.visit(copy, ""); + converter.check_errors(); + return converter.format_grammar(); +} diff --git a/common/json-schema-to-grammar.h b/common/json-schema-to-grammar.h new file mode 100644 index 0000000000000..e1abed3037582 --- /dev/null +++ b/common/json-schema-to-grammar.h @@ -0,0 +1,4 @@ +#pragma once +#include "json.hpp" + +std::string json_schema_to_grammar(const nlohmann::ordered_json& schema); diff --git a/examples/server/json.hpp b/common/json.hpp similarity index 93% rename from examples/server/json.hpp rename to common/json.hpp index ea945f346d67b..a858728c4ceb8 100644 --- a/examples/server/json.hpp +++ b/common/json.hpp @@ -1,9 +1,9 @@ // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT /****************************************************************************\ @@ -27,7 +27,6 @@ #endif // JSON_NO_IO #include // random_access_iterator_tag #include // unique_ptr -#include // accumulate #include // string, stoi, to_string #include // declval, forward, move, pair, swap #include // vector @@ -35,10 +34,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -48,10 +47,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -60,7 +59,7 @@ #ifndef JSON_SKIP_LIBRARY_VERSION_CHECK #if defined(NLOHMANN_JSON_VERSION_MAJOR) && defined(NLOHMANN_JSON_VERSION_MINOR) && defined(NLOHMANN_JSON_VERSION_PATCH) - #if NLOHMANN_JSON_VERSION_MAJOR != 3 || NLOHMANN_JSON_VERSION_MINOR != 11 || NLOHMANN_JSON_VERSION_PATCH != 2 + #if NLOHMANN_JSON_VERSION_MAJOR != 3 || NLOHMANN_JSON_VERSION_MINOR != 11 || NLOHMANN_JSON_VERSION_PATCH != 3 #warning "Already included a different version of the library!" #endif #endif @@ -68,7 +67,7 @@ #define NLOHMANN_JSON_VERSION_MAJOR 3 // NOLINT(modernize-macro-to-enum) #define NLOHMANN_JSON_VERSION_MINOR 11 // NOLINT(modernize-macro-to-enum) -#define NLOHMANN_JSON_VERSION_PATCH 2 // NOLINT(modernize-macro-to-enum) +#define NLOHMANN_JSON_VERSION_PATCH 3 // NOLINT(modernize-macro-to-enum) #ifndef JSON_DIAGNOSTICS #define JSON_DIAGNOSTICS 0 @@ -150,10 +149,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -173,16 +172,19 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT #include // nullptr_t #include // exception +#if JSON_DIAGNOSTICS + #include // accumulate +#endif #include // runtime_error #include // to_string #include // vector @@ -190,10 +192,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -206,10 +208,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -218,10 +220,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -231,10 +233,10 @@ // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -318,10 +320,10 @@ NLOHMANN_JSON_NAMESPACE_END // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-FileCopyrightText: 2016-2021 Evan Nemerson // SPDX-License-Identifier: MIT @@ -2483,6 +2485,14 @@ JSON_HEDLEY_DIAGNOSTIC_POP #endif #endif +#ifndef JSON_HAS_STATIC_RTTI + #if !defined(_HAS_STATIC_RTTI) || _HAS_STATIC_RTTI != 0 + #define JSON_HAS_STATIC_RTTI 1 + #else + #define JSON_HAS_STATIC_RTTI 0 + #endif +#endif + #ifdef JSON_HAS_CPP_17 #define JSON_INLINE_VARIABLE inline #else @@ -2590,12 +2600,13 @@ JSON_HEDLEY_DIAGNOSTIC_POP class NumberUnsignedType, class NumberFloatType, \ template class AllocatorType, \ template class JSONSerializer, \ - class BinaryType> + class BinaryType, \ + class CustomBaseClass> #define NLOHMANN_BASIC_JSON_TPL \ basic_json + AllocatorType, JSONSerializer, BinaryType, CustomBaseClass> // Macros to simplify conversion from/to types @@ -2745,7 +2756,10 @@ JSON_HEDLEY_DIAGNOSTIC_POP #define NLOHMANN_DEFINE_TYPE_INTRUSIVE_WITH_DEFAULT(Type, ...) \ friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ - friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { Type nlohmann_json_default_obj; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_TYPE_INTRUSIVE_ONLY_SERIALIZE(Type, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } /*! @brief macro @@ -2756,10 +2770,12 @@ JSON_HEDLEY_DIAGNOSTIC_POP inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM, __VA_ARGS__)) } +#define NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE_ONLY_SERIALIZE(Type, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } + #define NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE_WITH_DEFAULT(Type, ...) \ inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ - inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { Type nlohmann_json_default_obj; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } - + inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } // inspired from https://stackoverflow.com/a/26745591 // allows to call any std function as if (e.g. with begin): @@ -2923,10 +2939,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -2998,10 +3014,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -3040,10 +3056,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-FileCopyrightText: 2018 The Abseil Authors // SPDX-License-Identifier: MIT @@ -3214,10 +3230,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -3226,14 +3242,15 @@ NLOHMANN_JSON_NAMESPACE_END #include // false_type, is_constructible, is_integral, is_same, true_type #include // declval #include // tuple +#include // char_traits // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -3298,10 +3315,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -3318,10 +3335,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -3342,10 +3359,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT #ifndef INCLUDE_NLOHMANN_JSON_FWD_HPP_ @@ -3389,7 +3406,8 @@ NLOHMANN_JSON_NAMESPACE_END template class AllocatorType = std::allocator, template class JSONSerializer = adl_serializer, - class BinaryType = std::vector> + class BinaryType = std::vector, // cppcheck-suppress syntaxError + class CustomBaseClass = void> class basic_json; /// @brief JSON Pointer defines a string syntax for identifying a specific value within a JSON document @@ -3577,6 +3595,63 @@ struct actual_object_comparator template using actual_object_comparator_t = typename actual_object_comparator::type; +///////////////// +// char_traits // +///////////////// + +// Primary template of char_traits calls std char_traits +template +struct char_traits : std::char_traits +{}; + +// Explicitly define char traits for unsigned char since it is not standard +template<> +struct char_traits : std::char_traits +{ + using char_type = unsigned char; + using int_type = uint64_t; + + // Redefine to_int_type function + static int_type to_int_type(char_type c) noexcept + { + return static_cast(c); + } + + static char_type to_char_type(int_type i) noexcept + { + return static_cast(i); + } + + static constexpr int_type eof() noexcept + { + return static_cast(EOF); + } +}; + +// Explicitly define char traits for signed char since it is not standard +template<> +struct char_traits : std::char_traits +{ + using char_type = signed char; + using int_type = uint64_t; + + // Redefine to_int_type function + static int_type to_int_type(char_type c) noexcept + { + return static_cast(c); + } + + static char_type to_char_type(int_type i) noexcept + { + return static_cast(i); + } + + static constexpr int_type eof() noexcept + { + return static_cast(EOF); + } +}; + /////////////////// // is_ functions // /////////////////// @@ -3613,7 +3688,6 @@ template struct is_default_constructible> : conjunction...> {}; - template struct is_constructible : std::is_constructible {}; @@ -3629,7 +3703,6 @@ struct is_constructible> : is_default_constructible struct is_constructible> : is_default_constructible> {}; - template struct is_iterator_traits : std::false_type {}; @@ -4039,7 +4112,6 @@ struct value_in_range_of_impl2 } }; - template struct value_in_range_of_impl2 { @@ -4138,10 +4210,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -4165,28 +4237,28 @@ inline std::size_t concat_length() } template -inline std::size_t concat_length(const char* cstr, Args&& ... rest); +inline std::size_t concat_length(const char* cstr, const Args& ... rest); template -inline std::size_t concat_length(const StringType& str, Args&& ... rest); +inline std::size_t concat_length(const StringType& str, const Args& ... rest); template -inline std::size_t concat_length(const char /*c*/, Args&& ... rest) +inline std::size_t concat_length(const char /*c*/, const Args& ... rest) { - return 1 + concat_length(std::forward(rest)...); + return 1 + concat_length(rest...); } template -inline std::size_t concat_length(const char* cstr, Args&& ... rest) +inline std::size_t concat_length(const char* cstr, const Args& ... rest) { // cppcheck-suppress ignoredReturnValue - return ::strlen(cstr) + concat_length(std::forward(rest)...); + return ::strlen(cstr) + concat_length(rest...); } template -inline std::size_t concat_length(const StringType& str, Args&& ... rest) +inline std::size_t concat_length(const StringType& str, const Args& ... rest) { - return str.size() + concat_length(std::forward(rest)...); + return str.size() + concat_length(rest...); } template @@ -4277,7 +4349,7 @@ template inline OutStringType concat(Args && ... args) { OutStringType str; - str.reserve(concat_length(std::forward(args)...)); + str.reserve(concat_length(args...)); concat_into(str, std::forward(args)...); return str; } @@ -4286,7 +4358,6 @@ inline OutStringType concat(Args && ... args) NLOHMANN_JSON_NAMESPACE_END - NLOHMANN_JSON_NAMESPACE_BEGIN namespace detail { @@ -4334,9 +4405,9 @@ class exception : public std::exception { case value_t::array: { - for (std::size_t i = 0; i < current->m_parent->m_value.array->size(); ++i) + for (std::size_t i = 0; i < current->m_parent->m_data.m_value.array->size(); ++i) { - if (¤t->m_parent->m_value.array->operator[](i) == current) + if (¤t->m_parent->m_data.m_value.array->operator[](i) == current) { tokens.emplace_back(std::to_string(i)); break; @@ -4347,7 +4418,7 @@ class exception : public std::exception case value_t::object: { - for (const auto& element : *current->m_parent->m_value.object) + for (const auto& element : *current->m_parent->m_data.m_value.object) { if (&element.second == current) { @@ -4410,17 +4481,17 @@ class parse_error : public exception template::value, int> = 0> static parse_error create(int id_, const position_t& pos, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("parse_error", id_), "parse error", - position_string(pos), ": ", exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("parse_error", id_), "parse error", + position_string(pos), ": ", exception::diagnostics(context), what_arg); return {id_, pos.chars_read_total, w.c_str()}; } template::value, int> = 0> static parse_error create(int id_, std::size_t byte_, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("parse_error", id_), "parse error", - (byte_ != 0 ? (concat(" at byte ", std::to_string(byte_))) : ""), - ": ", exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("parse_error", id_), "parse error", + (byte_ != 0 ? (concat(" at byte ", std::to_string(byte_))) : ""), + ": ", exception::diagnostics(context), what_arg); return {id_, byte_, w.c_str()}; } @@ -4454,7 +4525,7 @@ class invalid_iterator : public exception template::value, int> = 0> static invalid_iterator create(int id_, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("invalid_iterator", id_), exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("invalid_iterator", id_), exception::diagnostics(context), what_arg); return {id_, w.c_str()}; } @@ -4472,7 +4543,7 @@ class type_error : public exception template::value, int> = 0> static type_error create(int id_, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("type_error", id_), exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("type_error", id_), exception::diagnostics(context), what_arg); return {id_, w.c_str()}; } @@ -4489,7 +4560,7 @@ class out_of_range : public exception template::value, int> = 0> static out_of_range create(int id_, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("out_of_range", id_), exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("out_of_range", id_), exception::diagnostics(context), what_arg); return {id_, w.c_str()}; } @@ -4506,7 +4577,7 @@ class other_error : public exception template::value, int> = 0> static other_error create(int id_, const std::string& what_arg, BasicJsonContext context) { - std::string w = concat(exception::name("other_error", id_), exception::diagnostics(context), what_arg); + const std::string w = concat(exception::name("other_error", id_), exception::diagnostics(context), what_arg); return {id_, w.c_str()}; } @@ -4525,10 +4596,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -4549,10 +4620,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -5055,10 +5126,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -5075,10 +5146,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -5147,10 +5218,10 @@ template class iteration_proxy_value // older GCCs are a bit fussy and require explicit noexcept specifiers on defaulted functions iteration_proxy_value(iteration_proxy_value&&) noexcept(std::is_nothrow_move_constructible::value - && std::is_nothrow_move_constructible::value) = default; + && std::is_nothrow_move_constructible::value) = default; // NOLINT(hicpp-noexcept-move,performance-noexcept-move-constructor,cppcoreguidelines-noexcept-move-operations) iteration_proxy_value& operator=(iteration_proxy_value&&) noexcept(std::is_nothrow_move_assignable::value - && std::is_nothrow_move_assignable::value) = default; + && std::is_nothrow_move_assignable::value) = default; // NOLINT(hicpp-noexcept-move,performance-noexcept-move-constructor,cppcoreguidelines-noexcept-move-operations) ~iteration_proxy_value() = default; /// dereference operator (needed for range-based for) @@ -5297,11 +5368,11 @@ namespace std #pragma clang diagnostic ignored "-Wmismatched-tags" #endif template -class tuple_size<::nlohmann::detail::iteration_proxy_value> +class tuple_size<::nlohmann::detail::iteration_proxy_value> // NOLINT(cert-dcl58-cpp) : public std::integral_constant {}; template -class tuple_element> +class tuple_element> // NOLINT(cert-dcl58-cpp) { public: using type = decltype( @@ -5340,7 +5411,7 @@ namespace detail /* * Note all external_constructor<>::construct functions need to call - * j.m_value.destroy(j.m_type) to avoid a memory leak in case j contains an + * j.m_data.m_value.destroy(j.m_data.m_type) to avoid a memory leak in case j contains an * allocated value (e.g., a string). See bug issue * https://github.com/nlohmann/json/issues/2865 for more information. */ @@ -5353,9 +5424,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::boolean_t b) noexcept { - j.m_value.destroy(j.m_type); - j.m_type = value_t::boolean; - j.m_value = b; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::boolean; + j.m_data.m_value = b; j.assert_invariant(); } }; @@ -5366,18 +5437,18 @@ struct external_constructor template static void construct(BasicJsonType& j, const typename BasicJsonType::string_t& s) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::string; - j.m_value = s; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::string; + j.m_data.m_value = s; j.assert_invariant(); } template static void construct(BasicJsonType& j, typename BasicJsonType::string_t&& s) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::string; - j.m_value = std::move(s); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::string; + j.m_data.m_value = std::move(s); j.assert_invariant(); } @@ -5386,9 +5457,9 @@ struct external_constructor int > = 0 > static void construct(BasicJsonType& j, const CompatibleStringType& str) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::string; - j.m_value.string = j.template create(str); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::string; + j.m_data.m_value.string = j.template create(str); j.assert_invariant(); } }; @@ -5399,18 +5470,18 @@ struct external_constructor template static void construct(BasicJsonType& j, const typename BasicJsonType::binary_t& b) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::binary; - j.m_value = typename BasicJsonType::binary_t(b); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::binary; + j.m_data.m_value = typename BasicJsonType::binary_t(b); j.assert_invariant(); } template static void construct(BasicJsonType& j, typename BasicJsonType::binary_t&& b) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::binary; - j.m_value = typename BasicJsonType::binary_t(std::move(b)); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::binary; + j.m_data.m_value = typename BasicJsonType::binary_t(std::move(b)); j.assert_invariant(); } }; @@ -5421,9 +5492,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::number_float_t val) noexcept { - j.m_value.destroy(j.m_type); - j.m_type = value_t::number_float; - j.m_value = val; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::number_float; + j.m_data.m_value = val; j.assert_invariant(); } }; @@ -5434,9 +5505,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::number_unsigned_t val) noexcept { - j.m_value.destroy(j.m_type); - j.m_type = value_t::number_unsigned; - j.m_value = val; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::number_unsigned; + j.m_data.m_value = val; j.assert_invariant(); } }; @@ -5447,9 +5518,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::number_integer_t val) noexcept { - j.m_value.destroy(j.m_type); - j.m_type = value_t::number_integer; - j.m_value = val; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::number_integer; + j.m_data.m_value = val; j.assert_invariant(); } }; @@ -5460,9 +5531,9 @@ struct external_constructor template static void construct(BasicJsonType& j, const typename BasicJsonType::array_t& arr) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::array; - j.m_value = arr; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::array; + j.m_data.m_value = arr; j.set_parents(); j.assert_invariant(); } @@ -5470,9 +5541,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::array_t&& arr) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::array; - j.m_value = std::move(arr); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::array; + j.m_data.m_value = std::move(arr); j.set_parents(); j.assert_invariant(); } @@ -5485,9 +5556,9 @@ struct external_constructor using std::begin; using std::end; - j.m_value.destroy(j.m_type); - j.m_type = value_t::array; - j.m_value.array = j.template create(begin(arr), end(arr)); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::array; + j.m_data.m_value.array = j.template create(begin(arr), end(arr)); j.set_parents(); j.assert_invariant(); } @@ -5495,14 +5566,14 @@ struct external_constructor template static void construct(BasicJsonType& j, const std::vector& arr) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::array; - j.m_value = value_t::array; - j.m_value.array->reserve(arr.size()); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::array; + j.m_data.m_value = value_t::array; + j.m_data.m_value.array->reserve(arr.size()); for (const bool x : arr) { - j.m_value.array->push_back(x); - j.set_parent(j.m_value.array->back()); + j.m_data.m_value.array->push_back(x); + j.set_parent(j.m_data.m_value.array->back()); } j.assert_invariant(); } @@ -5511,13 +5582,13 @@ struct external_constructor enable_if_t::value, int> = 0> static void construct(BasicJsonType& j, const std::valarray& arr) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::array; - j.m_value = value_t::array; - j.m_value.array->resize(arr.size()); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::array; + j.m_data.m_value = value_t::array; + j.m_data.m_value.array->resize(arr.size()); if (arr.size() > 0) { - std::copy(std::begin(arr), std::end(arr), j.m_value.array->begin()); + std::copy(std::begin(arr), std::end(arr), j.m_data.m_value.array->begin()); } j.set_parents(); j.assert_invariant(); @@ -5530,9 +5601,9 @@ struct external_constructor template static void construct(BasicJsonType& j, const typename BasicJsonType::object_t& obj) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::object; - j.m_value = obj; + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::object; + j.m_data.m_value = obj; j.set_parents(); j.assert_invariant(); } @@ -5540,9 +5611,9 @@ struct external_constructor template static void construct(BasicJsonType& j, typename BasicJsonType::object_t&& obj) { - j.m_value.destroy(j.m_type); - j.m_type = value_t::object; - j.m_value = std::move(obj); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::object; + j.m_data.m_value = std::move(obj); j.set_parents(); j.assert_invariant(); } @@ -5554,9 +5625,9 @@ struct external_constructor using std::begin; using std::end; - j.m_value.destroy(j.m_type); - j.m_type = value_t::object; - j.m_value.object = j.template create(begin(obj), end(obj)); + j.m_data.m_value.destroy(j.m_data.m_type); + j.m_data.m_type = value_t::object; + j.m_data.m_value.object = j.template create(begin(obj), end(obj)); j.set_parents(); j.assert_invariant(); } @@ -5626,7 +5697,8 @@ template::type; - external_constructor::construct(j, static_cast(e)); + static constexpr value_t integral_value_t = std::is_unsigned::value ? value_t::number_unsigned : value_t::number_integer; + external_constructor::construct(j, static_cast(e)); } #endif // JSON_DISABLE_ENUM_SERIALIZATION @@ -5796,10 +5868,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -5908,10 +5980,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -6041,10 +6113,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -6067,10 +6139,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -6094,6 +6166,8 @@ NLOHMANN_JSON_NAMESPACE_END // #include +// #include + NLOHMANN_JSON_NAMESPACE_BEGIN namespace detail @@ -6140,7 +6214,6 @@ class file_input_adapter std::FILE* m_file; }; - /*! Input adapter for a (caching) istream. Ignores a UFT Byte Order Mark at beginning of input. Does not support changing the underlying std::streambuf @@ -6214,16 +6287,16 @@ class iterator_input_adapter : current(std::move(first)), end(std::move(last)) {} - typename std::char_traits::int_type get_character() + typename char_traits::int_type get_character() { if (JSON_HEDLEY_LIKELY(current != end)) { - auto result = std::char_traits::to_int_type(*current); + auto result = char_traits::to_int_type(*current); std::advance(current, 1); return result; } - return std::char_traits::eof(); + return char_traits::eof(); } private: @@ -6239,7 +6312,6 @@ class iterator_input_adapter } }; - template struct wide_string_input_helper; @@ -6363,7 +6435,7 @@ struct wide_string_input_helper } }; -// Wraps another input apdater to convert wide character types into individual bytes. +// Wraps another input adapter to convert wide character types into individual bytes. template class wide_string_input_adapter { @@ -6408,7 +6480,6 @@ class wide_string_input_adapter std::size_t utf8_bytes_filled = 0; }; - template struct iterator_input_adapter_factory { @@ -6565,10 +6636,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -6710,7 +6781,6 @@ struct json_sax virtual ~json_sax() = default; }; - namespace detail { /*! @@ -6812,7 +6882,7 @@ class json_sax_dom_parser JSON_ASSERT(ref_stack.back()->is_object()); // add null at given key and store the reference for later - object_element = &(ref_stack.back()->m_value.object->operator[](val)); + object_element = &(ref_stack.back()->m_data.m_value.object->operator[](val)); return true; } @@ -6887,8 +6957,8 @@ class json_sax_dom_parser if (ref_stack.back()->is_array()) { - ref_stack.back()->m_value.array->emplace_back(std::forward(v)); - return &(ref_stack.back()->m_value.array->back()); + ref_stack.back()->m_data.m_value.array->emplace_back(std::forward(v)); + return &(ref_stack.back()->m_data.m_value.array->back()); } JSON_ASSERT(ref_stack.back()->is_object()); @@ -7007,7 +7077,7 @@ class json_sax_dom_callback_parser // add discarded value at given key and store the reference for later if (keep && ref_stack.back()) { - object_element = &(ref_stack.back()->m_value.object->operator[](val) = discarded); + object_element = &(ref_stack.back()->m_data.m_value.object->operator[](val) = discarded); } return true; @@ -7092,7 +7162,7 @@ class json_sax_dom_callback_parser // remove discarded value if (!keep && !ref_stack.empty() && ref_stack.back()->is_array()) { - ref_stack.back()->m_value.array->pop_back(); + ref_stack.back()->m_data.m_value.array->pop_back(); } return true; @@ -7159,7 +7229,7 @@ class json_sax_dom_callback_parser if (ref_stack.empty()) { root = std::move(value); - return {true, &root}; + return {true, & root}; } // skip this value if we already decided to skip the parent @@ -7175,8 +7245,8 @@ class json_sax_dom_callback_parser // array if (ref_stack.back()->is_array()) { - ref_stack.back()->m_value.array->emplace_back(std::move(value)); - return {true, &(ref_stack.back()->m_value.array->back())}; + ref_stack.back()->m_data.m_value.array->emplace_back(std::move(value)); + return {true, & (ref_stack.back()->m_data.m_value.array->back())}; } // object @@ -7201,9 +7271,9 @@ class json_sax_dom_callback_parser /// stack to model hierarchy of values std::vector ref_stack {}; /// stack to manage which values to keep - std::vector keep_stack {}; + std::vector keep_stack {}; // NOLINT(readability-redundant-member-init) /// stack to manage which object keys to keep - std::vector key_keep_stack {}; + std::vector key_keep_stack {}; // NOLINT(readability-redundant-member-init) /// helper to hold the reference for the next object element BasicJsonType* object_element = nullptr; /// whether a syntax error occurred @@ -7298,10 +7368,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -7322,6 +7392,8 @@ NLOHMANN_JSON_NAMESPACE_END // #include +// #include + NLOHMANN_JSON_NAMESPACE_BEGIN namespace detail @@ -7416,7 +7488,7 @@ class lexer : public lexer_base using number_float_t = typename BasicJsonType::number_float_t; using string_t = typename BasicJsonType::string_t; using char_type = typename InputAdapterType::char_type; - using char_int_type = typename std::char_traits::int_type; + using char_int_type = typename char_traits::int_type; public: using token_type = typename lexer_base::token_type; @@ -7523,7 +7595,7 @@ class lexer : public lexer_base for (auto range = ranges.begin(); range != ranges.end(); ++range) { get(); - if (JSON_HEDLEY_LIKELY(*range <= current && current <= *(++range))) + if (JSON_HEDLEY_LIKELY(*range <= current && current <= *(++range))) // NOLINT(bugprone-inc-dec-in-conditions) { add(current); } @@ -7566,7 +7638,7 @@ class lexer : public lexer_base switch (get()) { // end of file while parsing string - case std::char_traits::eof(): + case char_traits::eof(): { error_message = "invalid string: missing closing quote"; return token_type::parse_error; @@ -8155,7 +8227,7 @@ class lexer : public lexer_base { case '\n': case '\r': - case std::char_traits::eof(): + case char_traits::eof(): case '\0': return true; @@ -8172,7 +8244,7 @@ class lexer : public lexer_base { switch (get()) { - case std::char_traits::eof(): + case char_traits::eof(): case '\0': { error_message = "invalid comment; missing closing '*/'"; @@ -8601,10 +8673,10 @@ class lexer : public lexer_base token_type scan_literal(const char_type* literal_text, const std::size_t length, token_type return_type) { - JSON_ASSERT(std::char_traits::to_char_type(current) == literal_text[0]); + JSON_ASSERT(char_traits::to_char_type(current) == literal_text[0]); for (std::size_t i = 1; i < length; ++i) { - if (JSON_HEDLEY_UNLIKELY(std::char_traits::to_char_type(get()) != literal_text[i])) + if (JSON_HEDLEY_UNLIKELY(char_traits::to_char_type(get()) != literal_text[i])) { error_message = "invalid literal"; return token_type::parse_error; @@ -8622,7 +8694,7 @@ class lexer : public lexer_base { token_buffer.clear(); token_string.clear(); - token_string.push_back(std::char_traits::to_char_type(current)); + token_string.push_back(char_traits::to_char_type(current)); } /* @@ -8630,7 +8702,7 @@ class lexer : public lexer_base This function provides the interface to the used input adapter. It does not throw in case the input reached EOF, but returns a - `std::char_traits::eof()` in that case. Stores the scanned characters + `char_traits::eof()` in that case. Stores the scanned characters for use in error messages. @return character read from the input @@ -8650,9 +8722,9 @@ class lexer : public lexer_base current = ia.get_character(); } - if (JSON_HEDLEY_LIKELY(current != std::char_traits::eof())) + if (JSON_HEDLEY_LIKELY(current != char_traits::eof())) { - token_string.push_back(std::char_traits::to_char_type(current)); + token_string.push_back(char_traits::to_char_type(current)); } if (current == '\n') @@ -8691,7 +8763,7 @@ class lexer : public lexer_base --position.chars_read_current_line; } - if (JSON_HEDLEY_LIKELY(current != std::char_traits::eof())) + if (JSON_HEDLEY_LIKELY(current != char_traits::eof())) { JSON_ASSERT(!token_string.empty()); token_string.pop_back(); @@ -8885,7 +8957,7 @@ class lexer : public lexer_base // end of input (the null byte is needed when parsing from // string literals) case '\0': - case std::char_traits::eof(): + case char_traits::eof(): return token_type::end_of_input; // error @@ -8903,7 +8975,7 @@ class lexer : public lexer_base const bool ignore_comments = false; /// the current character - char_int_type current = std::char_traits::eof(); + char_int_type current = char_traits::eof(); /// whether the next get() call should just return current bool next_unget = false; @@ -8937,10 +9009,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -9129,7 +9201,6 @@ static inline bool little_endianness(int num = 1) noexcept return *reinterpret_cast(&num) == 1; } - /////////////////// // binary reader // /////////////////// @@ -9147,7 +9218,7 @@ class binary_reader using binary_t = typename BasicJsonType::binary_t; using json_sax_t = SAX; using char_type = typename InputAdapterType::char_type; - using char_int_type = typename std::char_traits::int_type; + using char_int_type = typename char_traits::int_type; public: /*! @@ -9220,7 +9291,7 @@ class binary_reader get(); } - if (JSON_HEDLEY_UNLIKELY(current != std::char_traits::eof())) + if (JSON_HEDLEY_UNLIKELY(current != char_traits::eof())) { return sax->parse_error(chars_read, get_token_string(), parse_error::create(110, chars_read, exception_message(input_format, concat("expected end of input; last byte: 0x", get_token_string()), "value"), nullptr)); @@ -9303,7 +9374,7 @@ class binary_reader exception_message(input_format_t::bson, concat("string length must be at least 1, is ", std::to_string(len)), "string"), nullptr)); } - return get_string(input_format_t::bson, len - static_cast(1), result) && get() != std::char_traits::eof(); + return get_string(input_format_t::bson, len - static_cast(1), result) && get() != char_traits::eof(); } /*! @@ -9404,7 +9475,7 @@ class binary_reader { std::array cr{{}}; static_cast((std::snprintf)(cr.data(), cr.size(), "%.2hhX", static_cast(element_type))); // NOLINT(cppcoreguidelines-pro-type-vararg,hicpp-vararg) - std::string cr_str{cr.data()}; + const std::string cr_str{cr.data()}; return sax->parse_error(element_type_parse_position, cr_str, parse_error::create(114, element_type_parse_position, concat("Unsupported BSON record type 0x", cr_str), nullptr)); } @@ -9497,7 +9568,7 @@ class binary_reader switch (get_char ? get() : current) { // EOF - case std::char_traits::eof(): + case char_traits::eof(): return unexpect_eof(input_format_t::cbor, "value"); // Integer 0x00..0x17 (0..23) @@ -10272,7 +10343,7 @@ class binary_reader switch (get()) { // EOF - case std::char_traits::eof(): + case char_traits::eof(): return unexpect_eof(input_format_t::msgpack, "value"); // positive fixint @@ -11339,7 +11410,7 @@ class binary_reader exception_message(input_format, concat("expected '#' after type information; last byte: 0x", last_token), "size"), nullptr)); } - bool is_error = get_ubjson_size_value(result.first, is_ndarray); + const bool is_error = get_ubjson_size_value(result.first, is_ndarray); if (input_format == input_format_t::bjdata && is_ndarray) { if (inside_ndarray) @@ -11354,7 +11425,7 @@ class binary_reader if (current == '#') { - bool is_error = get_ubjson_size_value(result.first, is_ndarray); + const bool is_error = get_ubjson_size_value(result.first, is_ndarray); if (input_format == input_format_t::bjdata && is_ndarray) { return sax->parse_error(chars_read, get_token_string(), parse_error::create(112, chars_read, @@ -11374,7 +11445,7 @@ class binary_reader { switch (prefix) { - case std::char_traits::eof(): // EOF + case char_traits::eof(): // EOF return unexpect_eof(input_format, "value"); case 'T': // true @@ -11819,7 +11890,7 @@ class binary_reader This function provides the interface to the used input adapter. It does not throw in case the input reached EOF, but returns a -'ve valued - `std::char_traits::eof()` in that case. + `char_traits::eof()` in that case. @return character read from the input */ @@ -11961,7 +12032,7 @@ class binary_reader JSON_HEDLEY_NON_NULL(3) bool unexpect_eof(const input_format_t format, const char* context) const { - if (JSON_HEDLEY_UNLIKELY(current == std::char_traits::eof())) + if (JSON_HEDLEY_UNLIKELY(current == char_traits::eof())) { return sax->parse_error(chars_read, "", parse_error::create(110, chars_read, exception_message(format, "unexpected end of input", context), nullptr)); @@ -12028,7 +12099,7 @@ class binary_reader InputAdapterType ia; /// the current character - char_int_type current = std::char_traits::eof(); + char_int_type current = char_traits::eof(); /// the number of characters read std::size_t chars_read = 0; @@ -12090,10 +12161,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -12439,13 +12510,25 @@ class parser m_lexer.get_token_string(), parse_error::create(101, m_lexer.get_position(), exception_message(token_type::uninitialized, "value"), nullptr)); } + case token_type::end_of_input: + { + if (JSON_HEDLEY_UNLIKELY(m_lexer.get_position().chars_read_total == 1)) + { + return sax->parse_error(m_lexer.get_position(), + m_lexer.get_token_string(), + parse_error::create(101, m_lexer.get_position(), + "attempting to parse an empty input; check that your input string or stream contains the expected JSON", nullptr)); + } + return sax->parse_error(m_lexer.get_position(), + m_lexer.get_token_string(), + parse_error::create(101, m_lexer.get_position(), exception_message(token_type::literal_or_value, "value"), nullptr)); + } case token_type::uninitialized: case token_type::end_array: case token_type::end_object: case token_type::name_separator: case token_type::value_separator: - case token_type::end_of_input: case token_type::literal_or_value: default: // the last token was unexpected { @@ -12607,10 +12690,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -12620,10 +12703,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -12779,10 +12862,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -12887,7 +12970,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { @@ -12984,17 +13067,17 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { - m_it.object_iterator = m_object->m_value.object->begin(); + m_it.object_iterator = m_object->m_data.m_value.object->begin(); break; } case value_t::array: { - m_it.array_iterator = m_object->m_value.array->begin(); + m_it.array_iterator = m_object->m_data.m_value.array->begin(); break; } @@ -13028,17 +13111,17 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { - m_it.object_iterator = m_object->m_value.object->end(); + m_it.object_iterator = m_object->m_data.m_value.object->end(); break; } case value_t::array: { - m_it.array_iterator = m_object->m_value.array->end(); + m_it.array_iterator = m_object->m_data.m_value.array->end(); break; } @@ -13067,17 +13150,17 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { - JSON_ASSERT(m_it.object_iterator != m_object->m_value.object->end()); + JSON_ASSERT(m_it.object_iterator != m_object->m_data.m_value.object->end()); return m_it.object_iterator->second; } case value_t::array: { - JSON_ASSERT(m_it.array_iterator != m_object->m_value.array->end()); + JSON_ASSERT(m_it.array_iterator != m_object->m_data.m_value.array->end()); return *m_it.array_iterator; } @@ -13111,17 +13194,17 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { - JSON_ASSERT(m_it.object_iterator != m_object->m_value.object->end()); + JSON_ASSERT(m_it.object_iterator != m_object->m_data.m_value.object->end()); return &(m_it.object_iterator->second); } case value_t::array: { - JSON_ASSERT(m_it.array_iterator != m_object->m_value.array->end()); + JSON_ASSERT(m_it.array_iterator != m_object->m_data.m_value.array->end()); return &*m_it.array_iterator; } @@ -13164,7 +13247,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { @@ -13215,7 +13298,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: { @@ -13262,7 +13345,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: return (m_it.object_iterator == other.m_it.object_iterator); @@ -13307,7 +13390,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: JSON_THROW(invalid_iterator::create(213, "cannot compare order of object iterators", m_object)); @@ -13363,7 +13446,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: JSON_THROW(invalid_iterator::create(209, "cannot use offsets with object iterators", m_object)); @@ -13442,7 +13525,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: JSON_THROW(invalid_iterator::create(209, "cannot use offsets with object iterators", m_object)); @@ -13471,7 +13554,7 @@ class iter_impl // NOLINT(cppcoreguidelines-special-member-functions,hicpp-speci { JSON_ASSERT(m_object != nullptr); - switch (m_object->m_type) + switch (m_object->m_data.m_type) { case value_t::object: JSON_THROW(invalid_iterator::create(208, "cannot use operator[] for object iterators", m_object)); @@ -13541,10 +13624,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -13673,13 +13756,55 @@ NLOHMANN_JSON_NAMESPACE_END // #include +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // conditional, is_same + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +/*! +@brief Default base class of the @ref basic_json class. + +So that the correct implementations of the copy / move ctors / assign operators +of @ref basic_json do not require complex case distinctions +(no base class / custom base class used as customization point), +@ref basic_json always has a base class. +By default, this class is used because it is empty and thus has no effect +on the behavior of @ref basic_json. +*/ +struct json_default_base {}; + +template +using json_base_class = typename std::conditional < + std::is_same::value, + json_default_base, + T + >::type; + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -13911,7 +14036,7 @@ class json_pointer const char* p = s.c_str(); char* p_end = nullptr; errno = 0; // strtoull doesn't reset errno - unsigned long long res = std::strtoull(p, &p_end, 10); // NOLINT(runtime/int) + const unsigned long long res = std::strtoull(p, &p_end, 10); // NOLINT(runtime/int) if (p == p_end // invalid input or empty string || errno == ERANGE // out of range || JSON_HEDLEY_UNLIKELY(static_cast(p_end - p) != s.size())) // incomplete read @@ -14067,7 +14192,7 @@ class json_pointer if (reference_token == "-") { // explicitly treat "-" as index beyond the end - ptr = &ptr->operator[](ptr->m_value.array->size()); + ptr = &ptr->operator[](ptr->m_data.m_value.array->size()); } else { @@ -14119,7 +14244,7 @@ class json_pointer { // "-" always fails the range check JSON_THROW(detail::out_of_range::create(402, detail::concat( - "array index '-' (", std::to_string(ptr->m_value.array->size()), + "array index '-' (", std::to_string(ptr->m_data.m_value.array->size()), ") is out of range"), ptr)); } @@ -14176,7 +14301,7 @@ class json_pointer if (JSON_HEDLEY_UNLIKELY(reference_token == "-")) { // "-" cannot be used for const access - JSON_THROW(detail::out_of_range::create(402, detail::concat("array index '-' (", std::to_string(ptr->m_value.array->size()), ") is out of range"), ptr)); + JSON_THROW(detail::out_of_range::create(402, detail::concat("array index '-' (", std::to_string(ptr->m_data.m_value.array->size()), ") is out of range"), ptr)); } // use unchecked array access @@ -14226,7 +14351,7 @@ class json_pointer { // "-" always fails the range check JSON_THROW(detail::out_of_range::create(402, detail::concat( - "array index '-' (", std::to_string(ptr->m_value.array->size()), + "array index '-' (", std::to_string(ptr->m_data.m_value.array->size()), ") is out of range"), ptr)); } @@ -14421,7 +14546,7 @@ class json_pointer { case detail::value_t::array: { - if (value.m_value.array->empty()) + if (value.m_data.m_value.array->empty()) { // flatten empty array as null result[reference_string] = nullptr; @@ -14429,10 +14554,10 @@ class json_pointer else { // iterate array and use index as reference string - for (std::size_t i = 0; i < value.m_value.array->size(); ++i) + for (std::size_t i = 0; i < value.m_data.m_value.array->size(); ++i) { flatten(detail::concat(reference_string, '/', std::to_string(i)), - value.m_value.array->operator[](i), result); + value.m_data.m_value.array->operator[](i), result); } } break; @@ -14440,7 +14565,7 @@ class json_pointer case detail::value_t::object: { - if (value.m_value.object->empty()) + if (value.m_data.m_value.object->empty()) { // flatten empty object as null result[reference_string] = nullptr; @@ -14448,7 +14573,7 @@ class json_pointer else { // iterate object and use keys as reference string - for (const auto& element : *value.m_value.object) + for (const auto& element : *value.m_data.m_value.object) { flatten(detail::concat(reference_string, '/', detail::escape(element.first)), element.second, result); } @@ -14495,7 +14620,7 @@ class json_pointer BasicJsonType result; // iterate the JSON object values - for (const auto& element : *value.m_value.object) + for (const auto& element : *value.m_data.m_value.object) { if (JSON_HEDLEY_UNLIKELY(!element.second.is_primitive())) { @@ -14671,10 +14796,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -14763,10 +14888,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -14789,10 +14914,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -14978,7 +15103,7 @@ class binary_writer { case value_t::object: { - write_bson_object(*j.m_value.object); + write_bson_object(*j.m_data.m_value.object); break; } @@ -15013,7 +15138,7 @@ class binary_writer case value_t::boolean: { - oa->write_character(j.m_value.boolean + oa->write_character(j.m_data.m_value.boolean ? to_char_type(0xF5) : to_char_type(0xF4)); break; @@ -15021,42 +15146,42 @@ class binary_writer case value_t::number_integer: { - if (j.m_value.number_integer >= 0) + if (j.m_data.m_value.number_integer >= 0) { // CBOR does not differentiate between positive signed // integers and unsigned integers. Therefore, we used the // code from the value_t::number_unsigned case here. - if (j.m_value.number_integer <= 0x17) + if (j.m_data.m_value.number_integer <= 0x17) { - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x18)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x19)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x1A)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } else { oa->write_character(to_char_type(0x1B)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } } else { // The conversions below encode the sign in the first // byte, and the value is converted to a positive number. - const auto positive_number = -1 - j.m_value.number_integer; - if (j.m_value.number_integer >= -24) + const auto positive_number = -1 - j.m_data.m_value.number_integer; + if (j.m_data.m_value.number_integer >= -24) { write_number(static_cast(0x20 + positive_number)); } @@ -15086,52 +15211,52 @@ class binary_writer case value_t::number_unsigned: { - if (j.m_value.number_unsigned <= 0x17) + if (j.m_data.m_value.number_unsigned <= 0x17) { - write_number(static_cast(j.m_value.number_unsigned)); + write_number(static_cast(j.m_data.m_value.number_unsigned)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x18)); - write_number(static_cast(j.m_value.number_unsigned)); + write_number(static_cast(j.m_data.m_value.number_unsigned)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x19)); - write_number(static_cast(j.m_value.number_unsigned)); + write_number(static_cast(j.m_data.m_value.number_unsigned)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { oa->write_character(to_char_type(0x1A)); - write_number(static_cast(j.m_value.number_unsigned)); + write_number(static_cast(j.m_data.m_value.number_unsigned)); } else { oa->write_character(to_char_type(0x1B)); - write_number(static_cast(j.m_value.number_unsigned)); + write_number(static_cast(j.m_data.m_value.number_unsigned)); } break; } case value_t::number_float: { - if (std::isnan(j.m_value.number_float)) + if (std::isnan(j.m_data.m_value.number_float)) { // NaN is 0xf97e00 in CBOR oa->write_character(to_char_type(0xF9)); oa->write_character(to_char_type(0x7E)); oa->write_character(to_char_type(0x00)); } - else if (std::isinf(j.m_value.number_float)) + else if (std::isinf(j.m_data.m_value.number_float)) { // Infinity is 0xf97c00, -Infinity is 0xf9fc00 oa->write_character(to_char_type(0xf9)); - oa->write_character(j.m_value.number_float > 0 ? to_char_type(0x7C) : to_char_type(0xFC)); + oa->write_character(j.m_data.m_value.number_float > 0 ? to_char_type(0x7C) : to_char_type(0xFC)); oa->write_character(to_char_type(0x00)); } else { - write_compact_float(j.m_value.number_float, detail::input_format_t::cbor); + write_compact_float(j.m_data.m_value.number_float, detail::input_format_t::cbor); } break; } @@ -15139,7 +15264,7 @@ class binary_writer case value_t::string: { // step 1: write control byte and the string length - const auto N = j.m_value.string->size(); + const auto N = j.m_data.m_value.string->size(); if (N <= 0x17) { write_number(static_cast(0x60 + N)); @@ -15169,15 +15294,15 @@ class binary_writer // step 2: write the string oa->write_characters( - reinterpret_cast(j.m_value.string->c_str()), - j.m_value.string->size()); + reinterpret_cast(j.m_data.m_value.string->c_str()), + j.m_data.m_value.string->size()); break; } case value_t::array: { // step 1: write control byte and the array size - const auto N = j.m_value.array->size(); + const auto N = j.m_data.m_value.array->size(); if (N <= 0x17) { write_number(static_cast(0x80 + N)); @@ -15206,7 +15331,7 @@ class binary_writer // LCOV_EXCL_STOP // step 2: write each element - for (const auto& el : *j.m_value.array) + for (const auto& el : *j.m_data.m_value.array) { write_cbor(el); } @@ -15215,32 +15340,32 @@ class binary_writer case value_t::binary: { - if (j.m_value.binary->has_subtype()) + if (j.m_data.m_value.binary->has_subtype()) { - if (j.m_value.binary->subtype() <= (std::numeric_limits::max)()) + if (j.m_data.m_value.binary->subtype() <= (std::numeric_limits::max)()) { write_number(static_cast(0xd8)); - write_number(static_cast(j.m_value.binary->subtype())); + write_number(static_cast(j.m_data.m_value.binary->subtype())); } - else if (j.m_value.binary->subtype() <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.binary->subtype() <= (std::numeric_limits::max)()) { write_number(static_cast(0xd9)); - write_number(static_cast(j.m_value.binary->subtype())); + write_number(static_cast(j.m_data.m_value.binary->subtype())); } - else if (j.m_value.binary->subtype() <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.binary->subtype() <= (std::numeric_limits::max)()) { write_number(static_cast(0xda)); - write_number(static_cast(j.m_value.binary->subtype())); + write_number(static_cast(j.m_data.m_value.binary->subtype())); } - else if (j.m_value.binary->subtype() <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.binary->subtype() <= (std::numeric_limits::max)()) { write_number(static_cast(0xdb)); - write_number(static_cast(j.m_value.binary->subtype())); + write_number(static_cast(j.m_data.m_value.binary->subtype())); } } // step 1: write control byte and the binary array size - const auto N = j.m_value.binary->size(); + const auto N = j.m_data.m_value.binary->size(); if (N <= 0x17) { write_number(static_cast(0x40 + N)); @@ -15270,7 +15395,7 @@ class binary_writer // step 2: write each element oa->write_characters( - reinterpret_cast(j.m_value.binary->data()), + reinterpret_cast(j.m_data.m_value.binary->data()), N); break; @@ -15279,7 +15404,7 @@ class binary_writer case value_t::object: { // step 1: write control byte and the object size - const auto N = j.m_value.object->size(); + const auto N = j.m_data.m_value.object->size(); if (N <= 0x17) { write_number(static_cast(0xA0 + N)); @@ -15308,7 +15433,7 @@ class binary_writer // LCOV_EXCL_STOP // step 2: write each element - for (const auto& el : *j.m_value.object) + for (const auto& el : *j.m_data.m_value.object) { write_cbor(el.first); write_cbor(el.second); @@ -15337,7 +15462,7 @@ class binary_writer case value_t::boolean: // true and false { - oa->write_character(j.m_value.boolean + oa->write_character(j.m_data.m_value.boolean ? to_char_type(0xC3) : to_char_type(0xC2)); break; @@ -15345,75 +15470,75 @@ class binary_writer case value_t::number_integer: { - if (j.m_value.number_integer >= 0) + if (j.m_data.m_value.number_integer >= 0) { // MessagePack does not differentiate between positive // signed integers and unsigned integers. Therefore, we used // the code from the value_t::number_unsigned case here. - if (j.m_value.number_unsigned < 128) + if (j.m_data.m_value.number_unsigned < 128) { // positive fixnum - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 8 oa->write_character(to_char_type(0xCC)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 16 oa->write_character(to_char_type(0xCD)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 32 oa->write_character(to_char_type(0xCE)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 64 oa->write_character(to_char_type(0xCF)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } } else { - if (j.m_value.number_integer >= -32) + if (j.m_data.m_value.number_integer >= -32) { // negative fixnum - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer >= (std::numeric_limits::min)() && - j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer >= (std::numeric_limits::min)() && + j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { // int 8 oa->write_character(to_char_type(0xD0)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer >= (std::numeric_limits::min)() && - j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer >= (std::numeric_limits::min)() && + j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { // int 16 oa->write_character(to_char_type(0xD1)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer >= (std::numeric_limits::min)() && - j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer >= (std::numeric_limits::min)() && + j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { // int 32 oa->write_character(to_char_type(0xD2)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_integer >= (std::numeric_limits::min)() && - j.m_value.number_integer <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_integer >= (std::numeric_limits::min)() && + j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { // int 64 oa->write_character(to_char_type(0xD3)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } } break; @@ -15421,48 +15546,48 @@ class binary_writer case value_t::number_unsigned: { - if (j.m_value.number_unsigned < 128) + if (j.m_data.m_value.number_unsigned < 128) { // positive fixnum - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 8 oa->write_character(to_char_type(0xCC)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 16 oa->write_character(to_char_type(0xCD)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 32 oa->write_character(to_char_type(0xCE)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } - else if (j.m_value.number_unsigned <= (std::numeric_limits::max)()) + else if (j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { // uint 64 oa->write_character(to_char_type(0xCF)); - write_number(static_cast(j.m_value.number_integer)); + write_number(static_cast(j.m_data.m_value.number_integer)); } break; } case value_t::number_float: { - write_compact_float(j.m_value.number_float, detail::input_format_t::msgpack); + write_compact_float(j.m_data.m_value.number_float, detail::input_format_t::msgpack); break; } case value_t::string: { // step 1: write control byte and the string length - const auto N = j.m_value.string->size(); + const auto N = j.m_data.m_value.string->size(); if (N <= 31) { // fixstr @@ -15489,15 +15614,15 @@ class binary_writer // step 2: write the string oa->write_characters( - reinterpret_cast(j.m_value.string->c_str()), - j.m_value.string->size()); + reinterpret_cast(j.m_data.m_value.string->c_str()), + j.m_data.m_value.string->size()); break; } case value_t::array: { // step 1: write control byte and the array size - const auto N = j.m_value.array->size(); + const auto N = j.m_data.m_value.array->size(); if (N <= 15) { // fixarray @@ -15517,7 +15642,7 @@ class binary_writer } // step 2: write each element - for (const auto& el : *j.m_value.array) + for (const auto& el : *j.m_data.m_value.array) { write_msgpack(el); } @@ -15528,10 +15653,10 @@ class binary_writer { // step 0: determine if the binary type has a set subtype to // determine whether or not to use the ext or fixext types - const bool use_ext = j.m_value.binary->has_subtype(); + const bool use_ext = j.m_data.m_value.binary->has_subtype(); // step 1: write control byte and the byte string length - const auto N = j.m_value.binary->size(); + const auto N = j.m_data.m_value.binary->size(); if (N <= (std::numeric_limits::max)()) { std::uint8_t output_type{}; @@ -15576,18 +15701,18 @@ class binary_writer } else if (N <= (std::numeric_limits::max)()) { - std::uint8_t output_type = use_ext - ? 0xC8 // ext 16 - : 0xC5; // bin 16 + const std::uint8_t output_type = use_ext + ? 0xC8 // ext 16 + : 0xC5; // bin 16 oa->write_character(to_char_type(output_type)); write_number(static_cast(N)); } else if (N <= (std::numeric_limits::max)()) { - std::uint8_t output_type = use_ext - ? 0xC9 // ext 32 - : 0xC6; // bin 32 + const std::uint8_t output_type = use_ext + ? 0xC9 // ext 32 + : 0xC6; // bin 32 oa->write_character(to_char_type(output_type)); write_number(static_cast(N)); @@ -15596,12 +15721,12 @@ class binary_writer // step 1.5: if this is an ext type, write the subtype if (use_ext) { - write_number(static_cast(j.m_value.binary->subtype())); + write_number(static_cast(j.m_data.m_value.binary->subtype())); } // step 2: write the byte string oa->write_characters( - reinterpret_cast(j.m_value.binary->data()), + reinterpret_cast(j.m_data.m_value.binary->data()), N); break; @@ -15610,7 +15735,7 @@ class binary_writer case value_t::object: { // step 1: write control byte and the object size - const auto N = j.m_value.object->size(); + const auto N = j.m_data.m_value.object->size(); if (N <= 15) { // fixmap @@ -15630,7 +15755,7 @@ class binary_writer } // step 2: write each element - for (const auto& el : *j.m_value.object) + for (const auto& el : *j.m_data.m_value.object) { write_msgpack(el.first); write_msgpack(el.second); @@ -15670,7 +15795,7 @@ class binary_writer { if (add_prefix) { - oa->write_character(j.m_value.boolean + oa->write_character(j.m_data.m_value.boolean ? to_char_type('T') : to_char_type('F')); } @@ -15679,19 +15804,19 @@ class binary_writer case value_t::number_integer: { - write_number_with_ubjson_prefix(j.m_value.number_integer, add_prefix, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.number_integer, add_prefix, use_bjdata); break; } case value_t::number_unsigned: { - write_number_with_ubjson_prefix(j.m_value.number_unsigned, add_prefix, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.number_unsigned, add_prefix, use_bjdata); break; } case value_t::number_float: { - write_number_with_ubjson_prefix(j.m_value.number_float, add_prefix, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.number_float, add_prefix, use_bjdata); break; } @@ -15701,10 +15826,10 @@ class binary_writer { oa->write_character(to_char_type('S')); } - write_number_with_ubjson_prefix(j.m_value.string->size(), true, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.string->size(), true, use_bjdata); oa->write_characters( - reinterpret_cast(j.m_value.string->c_str()), - j.m_value.string->size()); + reinterpret_cast(j.m_data.m_value.string->c_str()), + j.m_data.m_value.string->size()); break; } @@ -15716,7 +15841,7 @@ class binary_writer } bool prefix_required = true; - if (use_type && !j.m_value.array->empty()) + if (use_type && !j.m_data.m_value.array->empty()) { JSON_ASSERT(use_count); const CharType first_prefix = ubjson_prefix(j.front(), use_bjdata); @@ -15739,10 +15864,10 @@ class binary_writer if (use_count) { oa->write_character(to_char_type('#')); - write_number_with_ubjson_prefix(j.m_value.array->size(), true, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.array->size(), true, use_bjdata); } - for (const auto& el : *j.m_value.array) + for (const auto& el : *j.m_data.m_value.array) { write_ubjson(el, use_count, use_type, prefix_required, use_bjdata); } @@ -15762,7 +15887,7 @@ class binary_writer oa->write_character(to_char_type('[')); } - if (use_type && !j.m_value.binary->empty()) + if (use_type && !j.m_data.m_value.binary->empty()) { JSON_ASSERT(use_count); oa->write_character(to_char_type('$')); @@ -15772,21 +15897,21 @@ class binary_writer if (use_count) { oa->write_character(to_char_type('#')); - write_number_with_ubjson_prefix(j.m_value.binary->size(), true, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.binary->size(), true, use_bjdata); } if (use_type) { oa->write_characters( - reinterpret_cast(j.m_value.binary->data()), - j.m_value.binary->size()); + reinterpret_cast(j.m_data.m_value.binary->data()), + j.m_data.m_value.binary->size()); } else { - for (size_t i = 0; i < j.m_value.binary->size(); ++i) + for (size_t i = 0; i < j.m_data.m_value.binary->size(); ++i) { oa->write_character(to_char_type('U')); - oa->write_character(j.m_value.binary->data()[i]); + oa->write_character(j.m_data.m_value.binary->data()[i]); } } @@ -15800,9 +15925,9 @@ class binary_writer case value_t::object: { - if (use_bjdata && j.m_value.object->size() == 3 && j.m_value.object->find("_ArrayType_") != j.m_value.object->end() && j.m_value.object->find("_ArraySize_") != j.m_value.object->end() && j.m_value.object->find("_ArrayData_") != j.m_value.object->end()) + if (use_bjdata && j.m_data.m_value.object->size() == 3 && j.m_data.m_value.object->find("_ArrayType_") != j.m_data.m_value.object->end() && j.m_data.m_value.object->find("_ArraySize_") != j.m_data.m_value.object->end() && j.m_data.m_value.object->find("_ArrayData_") != j.m_data.m_value.object->end()) { - if (!write_bjdata_ndarray(*j.m_value.object, use_count, use_type)) // decode bjdata ndarray in the JData format (https://github.com/NeuroJSON/jdata) + if (!write_bjdata_ndarray(*j.m_data.m_value.object, use_count, use_type)) // decode bjdata ndarray in the JData format (https://github.com/NeuroJSON/jdata) { break; } @@ -15814,7 +15939,7 @@ class binary_writer } bool prefix_required = true; - if (use_type && !j.m_value.object->empty()) + if (use_type && !j.m_data.m_value.object->empty()) { JSON_ASSERT(use_count); const CharType first_prefix = ubjson_prefix(j.front(), use_bjdata); @@ -15837,10 +15962,10 @@ class binary_writer if (use_count) { oa->write_character(to_char_type('#')); - write_number_with_ubjson_prefix(j.m_value.object->size(), true, use_bjdata); + write_number_with_ubjson_prefix(j.m_data.m_value.object->size(), true, use_bjdata); } - for (const auto& el : *j.m_value.object) + for (const auto& el : *j.m_data.m_value.object) { write_number_with_ubjson_prefix(el.first.size(), true, use_bjdata); oa->write_characters( @@ -15990,19 +16115,19 @@ class binary_writer void write_bson_unsigned(const string_t& name, const BasicJsonType& j) { - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { write_bson_entry_header(name, 0x10 /* int32 */); - write_number(static_cast(j.m_value.number_unsigned), true); + write_number(static_cast(j.m_data.m_value.number_unsigned), true); } - else if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + else if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { write_bson_entry_header(name, 0x12 /* int64 */); - write_number(static_cast(j.m_value.number_unsigned), true); + write_number(static_cast(j.m_data.m_value.number_unsigned), true); } else { - JSON_THROW(out_of_range::create(407, concat("integer number ", std::to_string(j.m_value.number_unsigned), " cannot be represented by BSON as it does not fit int64"), &j)); + JSON_THROW(out_of_range::create(407, concat("integer number ", std::to_string(j.m_data.m_value.number_unsigned), " cannot be represented by BSON as it does not fit int64"), &j)); } } @@ -16083,13 +16208,13 @@ class binary_writer switch (j.type()) { case value_t::object: - return header_size + calc_bson_object_size(*j.m_value.object); + return header_size + calc_bson_object_size(*j.m_data.m_value.object); case value_t::array: - return header_size + calc_bson_array_size(*j.m_value.array); + return header_size + calc_bson_array_size(*j.m_data.m_value.array); case value_t::binary: - return header_size + calc_bson_binary_size(*j.m_value.binary); + return header_size + calc_bson_binary_size(*j.m_data.m_value.binary); case value_t::boolean: return header_size + 1ul; @@ -16098,13 +16223,13 @@ class binary_writer return header_size + 8ul; case value_t::number_integer: - return header_size + calc_bson_integer_size(j.m_value.number_integer); + return header_size + calc_bson_integer_size(j.m_data.m_value.number_integer); case value_t::number_unsigned: - return header_size + calc_bson_unsigned_size(j.m_value.number_unsigned); + return header_size + calc_bson_unsigned_size(j.m_data.m_value.number_unsigned); case value_t::string: - return header_size + calc_bson_string_size(*j.m_value.string); + return header_size + calc_bson_string_size(*j.m_data.m_value.string); case value_t::null: return header_size + 0ul; @@ -16130,28 +16255,28 @@ class binary_writer switch (j.type()) { case value_t::object: - return write_bson_object_entry(name, *j.m_value.object); + return write_bson_object_entry(name, *j.m_data.m_value.object); case value_t::array: - return write_bson_array(name, *j.m_value.array); + return write_bson_array(name, *j.m_data.m_value.array); case value_t::binary: - return write_bson_binary(name, *j.m_value.binary); + return write_bson_binary(name, *j.m_data.m_value.binary); case value_t::boolean: - return write_bson_boolean(name, j.m_value.boolean); + return write_bson_boolean(name, j.m_data.m_value.boolean); case value_t::number_float: - return write_bson_double(name, j.m_value.number_float); + return write_bson_double(name, j.m_data.m_value.number_float); case value_t::number_integer: - return write_bson_integer(name, j.m_value.number_integer); + return write_bson_integer(name, j.m_data.m_value.number_integer); case value_t::number_unsigned: return write_bson_unsigned(name, j); case value_t::string: - return write_bson_string(name, *j.m_value.string); + return write_bson_string(name, *j.m_data.m_value.string); case value_t::null: return write_bson_null(name); @@ -16173,8 +16298,8 @@ class binary_writer */ static std::size_t calc_bson_object_size(const typename BasicJsonType::object_t& value) { - std::size_t document_size = std::accumulate(value.begin(), value.end(), static_cast(0), - [](size_t result, const typename BasicJsonType::object_t::value_type & el) + const std::size_t document_size = std::accumulate(value.begin(), value.end(), static_cast(0), + [](size_t result, const typename BasicJsonType::object_t::value_type & el) { return result += calc_bson_element_size(el.first, el.second); }); @@ -16424,35 +16549,35 @@ class binary_writer return 'Z'; case value_t::boolean: - return j.m_value.boolean ? 'T' : 'F'; + return j.m_data.m_value.boolean ? 'T' : 'F'; case value_t::number_integer: { - if ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)()) + if ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { return 'i'; } - if ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)()) + if ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { return 'U'; } - if ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)()) + if ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { return 'I'; } - if (use_bjdata && ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)())) + if (use_bjdata && ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)())) { return 'u'; } - if ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)()) + if ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { return 'l'; } - if (use_bjdata && ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)())) + if (use_bjdata && ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)())) { return 'm'; } - if ((std::numeric_limits::min)() <= j.m_value.number_integer && j.m_value.number_integer <= (std::numeric_limits::max)()) + if ((std::numeric_limits::min)() <= j.m_data.m_value.number_integer && j.m_data.m_value.number_integer <= (std::numeric_limits::max)()) { return 'L'; } @@ -16462,35 +16587,35 @@ class binary_writer case value_t::number_unsigned: { - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'i'; } - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'U'; } - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'I'; } - if (use_bjdata && j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (use_bjdata && j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'u'; } - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'l'; } - if (use_bjdata && j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (use_bjdata && j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'm'; } - if (j.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) + if (j.m_data.m_value.number_unsigned <= static_cast((std::numeric_limits::max)())) { return 'L'; } - if (use_bjdata && j.m_value.number_unsigned <= (std::numeric_limits::max)()) + if (use_bjdata && j.m_data.m_value.number_unsigned <= (std::numeric_limits::max)()) { return 'M'; } @@ -16499,7 +16624,7 @@ class binary_writer } case value_t::number_float: - return get_ubjson_float_prefix(j.m_value.number_float); + return get_ubjson_float_prefix(j.m_data.m_value.number_float); case value_t::string: return 'S'; @@ -16548,7 +16673,7 @@ class binary_writer std::size_t len = (value.at(key).empty() ? 0 : 1); for (const auto& el : value.at(key)) { - len *= static_cast(el.m_value.number_unsigned); + len *= static_cast(el.m_data.m_value.number_unsigned); } key = "_ArrayData_"; @@ -16570,70 +16695,70 @@ class binary_writer { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_unsigned), true); + write_number(static_cast(el.m_data.m_value.number_unsigned), true); } } else if (dtype == 'i') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_integer), true); + write_number(static_cast(el.m_data.m_value.number_integer), true); } } else if (dtype == 'u') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_unsigned), true); + write_number(static_cast(el.m_data.m_value.number_unsigned), true); } } else if (dtype == 'I') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_integer), true); + write_number(static_cast(el.m_data.m_value.number_integer), true); } } else if (dtype == 'm') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_unsigned), true); + write_number(static_cast(el.m_data.m_value.number_unsigned), true); } } else if (dtype == 'l') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_integer), true); + write_number(static_cast(el.m_data.m_value.number_integer), true); } } else if (dtype == 'M') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_unsigned), true); + write_number(static_cast(el.m_data.m_value.number_unsigned), true); } } else if (dtype == 'L') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_integer), true); + write_number(static_cast(el.m_data.m_value.number_integer), true); } } else if (dtype == 'd') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_float), true); + write_number(static_cast(el.m_data.m_value.number_float), true); } } else if (dtype == 'D') { for (const auto& el : value.at(key)) { - write_number(static_cast(el.m_value.number_float), true); + write_number(static_cast(el.m_data.m_value.number_float), true); } } return false; @@ -16757,11 +16882,11 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // // SPDX-FileCopyrightText: 2008-2009 Björn Hoehrmann -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -16782,11 +16907,11 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // // SPDX-FileCopyrightText: 2009 Florian Loitsch -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -17692,7 +17817,7 @@ void grisu2(char* buf, int& len, int& decimal_exponent, FloatType value) // NB: If the neighbors are computed for single-precision numbers, there is a single float // (7.0385307e-26f) which can't be recovered using strtod. The resulting double precision // value is off by 1 ulp. -#if 0 +#if 0 // NOLINT(readability-avoid-unconditional-preprocessor-if) const boundaries w = compute_boundaries(static_cast(value)); #else const boundaries w = compute_boundaries(value); @@ -17994,11 +18119,11 @@ class serializer const unsigned int indent_step, const unsigned int current_indent = 0) { - switch (val.m_type) + switch (val.m_data.m_type) { case value_t::object: { - if (val.m_value.object->empty()) + if (val.m_data.m_value.object->empty()) { o->write_characters("{}", 2); return; @@ -18016,8 +18141,8 @@ class serializer } // first n-1 elements - auto i = val.m_value.object->cbegin(); - for (std::size_t cnt = 0; cnt < val.m_value.object->size() - 1; ++cnt, ++i) + auto i = val.m_data.m_value.object->cbegin(); + for (std::size_t cnt = 0; cnt < val.m_data.m_value.object->size() - 1; ++cnt, ++i) { o->write_characters(indent_string.c_str(), new_indent); o->write_character('\"'); @@ -18028,8 +18153,8 @@ class serializer } // last element - JSON_ASSERT(i != val.m_value.object->cend()); - JSON_ASSERT(std::next(i) == val.m_value.object->cend()); + JSON_ASSERT(i != val.m_data.m_value.object->cend()); + JSON_ASSERT(std::next(i) == val.m_data.m_value.object->cend()); o->write_characters(indent_string.c_str(), new_indent); o->write_character('\"'); dump_escaped(i->first, ensure_ascii); @@ -18045,8 +18170,8 @@ class serializer o->write_character('{'); // first n-1 elements - auto i = val.m_value.object->cbegin(); - for (std::size_t cnt = 0; cnt < val.m_value.object->size() - 1; ++cnt, ++i) + auto i = val.m_data.m_value.object->cbegin(); + for (std::size_t cnt = 0; cnt < val.m_data.m_value.object->size() - 1; ++cnt, ++i) { o->write_character('\"'); dump_escaped(i->first, ensure_ascii); @@ -18056,8 +18181,8 @@ class serializer } // last element - JSON_ASSERT(i != val.m_value.object->cend()); - JSON_ASSERT(std::next(i) == val.m_value.object->cend()); + JSON_ASSERT(i != val.m_data.m_value.object->cend()); + JSON_ASSERT(std::next(i) == val.m_data.m_value.object->cend()); o->write_character('\"'); dump_escaped(i->first, ensure_ascii); o->write_characters("\":", 2); @@ -18071,7 +18196,7 @@ class serializer case value_t::array: { - if (val.m_value.array->empty()) + if (val.m_data.m_value.array->empty()) { o->write_characters("[]", 2); return; @@ -18089,8 +18214,8 @@ class serializer } // first n-1 elements - for (auto i = val.m_value.array->cbegin(); - i != val.m_value.array->cend() - 1; ++i) + for (auto i = val.m_data.m_value.array->cbegin(); + i != val.m_data.m_value.array->cend() - 1; ++i) { o->write_characters(indent_string.c_str(), new_indent); dump(*i, true, ensure_ascii, indent_step, new_indent); @@ -18098,9 +18223,9 @@ class serializer } // last element - JSON_ASSERT(!val.m_value.array->empty()); + JSON_ASSERT(!val.m_data.m_value.array->empty()); o->write_characters(indent_string.c_str(), new_indent); - dump(val.m_value.array->back(), true, ensure_ascii, indent_step, new_indent); + dump(val.m_data.m_value.array->back(), true, ensure_ascii, indent_step, new_indent); o->write_character('\n'); o->write_characters(indent_string.c_str(), current_indent); @@ -18111,16 +18236,16 @@ class serializer o->write_character('['); // first n-1 elements - for (auto i = val.m_value.array->cbegin(); - i != val.m_value.array->cend() - 1; ++i) + for (auto i = val.m_data.m_value.array->cbegin(); + i != val.m_data.m_value.array->cend() - 1; ++i) { dump(*i, false, ensure_ascii, indent_step, current_indent); o->write_character(','); } // last element - JSON_ASSERT(!val.m_value.array->empty()); - dump(val.m_value.array->back(), false, ensure_ascii, indent_step, current_indent); + JSON_ASSERT(!val.m_data.m_value.array->empty()); + dump(val.m_data.m_value.array->back(), false, ensure_ascii, indent_step, current_indent); o->write_character(']'); } @@ -18131,7 +18256,7 @@ class serializer case value_t::string: { o->write_character('\"'); - dump_escaped(*val.m_value.string, ensure_ascii); + dump_escaped(*val.m_data.m_value.string, ensure_ascii); o->write_character('\"'); return; } @@ -18153,24 +18278,24 @@ class serializer o->write_characters("\"bytes\": [", 10); - if (!val.m_value.binary->empty()) + if (!val.m_data.m_value.binary->empty()) { - for (auto i = val.m_value.binary->cbegin(); - i != val.m_value.binary->cend() - 1; ++i) + for (auto i = val.m_data.m_value.binary->cbegin(); + i != val.m_data.m_value.binary->cend() - 1; ++i) { dump_integer(*i); o->write_characters(", ", 2); } - dump_integer(val.m_value.binary->back()); + dump_integer(val.m_data.m_value.binary->back()); } o->write_characters("],\n", 3); o->write_characters(indent_string.c_str(), new_indent); o->write_characters("\"subtype\": ", 11); - if (val.m_value.binary->has_subtype()) + if (val.m_data.m_value.binary->has_subtype()) { - dump_integer(val.m_value.binary->subtype()); + dump_integer(val.m_data.m_value.binary->subtype()); } else { @@ -18184,21 +18309,21 @@ class serializer { o->write_characters("{\"bytes\":[", 10); - if (!val.m_value.binary->empty()) + if (!val.m_data.m_value.binary->empty()) { - for (auto i = val.m_value.binary->cbegin(); - i != val.m_value.binary->cend() - 1; ++i) + for (auto i = val.m_data.m_value.binary->cbegin(); + i != val.m_data.m_value.binary->cend() - 1; ++i) { dump_integer(*i); o->write_character(','); } - dump_integer(val.m_value.binary->back()); + dump_integer(val.m_data.m_value.binary->back()); } o->write_characters("],\"subtype\":", 12); - if (val.m_value.binary->has_subtype()) + if (val.m_data.m_value.binary->has_subtype()) { - dump_integer(val.m_value.binary->subtype()); + dump_integer(val.m_data.m_value.binary->subtype()); o->write_character('}'); } else @@ -18211,7 +18336,7 @@ class serializer case value_t::boolean: { - if (val.m_value.boolean) + if (val.m_data.m_value.boolean) { o->write_characters("true", 4); } @@ -18224,19 +18349,19 @@ class serializer case value_t::number_integer: { - dump_integer(val.m_value.number_integer); + dump_integer(val.m_data.m_value.number_integer); return; } case value_t::number_unsigned: { - dump_integer(val.m_value.number_unsigned); + dump_integer(val.m_data.m_value.number_unsigned); return; } case value_t::number_float: { - dump_float(val.m_value.number_float); + dump_float(val.m_data.m_value.number_float); return; } @@ -18810,8 +18935,8 @@ class serializer ? (byte & 0x3fu) | (codep << 6u) : (0xFFu >> type) & (byte); - std::size_t index = 256u + static_cast(state) * 16u + static_cast(type); - JSON_ASSERT(index < 400); + const std::size_t index = 256u + static_cast(state) * 16u + static_cast(type); + JSON_ASSERT(index < utf8d.size()); state = utf8d[index]; return state; } @@ -18878,10 +19003,10 @@ NLOHMANN_JSON_NAMESPACE_END // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -18998,7 +19123,7 @@ template , template::value, int> = 0> - T & at(KeyType && key) + T & at(KeyType && key) // NOLINT(cppcoreguidelines-missing-std-forward) { for (auto it = this->begin(); it != this->end(); ++it) { @@ -19026,7 +19151,7 @@ template , template::value, int> = 0> - const T & at(KeyType && key) const + const T & at(KeyType && key) const // NOLINT(cppcoreguidelines-missing-std-forward) { for (auto it = this->begin(); it != this->end(); ++it) { @@ -19060,7 +19185,7 @@ template , template::value, int> = 0> - size_type erase(KeyType && key) + size_type erase(KeyType && key) // NOLINT(cppcoreguidelines-missing-std-forward) { for (auto it = this->begin(); it != this->end(); ++it) { @@ -19151,7 +19276,7 @@ template , template::value, int> = 0> - size_type count(KeyType && key) const + size_type count(KeyType && key) const // NOLINT(cppcoreguidelines-missing-std-forward) { for (auto it = this->begin(); it != this->end(); ++it) { @@ -19177,7 +19302,7 @@ template , template::value, int> = 0> - iterator find(KeyType && key) + iterator find(KeyType && key) // NOLINT(cppcoreguidelines-missing-std-forward) { for (auto it = this->begin(); it != this->end(); ++it) { @@ -19240,7 +19365,9 @@ NLOHMANN_JSON_NAMESPACE_END #if defined(JSON_HAS_CPP_17) - #include + #if JSON_HAS_STATIC_RTTI + #include + #endif #include #endif @@ -19271,6 +19398,7 @@ The invariants are checked by member function assert_invariant(). */ NLOHMANN_BASIC_JSON_TPL_DECLARATION class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-special-member-functions) + : public ::nlohmann::detail::json_base_class { private: template friend struct detail::external_constructor; @@ -19297,6 +19425,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// workaround type for MSVC using basic_json_t = NLOHMANN_BASIC_JSON_TPL; + using json_base_class_t = ::nlohmann::detail::json_base_class; JSON_PRIVATE_UNLESS_TESTED: // convenience aliases for types residing in namespace detail; @@ -19368,7 +19497,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - ///////////////////// // container types // ///////////////////// @@ -19410,7 +19538,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - /// @brief returns the allocator associated with the container /// @sa https://json.nlohmann.me/api/basic_json/get_allocator/ static allocator_type get_allocator() @@ -19425,7 +19552,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { basic_json result; - result["copyright"] = "(C) 2013-2022 Niels Lohmann"; + result["copyright"] = "(C) 2013-2023 Niels Lohmann"; result["name"] = "JSON for Modern C++"; result["url"] = "https://github.com/nlohmann/json"; result["version"]["string"] = @@ -19473,7 +19600,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec result["compiler"] = {{"family", "unknown"}, {"version", "unknown"}}; #endif - #if defined(_MSVC_LANG) result["compiler"]["c++"] = std::to_string(_MSVC_LANG); #elif defined(__cplusplus) @@ -19484,7 +19610,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec return result; } - /////////////////////////// // JSON value data types // /////////////////////////// @@ -19692,7 +19817,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec object = nullptr; // silence warning, see #821 if (JSON_HEDLEY_UNLIKELY(t == value_t::null)) { - JSON_THROW(other_error::create(500, "961c151d2e87f2686a955a9be24d316f1362bf21 3.11.2", nullptr)); // LCOV_EXCL_LINE + JSON_THROW(other_error::create(500, "961c151d2e87f2686a955a9be24d316f1362bf21 3.11.3", nullptr)); // LCOV_EXCL_LINE } break; } @@ -19731,6 +19856,16 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec void destroy(value_t t) { + if ( + (t == value_t::object && object == nullptr) || + (t == value_t::array && array == nullptr) || + (t == value_t::string && string == nullptr) || + (t == value_t::binary && binary == nullptr) + ) + { + //not initialized (e.g. due to exception in the ctor) + return; + } if (t == value_t::array || t == value_t::object) { // flatten the current json_value to a heap-allocated stack @@ -19761,18 +19896,18 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // its children to the stack to be processed later if (current_item.is_array()) { - std::move(current_item.m_value.array->begin(), current_item.m_value.array->end(), std::back_inserter(stack)); + std::move(current_item.m_data.m_value.array->begin(), current_item.m_data.m_value.array->end(), std::back_inserter(stack)); - current_item.m_value.array->clear(); + current_item.m_data.m_value.array->clear(); } else if (current_item.is_object()) { - for (auto&& it : *current_item.m_value.object) + for (auto&& it : *current_item.m_data.m_value.object) { stack.push_back(std::move(it.second)); } - current_item.m_value.object->clear(); + current_item.m_data.m_value.object->clear(); } // it's now safe that current_item get destructed @@ -19849,10 +19984,10 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec */ void assert_invariant(bool check_parents = true) const noexcept { - JSON_ASSERT(m_type != value_t::object || m_value.object != nullptr); - JSON_ASSERT(m_type != value_t::array || m_value.array != nullptr); - JSON_ASSERT(m_type != value_t::string || m_value.string != nullptr); - JSON_ASSERT(m_type != value_t::binary || m_value.binary != nullptr); + JSON_ASSERT(m_data.m_type != value_t::object || m_data.m_value.object != nullptr); + JSON_ASSERT(m_data.m_type != value_t::array || m_data.m_value.array != nullptr); + JSON_ASSERT(m_data.m_type != value_t::string || m_data.m_value.string != nullptr); + JSON_ASSERT(m_data.m_type != value_t::binary || m_data.m_value.binary != nullptr); #if JSON_DIAGNOSTICS JSON_TRY @@ -19871,11 +20006,11 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec void set_parents() { #if JSON_DIAGNOSTICS - switch (m_type) + switch (m_data.m_type) { case value_t::array: { - for (auto& element : *m_value.array) + for (auto& element : *m_data.m_value.array) { element.m_parent = this; } @@ -19884,7 +20019,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec case value_t::object: { - for (auto& element : *m_value.object) + for (auto& element : *m_data.m_value.object) { element.second.m_parent = this; } @@ -19925,7 +20060,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { // see https://github.com/nlohmann/json/issues/2838 JSON_ASSERT(type() == value_t::array); - if (JSON_HEDLEY_UNLIKELY(m_value.array->capacity() != old_capacity)) + if (JSON_HEDLEY_UNLIKELY(m_data.m_value.array->capacity() != old_capacity)) { // capacity has changed: update all parents set_parents(); @@ -19981,7 +20116,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief create an empty value with a given type /// @sa https://json.nlohmann.me/api/basic_json/basic_json/ basic_json(const value_t v) - : m_type(v), m_value(v) + : m_data(v) { assert_invariant(); } @@ -20055,12 +20190,12 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec *this = nullptr; break; case value_t::discarded: - m_type = value_t::discarded; + m_data.m_type = value_t::discarded; break; default: // LCOV_EXCL_LINE JSON_ASSERT(false); // NOLINT(cert-dcl03-c,hicpp-static-assert,misc-static-assert) LCOV_EXCL_LINE } - JSON_ASSERT(m_type == val.type()); + JSON_ASSERT(m_data.m_type == val.type()); set_parents(); assert_invariant(); } @@ -20076,7 +20211,10 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec bool is_an_object = std::all_of(init.begin(), init.end(), [](const detail::json_ref& element_ref) { - return element_ref->is_array() && element_ref->size() == 2 && (*element_ref)[0].is_string(); + // The cast is to ensure op[size_type] is called, bearing in mind size_type may not be int; + // (many string types can be constructed from 0 via its null-pointer guise, so we get a + // broken call to op[key_type], the wrong semantics and a 4804 warning on Windows) + return element_ref->is_array() && element_ref->size() == 2 && (*element_ref)[static_cast(0)].is_string(); }); // adjust type if type deduction is not wanted @@ -20098,22 +20236,22 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_an_object) { // the initializer list is a list of pairs -> create object - m_type = value_t::object; - m_value = value_t::object; + m_data.m_type = value_t::object; + m_data.m_value = value_t::object; for (auto& element_ref : init) { auto element = element_ref.moved_or_copied(); - m_value.object->emplace( - std::move(*((*element.m_value.array)[0].m_value.string)), - std::move((*element.m_value.array)[1])); + m_data.m_value.object->emplace( + std::move(*((*element.m_data.m_value.array)[0].m_data.m_value.string)), + std::move((*element.m_data.m_value.array)[1])); } } else { // the initializer list describes an array -> create array - m_type = value_t::array; - m_value.array = create(init.begin(), init.end()); + m_data.m_type = value_t::array; + m_data.m_value.array = create(init.begin(), init.end()); } set_parents(); @@ -20126,8 +20264,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec static basic_json binary(const typename binary_t::container_type& init) { auto res = basic_json(); - res.m_type = value_t::binary; - res.m_value = init; + res.m_data.m_type = value_t::binary; + res.m_data.m_value = init; return res; } @@ -20137,8 +20275,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec static basic_json binary(const typename binary_t::container_type& init, typename binary_t::subtype_type subtype) { auto res = basic_json(); - res.m_type = value_t::binary; - res.m_value = binary_t(init, subtype); + res.m_data.m_type = value_t::binary; + res.m_data.m_value = binary_t(init, subtype); return res; } @@ -20148,8 +20286,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec static basic_json binary(typename binary_t::container_type&& init) { auto res = basic_json(); - res.m_type = value_t::binary; - res.m_value = std::move(init); + res.m_data.m_type = value_t::binary; + res.m_data.m_value = std::move(init); return res; } @@ -20159,8 +20297,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec static basic_json binary(typename binary_t::container_type&& init, typename binary_t::subtype_type subtype) { auto res = basic_json(); - res.m_type = value_t::binary; - res.m_value = binary_t(std::move(init), subtype); + res.m_data.m_type = value_t::binary; + res.m_data.m_value = binary_t(std::move(init), subtype); return res; } @@ -20182,10 +20320,9 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief construct an array with count copies of given value /// @sa https://json.nlohmann.me/api/basic_json/basic_json/ - basic_json(size_type cnt, const basic_json& val) - : m_type(value_t::array) + basic_json(size_type cnt, const basic_json& val): + m_data{cnt, val} { - m_value.array = create(cnt, val); set_parents(); assert_invariant(); } @@ -20207,10 +20344,10 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec } // copy type from first iterator - m_type = first.m_object->m_type; + m_data.m_type = first.m_object->m_data.m_type; // check if iterator range is complete for primitive values - switch (m_type) + switch (m_data.m_type) { case value_t::boolean: case value_t::number_float: @@ -20235,55 +20372,55 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec break; } - switch (m_type) + switch (m_data.m_type) { case value_t::number_integer: { - m_value.number_integer = first.m_object->m_value.number_integer; + m_data.m_value.number_integer = first.m_object->m_data.m_value.number_integer; break; } case value_t::number_unsigned: { - m_value.number_unsigned = first.m_object->m_value.number_unsigned; + m_data.m_value.number_unsigned = first.m_object->m_data.m_value.number_unsigned; break; } case value_t::number_float: { - m_value.number_float = first.m_object->m_value.number_float; + m_data.m_value.number_float = first.m_object->m_data.m_value.number_float; break; } case value_t::boolean: { - m_value.boolean = first.m_object->m_value.boolean; + m_data.m_value.boolean = first.m_object->m_data.m_value.boolean; break; } case value_t::string: { - m_value = *first.m_object->m_value.string; + m_data.m_value = *first.m_object->m_data.m_value.string; break; } case value_t::object: { - m_value.object = create(first.m_it.object_iterator, - last.m_it.object_iterator); + m_data.m_value.object = create(first.m_it.object_iterator, + last.m_it.object_iterator); break; } case value_t::array: { - m_value.array = create(first.m_it.array_iterator, - last.m_it.array_iterator); + m_data.m_value.array = create(first.m_it.array_iterator, + last.m_it.array_iterator); break; } case value_t::binary: { - m_value = *first.m_object->m_value.binary; + m_data.m_value = *first.m_object->m_data.m_value.binary; break; } @@ -20297,7 +20434,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec assert_invariant(); } - /////////////////////////////////////// // other constructors and destructor // /////////////////////////////////////// @@ -20310,58 +20446,59 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief copy constructor /// @sa https://json.nlohmann.me/api/basic_json/basic_json/ basic_json(const basic_json& other) - : m_type(other.m_type) + : json_base_class_t(other) { + m_data.m_type = other.m_data.m_type; // check of passed value is valid other.assert_invariant(); - switch (m_type) + switch (m_data.m_type) { case value_t::object: { - m_value = *other.m_value.object; + m_data.m_value = *other.m_data.m_value.object; break; } case value_t::array: { - m_value = *other.m_value.array; + m_data.m_value = *other.m_data.m_value.array; break; } case value_t::string: { - m_value = *other.m_value.string; + m_data.m_value = *other.m_data.m_value.string; break; } case value_t::boolean: { - m_value = other.m_value.boolean; + m_data.m_value = other.m_data.m_value.boolean; break; } case value_t::number_integer: { - m_value = other.m_value.number_integer; + m_data.m_value = other.m_data.m_value.number_integer; break; } case value_t::number_unsigned: { - m_value = other.m_value.number_unsigned; + m_data.m_value = other.m_data.m_value.number_unsigned; break; } case value_t::number_float: { - m_value = other.m_value.number_float; + m_data.m_value = other.m_data.m_value.number_float; break; } case value_t::binary: { - m_value = *other.m_value.binary; + m_data.m_value = *other.m_data.m_value.binary; break; } @@ -20378,15 +20515,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief move constructor /// @sa https://json.nlohmann.me/api/basic_json/basic_json/ basic_json(basic_json&& other) noexcept - : m_type(std::move(other.m_type)), - m_value(std::move(other.m_value)) + : json_base_class_t(std::forward(other)), + m_data(std::move(other.m_data)) { // check that passed value is valid other.assert_invariant(false); // invalidate payload - other.m_type = value_t::null; - other.m_value = {}; + other.m_data.m_type = value_t::null; + other.m_data.m_value = {}; set_parents(); assert_invariant(); @@ -20398,15 +20535,17 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec std::is_nothrow_move_constructible::value&& std::is_nothrow_move_assignable::value&& std::is_nothrow_move_constructible::value&& - std::is_nothrow_move_assignable::value + std::is_nothrow_move_assignable::value&& + std::is_nothrow_move_assignable::value ) { // check that passed value is valid other.assert_invariant(); using std::swap; - swap(m_type, other.m_type); - swap(m_value, other.m_value); + swap(m_data.m_type, other.m_data.m_type); + swap(m_data.m_value, other.m_data.m_value); + json_base_class_t::operator=(std::move(other)); set_parents(); assert_invariant(); @@ -20418,7 +20557,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec ~basic_json() noexcept { assert_invariant(false); - m_value.destroy(m_type); } /// @} @@ -20458,7 +20596,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/type/ constexpr value_t type() const noexcept { - return m_type; + return m_data.m_type; } /// @brief return whether type is primitive @@ -20479,14 +20617,14 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/is_null/ constexpr bool is_null() const noexcept { - return m_type == value_t::null; + return m_data.m_type == value_t::null; } /// @brief return whether value is a boolean /// @sa https://json.nlohmann.me/api/basic_json/is_boolean/ constexpr bool is_boolean() const noexcept { - return m_type == value_t::boolean; + return m_data.m_type == value_t::boolean; } /// @brief return whether value is a number @@ -20500,63 +20638,63 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/is_number_integer/ constexpr bool is_number_integer() const noexcept { - return m_type == value_t::number_integer || m_type == value_t::number_unsigned; + return m_data.m_type == value_t::number_integer || m_data.m_type == value_t::number_unsigned; } /// @brief return whether value is an unsigned integer number /// @sa https://json.nlohmann.me/api/basic_json/is_number_unsigned/ constexpr bool is_number_unsigned() const noexcept { - return m_type == value_t::number_unsigned; + return m_data.m_type == value_t::number_unsigned; } /// @brief return whether value is a floating-point number /// @sa https://json.nlohmann.me/api/basic_json/is_number_float/ constexpr bool is_number_float() const noexcept { - return m_type == value_t::number_float; + return m_data.m_type == value_t::number_float; } /// @brief return whether value is an object /// @sa https://json.nlohmann.me/api/basic_json/is_object/ constexpr bool is_object() const noexcept { - return m_type == value_t::object; + return m_data.m_type == value_t::object; } /// @brief return whether value is an array /// @sa https://json.nlohmann.me/api/basic_json/is_array/ constexpr bool is_array() const noexcept { - return m_type == value_t::array; + return m_data.m_type == value_t::array; } /// @brief return whether value is a string /// @sa https://json.nlohmann.me/api/basic_json/is_string/ constexpr bool is_string() const noexcept { - return m_type == value_t::string; + return m_data.m_type == value_t::string; } /// @brief return whether value is a binary array /// @sa https://json.nlohmann.me/api/basic_json/is_binary/ constexpr bool is_binary() const noexcept { - return m_type == value_t::binary; + return m_data.m_type == value_t::binary; } /// @brief return whether value is discarded /// @sa https://json.nlohmann.me/api/basic_json/is_discarded/ constexpr bool is_discarded() const noexcept { - return m_type == value_t::discarded; + return m_data.m_type == value_t::discarded; } /// @brief return the type of the JSON value (implicit) /// @sa https://json.nlohmann.me/api/basic_json/operator_value_t/ constexpr operator value_t() const noexcept { - return m_type; + return m_data.m_type; } /// @} @@ -20571,7 +20709,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { if (JSON_HEDLEY_LIKELY(is_boolean())) { - return m_value.boolean; + return m_data.m_value.boolean; } JSON_THROW(type_error::create(302, detail::concat("type must be boolean, but is ", type_name()), this)); @@ -20580,97 +20718,97 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// get a pointer to the value (object) object_t* get_impl_ptr(object_t* /*unused*/) noexcept { - return is_object() ? m_value.object : nullptr; + return is_object() ? m_data.m_value.object : nullptr; } /// get a pointer to the value (object) constexpr const object_t* get_impl_ptr(const object_t* /*unused*/) const noexcept { - return is_object() ? m_value.object : nullptr; + return is_object() ? m_data.m_value.object : nullptr; } /// get a pointer to the value (array) array_t* get_impl_ptr(array_t* /*unused*/) noexcept { - return is_array() ? m_value.array : nullptr; + return is_array() ? m_data.m_value.array : nullptr; } /// get a pointer to the value (array) constexpr const array_t* get_impl_ptr(const array_t* /*unused*/) const noexcept { - return is_array() ? m_value.array : nullptr; + return is_array() ? m_data.m_value.array : nullptr; } /// get a pointer to the value (string) string_t* get_impl_ptr(string_t* /*unused*/) noexcept { - return is_string() ? m_value.string : nullptr; + return is_string() ? m_data.m_value.string : nullptr; } /// get a pointer to the value (string) constexpr const string_t* get_impl_ptr(const string_t* /*unused*/) const noexcept { - return is_string() ? m_value.string : nullptr; + return is_string() ? m_data.m_value.string : nullptr; } /// get a pointer to the value (boolean) boolean_t* get_impl_ptr(boolean_t* /*unused*/) noexcept { - return is_boolean() ? &m_value.boolean : nullptr; + return is_boolean() ? &m_data.m_value.boolean : nullptr; } /// get a pointer to the value (boolean) constexpr const boolean_t* get_impl_ptr(const boolean_t* /*unused*/) const noexcept { - return is_boolean() ? &m_value.boolean : nullptr; + return is_boolean() ? &m_data.m_value.boolean : nullptr; } /// get a pointer to the value (integer number) number_integer_t* get_impl_ptr(number_integer_t* /*unused*/) noexcept { - return is_number_integer() ? &m_value.number_integer : nullptr; + return is_number_integer() ? &m_data.m_value.number_integer : nullptr; } /// get a pointer to the value (integer number) constexpr const number_integer_t* get_impl_ptr(const number_integer_t* /*unused*/) const noexcept { - return is_number_integer() ? &m_value.number_integer : nullptr; + return is_number_integer() ? &m_data.m_value.number_integer : nullptr; } /// get a pointer to the value (unsigned number) number_unsigned_t* get_impl_ptr(number_unsigned_t* /*unused*/) noexcept { - return is_number_unsigned() ? &m_value.number_unsigned : nullptr; + return is_number_unsigned() ? &m_data.m_value.number_unsigned : nullptr; } /// get a pointer to the value (unsigned number) constexpr const number_unsigned_t* get_impl_ptr(const number_unsigned_t* /*unused*/) const noexcept { - return is_number_unsigned() ? &m_value.number_unsigned : nullptr; + return is_number_unsigned() ? &m_data.m_value.number_unsigned : nullptr; } /// get a pointer to the value (floating-point number) number_float_t* get_impl_ptr(number_float_t* /*unused*/) noexcept { - return is_number_float() ? &m_value.number_float : nullptr; + return is_number_float() ? &m_data.m_value.number_float : nullptr; } /// get a pointer to the value (floating-point number) constexpr const number_float_t* get_impl_ptr(const number_float_t* /*unused*/) const noexcept { - return is_number_float() ? &m_value.number_float : nullptr; + return is_number_float() ? &m_data.m_value.number_float : nullptr; } /// get a pointer to the value (binary) binary_t* get_impl_ptr(binary_t* /*unused*/) noexcept { - return is_binary() ? m_value.binary : nullptr; + return is_binary() ? m_data.m_value.binary : nullptr; } /// get a pointer to the value (binary) constexpr const binary_t* get_impl_ptr(const binary_t* /*unused*/) const noexcept { - return is_binary() ? m_value.binary : nullptr; + return is_binary() ? m_data.m_value.binary : nullptr; } /*! @@ -21053,7 +21191,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec #if defined(JSON_HAS_CPP_17) && (defined(__GNUC__) || (defined(_MSC_VER) && _MSC_VER >= 1910 && _MSC_VER <= 1914)) detail::negation>, #endif -#if defined(JSON_HAS_CPP_17) +#if defined(JSON_HAS_CPP_17) && JSON_HAS_STATIC_RTTI detail::negation>, #endif detail::is_detected_lazy @@ -21090,7 +21228,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - //////////////////// // element access // //////////////////// @@ -21108,7 +21245,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { JSON_TRY { - return set_parent(m_value.array->at(idx)); + return set_parent(m_data.m_value.array->at(idx)); } JSON_CATCH (std::out_of_range&) { @@ -21131,7 +21268,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { JSON_TRY { - return m_value.array->at(idx); + return m_data.m_value.array->at(idx); } JSON_CATCH (std::out_of_range&) { @@ -21155,8 +21292,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(304, detail::concat("cannot use at() with ", type_name()), this)); } - auto it = m_value.object->find(key); - if (it == m_value.object->end()) + auto it = m_data.m_value.object->find(key); + if (it == m_data.m_value.object->end()) { JSON_THROW(out_of_range::create(403, detail::concat("key '", key, "' not found"), this)); } @@ -21175,8 +21312,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(304, detail::concat("cannot use at() with ", type_name()), this)); } - auto it = m_value.object->find(std::forward(key)); - if (it == m_value.object->end()) + auto it = m_data.m_value.object->find(std::forward(key)); + if (it == m_data.m_value.object->end()) { JSON_THROW(out_of_range::create(403, detail::concat("key '", string_t(std::forward(key)), "' not found"), this)); } @@ -21193,8 +21330,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(304, detail::concat("cannot use at() with ", type_name()), this)); } - auto it = m_value.object->find(key); - if (it == m_value.object->end()) + auto it = m_data.m_value.object->find(key); + if (it == m_data.m_value.object->end()) { JSON_THROW(out_of_range::create(403, detail::concat("key '", key, "' not found"), this)); } @@ -21213,8 +21350,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(304, detail::concat("cannot use at() with ", type_name()), this)); } - auto it = m_value.object->find(std::forward(key)); - if (it == m_value.object->end()) + auto it = m_data.m_value.object->find(std::forward(key)); + if (it == m_data.m_value.object->end()) { JSON_THROW(out_of_range::create(403, detail::concat("key '", string_t(std::forward(key)), "' not found"), this)); } @@ -21228,8 +21365,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // implicitly convert null value to an empty array if (is_null()) { - m_type = value_t::array; - m_value.array = create(); + m_data.m_type = value_t::array; + m_data.m_value.array = create(); assert_invariant(); } @@ -21237,17 +21374,17 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (JSON_HEDLEY_LIKELY(is_array())) { // fill up array with null values if given idx is outside range - if (idx >= m_value.array->size()) + if (idx >= m_data.m_value.array->size()) { #if JSON_DIAGNOSTICS // remember array size & capacity before resizing - const auto old_size = m_value.array->size(); - const auto old_capacity = m_value.array->capacity(); + const auto old_size = m_data.m_value.array->size(); + const auto old_capacity = m_data.m_value.array->capacity(); #endif - m_value.array->resize(idx + 1); + m_data.m_value.array->resize(idx + 1); #if JSON_DIAGNOSTICS - if (JSON_HEDLEY_UNLIKELY(m_value.array->capacity() != old_capacity)) + if (JSON_HEDLEY_UNLIKELY(m_data.m_value.array->capacity() != old_capacity)) { // capacity has changed: update all parents set_parents(); @@ -21261,7 +21398,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec assert_invariant(); } - return m_value.array->operator[](idx); + return m_data.m_value.array->operator[](idx); } JSON_THROW(type_error::create(305, detail::concat("cannot use operator[] with a numeric argument with ", type_name()), this)); @@ -21274,7 +21411,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // const operator[] only works for arrays if (JSON_HEDLEY_LIKELY(is_array())) { - return m_value.array->operator[](idx); + return m_data.m_value.array->operator[](idx); } JSON_THROW(type_error::create(305, detail::concat("cannot use operator[] with a numeric argument with ", type_name()), this)); @@ -21287,15 +21424,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // implicitly convert null value to an empty object if (is_null()) { - m_type = value_t::object; - m_value.object = create(); + m_data.m_type = value_t::object; + m_data.m_value.object = create(); assert_invariant(); } // operator[] only works for objects if (JSON_HEDLEY_LIKELY(is_object())) { - auto result = m_value.object->emplace(std::move(key), nullptr); + auto result = m_data.m_value.object->emplace(std::move(key), nullptr); return set_parent(result.first->second); } @@ -21309,8 +21446,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // const operator[] only works for objects if (JSON_HEDLEY_LIKELY(is_object())) { - auto it = m_value.object->find(key); - JSON_ASSERT(it != m_value.object->end()); + auto it = m_data.m_value.object->find(key); + JSON_ASSERT(it != m_data.m_value.object->end()); return it->second; } @@ -21340,15 +21477,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // implicitly convert null value to an empty object if (is_null()) { - m_type = value_t::object; - m_value.object = create(); + m_data.m_type = value_t::object; + m_data.m_value.object = create(); assert_invariant(); } // operator[] only works for objects if (JSON_HEDLEY_LIKELY(is_object())) { - auto result = m_value.object->emplace(std::forward(key), nullptr); + auto result = m_data.m_value.object->emplace(std::forward(key), nullptr); return set_parent(result.first->second); } @@ -21364,8 +21501,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // const operator[] only works for objects if (JSON_HEDLEY_LIKELY(is_object())) { - auto it = m_value.object->find(std::forward(key)); - JSON_ASSERT(it != m_value.object->end()); + auto it = m_data.m_value.object->find(std::forward(key)); + JSON_ASSERT(it != m_data.m_value.object->end()); return it->second; } @@ -21602,7 +21739,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec IteratorType result = end(); - switch (m_type) + switch (m_data.m_type) { case value_t::boolean: case value_t::number_float: @@ -21619,32 +21756,32 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_string()) { AllocatorType alloc; - std::allocator_traits::destroy(alloc, m_value.string); - std::allocator_traits::deallocate(alloc, m_value.string, 1); - m_value.string = nullptr; + std::allocator_traits::destroy(alloc, m_data.m_value.string); + std::allocator_traits::deallocate(alloc, m_data.m_value.string, 1); + m_data.m_value.string = nullptr; } else if (is_binary()) { AllocatorType alloc; - std::allocator_traits::destroy(alloc, m_value.binary); - std::allocator_traits::deallocate(alloc, m_value.binary, 1); - m_value.binary = nullptr; + std::allocator_traits::destroy(alloc, m_data.m_value.binary); + std::allocator_traits::deallocate(alloc, m_data.m_value.binary, 1); + m_data.m_value.binary = nullptr; } - m_type = value_t::null; + m_data.m_type = value_t::null; assert_invariant(); break; } case value_t::object: { - result.m_it.object_iterator = m_value.object->erase(pos.m_it.object_iterator); + result.m_it.object_iterator = m_data.m_value.object->erase(pos.m_it.object_iterator); break; } case value_t::array: { - result.m_it.array_iterator = m_value.array->erase(pos.m_it.array_iterator); + result.m_it.array_iterator = m_data.m_value.array->erase(pos.m_it.array_iterator); break; } @@ -21672,7 +21809,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec IteratorType result = end(); - switch (m_type) + switch (m_data.m_type) { case value_t::boolean: case value_t::number_float: @@ -21690,33 +21827,33 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_string()) { AllocatorType alloc; - std::allocator_traits::destroy(alloc, m_value.string); - std::allocator_traits::deallocate(alloc, m_value.string, 1); - m_value.string = nullptr; + std::allocator_traits::destroy(alloc, m_data.m_value.string); + std::allocator_traits::deallocate(alloc, m_data.m_value.string, 1); + m_data.m_value.string = nullptr; } else if (is_binary()) { AllocatorType alloc; - std::allocator_traits::destroy(alloc, m_value.binary); - std::allocator_traits::deallocate(alloc, m_value.binary, 1); - m_value.binary = nullptr; + std::allocator_traits::destroy(alloc, m_data.m_value.binary); + std::allocator_traits::deallocate(alloc, m_data.m_value.binary, 1); + m_data.m_value.binary = nullptr; } - m_type = value_t::null; + m_data.m_type = value_t::null; assert_invariant(); break; } case value_t::object: { - result.m_it.object_iterator = m_value.object->erase(first.m_it.object_iterator, + result.m_it.object_iterator = m_data.m_value.object->erase(first.m_it.object_iterator, last.m_it.object_iterator); break; } case value_t::array: { - result.m_it.array_iterator = m_value.array->erase(first.m_it.array_iterator, + result.m_it.array_iterator = m_data.m_value.array->erase(first.m_it.array_iterator, last.m_it.array_iterator); break; } @@ -21741,7 +21878,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(307, detail::concat("cannot use erase() with ", type_name()), this)); } - return m_value.object->erase(std::forward(key)); + return m_data.m_value.object->erase(std::forward(key)); } template < typename KeyType, detail::enable_if_t < @@ -21754,10 +21891,10 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(type_error::create(307, detail::concat("cannot use erase() with ", type_name()), this)); } - const auto it = m_value.object->find(std::forward(key)); - if (it != m_value.object->end()) + const auto it = m_data.m_value.object->find(std::forward(key)); + if (it != m_data.m_value.object->end()) { - m_value.object->erase(it); + m_data.m_value.object->erase(it); return 1; } return 0; @@ -21795,7 +21932,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(out_of_range::create(401, detail::concat("array index ", std::to_string(idx), " is out of range"), this)); } - m_value.array->erase(m_value.array->begin() + static_cast(idx)); + m_data.m_value.array->erase(m_data.m_value.array->begin() + static_cast(idx)); } else { @@ -21805,7 +21942,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - //////////// // lookup // //////////// @@ -21821,7 +21957,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_object()) { - result.m_it.object_iterator = m_value.object->find(key); + result.m_it.object_iterator = m_data.m_value.object->find(key); } return result; @@ -21835,7 +21971,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_object()) { - result.m_it.object_iterator = m_value.object->find(key); + result.m_it.object_iterator = m_data.m_value.object->find(key); } return result; @@ -21851,7 +21987,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_object()) { - result.m_it.object_iterator = m_value.object->find(std::forward(key)); + result.m_it.object_iterator = m_data.m_value.object->find(std::forward(key)); } return result; @@ -21867,7 +22003,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (is_object()) { - result.m_it.object_iterator = m_value.object->find(std::forward(key)); + result.m_it.object_iterator = m_data.m_value.object->find(std::forward(key)); } return result; @@ -21878,7 +22014,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec size_type count(const typename object_t::key_type& key) const { // return 0 for all nonobject types - return is_object() ? m_value.object->count(key) : 0; + return is_object() ? m_data.m_value.object->count(key) : 0; } /// @brief returns the number of occurrences of a key in a JSON object @@ -21888,14 +22024,14 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec size_type count(KeyType && key) const { // return 0 for all nonobject types - return is_object() ? m_value.object->count(std::forward(key)) : 0; + return is_object() ? m_data.m_value.object->count(std::forward(key)) : 0; } /// @brief check the existence of an element in a JSON object /// @sa https://json.nlohmann.me/api/basic_json/contains/ bool contains(const typename object_t::key_type& key) const { - return is_object() && m_value.object->find(key) != m_value.object->end(); + return is_object() && m_data.m_value.object->find(key) != m_data.m_value.object->end(); } /// @brief check the existence of an element in a JSON object @@ -21904,7 +22040,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec detail::is_usable_as_basic_json_key_type::value, int> = 0> bool contains(KeyType && key) const { - return is_object() && m_value.object->find(std::forward(key)) != m_value.object->end(); + return is_object() && m_data.m_value.object->find(std::forward(key)) != m_data.m_value.object->end(); } /// @brief check the existence of an element in a JSON object given a JSON pointer @@ -21923,7 +22059,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - /////////////// // iterators // /////////////// @@ -22062,7 +22197,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - ////////////// // capacity // ////////////// @@ -22074,7 +22208,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/empty/ bool empty() const noexcept { - switch (m_type) + switch (m_data.m_type) { case value_t::null: { @@ -22085,13 +22219,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec case value_t::array: { // delegate call to array_t::empty() - return m_value.array->empty(); + return m_data.m_value.array->empty(); } case value_t::object: { // delegate call to object_t::empty() - return m_value.object->empty(); + return m_data.m_value.object->empty(); } case value_t::string: @@ -22113,7 +22247,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/size/ size_type size() const noexcept { - switch (m_type) + switch (m_data.m_type) { case value_t::null: { @@ -22124,13 +22258,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec case value_t::array: { // delegate call to array_t::size() - return m_value.array->size(); + return m_data.m_value.array->size(); } case value_t::object: { // delegate call to object_t::size() - return m_value.object->size(); + return m_data.m_value.object->size(); } case value_t::string: @@ -22152,18 +22286,18 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/max_size/ size_type max_size() const noexcept { - switch (m_type) + switch (m_data.m_type) { case value_t::array: { // delegate call to array_t::max_size() - return m_value.array->max_size(); + return m_data.m_value.array->max_size(); } case value_t::object: { // delegate call to object_t::max_size() - return m_value.object->max_size(); + return m_data.m_value.object->max_size(); } case value_t::null: @@ -22184,7 +22318,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @} - /////////////// // modifiers // /////////////// @@ -22196,53 +22329,53 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @sa https://json.nlohmann.me/api/basic_json/clear/ void clear() noexcept { - switch (m_type) + switch (m_data.m_type) { case value_t::number_integer: { - m_value.number_integer = 0; + m_data.m_value.number_integer = 0; break; } case value_t::number_unsigned: { - m_value.number_unsigned = 0; + m_data.m_value.number_unsigned = 0; break; } case value_t::number_float: { - m_value.number_float = 0.0; + m_data.m_value.number_float = 0.0; break; } case value_t::boolean: { - m_value.boolean = false; + m_data.m_value.boolean = false; break; } case value_t::string: { - m_value.string->clear(); + m_data.m_value.string->clear(); break; } case value_t::binary: { - m_value.binary->clear(); + m_data.m_value.binary->clear(); break; } case value_t::array: { - m_value.array->clear(); + m_data.m_value.array->clear(); break; } case value_t::object: { - m_value.object->clear(); + m_data.m_value.object->clear(); break; } @@ -22266,15 +22399,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // transform null object into an array if (is_null()) { - m_type = value_t::array; - m_value = value_t::array; + m_data.m_type = value_t::array; + m_data.m_value = value_t::array; assert_invariant(); } // add element to array (move semantics) - const auto old_capacity = m_value.array->capacity(); - m_value.array->push_back(std::move(val)); - set_parent(m_value.array->back(), old_capacity); + const auto old_capacity = m_data.m_value.array->capacity(); + m_data.m_value.array->push_back(std::move(val)); + set_parent(m_data.m_value.array->back(), old_capacity); // if val is moved from, basic_json move constructor marks it null, so we do not call the destructor } @@ -22299,15 +22432,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // transform null object into an array if (is_null()) { - m_type = value_t::array; - m_value = value_t::array; + m_data.m_type = value_t::array; + m_data.m_value = value_t::array; assert_invariant(); } // add element to array - const auto old_capacity = m_value.array->capacity(); - m_value.array->push_back(val); - set_parent(m_value.array->back(), old_capacity); + const auto old_capacity = m_data.m_value.array->capacity(); + m_data.m_value.array->push_back(val); + set_parent(m_data.m_value.array->back(), old_capacity); } /// @brief add an object to an array @@ -22331,13 +22464,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // transform null object into an object if (is_null()) { - m_type = value_t::object; - m_value = value_t::object; + m_data.m_type = value_t::object; + m_data.m_value = value_t::object; assert_invariant(); } // add element to object - auto res = m_value.object->insert(val); + auto res = m_data.m_value.object->insert(val); set_parent(res.first->second); } @@ -22387,15 +22520,15 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // transform null object into an array if (is_null()) { - m_type = value_t::array; - m_value = value_t::array; + m_data.m_type = value_t::array; + m_data.m_value = value_t::array; assert_invariant(); } // add element to array (perfect forwarding) - const auto old_capacity = m_value.array->capacity(); - m_value.array->emplace_back(std::forward(args)...); - return set_parent(m_value.array->back(), old_capacity); + const auto old_capacity = m_data.m_value.array->capacity(); + m_data.m_value.array->emplace_back(std::forward(args)...); + return set_parent(m_data.m_value.array->back(), old_capacity); } /// @brief add an object to an object if key does not exist @@ -22412,13 +22545,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // transform null object into an object if (is_null()) { - m_type = value_t::object; - m_value = value_t::object; + m_data.m_type = value_t::object; + m_data.m_value = value_t::object; assert_invariant(); } // add element to array (perfect forwarding) - auto res = m_value.object->emplace(std::forward(args)...); + auto res = m_data.m_value.object->emplace(std::forward(args)...); set_parent(res.first->second); // create result iterator and set iterator to the result of emplace @@ -22436,14 +22569,14 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec iterator insert_iterator(const_iterator pos, Args&& ... args) { iterator result(this); - JSON_ASSERT(m_value.array != nullptr); + JSON_ASSERT(m_data.m_value.array != nullptr); - auto insert_pos = std::distance(m_value.array->begin(), pos.m_it.array_iterator); - m_value.array->insert(pos.m_it.array_iterator, std::forward(args)...); - result.m_it.array_iterator = m_value.array->begin() + insert_pos; + auto insert_pos = std::distance(m_data.m_value.array->begin(), pos.m_it.array_iterator); + m_data.m_value.array->insert(pos.m_it.array_iterator, std::forward(args)...); + result.m_it.array_iterator = m_data.m_value.array->begin() + insert_pos; // This could have been written as: - // result.m_it.array_iterator = m_value.array->insert(pos.m_it.array_iterator, cnt, val); + // result.m_it.array_iterator = m_data.m_value.array->insert(pos.m_it.array_iterator, cnt, val); // but the return value of insert is missing in GCC 4.8, so it is written this way instead. set_parents(); @@ -22570,7 +22703,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_THROW(invalid_iterator::create(202, "iterators first and last must point to objects", this)); } - m_value.object->insert(first.m_it.object_iterator, last.m_it.object_iterator); + m_data.m_value.object->insert(first.m_it.object_iterator, last.m_it.object_iterator); } /// @brief updates a JSON object from another object, overwriting existing keys @@ -22587,8 +22720,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // implicitly convert null value to an empty object if (is_null()) { - m_type = value_t::object; - m_value.object = create(); + m_data.m_type = value_t::object; + m_data.m_value.object = create(); assert_invariant(); } @@ -22613,16 +22746,16 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec { if (merge_objects && it.value().is_object()) { - auto it2 = m_value.object->find(it.key()); - if (it2 != m_value.object->end()) + auto it2 = m_data.m_value.object->find(it.key()); + if (it2 != m_data.m_value.object->end()) { it2->second.update(it.value(), true); continue; } } - m_value.object->operator[](it.key()) = it.value(); + m_data.m_value.object->operator[](it.key()) = it.value(); #if JSON_DIAGNOSTICS - m_value.object->operator[](it.key()).m_parent = this; + m_data.m_value.object->operator[](it.key()).m_parent = this; #endif } } @@ -22632,12 +22765,12 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec void swap(reference other) noexcept ( std::is_nothrow_move_constructible::value&& std::is_nothrow_move_assignable::value&& - std::is_nothrow_move_constructible::value&& + std::is_nothrow_move_constructible::value&& // NOLINT(cppcoreguidelines-noexcept-swap,performance-noexcept-swap) std::is_nothrow_move_assignable::value ) { - std::swap(m_type, other.m_type); - std::swap(m_value, other.m_value); + std::swap(m_data.m_type, other.m_data.m_type); + std::swap(m_data.m_value, other.m_data.m_value); set_parents(); other.set_parents(); @@ -22649,7 +22782,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec friend void swap(reference left, reference right) noexcept ( std::is_nothrow_move_constructible::value&& std::is_nothrow_move_assignable::value&& - std::is_nothrow_move_constructible::value&& + std::is_nothrow_move_constructible::value&& // NOLINT(cppcoreguidelines-noexcept-swap,performance-noexcept-swap) std::is_nothrow_move_assignable::value ) { @@ -22658,13 +22791,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief exchanges the values /// @sa https://json.nlohmann.me/api/basic_json/swap/ - void swap(array_t& other) // NOLINT(bugprone-exception-escape) + void swap(array_t& other) // NOLINT(bugprone-exception-escape,cppcoreguidelines-noexcept-swap,performance-noexcept-swap) { // swap only works for arrays if (JSON_HEDLEY_LIKELY(is_array())) { using std::swap; - swap(*(m_value.array), other); + swap(*(m_data.m_value.array), other); } else { @@ -22674,13 +22807,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief exchanges the values /// @sa https://json.nlohmann.me/api/basic_json/swap/ - void swap(object_t& other) // NOLINT(bugprone-exception-escape) + void swap(object_t& other) // NOLINT(bugprone-exception-escape,cppcoreguidelines-noexcept-swap,performance-noexcept-swap) { // swap only works for objects if (JSON_HEDLEY_LIKELY(is_object())) { using std::swap; - swap(*(m_value.object), other); + swap(*(m_data.m_value.object), other); } else { @@ -22690,13 +22823,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief exchanges the values /// @sa https://json.nlohmann.me/api/basic_json/swap/ - void swap(string_t& other) // NOLINT(bugprone-exception-escape) + void swap(string_t& other) // NOLINT(bugprone-exception-escape,cppcoreguidelines-noexcept-swap,performance-noexcept-swap) { // swap only works for strings if (JSON_HEDLEY_LIKELY(is_string())) { using std::swap; - swap(*(m_value.string), other); + swap(*(m_data.m_value.string), other); } else { @@ -22706,13 +22839,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec /// @brief exchanges the values /// @sa https://json.nlohmann.me/api/basic_json/swap/ - void swap(binary_t& other) // NOLINT(bugprone-exception-escape) + void swap(binary_t& other) // NOLINT(bugprone-exception-escape,cppcoreguidelines-noexcept-swap,performance-noexcept-swap) { // swap only works for strings if (JSON_HEDLEY_LIKELY(is_binary())) { using std::swap; - swap(*(m_value.binary), other); + swap(*(m_data.m_value.binary), other); } else { @@ -22728,7 +22861,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec if (JSON_HEDLEY_LIKELY(is_binary())) { using std::swap; - swap(*(m_value.binary), other); + swap(*(m_data.m_value.binary), other); } else { @@ -22756,31 +22889,31 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec switch (lhs_type) \ { \ case value_t::array: \ - return (*lhs.m_value.array) op (*rhs.m_value.array); \ + return (*lhs.m_data.m_value.array) op (*rhs.m_data.m_value.array); \ \ case value_t::object: \ - return (*lhs.m_value.object) op (*rhs.m_value.object); \ + return (*lhs.m_data.m_value.object) op (*rhs.m_data.m_value.object); \ \ case value_t::null: \ return (null_result); \ \ case value_t::string: \ - return (*lhs.m_value.string) op (*rhs.m_value.string); \ + return (*lhs.m_data.m_value.string) op (*rhs.m_data.m_value.string); \ \ case value_t::boolean: \ - return (lhs.m_value.boolean) op (rhs.m_value.boolean); \ + return (lhs.m_data.m_value.boolean) op (rhs.m_data.m_value.boolean); \ \ case value_t::number_integer: \ - return (lhs.m_value.number_integer) op (rhs.m_value.number_integer); \ + return (lhs.m_data.m_value.number_integer) op (rhs.m_data.m_value.number_integer); \ \ case value_t::number_unsigned: \ - return (lhs.m_value.number_unsigned) op (rhs.m_value.number_unsigned); \ + return (lhs.m_data.m_value.number_unsigned) op (rhs.m_data.m_value.number_unsigned); \ \ case value_t::number_float: \ - return (lhs.m_value.number_float) op (rhs.m_value.number_float); \ + return (lhs.m_data.m_value.number_float) op (rhs.m_data.m_value.number_float); \ \ case value_t::binary: \ - return (*lhs.m_value.binary) op (*rhs.m_value.binary); \ + return (*lhs.m_data.m_value.binary) op (*rhs.m_data.m_value.binary); \ \ case value_t::discarded: \ default: \ @@ -22789,27 +22922,27 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec } \ else if (lhs_type == value_t::number_integer && rhs_type == value_t::number_float) \ { \ - return static_cast(lhs.m_value.number_integer) op rhs.m_value.number_float; \ + return static_cast(lhs.m_data.m_value.number_integer) op rhs.m_data.m_value.number_float; \ } \ else if (lhs_type == value_t::number_float && rhs_type == value_t::number_integer) \ { \ - return lhs.m_value.number_float op static_cast(rhs.m_value.number_integer); \ + return lhs.m_data.m_value.number_float op static_cast(rhs.m_data.m_value.number_integer); \ } \ else if (lhs_type == value_t::number_unsigned && rhs_type == value_t::number_float) \ { \ - return static_cast(lhs.m_value.number_unsigned) op rhs.m_value.number_float; \ + return static_cast(lhs.m_data.m_value.number_unsigned) op rhs.m_data.m_value.number_float; \ } \ else if (lhs_type == value_t::number_float && rhs_type == value_t::number_unsigned) \ { \ - return lhs.m_value.number_float op static_cast(rhs.m_value.number_unsigned); \ + return lhs.m_data.m_value.number_float op static_cast(rhs.m_data.m_value.number_unsigned); \ } \ else if (lhs_type == value_t::number_unsigned && rhs_type == value_t::number_integer) \ { \ - return static_cast(lhs.m_value.number_unsigned) op rhs.m_value.number_integer; \ + return static_cast(lhs.m_data.m_value.number_unsigned) op rhs.m_data.m_value.number_integer; \ } \ else if (lhs_type == value_t::number_integer && rhs_type == value_t::number_unsigned) \ { \ - return lhs.m_value.number_integer op static_cast(rhs.m_value.number_unsigned); \ + return lhs.m_data.m_value.number_integer op static_cast(rhs.m_data.m_value.number_unsigned); \ } \ else if(compares_unordered(lhs, rhs))\ {\ @@ -22826,8 +22959,8 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // an operation is computed as an odd number of inverses of others static bool compares_unordered(const_reference lhs, const_reference rhs, bool inverse = false) noexcept { - if ((lhs.is_number_float() && std::isnan(lhs.m_value.number_float) && rhs.is_number()) - || (rhs.is_number_float() && std::isnan(rhs.m_value.number_float) && lhs.is_number())) + if ((lhs.is_number_float() && std::isnan(lhs.m_data.m_value.number_float) && rhs.is_number()) + || (rhs.is_number_float() && std::isnan(rhs.m_data.m_value.number_float) && lhs.is_number())) { return true; } @@ -23171,7 +23304,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec #endif // JSON_NO_IO /// @} - ///////////////////// // deserialization // ///////////////////// @@ -23328,7 +23460,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec JSON_HEDLEY_RETURNS_NON_NULL const char* type_name() const noexcept { - switch (m_type) + switch (m_data.m_type) { case value_t::null: return "null"; @@ -23352,17 +23484,43 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec } } - JSON_PRIVATE_UNLESS_TESTED: ////////////////////// // member variables // ////////////////////// - /// the type of the current element - value_t m_type = value_t::null; + struct data + { + /// the type of the current element + value_t m_type = value_t::null; + + /// the value of the current element + json_value m_value = {}; + + data(const value_t v) + : m_type(v), m_value(v) + { + } + + data(size_type cnt, const basic_json& val) + : m_type(value_t::array) + { + m_value.array = create(cnt, val); + } + + data() noexcept = default; + data(data&&) noexcept = default; + data(const data&) noexcept = delete; + data& operator=(data&&) noexcept = delete; + data& operator=(const data&) noexcept = delete; + + ~data() noexcept + { + m_value.destroy(m_type); + } + }; - /// the value of the current element - json_value m_value = {}; + data m_data = {}; #if JSON_DIAGNOSTICS /// a pointer to a parent value (for debugging purposes) @@ -23543,7 +23701,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec return from_cbor(ptr, ptr + len, strict, allow_exceptions, tag_handler); } - JSON_HEDLEY_WARN_UNUSED_RESULT JSON_HEDLEY_DEPRECATED_FOR(3.8.0, from_cbor(ptr, ptr + len)) static basic_json from_cbor(detail::span_input_adapter&& i, @@ -23667,7 +23824,6 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec return res ? result : basic_json(value_t::discarded); } - /// @brief create a JSON value from an input in BJData format /// @sa https://json.nlohmann.me/api/basic_json/from_bjdata/ template @@ -23890,7 +24046,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec } // make sure the top element of the pointer exists - json_pointer top_pointer = ptr.top(); + json_pointer const top_pointer = ptr.top(); if (top_pointer != ptr) { result.at(top_pointer); @@ -23902,7 +24058,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec // parent must exist when performing patch add per RFC6902 specs basic_json& parent = result.at(ptr); - switch (parent.m_type) + switch (parent.m_data.m_type) { case value_t::null: case value_t::object: @@ -23948,7 +24104,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec }; // wrapper for "remove" operation; remove value at ptr - const auto operation_remove = [this, &result](json_pointer & ptr) + const auto operation_remove = [this, & result](json_pointer & ptr) { // get reference to parent of JSON pointer ptr const auto last_path = ptr.back(); @@ -23991,13 +24147,13 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec bool string_type) -> basic_json & { // find value - auto it = val.m_value.object->find(member); + auto it = val.m_data.m_value.object->find(member); // context-sensitive error message - const auto error_msg = (op == "op") ? "operation" : detail::concat("operation '", op, '\''); + const auto error_msg = (op == "op") ? "operation" : detail::concat("operation '", op, '\''); // NOLINT(bugprone-unused-local-non-trivial-variable) // check if desired value is present - if (JSON_HEDLEY_UNLIKELY(it == val.m_value.object->end())) + if (JSON_HEDLEY_UNLIKELY(it == val.m_data.m_value.object->end())) { // NOLINTNEXTLINE(performance-inefficient-string-concatenation) JSON_THROW(parse_error::create(105, 0, detail::concat(error_msg, " must have member '", member, "'"), &val)); @@ -24052,7 +24208,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec json_pointer from_ptr(from_path); // the "from" location must exist - use at() - basic_json v = result.at(from_ptr); + basic_json const v = result.at(from_ptr); // The move operation is functionally identical to a // "remove" operation on the "from" location, followed @@ -24069,7 +24225,7 @@ class basic_json // NOLINT(cppcoreguidelines-special-member-functions,hicpp-spec const json_pointer from_ptr(from_path); // the "from" location must exist - use at() - basic_json v = result.at(from_ptr); + basic_json const v = result.at(from_ptr); // The copy is functionally identical to an "add" // operation at the target location using the value @@ -24311,7 +24467,11 @@ inline namespace json_literals /// @brief user-defined string literal for JSON values /// @sa https://json.nlohmann.me/api/basic_json/operator_literal_json/ JSON_HEDLEY_NON_NULL(1) -inline nlohmann::json operator "" _json(const char* s, std::size_t n) +#if !defined(JSON_HEDLEY_GCC_VERSION) || JSON_HEDLEY_GCC_VERSION_CHECK(4,9,0) + inline nlohmann::json operator ""_json(const char* s, std::size_t n) +#else + inline nlohmann::json operator "" _json(const char* s, std::size_t n) +#endif { return nlohmann::json::parse(s, s + n); } @@ -24319,7 +24479,11 @@ inline nlohmann::json operator "" _json(const char* s, std::size_t n) /// @brief user-defined string literal for JSON pointer /// @sa https://json.nlohmann.me/api/basic_json/operator_literal_json_pointer/ JSON_HEDLEY_NON_NULL(1) -inline nlohmann::json::json_pointer operator "" _json_pointer(const char* s, std::size_t n) +#if !defined(JSON_HEDLEY_GCC_VERSION) || JSON_HEDLEY_GCC_VERSION_CHECK(4,9,0) + inline nlohmann::json::json_pointer operator ""_json_pointer(const char* s, std::size_t n) +#else + inline nlohmann::json::json_pointer operator "" _json_pointer(const char* s, std::size_t n) +#endif { return nlohmann::json::json_pointer(std::string(s, n)); } @@ -24338,7 +24502,7 @@ namespace std // NOLINT(cert-dcl58-cpp) /// @brief hash value for JSON objects /// @sa https://json.nlohmann.me/api/basic_json/std_hash/ NLOHMANN_BASIC_JSON_TPL_DECLARATION -struct hash +struct hash // NOLINT(cert-dcl58-cpp) { std::size_t operator()(const nlohmann::NLOHMANN_BASIC_JSON_TPL& j) const { @@ -24371,8 +24535,8 @@ struct less< ::nlohmann::detail::value_t> // do not remove the space after '<', /// @brief exchanges the values of two JSON objects /// @sa https://json.nlohmann.me/api/basic_json/std_swap/ NLOHMANN_BASIC_JSON_TPL_DECLARATION -inline void swap(nlohmann::NLOHMANN_BASIC_JSON_TPL& j1, nlohmann::NLOHMANN_BASIC_JSON_TPL& j2) noexcept( // NOLINT(readability-inconsistent-declaration-parameter-name) - is_nothrow_move_constructible::value&& // NOLINT(misc-redundant-expression) +inline void swap(nlohmann::NLOHMANN_BASIC_JSON_TPL& j1, nlohmann::NLOHMANN_BASIC_JSON_TPL& j2) noexcept( // NOLINT(readability-inconsistent-declaration-parameter-name, cert-dcl58-cpp) + is_nothrow_move_constructible::value&& // NOLINT(misc-redundant-expression,cppcoreguidelines-noexcept-swap,performance-noexcept-swap) is_nothrow_move_assignable::value) { j1.swap(j2); @@ -24383,17 +24547,22 @@ inline void swap(nlohmann::NLOHMANN_BASIC_JSON_TPL& j1, nlohmann::NLOHMANN_BASIC } // namespace std #if JSON_USE_GLOBAL_UDLS - using nlohmann::literals::json_literals::operator "" _json; // NOLINT(misc-unused-using-decls,google-global-names-in-headers) - using nlohmann::literals::json_literals::operator "" _json_pointer; //NOLINT(misc-unused-using-decls,google-global-names-in-headers) + #if !defined(JSON_HEDLEY_GCC_VERSION) || JSON_HEDLEY_GCC_VERSION_CHECK(4,9,0) + using nlohmann::literals::json_literals::operator ""_json; // NOLINT(misc-unused-using-decls,google-global-names-in-headers) + using nlohmann::literals::json_literals::operator ""_json_pointer; //NOLINT(misc-unused-using-decls,google-global-names-in-headers) + #else + using nlohmann::literals::json_literals::operator "" _json; // NOLINT(misc-unused-using-decls,google-global-names-in-headers) + using nlohmann::literals::json_literals::operator "" _json_pointer; //NOLINT(misc-unused-using-decls,google-global-names-in-headers) + #endif #endif // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT @@ -24428,16 +24597,17 @@ inline void swap(nlohmann::NLOHMANN_BASIC_JSON_TPL& j1, nlohmann::NLOHMANN_BASIC #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM #undef JSON_HAS_THREE_WAY_COMPARISON #undef JSON_HAS_RANGES + #undef JSON_HAS_STATIC_RTTI #undef JSON_USE_LEGACY_DISCARDED_VALUE_COMPARISON #endif // #include // __ _____ _____ _____ // __| | __| | | | JSON for Modern C++ -// | | |__ | | | | | | version 3.11.2 +// | | |__ | | | | | | version 3.11.3 // |_____|_____|_____|_|___| https://github.com/nlohmann/json // -// SPDX-FileCopyrightText: 2013-2022 Niels Lohmann +// SPDX-FileCopyrightText: 2013-2023 Niels Lohmann // SPDX-License-Identifier: MIT diff --git a/common/log.h b/common/log.h index eb111e784bc9f..e4edcac7d7735 100644 --- a/common/log.h +++ b/common/log.h @@ -234,7 +234,7 @@ inline std::string log_filename_generator_impl(LogTriState multilog, const std:: // INTERNAL, DO NOT USE // USE LOG() INSTEAD // -#ifndef _MSC_VER +#if !defined(_MSC_VER) or defined(__INTEL_LLVM_COMPILER) #define LOG_IMPL(str, ...) \ do { \ if (LOG_TARGET != nullptr) \ @@ -257,7 +257,7 @@ inline std::string log_filename_generator_impl(LogTriState multilog, const std:: // INTERNAL, DO NOT USE // USE LOG_TEE() INSTEAD // -#ifndef _MSC_VER +#if !defined(_MSC_VER) or defined(__INTEL_LLVM_COMPILER) #define LOG_TEE_IMPL(str, ...) \ do { \ if (LOG_TARGET != nullptr) \ @@ -566,6 +566,7 @@ inline void log_print_usage() printf(" --log-new Create a separate new log file on start. " "Each log file will have unique name: \"..log\"\n"); printf(" --log-append Don't truncate the old log file.\n"); + printf("\n"); } #define log_dump_cmdline(argc, argv) log_dump_cmdline_impl(argc, argv) diff --git a/common/ngram-cache.cpp b/common/ngram-cache.cpp new file mode 100644 index 0000000000000..3ca112ef1613d --- /dev/null +++ b/common/ngram-cache.cpp @@ -0,0 +1,282 @@ +#include "ngram-cache.h" +#include "common.h" +#include "log.h" + +#include +#include + +void llama_ngram_cache_update(llama_ngram_cache & ngram_cache, int ngram_min, int ngram_max, + std::vector & inp, int nnew, bool print_progress) { + const int64_t t_start_ms = ggml_time_ms(); + const int64_t inp_size = inp.size(); + + const int64_t n_todo = inp_size * (ngram_max - ngram_min + 1); + int64_t n_done = 0; + + for (int64_t ngram_size = ngram_min; ngram_size <= ngram_max; ++ngram_size) { + const int64_t i_start = std::max(inp_size - nnew, ngram_size); + for (int64_t i = i_start; i < inp_size; ++i) { + const int64_t ngram_start = i - ngram_size; + llama_ngram ngram(&inp[ngram_start], ngram_size); + const llama_token token = inp[i]; + + llama_ngram_cache::iterator part_it = ngram_cache.find(ngram); + if (part_it == ngram_cache.end()) { + llama_ngram_cache_part part; + part.emplace(token, 1); + ngram_cache.emplace(ngram, part); + } else { + llama_ngram_cache_part::iterator token_count_it = part_it->second.find(token); + if (token_count_it == part_it->second.end()) { + part_it->second.emplace(token, 1); + } else { + token_count_it->second++; + } + } + ++n_done; + + if (print_progress && n_done % 10000000 == 0) { + const int64_t t_now_ms = ggml_time_ms(); + const int64_t eta_ms = (inp_size*(ngram_max-ngram_min+1) - n_done) * (t_now_ms - t_start_ms) / n_done; + const int64_t eta_min = eta_ms / (60*1000); + const int64_t eta_s = (eta_ms - 60*1000*eta_min) / 1000; + + fprintf(stderr, "%s: %" PRId64 "/%" PRId64 " done, ETA: %02" PRId64 ":%02" PRId64 "\n", __func__, n_done, n_todo, eta_min, eta_s); + } + } + } +} + +// Helper function to get a token from the combined, speculative sequence of inp and draft. +static llama_token get_token(const std::vector & inp, const std::vector & draft, const size_t i) { + return i < inp.size() ? inp[i] : draft[1 + i - inp.size()]; +} + +// If sample size or percentage are below these thresholds the draft is aborted early: +constexpr int draft_min_sample_size_lax[LLAMA_NGRAM_MAX] = { 2, 2, 1, 1}; +constexpr int draft_min_percent_lax[LLAMA_NGRAM_MAX] = {66, 50, 50, 50}; +constexpr int draft_min_sample_size_strict[LLAMA_NGRAM_MAX] = { 4, 3, 2, 2}; +constexpr int draft_min_percent_strict[LLAMA_NGRAM_MAX] = {75, 66, 66, 66}; + +// Helper function that tries to draft a token from only the static ngram cache: +static llama_token try_draft(llama_ngram_cache & nc_static, const llama_ngram ngram_static) { + llama_ngram_cache::iterator part_static_it = nc_static.find(ngram_static); + if (part_static_it == nc_static.end()) { + return -1; + } + const llama_ngram_cache_part part_static = part_static_it->second; + + int max_count_static = 0; + int sum_count_static = 0; + llama_token max_token = -1; + + for (std::pair token_count_static : part_static) { + const llama_token token = token_count_static.first; + const int32_t count_static = token_count_static.second; + + if (count_static > max_count_static) { + max_token = token; + max_count_static = count_static; + } + sum_count_static += count_static; + } + + if (sum_count_static < draft_min_sample_size_lax[LLAMA_NGRAM_STATIC-1]) { + return -1; + } + if (100*max_count_static < draft_min_percent_lax[LLAMA_NGRAM_STATIC-1]*sum_count_static) { + return -1; + } + return max_token; +} + +// Try to draft a token from primary cache (context/dynamic), validate with static cache: +static llama_token try_draft( + llama_ngram_cache & nc_primary, const std::vector & ngrams_primary, llama_ngram_cache_part & part_static, + const int * min_sample_size, const int * min_percent) { + + llama_token drafted_token = -1; + + for (int i = ngrams_primary.size()-1; i >= 0 && drafted_token == -1; --i) { + const llama_ngram ngram_primary = ngrams_primary[i]; + + llama_ngram_cache::iterator part_primary_it = nc_primary.find(ngram_primary); + if (part_primary_it == nc_primary.end()) { + continue; + } + const llama_ngram_cache_part part_primary = part_primary_it->second; + + int max_count_primary = 0; + int max_count_static = 0; + int sum_count_primary = 0; + llama_token max_token = -1; + + for (std::pair token_count_primary : part_primary) { + const llama_token token = token_count_primary.first; + + llama_ngram_cache_part::iterator token_count_static_it = part_static.find(token); + + const int32_t count_primary = token_count_primary.second; + const int32_t count_static = token_count_static_it != part_static.end() ? 100*token_count_static_it->second : 1; + + if (count_primary*count_static > max_count_primary*max_count_static) { + max_token = token; + max_count_primary = count_primary; + max_count_static = count_static; + } + sum_count_primary += count_primary; + } + + if (sum_count_primary < min_sample_size[i]) { + continue; + } + if (100*max_count_primary < min_percent[i]*sum_count_primary) { + continue;; + } + drafted_token = max_token; + } + + return drafted_token; +} + +void llama_ngram_cache_draft( + std::vector & inp, std::vector & draft, int n_draft, int ngram_min, int ngram_max, + llama_ngram_cache & nc_context, llama_ngram_cache & nc_dynamic, llama_ngram_cache & nc_static +) { + GGML_ASSERT(draft.size() == 1); + const int inp_size = inp.size(); + + if (inp_size < LLAMA_NGRAM_STATIC) { + return; + } + + while ((int) draft.size()-1 < n_draft) { + llama_token drafted_token = -1; + + const int ngram_start_static = inp_size-LLAMA_NGRAM_STATIC + draft.size()-1; + llama_ngram ngram_static; + for (int j = ngram_start_static; j < ngram_start_static + LLAMA_NGRAM_STATIC; ++j) { + ngram_static.tokens[j-ngram_start_static] = get_token(inp, draft, j); + } + llama_ngram_cache::iterator part_static_it = nc_static.find(ngram_static); + llama_ngram_cache_part part_static; + if (part_static_it != nc_static.end()) { + part_static = part_static_it->second; + } + + // cd = context + dynamic + std::vector ngrams_cd; + for (int ngram_size_cd = ngram_min; ngram_size_cd <= ngram_max; ++ngram_size_cd) { + const int ngram_start_cd = inp_size-ngram_size_cd + draft.size()-1; + llama_ngram ngram_cd; + for (int j = ngram_start_cd; j < ngram_start_cd + ngram_size_cd; ++j) { + ngram_cd.tokens[j-ngram_start_cd] = get_token(inp, draft, j); + } + ngrams_cd.push_back(ngram_cd); + } + if (drafted_token == -1) { + drafted_token = try_draft(nc_context, ngrams_cd, part_static, draft_min_sample_size_lax, draft_min_percent_lax); + } + if (drafted_token == -1) { + drafted_token = try_draft(nc_dynamic, ngrams_cd, part_static, draft_min_sample_size_strict, draft_min_percent_strict); + } + if (drafted_token == -1) { + drafted_token = try_draft(nc_static, ngram_static); + } + + if (drafted_token == -1) { + break; + } + + LOG(" - draft candidate: token=%d\n", drafted_token); + draft.push_back(drafted_token); + } +} + +void llama_ngram_cache_save(llama_ngram_cache & ngram_cache, std::string & filename) { + std::ofstream file_out(filename, std::ios::binary); + for (std::pair item : ngram_cache) { + const llama_ngram ngram = item.first; + llama_ngram_cache_part token_counts = item.second; + GGML_ASSERT(!token_counts.empty()); + const int32_t ntokens = token_counts.size(); + GGML_ASSERT(ntokens > 0); + + file_out.write(reinterpret_cast(&ngram), sizeof(llama_ngram)); + file_out.write(reinterpret_cast(&ntokens), sizeof(int32_t)); + for (std::pair item2 : token_counts) { + const llama_token token = item2.first; + const int32_t count = item2.second; + GGML_ASSERT(count > 0); + + file_out.write(reinterpret_cast(&token), sizeof(llama_token)); + file_out.write(reinterpret_cast(&count), sizeof(int32_t)); + } + } + +} + +llama_ngram_cache llama_ngram_cache_load(std::string & filename) { + std::ifstream hashmap_file(filename, std::ios::binary); + if (!hashmap_file) { + throw std::ifstream::failure("Unable to open file " + filename); + } + llama_ngram_cache ngram_cache; + + llama_ngram ngram; + int32_t ntokens; + llama_token token; + int32_t count; + + char * ngramc = reinterpret_cast(&ngram); + char * ntokensc = reinterpret_cast(&ntokens); + char * tokenc = reinterpret_cast(&token); + char * countc = reinterpret_cast(&count); + while(hashmap_file.read(ngramc, sizeof(llama_ngram))) { + GGML_ASSERT(!hashmap_file.eof()); + GGML_ASSERT(hashmap_file.read(ntokensc, sizeof(int32_t))); + GGML_ASSERT(ntokens > 0); + llama_ngram_cache_part token_counts; + + for (int i = 0; i < ntokens; ++i) { + GGML_ASSERT(!hashmap_file.eof()); + GGML_ASSERT(hashmap_file.read(tokenc, sizeof(llama_token))); + GGML_ASSERT(!hashmap_file.eof()); + GGML_ASSERT(hashmap_file.read(countc, sizeof(int32_t))); + GGML_ASSERT(count > 0); + token_counts.emplace(token, count); + } + + ngram_cache.emplace(ngram, token_counts); + } + GGML_ASSERT(hashmap_file.eof()); + + return ngram_cache; +} + +void llama_ngram_cache_merge(llama_ngram_cache & ngram_cache_target, llama_ngram_cache & ngram_cache_add) { + for (std::pair ngram_part : ngram_cache_add) { + const llama_ngram ngram = ngram_part.first; + llama_ngram_cache_part part = ngram_part.second; + + llama_ngram_cache::iterator part_merged_it = ngram_cache_target.find(ngram); + if (part_merged_it == ngram_cache_target.end()) { + ngram_cache_target.emplace(ngram, part); + continue; + } + + for (std::pair token_count : part) { + const llama_token token = token_count.first; + const int32_t count = token_count.second; + GGML_ASSERT(count > 0); + + llama_ngram_cache_part::iterator token_count_merged_it = part_merged_it->second.find(token); + if (token_count_merged_it == part_merged_it->second.end()) { + part_merged_it->second.emplace(token, count); + continue; + } + + token_count_merged_it->second += count; + } + } +} diff --git a/common/ngram-cache.h b/common/ngram-cache.h new file mode 100644 index 0000000000000..e4fa4cbd12f11 --- /dev/null +++ b/common/ngram-cache.h @@ -0,0 +1,94 @@ +#pragma once + +#include "llama.h" + +#include +#include +#include + +#define LLAMA_NGRAM_MIN 1 +#define LLAMA_NGRAM_MAX 4 +#define LLAMA_NGRAM_STATIC 2 + +// Data structures to map n-grams to empirical token probabilities: + +struct llama_ngram { + llama_token tokens[LLAMA_NGRAM_MAX]; + + llama_ngram() { + for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { + tokens[i] = -1; + } + } + + llama_ngram(const llama_token * input, const int ngram_size) { + for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { + tokens[i] = i < ngram_size ? input[i] : -1; + } + } + + bool operator==(const llama_ngram & other) const { + for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { + if (tokens[i] != other.tokens[i]) { + return false; + } + } + return true; + } +}; + +struct llama_ngram_hash_function { + size_t operator()(const llama_ngram & ngram) const { + size_t hash = 0; + for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { + hash ^= std::hash{}(ngram.tokens[i]); + } + return hash; + } +}; + +// token -> number of times token has been seen +typedef std::unordered_map llama_ngram_cache_part; + +// n-gram -> empirical distribution of following tokens +typedef std::unordered_map llama_ngram_cache; + + +// Update an ngram cache with tokens. +// ngram_cache: the cache to modify. +// ngram_min/ngram_max: the min/max size of the ngrams to extract from inp_data. +// inp_data: the token sequence with which to update ngram_cache. +// nnew: how many new tokens have been appended to inp_data since the last call to this function. +// print_progress: whether to print progress to stderr. +// +// In order to get correct results inp_data can ONLY BE APPENDED TO. +// Changes in the middle need a complete rebuild. +void llama_ngram_cache_update( + llama_ngram_cache & ngram_cache, int ngram_min, int ngram_max, std::vector & inp_data, int nnew, bool print_progress); + +// Try to draft tokens from ngram caches. +// inp: the tokens generated so far. +// draft: the token sequence to draft. Expected to initially contain the previously sampled token. +// n_draft: maximum number of tokens to add to draft. +// ngram_min/gram_max: the min/max size of the ngrams in nc_context and nc_dynamic. +// nc_context: ngram cache based on current context. +// nc_dynamic: ngram cache based on previous user generations. +// nc_static: ngram cache generated from a large text corpus, used for validation. +void llama_ngram_cache_draft( + std::vector & inp, std::vector & draft, int n_draft, int ngram_min, int ngram_max, + llama_ngram_cache & nc_context, llama_ngram_cache & nc_dynamic, llama_ngram_cache & nc_static); + +// Save an ngram cache to a file. +// ngram_cache: the ngram cache to save. +// filename: the path under which to save the ngram cache. +void llama_ngram_cache_save(llama_ngram_cache & ngram_cache, std::string & filename); + +// Load an ngram cache saved with llama_ngram_cache_save. +// filename: the path from which to load the ngram cache. +// returns: an ngram cache containing the information saved to filename. +llama_ngram_cache llama_ngram_cache_load(std::string & filename); + +// Merge two ngram caches. +// ngram_cache_target: the ngram cache to which to add the information from ngram_cache_add. +// ngram_cache_add: the ngram cache to add to ngram_cache_target. +void llama_ngram_cache_merge(llama_ngram_cache & ngram_cache_target, llama_ngram_cache & ngram_cache_add); diff --git a/common/sampling.cpp b/common/sampling.cpp index da06f16f05de3..53319d3108a58 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -168,76 +168,19 @@ static llama_token llama_sampling_sample_impl( bool is_resampling) { // Add a parameter to indicate if we are resampling const llama_sampling_params & params = ctx_sampling->params; - const int n_vocab = llama_n_vocab(llama_get_model(ctx_main)); - const float temp = params.temp; - const int32_t penalty_last_n = params.penalty_last_n < 0 ? params.n_prev : params.penalty_last_n; - const float penalty_repeat = params.penalty_repeat; - const float penalty_freq = params.penalty_freq; - const float penalty_present = params.penalty_present; const int mirostat = params.mirostat; const float mirostat_tau = params.mirostat_tau; const float mirostat_eta = params.mirostat_eta; - const bool penalize_nl = params.penalize_nl; - auto & prev = ctx_sampling->prev; - auto & cur = ctx_sampling->cur; - - llama_token id = 0; - - // Get a pointer to the logits - float * logits = llama_get_logits_ith(ctx_main, idx); - - // Declare original_logits at the beginning of the function scope std::vector original_logits; - + auto cur_p = llama_sampling_prepare(ctx_sampling, ctx_main, ctx_cfg, idx, !is_resampling, &original_logits); if (!is_resampling) { - // Only make a copy of the original logits if we are not in the resampling phase, not sure if I actually have to do this. - original_logits = std::vector(logits, logits + llama_n_vocab(llama_get_model(ctx_main))); - } - - // apply params.logit_bias map - for (auto it = params.logit_bias.begin(); it != params.logit_bias.end(); it++) { - logits[it->first] += it->second; - } - - if (ctx_cfg) { - float * logits_guidance = llama_get_logits_ith(ctx_cfg, idx); - llama_sample_apply_guidance(ctx_main, logits, logits_guidance, params.cfg_scale); - } - - cur.clear(); - - for (llama_token token_id = 0; token_id < n_vocab; token_id++) { - cur.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f}); - } - - llama_token_data_array cur_p = { cur.data(), cur.size(), false }; - - // apply penalties - const auto& penalty_tokens = params.use_penalty_prompt_tokens ? params.penalty_prompt_tokens : prev; - const int penalty_tokens_used_size = std::min((int)penalty_tokens.size(), penalty_last_n); - if (penalty_tokens_used_size) { - const float nl_logit = logits[llama_token_nl(llama_get_model(ctx_main))]; - - llama_sample_repetition_penalties(ctx_main, &cur_p, - penalty_tokens.data() + penalty_tokens.size() - penalty_tokens_used_size, - penalty_tokens_used_size, penalty_repeat, penalty_freq, penalty_present); - - if (!penalize_nl) { - for (size_t idx = 0; idx < cur_p.size; idx++) { - if (cur_p.data[idx].id == llama_token_nl(llama_get_model(ctx_main))) { - cur_p.data[idx].logit = nl_logit; - break; - } - } - } - } - - // If we are in the resampling phase, apply grammar checks before sampling logic - if (is_resampling && ctx_sampling->grammar != NULL) { - llama_sample_grammar(ctx_main, &cur_p, ctx_sampling->grammar); + GGML_ASSERT(!original_logits.empty()); } + llama_token id = 0; + // Get a pointer to the logits + float * logits = llama_get_logits_ith(ctx_main, idx); if (temp < 0.0) { // greedy sampling, with probs @@ -302,11 +245,13 @@ static llama_token llama_sampling_sample_impl( return id; } -static llama_token_data_array llama_sample_probability_distribution_impl( +static llama_token_data_array llama_sampling_prepare_impl( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, struct llama_context * ctx_cfg, - const int idx) { + const int idx, + bool apply_grammar, + std::vector * original_logits) { const llama_sampling_params & params = ctx_sampling->params; const int n_vocab = llama_n_vocab(llama_get_model(ctx_main)); @@ -315,6 +260,7 @@ static llama_token_data_array llama_sample_probability_distribution_impl( const float penalty_repeat = params.penalty_repeat; const float penalty_freq = params.penalty_freq; const float penalty_present = params.penalty_present; + const bool penalize_nl = params.penalize_nl; auto & prev = ctx_sampling->prev; @@ -323,8 +269,10 @@ static llama_token_data_array llama_sample_probability_distribution_impl( // Get a pointer to the logits float * logits = llama_get_logits_ith(ctx_main, idx); - // Declare original_logits at the beginning of the function scope - std::vector original_logits; + if (apply_grammar && original_logits != NULL) { + // Only make a copy of the original logits if we are not applying grammar checks, not sure if I actually have to do this. + *original_logits = {logits, logits + llama_n_vocab(llama_get_model(ctx_main))}; + } // apply params.logit_bias map for (auto it = params.logit_bias.begin(); it != params.logit_bias.end(); it++) { @@ -364,12 +312,11 @@ static llama_token_data_array llama_sample_probability_distribution_impl( } } - // apply grammar checks - if (ctx_sampling->grammar != NULL) { + // apply grammar checks before sampling logic + if (apply_grammar && ctx_sampling->grammar != NULL) { llama_sample_grammar(ctx_main, &cur_p, ctx_sampling->grammar); } - llama_sample_softmax(ctx_main, &cur_p); return cur_p; } @@ -382,12 +329,14 @@ llama_token llama_sampling_sample( return llama_sampling_sample_impl(ctx_sampling, ctx_main, ctx_cfg, idx, false); } -llama_token_data_array llama_sampling_probability_distribution( +llama_token_data_array llama_sampling_prepare( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, struct llama_context * ctx_cfg, - const int idx) { - return llama_sample_probability_distribution_impl(ctx_sampling,ctx_main, ctx_cfg, idx); + const int idx, + bool apply_grammar, + std::vector * original_logits) { + return llama_sampling_prepare_impl(ctx_sampling,ctx_main, ctx_cfg, idx, apply_grammar, original_logits); } void llama_sampling_accept( diff --git a/common/sampling.h b/common/sampling.h index a5b8e6079c424..3bc277f60b3e2 100644 --- a/common/sampling.h +++ b/common/sampling.h @@ -33,13 +33,13 @@ typedef struct llama_sampling_params { float dynatemp_range = 0.00f; // 0.0 = disabled float dynatemp_exponent = 1.00f; // controls how entropy maps to temperature in dynamic temperature sampler int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size) - float penalty_repeat = 1.10f; // 1.0 = disabled + float penalty_repeat = 1.00f; // 1.0 = disabled float penalty_freq = 0.00f; // 0.0 = disabled float penalty_present = 0.00f; // 0.0 = disabled int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0 float mirostat_tau = 5.00f; // target entropy float mirostat_eta = 0.10f; // learning rate - bool penalize_nl = true; // consider newlines as a repeatable token + bool penalize_nl = false; // consider newlines as a repeatable token std::vector samplers_sequence = { llama_sampler_type::TOP_K, @@ -130,14 +130,16 @@ llama_token llama_sampling_sample( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, struct llama_context * ctx_cfg, - int idx = 0); + int idx = -1); -// returns the probability that token of given id will be sampled -llama_token_data_array llama_sampling_probability_distribution( +// Prepares and adjusts the set of token candidates for sampling based on penalties, biases, and sampling parameters. +llama_token_data_array llama_sampling_prepare( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, struct llama_context * ctx_cfg, - int idx = 0); + int idx = 0, + bool apply_grammar = true, + std::vector * original_logits = nullptr); void llama_sampling_accept( struct llama_sampling_context * ctx_sampling, diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 5eee320163d29..37af6328a1705 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -23,7 +23,7 @@ sys.path.insert(1, str(Path(__file__).parent / 'gguf-py')) import gguf -from convert import HfVocab +from convert import LlamaHfVocab, permute ###### MODEL DEFINITIONS ###### @@ -93,31 +93,42 @@ def set_gguf_parameters(self): if (n_ctx := self.find_hparam(["max_position_embeddings", "n_ctx"], optional=True)) is not None: self.gguf_writer.add_context_length(n_ctx) + print(f"gguf: context length = {n_ctx}") n_embd = self.find_hparam(["hidden_size", "n_embd"]) self.gguf_writer.add_embedding_length(n_embd) + print(f"gguf: embedding length = {n_embd}") if (n_ff := self.find_hparam(["intermediate_size", "n_inner"], optional=True)) is not None: self.gguf_writer.add_feed_forward_length(n_ff) + print(f"gguf: feed forward length = {n_ff}") n_head = self.find_hparam(["num_attention_heads", "n_head"]) self.gguf_writer.add_head_count(n_head) + print(f"gguf: head count = {n_head}") if (n_head_kv := self.hparams.get("num_key_value_heads")) is not None: self.gguf_writer.add_head_count_kv(n_head_kv) + print(f"gguf: key-value head count = {n_head_kv}") if (rope_theta := self.hparams.get("rope_theta")) is not None: self.gguf_writer.add_rope_freq_base(rope_theta) + print(f"gguf: rope theta = {rope_theta}") if (f_rms_eps := self.hparams.get("rms_norm_eps")) is not None: self.gguf_writer.add_layer_norm_rms_eps(f_rms_eps) + print(f"gguf: rms norm epsilon = {f_rms_eps}") if (f_norm_eps := self.find_hparam(["layer_norm_eps", "layer_norm_epsilon", "norm_epsilon"], optional=True)) is not None: self.gguf_writer.add_layer_norm_eps(f_norm_eps) + print(f"gguf: layer norm epsilon = {f_norm_eps}") if (n_experts := self.hparams.get("num_local_experts")) is not None: self.gguf_writer.add_expert_count(n_experts) + print(f"gguf: expert count = {n_experts}") if (n_experts_used := self.hparams.get("num_experts_per_tok")) is not None: self.gguf_writer.add_expert_used_count(n_experts_used) + print(f"gguf: experts used count = {n_experts_used}") self.gguf_writer.add_file_type(self.ftype) + print(f"gguf: file type = {self.ftype}") def write_tensors(self): block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) @@ -149,7 +160,7 @@ def write_tensors(self): data = data.astype(np.float32) # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 - if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: + if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")): data = data.astype(np.float32) # if f16 desired, convert any float32 2-dim weight tensors to float16 @@ -219,7 +230,7 @@ def _get_part_names(self): def _set_vocab_gpt2(self): dir_model = self.dir_model hparams = self.hparams - tokens: list[bytearray] = [] + tokens: list[str] = [] toktypes: list[int] = [] from transformers import AutoTokenizer @@ -232,8 +243,7 @@ def _set_vocab_gpt2(self): for i in range(vocab_size): if i not in reverse_vocab: - pad_token = f"[PAD{i}]".encode('utf-8') - tokens.append(bytearray(pad_token)) + tokens.append(f"[PAD{i}]") toktypes.append(gguf.TokenType.USER_DEFINED) elif reverse_vocab[i] in added_vocab: tokens.append(reverse_vocab[i]) @@ -255,7 +265,7 @@ def _set_vocab_gpt2(self): def _set_vocab_qwen(self): dir_model = self.dir_model hparams = self.hparams - tokens: list[bytearray] = [] + tokens: list[str] = [] toktypes: list[int] = [] from transformers import AutoTokenizer @@ -280,8 +290,7 @@ def _set_vocab_qwen(self): for i in range(vocab_size): if i not in reverse_vocab: - pad_token = f"[PAD{i}]".encode("utf-8") - tokens.append(bytearray(pad_token)) + tokens.append(f"[PAD{i}]") toktypes.append(gguf.TokenType.USER_DEFINED) elif reverse_vocab[i] in added_vocab: tokens.append(reverse_vocab[i]) @@ -314,13 +323,12 @@ def _set_vocab_sentencepiece(self): toktypes: list[int] = [] if not tokenizer_path.is_file(): - print(f'Error: Missing {tokenizer_path}', file=sys.stderr) - sys.exit(1) + raise FileNotFoundError(f"File not found: {tokenizer_path}") tokenizer = SentencePieceProcessor(str(tokenizer_path)) vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size()) - for token_id in range(vocab_size): + for token_id in range(tokenizer.vocab_size()): piece = tokenizer.id_to_piece(token_id) text = piece.encode("utf-8") score = tokenizer.get_score(token_id) @@ -345,9 +353,13 @@ def _set_vocab_sentencepiece(self): added_tokens_json = json.load(f) for key in added_tokens_json: - tokens.append(key.encode("utf-8")) - scores.append(-1000.0) - toktypes.append(SentencePieceTokenTypes.USER_DEFINED) + key = key.encode("utf-8") + if key not in tokens: + tokens.append(key) + scores.append(-1000.0) + toktypes.append(SentencePieceTokenTypes.USER_DEFINED) + + assert len(tokens) == vocab_size self.gguf_writer.add_tokenizer_model("llama") self.gguf_writer.add_token_list(tokens) @@ -357,12 +369,8 @@ def _set_vocab_sentencepiece(self): special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens)) special_vocab.add_to_gguf(self.gguf_writer) - def _set_vocab_hf(self): - path = self.dir_model - added_tokens_path = self.dir_model - vocab = HfVocab( - path, added_tokens_path if added_tokens_path.exists() else None - ) + def _set_vocab_llama_hf(self): + vocab = LlamaHfVocab(self.dir_model) tokens = [] scores = [] toktypes = [] @@ -502,6 +510,17 @@ def write_tensors(self): class MPTModel(Model): model_arch = gguf.MODEL_ARCH.MPT + def set_vocab(self): + try: + self._set_vocab_gpt2() + except Exception: + # Fallback for SEA-LION model + self._set_vocab_sentencepiece() + self.gguf_writer.add_add_bos_token(False) + self.gguf_writer.add_pad_token_id(3) + self.gguf_writer.add_eos_token_id(1) + self.gguf_writer.add_unk_token_id(0) + def set_gguf_parameters(self): block_count = self.hparams["n_layers"] self.gguf_writer.add_name(self.dir_model.name) @@ -515,7 +534,10 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_eps(1e-5) if self.hparams["attn_config"]["clip_qkv"] is not None: self.gguf_writer.add_clamp_kqv(self.hparams["attn_config"]["clip_qkv"]) - self.gguf_writer.add_max_alibi_bias(self.hparams["attn_config"]["alibi_bias_max"]) + if self.hparams["attn_config"]["alibi"]: + self.gguf_writer.add_max_alibi_bias(self.hparams["attn_config"]["alibi_bias_max"]) + else: + self.gguf_writer.add_max_alibi_bias(0.0) def write_tensors(self): block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers")) @@ -764,6 +786,148 @@ def _reverse_hf_part(self, weights: Tensor, n_part: int) -> Tensor: return weights[r * n_part:r * n_part + r, ...] +@Model.register("XverseForCausalLM") +class XverseModel(Model): + model_arch = gguf.MODEL_ARCH.XVERSE + + def set_vocab(self): + assert (self.dir_model / "tokenizer.json").is_file() + dir_model = self.dir_model + hparams = self.hparams + + tokens: list[bytearray] = [] + toktypes: list[int] = [] + + from transformers import AutoTokenizer + tokenizer = AutoTokenizer.from_pretrained(dir_model) + vocab_size = hparams.get("vocab_size", len(tokenizer.vocab)) + assert max(tokenizer.vocab.values()) < vocab_size + + reverse_vocab = {id_: encoded_tok for encoded_tok, id_ in tokenizer.vocab.items()} + added_vocab = tokenizer.get_added_vocab() + + for token_id in range(vocab_size): + token_text = reverse_vocab[token_id].encode('utf-8') + # replace "\x00" to string with length > 0 + if token_text == b"\x00": + toktype = gguf.TokenType.BYTE # special + token_text = f"<{token_text}>".encode('utf-8') + elif re.fullmatch(br"<0x[0-9A-Fa-f]{2}>", token_text): + toktype = gguf.TokenType.BYTE # special + elif reverse_vocab[token_id] in added_vocab: + if tokenizer.added_tokens_decoder[token_id].special: + toktype = gguf.TokenType.CONTROL + else: + toktype = gguf.TokenType.USER_DEFINED + else: + toktype = gguf.TokenType.NORMAL + + tokens.append(token_text) + toktypes.append(toktype) + + self.gguf_writer.add_tokenizer_model("llama") + self.gguf_writer.add_token_list(tokens) + self.gguf_writer.add_token_types(toktypes) + + special_vocab = gguf.SpecialVocab(dir_model, n_vocab=len(tokens)) + special_vocab.add_to_gguf(self.gguf_writer) + + def set_gguf_parameters(self): + block_count = self.hparams["num_hidden_layers"] + head_count = self.hparams["num_attention_heads"] + head_count_kv = self.hparams.get("num_key_value_heads", head_count) + hf_repo = self.hparams.get("_name_or_path", "") + + ctx_length = 0 + if "max_sequence_length" in self.hparams: + ctx_length = self.hparams["max_sequence_length"] + elif "max_position_embeddings" in self.hparams: + ctx_length = self.hparams["max_position_embeddings"] + elif "model_max_length" in self.hparams: + ctx_length = self.hparams["model_max_length"] + else: + print("gguf: can not find ctx length parameter.") + sys.exit() + + self.gguf_writer.add_name(self.dir_model.name) + self.gguf_writer.add_source_hf_repo(hf_repo) + self.gguf_writer.add_tensor_data_layout("Meta AI original pth") + self.gguf_writer.add_context_length(ctx_length) + self.gguf_writer.add_embedding_length(self.hparams["hidden_size"]) + self.gguf_writer.add_block_count(block_count) + self.gguf_writer.add_feed_forward_length(self.hparams["intermediate_size"]) + self.gguf_writer.add_rope_dimension_count(self.hparams["hidden_size"] // self.hparams["num_attention_heads"]) + self.gguf_writer.add_head_count(head_count) + self.gguf_writer.add_head_count_kv(head_count_kv) + self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"]) + + if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]: + if self.hparams["rope_scaling"].get("type") == "linear": + self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR) + self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"]) + + def write_tensors(self): + # Collect tensors from generator object + model_kv = dict(self.get_tensors()) + block_count = self.hparams["num_hidden_layers"] + head_count = self.hparams["num_attention_heads"] + tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) + head_count_kv = self.hparams.get("num_key_value_heads", head_count) + + for name, data_torch in model_kv.items(): + # we don't need these + if name.endswith(".rotary_emb.inv_freq"): + continue + + old_dtype = data_torch.dtype + + # convert any unsupported data types to float32 + if data_torch.dtype not in (torch.float16, torch.float32): + data_torch = data_torch.to(torch.float32) + + # HF models permute some of the tensors, so we need to undo that + if name.endswith(("q_proj.weight")): + data_torch = self._reverse_hf_permute(data_torch, head_count, head_count) + if name.endswith(("k_proj.weight")): + data_torch = self._reverse_hf_permute(data_torch, head_count, head_count_kv) + + data = data_torch.squeeze().numpy() + + # map tensor names + new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) + if new_name is None: + print(f"Can not map tensor {name!r}") + sys.exit() + + n_dims = len(data.shape) + data_dtype = data.dtype + + # if f32 desired, convert any float16 to float32 + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) + + # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 + if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: + data = data.astype(np.float32) + + # if f16 desired, convert any float32 2-dim weight tensors to float16 + if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: + data = data.astype(np.float16) + + print(f"{name} -> {new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + self.gguf_writer.add_tensor(new_name, data) + + def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor: + if n_kv_head is not None and n_head != n_kv_head: + n_head //= n_kv_head + + return ( + weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:]) + .swapaxes(1, 2) + .reshape(weights.shape) + ) + + @Model.register("FalconForCausalLM", "RWForCausalLM") class FalconModel(Model): model_arch = gguf.MODEL_ARCH.FALCON @@ -1043,13 +1207,222 @@ def set_gguf_parameters(self): self.gguf_writer.add_layer_norm_eps(self.find_hparam(["layer_norm_eps", "norm_eps"])) -@Model.register("MixtralForCausalLM") -class MixtralModel(Model): +@Model.register("LlamaForCausalLM", "MistralForCausalLM", "MixtralForCausalLM") +class LlamaModel(Model): model_arch = gguf.MODEL_ARCH.LLAMA + def set_vocab(self): + try: + self. _set_vocab_sentencepiece() + except FileNotFoundError: + self._set_vocab_llama_hf() + + def set_gguf_parameters(self): + super().set_gguf_parameters() + hparams = self.hparams + self.gguf_writer.add_vocab_size(hparams["vocab_size"]) + self.gguf_writer.add_rope_dimension_count(hparams["hidden_size"] // hparams["num_attention_heads"]) + + # Same as super class, but permuting q_proj, k_proj + def write_tensors(self): + block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) + tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) + n_head = self.hparams.get("num_attention_heads") + n_kv_head = self.hparams.get("num_key_value_heads") + n_experts = self.hparams.get("num_local_experts") + experts = dict() + for name, data_torch in self.get_tensors(): + # we don't need these + if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): + continue + + old_dtype = data_torch.dtype + + # convert any unsupported data types to float32 + if data_torch.dtype not in (torch.float16, torch.float32): + data_torch = data_torch.to(torch.float32) + + data = data_torch.numpy() + + if name.endswith("q_proj.weight"): + data = permute(data, n_head, n_head) + if name.endswith("k_proj.weight"): + data = permute(data, n_head, n_kv_head) + + data = data.squeeze() + + # process the experts separately + if name.find("block_sparse_moe.experts") != -1: + experts[name] = data + if len(experts) >= n_experts: + # merge the experts into a single 3d tensor + for bid in range(block_count): + for wid in range(1, 4): + full = True + for xid in range(n_experts): + ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.w{wid}.weight" + if ename not in experts: + full = False + break + if not full: + continue + + datas = [] + for xid in range(n_experts): + ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.w{wid}.weight" + datas.append(experts[ename]) + del experts[ename] + + data = np.stack(datas, axis=0) + data_dtype = data.dtype + + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) + + if self.ftype == 1 and data_dtype == np.float32: + data = data.astype(np.float16) + + merged_name = f"layers.{bid}.feed_forward.experts.w{wid}.weight" + + new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) + if new_name is None: + print(f"Can not map tensor {name!r}") + sys.exit() + + print(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") + + self.gguf_writer.add_tensor(new_name, data) + continue + + # map tensor names + new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) + if new_name is None: + print(f"Can not map tensor {name!r}") + sys.exit() + + n_dims = len(data.shape) + data_dtype = data.dtype + + # if f32 desired, convert any float16 to float32 + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) + + # 1d tensors need to be converted to float32 + if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: + data = data.astype(np.float32) + + # if f16 desired, convert any float32 2-dim weight tensors to float16 + if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: + data = data.astype(np.float16) + + print(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + + self.gguf_writer.add_tensor(new_name, data) + + if len(experts) > 0: + raise ValueError(f"Unprocessed experts: {experts.keys()}") + + +@Model.register("GrokForCausalLM") +class GrokModel(Model): + model_arch = gguf.MODEL_ARCH.GROK + def set_vocab(self): self._set_vocab_sentencepiece() + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + def set_gguf_parameters(self): + super().set_gguf_parameters() + self.gguf_writer.add_name("Grok") + + def write_tensors(self): + block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer"))) + tensor_map = gguf.get_tensor_name_map(self.model_arch, block_count) + n_experts = self.hparams.get("num_local_experts") + experts = dict() + for name, data_torch in self.get_tensors(): + # we don't need these + if name.endswith((".attention.masked_bias", ".attention.bias", ".attention.rotary_emb.inv_freq")): + continue + + old_dtype = data_torch.dtype + + # convert any unsupported data types to float32 + if data_torch.dtype not in (torch.float16, torch.float32): + data_torch = data_torch.to(torch.float32) + + data = data_torch.squeeze().numpy() + + # process the experts separately + if name.find(".moe.") != -1: + experts[name] = data + if len(experts) >= n_experts: + # merge the experts into a single 3d tensor + for bid in range(block_count): + for wid in ["linear", "linear_1", "linear_v"]: + full = True + for xid in range(n_experts): + ename = f"transformer.decoder_layer.{bid}.moe.{xid}.{wid}.weight" + if ename not in experts: + full = False + break + if not full: + continue + + datas = [] + for xid in range(n_experts): + ename = f"transformer.decoder_layer.{bid}.moe.{xid}.{wid}.weight" + datas.append(experts[ename]) + del experts[ename] + + data = np.stack(datas, axis=0) + data_dtype = data.dtype + + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) + + if self.ftype == 1 and data_dtype == np.float32: + data = data.astype(np.float16) + + merged_name = f"transformer.decoder_layer.{bid}.moe.{wid}.weight" + + new_name = tensor_map.get_name(merged_name, try_suffixes=(".weight", ".bias")) + if new_name is None: + print(f"Can not map tensor {name!r}") + sys.exit() + + print(f"{new_name}, n_dims = {len(data.shape)}, shape = {data.shape} --> {data.dtype}") + + self.gguf_writer.add_tensor(new_name, data) + continue + + # map tensor names + new_name = tensor_map.get_name(name, try_suffixes=(".weight", ".bias")) + if new_name is None: + print(f"Can not map tensor {name!r}") + sys.exit() + + n_dims = len(data.shape) + data_dtype = data.dtype + + # if f32 desired, convert any float16 to float32 + if self.ftype == 0 and data_dtype == np.float16: + data = data.astype(np.float32) + + # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32 + if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1: + data = data.astype(np.float32) + + # if f16 desired, convert any float32 2-dim weight tensors to float16 + if self.ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2: + data = data.astype(np.float16) + + print(f"{new_name}, n_dims = {n_dims}, {old_dtype} --> {data.dtype}") + + self.gguf_writer.add_tensor(new_name, data) + @Model.register("MiniCPMForCausalLM") class MiniCPMModel(Model): @@ -1069,7 +1442,7 @@ def set_gguf_parameters(self): self.gguf_writer.add_file_type(self.ftype) def set_vocab(self): - self._set_vocab_hf() + self._set_vocab_llama_hf() def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor: if n_kv_head is not None and n_head != n_kv_head: @@ -1634,7 +2007,7 @@ def write_tensors(self): self.post_write_tensors(tensor_map, name, data_torch) -@Model.register("BertModel") +@Model.register("BertModel", "CamembertModel") class BertModel(Model): model_arch = gguf.MODEL_ARCH.BERT @@ -1670,11 +2043,8 @@ def set_gguf_parameters(self): self.gguf_writer.add_pooling_type(pooling_type) def set_vocab(self): - path = self.dir_model - added_tokens_path = self.dir_model if self.dir_model.exists() else None - # use huggingface vocab to get all tokens - vocab = HfVocab(path, added_tokens_path) + vocab = LlamaHfVocab(self.dir_model, ignore_nonllama=True) tokens, scores, toktypes = zip(*vocab.all_tokens()) assert len(tokens) == vocab.vocab_size self.vocab_size = vocab.vocab_size @@ -1965,6 +2335,23 @@ def write_tensors(self): self.gguf_writer.add_tensor(new_name, data) +@Model.register("CohereForCausalLM") +class CommandR2Model(Model): + model_arch = gguf.MODEL_ARCH.COMMAND_R + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + # max_position_embeddings = 8192 in config.json but model was actually + # trained on 128k context length + self.hparams["max_position_embeddings"] = self.hparams["model_max_length"] + + def set_gguf_parameters(self): + super().set_gguf_parameters() + self.gguf_writer.add_logit_scale(self.hparams["logit_scale"]) + self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.NONE) + + ###### CONVERSION LOGIC ###### diff --git a/convert-persimmon-to-gguf.py b/convert-persimmon-to-gguf.py index def210531e27b..ccb99279e20a8 100755 --- a/convert-persimmon-to-gguf.py +++ b/convert-persimmon-to-gguf.py @@ -106,12 +106,12 @@ def main(): tensor_map = gguf.get_tensor_name_map(arch, block_count) print(tensor_map) for name in tensors.keys(): - data = tensors[name] + data_torch = tensors[name] if name.endswith(".self_attention.rotary_emb.inv_freq"): continue - old_dtype = data.dtype + old_dtype = data_torch.dtype # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?) - data = data.to(torch.float32).squeeze().numpy() + data = data_torch.to(torch.float32).squeeze().numpy() new_name = tensor_map.get_name(name, try_suffixes = (".weight", ".bias")) if new_name is None: print("Can not map tensor '" + name + "'") diff --git a/convert.py b/convert.py index c15f8c47ea4f7..a37aeb5e5a652 100755 --- a/convert.py +++ b/convert.py @@ -16,13 +16,14 @@ import signal import struct import sys +import textwrap import time import zipfile -from abc import ABCMeta, abstractmethod +from abc import ABC, abstractmethod from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor from dataclasses import dataclass from pathlib import Path -from typing import IO, TYPE_CHECKING, Any, Callable, Iterable, Literal, TypeVar +from typing import TYPE_CHECKING, Any, Callable, ClassVar, IO, Iterable, Literal, Protocol, TypeVar, runtime_checkable import numpy as np from sentencepiece import SentencePieceProcessor @@ -43,6 +44,9 @@ DEFAULT_CONCURRENCY = 8 +ADDED_TOKENS_FILE = 'added_tokens.json' +FAST_TOKENIZER_FILE = 'tokenizer.json' + # # data types # @@ -135,7 +139,8 @@ def type_for_tensor(self, name: str, tensor: LazyTensor) -> DataType: dt = GGML_FILE_TYPE_TO_DATA_TYPE.get(self) if dt is None: raise ValueError(self) - # 1D tensors are always F32. + # Convert all 1D tensors to F32. Most of the codebase that takes in 1D tensors only handles F32 tensors, and most of the outputs tensors are F32. + # Also The 1d tensors aren't much of a performance/size issue. So instead of having to have separate F32 and F16 implementations of both, just convert everything to F32 for now. return dt if len(tensor.shape) > 1 else DT_F32 @@ -188,8 +193,10 @@ def guessed(model: LazyModel) -> Params: n_layer = next(i for i in itertools.count() if f"layers.{i}.attention.wq.weight" not in model) if n_layer < 1: - raise Exception("failed to guess 'n_layer'. This model is unknown or unsupported.\n" - "Suggestion: provide 'config.json' of the model in the same directory containing model files.") + msg = """\ + failed to guess 'n_layer'. This model is unknown or unsupported. + Suggestion: provide 'config.json' of the model in the same directory containing model files.""" + raise KeyError(textwrap.dedent(msg)) n_head = n_embd // 128 # guessed n_mult = 256 # guessed @@ -211,7 +218,8 @@ def guessed(model: LazyModel) -> Params: @staticmethod def loadHFTransformerJson(model: LazyModel, config_path: Path) -> Params: - config = json.load(open(config_path)) + with open(config_path) as f: + config = json.load(f) rope_scaling_type = f_rope_scale = n_orig_ctx = rope_finetuned = None rope_scaling = config.get("rope_scaling") @@ -233,8 +241,10 @@ def loadHFTransformerJson(model: LazyModel, config_path: Path) -> Params: elif "max_position_embeddings" in config: n_ctx = config["max_position_embeddings"] else: - raise Exception("failed to guess 'n_ctx'. This model is unknown or unsupported.\n" - "Suggestion: provide 'config.json' of the model in the same directory containing model files.") + msg = """\ + failed to guess 'n_ctx'. This model is unknown or unsupported. + Suggestion: provide 'config.json' of the model in the same directory containing model files.""" + raise KeyError(textwrap.dedent(msg)) n_experts = None n_experts_used = None @@ -265,7 +275,8 @@ def loadHFTransformerJson(model: LazyModel, config_path: Path) -> Params: # {"dim": 8192, "multiple_of": 4096, "ffn_dim_multiplier": 1.3, "n_heads": 64, "n_kv_heads": 8, "n_layers": 80, "norm_eps": 1e-05, "vocab_size": -1} @staticmethod def loadOriginalParamsJson(model: LazyModel, config_path: Path) -> Params: - config = json.load(open(config_path)) + with open(config_path) as f: + config = json.load(f) n_experts = None n_experts_used = None @@ -331,44 +342,86 @@ def load(model_plus: ModelPlus) -> Params: # vocab # -class BpeVocab: - def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None) -> None: - self.bpe_tokenizer = json.loads(open(str(fname_tokenizer), encoding="utf-8").read()) - if isinstance(self.bpe_tokenizer.get('model'), dict): - self.vocab = self.bpe_tokenizer["model"]["vocab"] - else: - self.vocab = self.bpe_tokenizer - added_tokens: dict[str, int] - if fname_added_tokens is not None: - # FIXME: Verify that added tokens here _cannot_ overlap with the main vocab. - added_tokens = json.load(open(fname_added_tokens, encoding="utf-8")) +@runtime_checkable +class BaseVocab(Protocol): + tokenizer_model: ClassVar[str] + name: ClassVar[str] + + +class NoVocab(BaseVocab): + tokenizer_model = "no_vocab" + name = "no_vocab" + + def __repr__(self) -> str: + return "" + + +@runtime_checkable +class Vocab(BaseVocab, Protocol): + vocab_size: int + added_tokens_dict: dict[str, int] + added_tokens_list: list[str] + fname_tokenizer: Path + + def __init__(self, base_path: Path): ... + def all_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: ... + + +class BpeVocab(Vocab): + tokenizer_model = "gpt2" + name = "bpe" + + def __init__(self, base_path: Path): + added_tokens: dict[str, int] = {} + + if (fname_tokenizer := base_path / 'vocab.json').exists(): + # "slow" tokenizer + with open(fname_tokenizer, encoding="utf-8") as f: + self.vocab = json.load(f) + + try: + # FIXME: Verify that added tokens here _cannot_ overlap with the main vocab. + with open(base_path / ADDED_TOKENS_FILE, encoding="utf-8") as f: + added_tokens = json.load(f) + except FileNotFoundError: + pass else: - # Fall back to trying to find the added tokens in tokenizer.json - tokenizer_json_file = fname_tokenizer.parent / 'tokenizer.json' - if not tokenizer_json_file.is_file(): - added_tokens = {} - else: - tokenizer_json = json.load(open(tokenizer_json_file, encoding="utf-8")) - added_tokens = dict( - (item['content'], item['id']) - for item in tokenizer_json.get('added_tokens', []) - # Added tokens here can be duplicates of the main vocabulary. - if item['content'] not in self.bpe_tokenizer) - - vocab_size: int = len(self.vocab) - expected_ids = list(range(vocab_size, vocab_size + len(added_tokens))) - actual_ids = sorted(added_tokens.values()) + # "fast" tokenizer + fname_tokenizer = base_path / FAST_TOKENIZER_FILE + + # if this fails, FileNotFoundError propagates to caller + with open(fname_tokenizer, encoding="utf-8") as f: + tokenizer_json = json.load(f) + + tokenizer_model: dict[str, Any] = tokenizer_json['model'] + if ( + tokenizer_model['type'] != 'BPE' or tokenizer_model.get('byte_fallback', False) + or tokenizer_json['decoder']['type'] != 'ByteLevel' + ): + raise FileNotFoundError('Cannot find GPT-2 BPE tokenizer') + + self.vocab = tokenizer_model["vocab"] + + if (added := tokenizer_json.get('added_tokens')) is not None: + # Added tokens here can be duplicates of the main vocabulary. + added_tokens = {item['content']: item['id'] + for item in added + if item['content'] not in self.vocab} + + vocab_size = len(self.vocab) + expected_ids = list(range(vocab_size, vocab_size + len(added_tokens))) + actual_ids = sorted(added_tokens.values()) if expected_ids != actual_ids: expected_end_id = vocab_size + len(actual_ids) - 1 - raise Exception(f"Expected the {len(actual_ids)} added token ID(s) to be sequential in the range {vocab_size} - {expected_end_id}; got {actual_ids}") + raise ValueError(f"Expected the {len(actual_ids)} added token ID(s) to be sequential in the range " + f"{vocab_size} - {expected_end_id}; got {actual_ids}") items = sorted(added_tokens.items(), key=lambda text_idx: text_idx[1]) self.added_tokens_dict = added_tokens self.added_tokens_list = [text for (text, idx) in items] - self.vocab_size_base: int = vocab_size - self.vocab_size: int = self.vocab_size_base + len(self.added_tokens_list) + self.vocab_size_base = vocab_size + self.vocab_size = self.vocab_size_base + len(self.added_tokens_list) self.fname_tokenizer = fname_tokenizer - self.fname_added_tokens = fname_added_tokens def bpe_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: reverse_vocab = {id: encoded_tok for encoded_tok, id in self.vocab.items()} @@ -389,16 +442,25 @@ def __repr__(self) -> str: return f"" -class SentencePieceVocab: - def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None) -> None: - self.sentencepiece_tokenizer = SentencePieceProcessor(str(fname_tokenizer)) - added_tokens: dict[str, int] - if fname_added_tokens is not None: - added_tokens = json.load(open(fname_added_tokens, encoding="utf-8")) - else: - added_tokens = {} +class SentencePieceVocab(Vocab): + tokenizer_model = "llama" + name = "spm" - vocab_size: int = self.sentencepiece_tokenizer.vocab_size() + def __init__(self, base_path: Path): + added_tokens: dict[str, int] = {} + if (fname_tokenizer := base_path / 'tokenizer.model').exists(): + # normal location + try: + with open(base_path / ADDED_TOKENS_FILE, encoding="utf-8") as f: + added_tokens = json.load(f) + except FileNotFoundError: + pass + elif not (fname_tokenizer := base_path.parent / 'tokenizer.model').exists(): + # not found in alternate location either + raise FileNotFoundError('Cannot find tokenizer.model') + + self.sentencepiece_tokenizer = SentencePieceProcessor(str(fname_tokenizer)) + vocab_size = self.sentencepiece_tokenizer.vocab_size() new_tokens = {id: piece for piece, id in added_tokens.items() if id >= vocab_size} expected_new_ids = list(range(vocab_size, vocab_size + len(new_tokens))) @@ -408,18 +470,17 @@ def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None) -> No raise ValueError(f"Expected new token IDs {expected_new_ids} to be sequential; got {actual_new_ids}") # Token pieces that were added to the base vocabulary. - self.added_tokens_dict = added_tokens + self.added_tokens_dict = added_tokens self.added_tokens_list = [new_tokens[id] for id in actual_new_ids] self.vocab_size_base = vocab_size self.vocab_size = self.vocab_size_base + len(self.added_tokens_list) self.fname_tokenizer = fname_tokenizer - self.fname_added_tokens = fname_added_tokens def sentencepiece_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: tokenizer = self.sentencepiece_tokenizer for i in range(tokenizer.vocab_size()): piece = tokenizer.id_to_piece(i) - text: bytes = piece.encode("utf-8") + text = piece.encode("utf-8") score: float = tokenizer.get_score(i) toktype = gguf.TokenType.NORMAL @@ -452,24 +513,42 @@ def __repr__(self) -> str: return f"" -class HfVocab: - def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None = None) -> None: +class LlamaHfVocab(Vocab): + tokenizer_model = "llama" + name = "hfft" + + def __init__(self, base_path: Path, ignore_nonllama: bool = False): + fname_tokenizer = base_path / FAST_TOKENIZER_FILE + # if this fails, FileNotFoundError propagates to caller + with open(fname_tokenizer, encoding='utf-8') as f: + tokenizer_json = json.load(f) + + # pre-check so we know if we need transformers + tokenizer_model: dict[str, Any] = tokenizer_json['model'] + if ignore_nonllama: + pass # workaround incorrect use of this class for WordPiece + elif ( + tokenizer_model['type'] != 'BPE' or not tokenizer_model.get('byte_fallback', False) + or tokenizer_json['decoder']['type'] != 'Sequence' + ): + raise FileNotFoundError('Cannot find Llama BPE tokenizer') + try: from transformers import AutoTokenizer except ImportError as e: raise ImportError( - "To use HfVocab, please install the `transformers` package. " + "To use LlamaHfVocab, please install the `transformers` package. " "You can install it with `pip install transformers`." ) from e - print("fname_tokenizer:", fname_tokenizer) # Allow the tokenizer to default to slow or fast versions. # Explicitly set tokenizer to use local paths. self.tokenizer = AutoTokenizer.from_pretrained( - fname_tokenizer, - cache_dir=fname_tokenizer, + base_path, + cache_dir=base_path, local_files_only=True, ) + assert self.tokenizer.is_fast # assume tokenizer.json is used # Initialize lists and dictionaries for added tokens self.added_tokens_list = [] @@ -497,8 +576,7 @@ def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None = None self.vocab_size_base = self.tokenizer.vocab_size self.vocab_size = self.vocab_size_base + len(self.added_tokens_list) - self.fname_tokenizer = fname_tokenizer - self.fname_added_tokens = fname_added_tokens + self.fname_tokenizer = fname_tokenizer def hf_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: reverse_vocab = { @@ -550,10 +628,7 @@ def all_tokens(self) -> Iterable[tuple[bytes, float, gguf.TokenType]]: yield from self.added_tokens() def __repr__(self) -> str: - return f"" - - -Vocab: TypeAlias = "BpeVocab | SentencePieceVocab | HfVocab" + return f"" # @@ -571,7 +646,7 @@ def permute(weights: NDArray, n_head: int, n_head_kv: int) -> NDArray: .reshape(weights.shape)) -class Tensor(metaclass=ABCMeta): +class Tensor(ABC): data_type: DataType @abstractmethod @@ -593,7 +668,7 @@ def bf16_to_fp32(bf16_arr: np.ndarray[Any, np.dtype[np.uint16]]) -> NDArray: class UnquantizedTensor(Tensor): - def __init__(self, ndarray: NDArray) -> None: + def __init__(self, ndarray: NDArray): assert isinstance(ndarray, np.ndarray) self.ndarray = ndarray self.data_type = NUMPY_TYPE_TO_DATA_TYPE[ndarray.dtype] @@ -672,7 +747,7 @@ class ModelPlus: model: LazyModel paths: list[Path] # Where this was read from. format: Literal['ggml', 'torch', 'safetensors', 'none'] - vocab: Vocab | None # For GGML models (which have vocab built in), the vocab. + vocab: BaseVocab | None # For GGML models (which have vocab built in), the vocab. def merge_sharded(models: list[LazyModel]) -> LazyModel: @@ -681,7 +756,7 @@ def merge_sharded(models: list[LazyModel]) -> LazyModel: names = {name: None for model in models for name in model} def convert(name: str) -> LazyTensor: - lazy_tensors: list[LazyTensor] = [model[name] for model in models] + lazy_tensors = [model[name] for model in models] if len(lazy_tensors) == 1: # only one file; don't go through this procedure since there might # be quantized tensors @@ -702,7 +777,7 @@ def convert(name: str) -> LazyTensor: def load() -> UnquantizedTensor: ndarrays = [load_unquantized(tensor) for tensor in lazy_tensors] - concatenated: NDArray = np.concatenate(ndarrays, axis=axis) + concatenated = np.concatenate(ndarrays, axis=axis) return UnquantizedTensor(concatenated) description = 'concatenated[[' + '] | ['.join(lt.description for lt in lazy_tensors) + ']]' return LazyTensor(load, concatenated_shape, lazy_tensors[0].data_type, description) @@ -754,6 +829,15 @@ def load() -> Tensor: return LazyTensor(load, s, lazy_tensor.data_type, 'part ' + lazy_tensor.description) +def pack_experts_lazy(lazy_tensors: list[LazyTensor]) -> LazyTensor: + def load() -> Tensor: + tensors = [lazy_tensor.load() for lazy_tensor in lazy_tensors] + return UnquantizedTensor(np.array([tensor.ndarray for tensor in tensors])) + s = lazy_tensors[0].shape.copy() + s.insert(0, len(lazy_tensors)) + return LazyTensor(load, s, lazy_tensors[0].data_type, 'pack_experts ' + ' | '.join(lt.description for lt in lazy_tensors)) + + # Functionality that simulates `torch.load` but where individual tensors are # only loaded into memory on demand, not all at once. # PyTorch can't do this natively as of time of writing: @@ -790,10 +874,10 @@ def persistent_load(self, pid: Any) -> Any: def load(offset: int, elm_count: int) -> NDArray: dtype = data_type.dtype - fp = self.zip_file.open(info) - fp.seek(offset * dtype.itemsize) - size = elm_count * dtype.itemsize - data = fp.read(size) + with self.zip_file.open(info) as fp: + fp.seek(offset * dtype.itemsize) + size = elm_count * dtype.itemsize + data = fp.read(size) assert len(data) == size return np.frombuffer(data, dtype) description = f'storage data_type={data_type} path-in-zip={filename} path={self.zip_file.filename}' @@ -814,7 +898,7 @@ def load() -> UnquantizedTensor: def rebuild_from_type_v2(func, new_type, args, state): return func(*args) - CLASSES: dict[tuple[str, str], Any] = { + CLASSES = { # getattr used here as a workaround for mypy not being smart enough to determine # the staticmethods have a __func__ attribute. ('torch._tensor', '_rebuild_from_type_v2'): getattr(rebuild_from_type_v2, '__func__'), @@ -873,7 +957,7 @@ def load() -> UnquantizedTensor: def must_read(fp: IO[bytes], length: int) -> bytes: ret = fp.read(length) if len(ret) < length: - raise Exception("unexpectedly reached end of file") + raise EOFError("unexpectedly reached end of file") return ret @@ -931,12 +1015,15 @@ def bounded_parallel_map(func: Callable[[In], Out], iterable: Iterable[In], conc yield result -def check_vocab_size(params: Params, vocab: Vocab, pad_vocab: bool = False) -> None: +def check_vocab_size(params: Params, vocab: BaseVocab, pad_vocab: bool = False) -> None: # Handle special case where the model's vocab size is not set if params.n_vocab == -1: raise ValueError( - f"The model's vocab size is set to -1 in params.json. Please update it manually. Maybe {vocab.vocab_size}?" + "The model's vocab size is set to -1 in params.json. Please update it manually." + + (f" Maybe {vocab.vocab_size}?" if isinstance(vocab, Vocab) else ""), ) + if not isinstance(vocab, Vocab): + return # model has no vocab # Check for a vocab size mismatch if params.n_vocab == vocab.vocab_size: @@ -960,11 +1047,11 @@ def check_vocab_size(params: Params, vocab: Vocab, pad_vocab: bool = False) -> N if vocab.vocab_size < params.n_vocab: msg += " Add the --pad-vocab option and try again." - raise Exception(msg) + raise ValueError(msg) class OutputFile: - def __init__(self, fname_out: Path, endianess:gguf.GGUFEndian = gguf.GGUFEndian.LITTLE) -> None: + def __init__(self, fname_out: Path, endianess:gguf.GGUFEndian = gguf.GGUFEndian.LITTLE): self.gguf = gguf.GGUFWriter(fname_out, gguf.MODEL_ARCH_NAMES[ARCH], endianess=endianess) def add_meta_arch(self, params: Params) -> None: @@ -977,6 +1064,7 @@ def add_meta_arch(self, params: Params) -> None: name = str(params.path_model.parent).split('/')[-1] self.gguf.add_name (name) + self.gguf.add_vocab_size (params.n_vocab) self.gguf.add_context_length (params.n_ctx) self.gguf.add_embedding_length (params.n_embd) self.gguf.add_block_count (params.n_layer) @@ -1013,20 +1101,6 @@ def add_meta_arch(self, params: Params) -> None: if params.ftype is not None: self.gguf.add_file_type(params.ftype) - def handle_tokenizer_model(self, vocab: Vocab) -> str: - # Map the vocab types to the supported tokenizer models - tokenizer_model = { - SentencePieceVocab: "llama", - HfVocab: "llama", - BpeVocab: "gpt2", - }.get(type(vocab)) - - # Block if vocab type is not predefined - if tokenizer_model is None: - raise ValueError("Unknown vocab type: Not supported") - - return tokenizer_model - def extract_vocabulary_from_model(self, vocab: Vocab) -> tuple[list[bytes], list[float], list[gguf.TokenType]]: tokens = [] scores = [] @@ -1043,11 +1117,8 @@ def extract_vocabulary_from_model(self, vocab: Vocab) -> tuple[list[bytes], list return tokens, scores, toktypes def add_meta_vocab(self, vocab: Vocab) -> None: - # Handle the tokenizer model - tokenizer_model = self.handle_tokenizer_model(vocab) - # Ensure that tokenizer_model is added to the GGUF model - self.gguf.add_tokenizer_model(tokenizer_model) + self.gguf.add_tokenizer_model(vocab.tokenizer_model) # Extract model vocabulary for model conversion tokens, scores, toktypes = self.extract_vocabulary_from_model(vocab) @@ -1074,6 +1145,26 @@ def write_meta(self) -> None: def write_tensor_info(self) -> None: self.gguf.write_ti_data_to_file() + def write_tensor_data(self, ftype: GGMLFileType, model: LazyModel, concurrency: int) -> None: + ndarrays_inner = bounded_parallel_map(OutputFile.do_item, model.items(), concurrency=concurrency) + if ftype == GGMLFileType.MostlyQ8_0: + ndarrays = bounded_parallel_map( + OutputFile.maybe_do_quantize, ndarrays_inner, concurrency=concurrency, max_workers=concurrency, + use_processpool_executor=True, + ) + else: + ndarrays = map(OutputFile.maybe_do_quantize, ndarrays_inner) + + start = time.time() + for i, ((name, lazy_tensor), ndarray) in enumerate(zip(model.items(), ndarrays)): + elapsed = time.time() - start + size = ' x '.join(f"{dim:6d}" for dim in lazy_tensor.shape) + padi = len(str(len(model))) + print( + f"[{i + 1:{padi}d}/{len(model)}] Writing tensor {name:38s} | size {size:16} | type {lazy_tensor.data_type.name:4} | T+{int(elapsed):4}" + ) + self.gguf.write_tensor_data(ndarray) + def close(self) -> None: self.gguf.close() @@ -1082,7 +1173,7 @@ def write_vocab_only( fname_out: Path, params: Params, vocab: Vocab, svocab: gguf.SpecialVocab, endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, ) -> None: - check_vocab_size(params, vocab, pad_vocab = pad_vocab) + check_vocab_size(params, vocab, pad_vocab=pad_vocab) of = OutputFile(fname_out, endianess=endianess) @@ -1110,7 +1201,7 @@ def maybe_do_quantize(item: tuple[DataType, NDArray]) -> NDArray: @staticmethod def write_all( - fname_out: Path, ftype: GGMLFileType, params: Params, model: LazyModel, vocab: Vocab, svocab: gguf.SpecialVocab, + fname_out: Path, ftype: GGMLFileType, params: Params, model: LazyModel, vocab: BaseVocab, svocab: gguf.SpecialVocab, concurrency: int = DEFAULT_CONCURRENCY, endianess: gguf.GGUFEndian = gguf.GGUFEndian.LITTLE, pad_vocab: bool = False, ) -> None: @@ -1120,8 +1211,11 @@ def write_all( # meta data of.add_meta_arch(params) - of.add_meta_vocab(vocab) - of.add_meta_special_vocab(svocab) + if isinstance(vocab, Vocab): + of.add_meta_vocab(vocab) + of.add_meta_special_vocab(svocab) + else: # NoVocab + of.gguf.add_tokenizer_model(vocab.tokenizer_model) # tensor info for name, lazy_tensor in model.items(): @@ -1131,24 +1225,7 @@ def write_all( of.write_tensor_info() # tensor data - ndarrays_inner = bounded_parallel_map(OutputFile.do_item, model.items(), concurrency = concurrency) - if ftype == GGMLFileType.MostlyQ8_0: - ndarrays = bounded_parallel_map( - OutputFile.maybe_do_quantize, ndarrays_inner, concurrency=concurrency, max_workers=concurrency, - use_processpool_executor=True, - ) - else: - ndarrays = map(OutputFile.maybe_do_quantize, ndarrays_inner) - - start = time.time() - for i, ((name, lazy_tensor), ndarray) in enumerate(zip(model.items(), ndarrays)): - elapsed = time.time() - start - size = ' x '.join(f"{dim:6d}" for dim in lazy_tensor.shape) - padi = len(str(len(model))) - print( - f"[{i+1:{padi}d}/{len(model)}] Writing tensor {name:38s} | size {size:16} | type {lazy_tensor.data_type.name:4} | T+{int(elapsed):4}" - ) - of.gguf.write_tensor_data(ndarray) + of.write_tensor_data(ftype, model, concurrency) of.close() @@ -1156,16 +1233,16 @@ def write_all( def pick_output_type(model: LazyModel, output_type_str: str | None) -> GGMLFileType: wq_type = model[gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.ATTN_Q].format(bid=0) + ".weight"].data_type - if output_type_str == "f32" or (output_type_str is None and wq_type == DT_F32): + if output_type_str == "f32" or (output_type_str is None and wq_type in (DT_F32, DT_BF16)): return GGMLFileType.AllF32 - if output_type_str == "f16" or (output_type_str is None and wq_type in (DT_F16, DT_BF16)): + if output_type_str == "f16" or (output_type_str is None and wq_type == DT_F16): return GGMLFileType.MostlyF16 if output_type_str == "q8_0": return GGMLFileType.MostlyQ8_0 name_to_type = {name: lazy_tensor.data_type for (name, lazy_tensor) in model.items()} - raise Exception(f"Unexpected combination of types: {name_to_type}") + raise ValueError(f"Unexpected combination of types: {name_to_type}") def convert_to_output_type(model: LazyModel, output_type: GGMLFileType) -> LazyModel: @@ -1175,10 +1252,26 @@ def convert_to_output_type(model: LazyModel, output_type: GGMLFileType) -> LazyM def convert_model_names(model: LazyModel, params: Params, skip_unknown: bool) -> LazyModel: tmap = gguf.TensorNameMap(ARCH, params.n_layer) - should_skip: set[gguf.MODEL_TENSOR] = set(gguf.MODEL_TENSOR_SKIP.get(ARCH, [])) + should_skip = set(gguf.MODEL_TENSOR_SKIP.get(ARCH, [])) tmp = model + # merge experts into one tensor + if params.n_experts and params.n_experts > 0: + for i_l in range(params.n_layer): + for w in range(1, 4): + experts = [] + for e in range(params.n_experts): + if f"layers.{i_l}.feed_forward.experts.{e}.w{w}.weight" in model: + experts.append(model[f"layers.{i_l}.feed_forward.experts.{e}.w{w}.weight"]) + del tmp[f"layers.{i_l}.feed_forward.experts.{e}.w{w}.weight"] + elif f"model.layers.{i_l}.block_sparse_moe.experts.{e}.w{w}.weight" in model: + experts.append(model[f"model.layers.{i_l}.block_sparse_moe.experts.{e}.w{w}.weight"]) + del tmp[f"model.layers.{i_l}.block_sparse_moe.experts.{e}.w{w}.weight"] + else: + raise ValueError(f"Expert tensor not found: layers.{i_l}.feed_forward.experts.{e}.w{w}.weight") + tmp[f"layers.{i_l}.feed_forward.experts.w{w}.weight"] = pack_experts_lazy(experts) + # HF models permut or pack some of the tensors, so we need to undo that for i in itertools.count(): if f"model.layers.{i}.self_attn.q_proj.weight" in model: @@ -1202,8 +1295,7 @@ def convert_model_names(model: LazyModel, params: Params, skip_unknown: bool) -> if skip_unknown: print(f"Unexpected tensor name: {name} - skipping") continue - else: - raise Exception(f"Unexpected tensor name: {name}. Use --skip-unknown to ignore it (e.g. LLaVA)") + raise ValueError(f"Unexpected tensor name: {name}. Use --skip-unknown to ignore it (e.g. LLaVA)") if tensor_type in should_skip: print(f"skipping tensor {name_new}") @@ -1220,7 +1312,7 @@ def nth_multifile_path(path: Path, n: int) -> Path | None: the nth path in the model. ''' # Support the following patterns: - patterns: list[tuple[str, str]] = [ + patterns = [ # - x.00.pth, x.01.pth, etc. (r'\.[0-9]{2}\.pth$', f'.{n:02}.pth'), # - x-00001-of-00002.bin, x-00002-of-00002.bin, etc. @@ -1266,9 +1358,9 @@ def load_some_model(path: Path) -> ModelPlus: globs = ["consolidated.00.pth", "pytorch_model-00001-of-*.bin", "*.pt", "pytorch_model.bin"] files = [file for glob in globs for file in path.glob(glob)] if not files: - raise Exception(f"Can't find model in directory {path}") + raise FileNotFoundError(f"Can't find model in directory {path}") if len(files) > 1: - raise Exception(f"Found multiple models in {path}, not sure which to pick: {files}") + raise ValueError(f"Found multiple models in {path}, not sure which to pick: {files}") path = files[0] paths = find_multifile_paths(path) @@ -1282,36 +1374,14 @@ def load_some_model(path: Path) -> ModelPlus: class VocabFactory: - _FILES = {"spm": "tokenizer.model", "bpe": "vocab.json", "hfft": "tokenizer.json"} + _VOCAB_CLASSES: list[type[Vocab]] = [SentencePieceVocab, BpeVocab, LlamaHfVocab] def __init__(self, path: Path): self.path = path - self.file_paths = self._detect_files() - print(f"Found vocab files: {self.file_paths}") - def _detect_files(self) -> dict[str, Path | None]: - def locate(file: str) -> Path | None: - if (path := self.path / file).exists(): - return path - if (path := self.path.parent / file).exists(): - return path - return None - - return {vt: locate(f) for vt, f in self._FILES.items()} - - def _select_file(self, vocab_types: list[str]) -> tuple[str, Path]: - for vtype in vocab_types: - try: - path = self.file_paths[vtype] - except KeyError: - raise ValueError(f"Unsupported vocabulary type {vtype}") from None - if path is not None: - return vtype, path - raise FileNotFoundError(f"Could not find any of {[self._FILES[vt] for vt in vocab_types]}") - - def _create_special_vocab(self, vocab: Vocab, vocabtype: str, model_parent_path: Path) -> gguf.SpecialVocab: - load_merges = vocabtype == "bpe" - n_vocab = vocab.vocab_size if hasattr(vocab, "vocab_size") else None + def _create_special_vocab(self, vocab: BaseVocab, model_parent_path: Path) -> gguf.SpecialVocab: + load_merges = vocab.name == "bpe" + n_vocab = vocab.vocab_size if isinstance(vocab, Vocab) else None return gguf.SpecialVocab( model_parent_path, load_merges=load_merges, @@ -1319,30 +1389,36 @@ def _create_special_vocab(self, vocab: Vocab, vocabtype: str, model_parent_path: n_vocab=n_vocab, ) - def load_vocab(self, vocab_types: list[str], model_parent_path: Path) -> tuple[Vocab, gguf.SpecialVocab]: - vocab_type, path = self._select_file(vocab_types) - print(f"Loading vocab file {path!r}, type {vocab_type!r}") + def _create_vocab_by_path(self, vocab_types: list[str]) -> Vocab: + vocab_classes: dict[str, type[Vocab]] = {cls.name: cls for cls in self._VOCAB_CLASSES} + selected_vocabs: dict[str, type[Vocab]] = {} + for vtype in vocab_types: + try: + selected_vocabs[vtype] = vocab_classes[vtype] + except KeyError: + raise ValueError(f"Unsupported vocabulary type {vtype}") from None + + for vtype, cls in selected_vocabs.items(): + try: + vocab = cls(self.path) + break + except FileNotFoundError: + pass # ignore unavailable tokenizers + else: + raise FileNotFoundError(f"Could not find a tokenizer matching any of {vocab_types}") - added_tokens_path = path.parent / "added_tokens.json" - vocab: Vocab - if vocab_type == "bpe": - vocab = BpeVocab( - path, added_tokens_path if added_tokens_path.exists() else None - ) - elif vocab_type == "spm": - vocab = SentencePieceVocab( - path, added_tokens_path if added_tokens_path.exists() else None - ) - elif vocab_type == "hfft": - vocab = HfVocab( - path.parent, added_tokens_path if added_tokens_path.exists() else None - ) + print(f"Loaded vocab file {vocab.fname_tokenizer!r}, type {vocab.name!r}") + return vocab + + def load_vocab(self, vocab_types: list[str] | None, model_parent_path: Path) -> tuple[BaseVocab, gguf.SpecialVocab]: + vocab: BaseVocab + if vocab_types is None: + vocab = NoVocab() else: - raise ValueError(vocab_type) + vocab = self._create_vocab_by_path(vocab_types) # FIXME: Respect --vocab-dir? special_vocab = self._create_special_vocab( vocab, - vocab_type, model_parent_path, ) return vocab, special_vocab @@ -1380,6 +1456,7 @@ def main(args_in: list[str] | None = None) -> None: parser.add_argument("--dump", action="store_true", help="don't convert, just show what's in the model") parser.add_argument("--dump-single", action="store_true", help="don't convert, just show what's in a single model file") parser.add_argument("--vocab-only", action="store_true", help="extract only the vocab") + parser.add_argument("--no-vocab", action="store_true", help="store model without the vocab") parser.add_argument("--outtype", choices=output_choices, help="output format - note: q8_0 may be very slow (default: f16 or f32 based on input)") parser.add_argument("--vocab-dir", type=Path, help="directory containing tokenizer.model, if separate from model file") parser.add_argument("--vocab-type", help="vocab types to try in order, choose from 'spm', 'bpe', 'hfft' (default: spm,hfft)", default="spm,hfft") @@ -1392,6 +1469,8 @@ def main(args_in: list[str] | None = None) -> None: parser.add_argument("--skip-unknown", action="store_true", help="skip unknown tensor names instead of failing") args = parser.parse_args(args_in) + if args.no_vocab and args.vocab_only: + raise ValueError("--vocab-only does not make sense with --no-vocab") if args.dump_single: model_plus = lazy_load_file(args.model) @@ -1413,10 +1492,12 @@ def main(args_in: list[str] | None = None) -> None: params = Params.load(model_plus) if params.n_ctx == -1: if args.ctx is None: - raise Exception("The model doesn't have a context size, and you didn't specify one with --ctx\n" - "Please specify one with --ctx:\n" - " - LLaMA v1: --ctx 2048\n" - " - LLaMA v2: --ctx 4096\n") + msg = """\ + The model doesn't have a context size, and you didn't specify one with --ctx + Please specify one with --ctx: + - LLaMA v1: --ctx 2048 + - LLaMA v2: --ctx 4096""" + parser.error(textwrap.dedent(msg)) params.n_ctx = args.ctx if args.outtype: @@ -1431,9 +1512,11 @@ def main(args_in: list[str] | None = None) -> None: model_parent_path = model_plus.paths[0].parent vocab_path = Path(args.vocab_dir or args.model or model_parent_path) vocab_factory = VocabFactory(vocab_path) - vocab, special_vocab = vocab_factory.load_vocab(args.vocab_type.split(","), model_parent_path) + vocab_types = None if args.no_vocab else args.vocab_type.split(",") + vocab, special_vocab = vocab_factory.load_vocab(vocab_types, model_parent_path) if args.vocab_only: + assert isinstance(vocab, Vocab) if not args.outfile: raise ValueError("need --outfile if using --vocab-only") outfile = args.outfile @@ -1442,7 +1525,7 @@ def main(args_in: list[str] | None = None) -> None: print(f"Wrote {outfile}") return - if model_plus.vocab is not None and args.vocab_dir is None: + if model_plus.vocab is not None and args.vocab_dir is None and not args.no_vocab: vocab = model_plus.vocab print(f"Vocab info: {vocab}") diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index e762cf8b9238b..76496bf06d135 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -21,6 +21,7 @@ else() add_subdirectory(embedding) add_subdirectory(finetune) add_subdirectory(gritlm) + add_subdirectory(gguf-split) add_subdirectory(infill) add_subdirectory(llama-bench) add_subdirectory(llava) @@ -33,6 +34,7 @@ else() add_subdirectory(perplexity) add_subdirectory(quantize) add_subdirectory(quantize-stats) + add_subdirectory(retrieval) add_subdirectory(save-load-state) add_subdirectory(simple) add_subdirectory(passkey) diff --git a/examples/batched-bench/README.md b/examples/batched-bench/README.md index 34b343f66d6b9..bf951baf7f096 100644 --- a/examples/batched-bench/README.md +++ b/examples/batched-bench/README.md @@ -10,16 +10,16 @@ There are 2 modes of operation: - `prompt is shared` - there is a common prompt of size `PP` used by all batches (i.e. `N_KV = PP + B*TG`) ```bash -./batched-bench MODEL_PATH [N_KV_MAX] [IS_PP_SHARED] [NGL] [MMQ] +./batched-bench MODEL_PATH [N_KV_MAX] [N_BATCH] [N_UBATCH] [IS_PP_SHARED] [NGL] [MMQ] # LLaMA 7B, F16, N_KV_MAX = 16384 (8GB), prompt not shared -./batched-bench ./models/llama-7b/ggml-model-f16.gguf 16384 0 99 +./batched-bench ./models/llama-7b/ggml-model-f16.gguf 16384 2048 512 0 99 # LLaMA 7B, Q8_0, N_KV_MAX = 16384 (8GB), prompt is shared -./batched-bench ./models/llama-7b/ggml-model-q8_0.gguf 16384 1 99 +./batched-bench ./models/llama-7b/ggml-model-q8_0.gguf 16384 2048 512 1 99 # custom set of batches -./batched-bench ./models/llama-7b/ggml-model-q8_0.gguf 2048 0 999 0 128,256,512 128,256 1,2,4,8,16,32 +./batched-bench ./models/llama-7b/ggml-model-q8_0.gguf 2048 512 512 0 999 0 128,256,512 128,256 1,2,4,8,16,32 ``` ## Sample results diff --git a/examples/batched-bench/batched-bench.cpp b/examples/batched-bench/batched-bench.cpp index 19674dfd36708..1e34de620a41b 100644 --- a/examples/batched-bench/batched-bench.cpp +++ b/examples/batched-bench/batched-bench.cpp @@ -32,13 +32,15 @@ int main(int argc, char ** argv) { gpt_params params; if (argc == 1 || argv[1][0] == '-') { - printf("usage: %s MODEL_PATH [N_KV_MAX] [IS_PP_SHARED] [NGL] \n" , argv[0]); + printf("usage: %s MODEL_PATH [N_KV_MAX] [N_BATCH] [N_UBATCH] [IS_PP_SHARED] [NGL] \n" , argv[0]); printf(" , and PL are comma-separated lists of numbers without spaces\n\n"); - printf(" example: %s ggml-model-f16.gguf 2048 0 999 128,256,512 128,256 1,2,4,8,16,32\n\n", argv[0]); + printf(" example: %s ggml-model-f16.gguf 2048 2048 512 0 999 128,256,512 128,256 1,2,4,8,16,32\n\n", argv[0]); return 1 ; } int n_kv_max = 2048; + int n_batch = 2048; + int n_ubatch = 512; int is_pp_shared = 0; int n_gpu_layers = 0; @@ -56,23 +58,31 @@ int main(int argc, char ** argv) { } if (argc >= 4) { - is_pp_shared = std::atoi(argv[3]); + n_batch = std::atoi(argv[3]); } if (argc >= 5) { - n_gpu_layers = std::atoi(argv[4]); + n_ubatch = std::atoi(argv[4]); } if (argc >= 6) { - n_pp = parse_list(argv[5]); + is_pp_shared = std::atoi(argv[5]); } if (argc >= 7) { - n_tg = parse_list(argv[6]); + n_gpu_layers = std::atoi(argv[6]); } if (argc >= 8) { - n_pl = parse_list(argv[7]); + n_pp = parse_list(argv[7]); + } + + if (argc >= 9) { + n_tg = parse_list(argv[8]); + } + + if (argc >= 10) { + n_pl = parse_list(argv[9]); } // init LLM @@ -100,7 +110,8 @@ int main(int argc, char ** argv) { ctx_params.seed = 1234; ctx_params.n_ctx = n_kv_max; - ctx_params.n_batch = 512; + ctx_params.n_batch = n_batch; + ctx_params.n_ubatch = n_ubatch; ctx_params.n_threads = params.n_threads; ctx_params.n_threads_batch = params.n_threads_batch == -1 ? params.n_threads : params.n_threads_batch; @@ -158,7 +169,7 @@ int main(int argc, char ** argv) { } LOG_TEE("\n"); - LOG_TEE("%s: n_kv_max = %d, is_pp_shared = %d, n_gpu_layers = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, is_pp_shared, n_gpu_layers, ctx_params.n_threads, ctx_params.n_threads_batch); + LOG_TEE("%s: n_kv_max = %d, n_batch = %d, n_ubatch = %d, is_pp_shared = %d, n_gpu_layers = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, n_batch, n_ubatch, is_pp_shared, n_gpu_layers, ctx_params.n_threads, ctx_params.n_threads_batch); LOG_TEE("\n"); LOG_TEE("|%6s | %6s | %4s | %6s | %8s | %8s | %8s | %8s | %8s | %8s |\n", "PP", "TG", "B", "N_KV", "T_PP s", "S_PP t/s", "T_TG s", "S_TG t/s", "T s", "S t/s"); diff --git a/examples/batched/batched.cpp b/examples/batched/batched.cpp index ee1f8f1bf5dd2..7aaf63ceb1a7c 100644 --- a/examples/batched/batched.cpp +++ b/examples/batched/batched.cpp @@ -48,6 +48,8 @@ int main(int argc, char ** argv) { params.prompt = "Hello my name is"; } + process_escapes(params.prompt); + // init LLM llama_backend_init(); @@ -78,7 +80,7 @@ int main(int argc, char ** argv) { llama_context_params ctx_params = llama_context_default_params(); ctx_params.seed = 1234; - ctx_params.n_ctx = n_kv_req; + ctx_params.n_ctx = n_kv_req; ctx_params.n_batch = std::max(n_len, n_parallel); ctx_params.n_seq_max = n_parallel; ctx_params.n_threads = params.n_threads; diff --git a/examples/convert-llama2c-to-ggml/README.md b/examples/convert-llama2c-to-ggml/README.md index 0f37d295bd9ee..6da2d7e1809a9 100644 --- a/examples/convert-llama2c-to-ggml/README.md +++ b/examples/convert-llama2c-to-ggml/README.md @@ -21,6 +21,8 @@ An example command using a model from [karpathy/tinyllamas](https://huggingface. `$ ./convert-llama2c-to-ggml --copy-vocab-from-model llama-2-7b-chat.gguf.q2_K.bin --llama2c-model stories42M.bin --llama2c-output-model stories42M.gguf.bin` +Note: The vocabulary for `stories260K.bin` should be its own tokenizer `tok512.bin` found in [karpathy/tinyllamas/stories260K](https://huggingface.co/karpathy/tinyllamas/tree/main/stories260K). + Now you can use the model with a command like: `$ ./main -m stories42M.gguf.bin -p "One day, Lily met a Shoggoth" -n 500 -c 256` diff --git a/examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp b/examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp index 8209dcb642bee..746c3fbef8412 100644 --- a/examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp +++ b/examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp @@ -1,6 +1,7 @@ #include "ggml.h" #include "llama.h" #include "common.h" +#include "log.h" #include #include @@ -78,111 +79,101 @@ typedef struct { struct TransformerWeights { // token embedding table - float* token_embedding_table; // (vocab_size, dim) + std::vector token_embedding_table; // (vocab_size, dim) // weights for rmsnorms - float* rms_att_weight; // (layer, dim) rmsnorm weights - float* rms_ffn_weight; // (layer, dim) + std::vector rms_att_weight; // (layer, dim) rmsnorm weights + std::vector rms_ffn_weight; // (layer, dim) // weights for matmuls - float* wq; // (layer, dim, dim) - float* wk; // (layer, dim, dim) - float* wv; // (layer, dim, dim) - float* wo; // (layer, dim, dim) + std::vector wq; // (layer, dim, dim) + std::vector wk; // (layer, dim, dim) + std::vector wv; // (layer, dim, dim) + std::vector wo; // (layer, dim, dim) // weights for ffn - float* w1; // (layer, hidden_dim, dim) - float* w2; // (layer, dim, hidden_dim) - float* w3; // (layer, hidden_dim, dim) + std::vector w1; // (layer, hidden_dim, dim) + std::vector w2; // (layer, dim, hidden_dim) + std::vector w3; // (layer, hidden_dim, dim) // final rmsnorm - float* rms_final_weight; // (dim,) + std::vector rms_final_weight; // (dim,) // freq_cis for RoPE relatively positional embeddings - // float* freq_cis_real; // (seq_len, dim/2) - // float* freq_cis_imag; // (seq_len, dim/2) + // std::vector freq_cis_real; // (seq_len, dim/2) + // std::vector freq_cis_imag; // (seq_len, dim/2) // (optional) classifier weights for the logits, on the last layer - float* wcls; - - ~TransformerWeights() { - delete[] token_embedding_table; - delete[] rms_att_weight; - delete[] rms_ffn_weight; - delete[] wq; - delete[] wk; - delete[] wv; - delete[] wo; - delete[] w1; - delete[] w2; - delete[] w3; - delete[] rms_final_weight; - delete[] wcls; - } + std::vector wcls; }; -static void malloc_weights(TransformerWeights* w, Config* p, bool shared_weights) { - // we calloc instead of malloc to keep valgrind happy - w->token_embedding_table = new float[p->vocab_size * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] = [%d] float space for w->token_embedding_table\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim); +static void alloc_weights(TransformerWeights * w, const Config * p, bool shared_weights) { + const int n_multiqueries = p->n_kv_heads <= 0 || p->n_kv_heads >= p->n_heads ? 1 : p->n_heads / p->n_kv_heads; + try { + w->token_embedding_table.resize(p->vocab_size * p->dim); + LOG("%s: Allocating [%d] x [%d] = [%d] float space for w->token_embedding_table\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim); - w->rms_att_weight = new float[p->n_layers * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] = [%d] float space for w->rms_att_weight\n",__func__,p->n_layers, p->dim, p->n_layers * p->dim); + w->rms_att_weight.resize(p->n_layers * p->dim); + LOG("%s: Allocating [%d] x [%d] = [%d] float space for w->rms_att_weight\n",__func__,p->n_layers, p->dim, p->n_layers * p->dim); - w->rms_ffn_weight = new float[p->n_layers * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] = [%d] float space for w->rms_ffn_weight\n",__func__,p->n_layers , p->dim, p->n_layers * p->dim); + w->rms_ffn_weight.resize(p->n_layers * p->dim); + LOG("%s: Allocating [%d] x [%d] = [%d] float space for w->rms_ffn_weight\n",__func__,p->n_layers , p->dim, p->n_layers * p->dim); - w->wq = new float[p->n_layers * p->dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->wq\n",__func__,p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); + w->wq.resize(p->n_layers * p->dim * p->dim); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->wq\n",__func__,p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); - w->wk = new float[p->n_layers * p->dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->wk\n",__func__,p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); + w->wk.resize(p->n_layers * p->dim * p->dim / n_multiqueries); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->wk\n",__func__,p->n_layers, p->dim, p->dim / n_multiqueries, p->n_layers * p->dim * p->dim / n_multiqueries); - w->wv = new float[p->n_layers * p->dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->wv\n",__func__, p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); + w->wv.resize(p->n_layers * p->dim * p->dim / n_multiqueries); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->wv\n",__func__, p->n_layers, p->dim, p->dim / n_multiqueries, p->n_layers * p->dim * p->dim / n_multiqueries); - w->wo = new float[p->n_layers * p->dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->wo\n",__func__,p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); + w->wo.resize(p->n_layers * p->dim * p->dim); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->wo\n",__func__,p->n_layers, p->dim, p->dim, p->n_layers * p->dim * p->dim); - w->w1 = new float[p->n_layers * p->hidden_dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->w1\n",__func__,p->n_layers, p->hidden_dim, p->dim, p->n_layers * p->hidden_dim * p->dim); + w->w1.resize(p->n_layers * p->hidden_dim * p->dim); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->w1\n",__func__,p->n_layers, p->hidden_dim, p->dim, p->n_layers * p->hidden_dim * p->dim); - w->w2 = new float[p->n_layers * p->hidden_dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->w2\n",__func__,p->n_layers, p->dim, p->hidden_dim, p->n_layers * p->hidden_dim * p->dim); + w->w2.resize(p->n_layers * p->hidden_dim * p->dim); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->w2\n",__func__,p->n_layers, p->dim, p->hidden_dim, p->n_layers * p->hidden_dim * p->dim); - w->w3 = new float[p->n_layers * p->hidden_dim * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] x [%d] = [%d] float space for w->w3\n",__func__,p->n_layers, p->hidden_dim, p->dim, p->n_layers * p->hidden_dim * p->dim); + w->w3.resize(p->n_layers * p->hidden_dim * p->dim); + LOG("%s: Allocating [%d] x [%d] x [%d] = [%d] float space for w->w3\n",__func__,p->n_layers, p->hidden_dim, p->dim, p->n_layers * p->hidden_dim * p->dim); - w->rms_final_weight = new float[p->dim](); - printf("[%s:AK] Allocating [%d] float space for w->rms_final_weight\n",__func__,p->dim); + w->rms_final_weight.resize(p->dim); + LOG("%s: Allocating [%d] float space for w->rms_final_weight\n",__func__,p->dim); - if (shared_weights) { - w->wcls = NULL; - } else { - w->wcls = new float[p->vocab_size * p->dim](); - printf("[%s:AK] Allocating [%d] x [%d] = [%d] float space for w->wcls\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim); + if (shared_weights) { + w->wcls = {}; + } else { + w->wcls.resize(p->vocab_size * p->dim); + LOG("%s: Allocating [%d] x [%d] = [%d] float space for w->wcls\n",__func__,p->vocab_size , p->dim, p->vocab_size * p->dim); + } + } + catch (std::length_error &) { + die("Invalid configuration. Failed to allocate memory for weights"); } } -static int checkpoint_init_weights(TransformerWeights *w, Config* p, FILE* f, bool shared_weights) { - if (fread(w->token_embedding_table, sizeof(float), p->vocab_size * p->dim, f) != static_cast(p->vocab_size * p->dim)) return 1; - if (fread(w->rms_att_weight, sizeof(float), p->n_layers * p->dim, f) != static_cast(p->n_layers * p->dim)) return 1; - if (fread(w->wq, sizeof(float), p->n_layers * p->dim * p->dim, f) != static_cast(p->n_layers * p->dim * p->dim)) return 1; - if (fread(w->wk, sizeof(float), p->n_layers * p->dim * p->dim, f) != static_cast(p->n_layers * p->dim * p->dim)) return 1; - if (fread(w->wv, sizeof(float), p->n_layers * p->dim * p->dim, f) != static_cast(p->n_layers * p->dim * p->dim)) return 1; - if (fread(w->wo, sizeof(float), p->n_layers * p->dim * p->dim, f) != static_cast(p->n_layers * p->dim * p->dim)) return 1; - if (fread(w->rms_ffn_weight, sizeof(float), p->n_layers * p->dim, f) != static_cast(p->n_layers * p->dim)) return 1; - if (fread(w->w1, sizeof(float), p->n_layers * p->dim * p->hidden_dim, f) != static_cast(p->n_layers * p->dim * p->hidden_dim)) return 1; - if (fread(w->w2, sizeof(float), p->n_layers * p->hidden_dim * p->dim, f) != static_cast(p->n_layers * p->hidden_dim * p->dim)) return 1; - if (fread(w->w3, sizeof(float), p->n_layers * p->dim * p->hidden_dim, f) != static_cast(p->n_layers * p->dim * p->hidden_dim)) return 1; - if (fread(w->rms_final_weight, sizeof(float), p->dim, f) != static_cast(p->dim)) return 1; +static int checkpoint_init_weights(TransformerWeights * w, const Config * p, FILE * f, bool shared_weights) { + if (fread(w->token_embedding_table.data(), sizeof(float), w->token_embedding_table.size(), f) != w->token_embedding_table.size()) return 1; + if (fread(w->rms_att_weight.data(), sizeof(float), w->rms_att_weight.size(), f) != w->rms_att_weight.size()) return 1; + if (fread(w->wq.data(), sizeof(float), w->wq.size(), f) != w->wq.size()) return 1; + if (fread(w->wk.data(), sizeof(float), w->wk.size(), f) != w->wk.size()) return 1; + if (fread(w->wv.data(), sizeof(float), w->wv.size(), f) != w->wv.size()) return 1; + if (fread(w->wo.data(), sizeof(float), w->wo.size(), f) != w->wo.size()) return 1; + if (fread(w->rms_ffn_weight.data(), sizeof(float), w->rms_ffn_weight.size(), f) != w->rms_ffn_weight.size()) return 1; + if (fread(w->w1.data(), sizeof(float), w->w1.size(), f) != w->w1.size()) return 1; + if (fread(w->w2.data(), sizeof(float), w->w2.size(), f) != w->w2.size()) return 1; + if (fread(w->w3.data(), sizeof(float), w->w3.size(), f) != w->w3.size()) return 1; + if (fread(w->rms_final_weight.data(), sizeof(float), w->rms_final_weight.size(), f) != w->rms_final_weight.size()) return 1; // Skip freq_cis_real & freq_cis_imag int head_size = p->dim / p->n_heads; fseek(f, p->seq_len * head_size * sizeof(float), SEEK_CUR); - if (!shared_weights && fread(w->wcls, sizeof(float), p->vocab_size * p->dim, f) != static_cast(p->vocab_size * p->dim)) return 1; + if (!shared_weights && fread(w->wcls.data(), sizeof(float), w->wcls.size(), f) != w->wcls.size()) return 1; // Check we didn't forget to read anything auto curr = ftell(f); fseek(f, 0, SEEK_END); auto end = ftell(f); if (curr != end) { - printf("Error: failed to read the checkpoint file to the end (curr = %ld, end = %ld)\n", curr, end); + LOG("%s: Error: failed to read the checkpoint file to the end (curr = %ld, end = %ld)\n", __func__, curr, end); return 1; } @@ -190,20 +181,20 @@ static int checkpoint_init_weights(TransformerWeights *w, Config* p, FILE* f, bo } static void print_sample_weights(TransformerWeights *w){ - printf("----- Quick print of first of the weight vales of all the variables\n"); - printf("%f\n", w->token_embedding_table[0]); - printf("%f\n", w->rms_att_weight[0]); - printf("%f\n", w->rms_ffn_weight[0]); - - printf("%f\n", w->wq[0]); - printf("%f\n", w->wk[0]); - printf("%f\n", w->wv[0]); - printf("%f\n", w->wo[0]); - printf("%f\n", w->w1[0]); - printf("%f\n", w->w2[0]); - printf("%f\n", w->w3[0]); - printf("%f\n", w->rms_att_weight[0]); - if (w->wcls) printf("%f\n", w->wcls[0]); + LOG("----- Quick print of first of the weight vales of all the variables\n"); + LOG("%f\n", w->token_embedding_table[0]); + LOG("%f\n", w->rms_att_weight[0]); + LOG("%f\n", w->rms_ffn_weight[0]); + + LOG("%f\n", w->wq[0]); + LOG("%f\n", w->wk[0]); + LOG("%f\n", w->wv[0]); + LOG("%f\n", w->wo[0]); + LOG("%f\n", w->w1[0]); + LOG("%f\n", w->w2[0]); + LOG("%f\n", w->w3[0]); + LOG("%f\n", w->rms_att_weight[0]); + if (!w->wcls.empty()) LOG("%f\n", w->wcls[0]); } //////////////////////////////////////////////////////////////////////////////////////////////////////////// @@ -225,14 +216,16 @@ struct llama_vocab { }; struct my_llama_hparams { - uint32_t n_vocab = 32000; - uint32_t n_ctx = 512; // this is provided as user input? - uint32_t n_embd = 4096; - uint32_t n_ff = 11008; - uint32_t n_mult = 4; - uint32_t n_head = 32; - uint32_t n_layer = 32; - uint32_t n_rot = 64; + uint32_t n_vocab = 32000; + uint32_t n_ctx = 512; // this is provided as user input? + uint32_t n_embd = 4096; + uint32_t n_ff = 11008; + uint32_t n_mult = 4; + uint32_t n_head = 32; + uint32_t n_head_kv = 32; + uint32_t n_layer = 32; + uint32_t n_rot = 64; + bool operator!=(const my_llama_hparams& other) const { return memcmp(this, &other, sizeof(my_llama_hparams)); } @@ -325,14 +318,30 @@ struct train_params { }; static void print_params(struct my_llama_hparams * params) { - printf("%s: n_vocab: %u\n", __func__, params->n_vocab); - printf("%s: n_ctx: %u\n", __func__, params->n_ctx); - printf("%s: n_embd: %u\n", __func__, params->n_embd); - printf("%s: n_mult: %u\n", __func__, params->n_mult); - printf("%s: n_head: %u\n", __func__, params->n_head); - printf("%s: n_ff: %u\n", __func__, params->n_ff); - printf("%s: n_layer: %u\n", __func__, params->n_layer); - printf("%s: n_rot: %u\n", __func__, params->n_rot); + LOG("%s: n_vocab: %u\n", __func__, params->n_vocab); + LOG("%s: n_ctx: %u\n", __func__, params->n_ctx); + LOG("%s: n_embd: %u\n", __func__, params->n_embd); + LOG("%s: n_mult: %u\n", __func__, params->n_mult); + LOG("%s: n_head: %u\n", __func__, params->n_head); + LOG("%s: n_head_kv: %u\n", __func__, params->n_head_kv); + LOG("%s: n_ff: %u\n", __func__, params->n_ff); + LOG("%s: n_layer: %u\n", __func__, params->n_layer); + LOG("%s: n_rot: %u\n", __func__, params->n_rot); +} + +static void print_tensor_info(const struct ggml_context * ctx) { + for (auto t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) { + LOG("%s: Allocating ", __func__); + int64_t total = 1; + int i = 0; + for (; i < ggml_n_dims(t); ++i) { + if (i > 0) LOG("x "); + LOG("[%" PRId64 "] ", t->ne[i]); + total *= t->ne[i]; + } + if (i > 1) LOG("= [%" PRId64 "] ", total); + LOG("float space for %s\n", ggml_get_name(t)); + } } static void init_model(struct my_llama_model * model) { @@ -342,6 +351,8 @@ static void init_model(struct my_llama_model * model) { const uint32_t n_layer = hparams.n_layer; const uint32_t n_vocab = hparams.n_vocab; + const uint32_t n_multiqueries = hparams.n_head_kv <= 0 || hparams.n_head_kv >= hparams.n_head ? 1 : hparams.n_head / hparams.n_head_kv; + const uint32_t n_ff = hparams.n_ff; struct ggml_context * ctx = model->ctx; @@ -350,25 +361,8 @@ static void init_model(struct my_llama_model * model) { model->train_tokens = 0; model->tok_embeddings = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_vocab); - printf("[%s:GG] Allocating [%u] x [%u] = [%u] float space for model->tok_embeddings\n",__func__,n_embd , n_vocab, n_embd * n_vocab); - model->norm = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_embd); - printf("[%s:GG] Allocating [%u] float space for model->norm\n",__func__,n_embd); - model->output = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_vocab); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for model->output\n",__func__,n_embd, n_vocab, n_embd * n_vocab); - - // printing the per-layer allocations here so we dont print in the for loop. - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.wq for [%u] layers\n",__func__, n_embd, n_embd, n_embd * n_embd, n_layer); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.wk for [%u] layers\n",__func__, n_embd, n_embd, n_embd * n_embd, n_layer); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.wv for [%u] layers\n",__func__, n_embd, n_embd, n_embd * n_embd, n_layer); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.wo for [%u] layers\n",__func__, n_embd, n_embd, n_embd * n_embd, n_layer); - - printf("[%s:GG] Allocating [%u] float space for layer.ffn_norm for [%u] layers\n",__func__,n_embd, n_layer); - - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.w1 for [%u] layers\n",__func__, n_ff, n_embd, n_embd * n_ff, n_layer); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.w2 for [%u] layers\n",__func__, n_embd, n_ff, n_ff * n_embd, n_layer); - printf("[%s:GG] Allocating [%u] x[%u] = [%u] float space for layer.w3 for [%u] layers\n",__func__, n_ff, n_embd, n_embd * n_ff, n_layer); ggml_set_name(model->tok_embeddings, "tok_embeddings.weight"); ggml_set_name(model->norm, "norm.weight"); @@ -383,8 +377,8 @@ static void init_model(struct my_llama_model * model) { layer.attention_norm = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_embd); layer.wq = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd); - layer.wk = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd); - layer.wv = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd); + layer.wk = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd / n_multiqueries); + layer.wv = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd / n_multiqueries); layer.wo = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, n_embd); layer.ffn_norm = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_embd); @@ -406,6 +400,8 @@ static void init_model(struct my_llama_model * model) { ggml_format_name(layer.w2, "%s.feed_forward.w2.weight", layers_i.c_str()); ggml_format_name(layer.w3, "%s.feed_forward.w3.weight", layers_i.c_str()); } + + print_tensor_info(ctx); } static float get_f32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) { @@ -421,9 +417,9 @@ static int32_t get_i32_2d(struct ggml_tensor * tensor, int64_t i0, int64_t i1) { static void print_row(struct ggml_tensor * probs, int i) { for (int k = 0; k < probs->ne[0]; ++k) { float p = get_f32_2d(probs, k, i); - printf(" %f", p); + LOG(" %f", p); } - printf("\n"); + LOG("\n"); } static void print_matrix(struct ggml_tensor * probs) { @@ -431,33 +427,12 @@ static void print_matrix(struct ggml_tensor * probs) { for (int i = 0; i < probs->ne[1]; ++i) { for (int k = 0; k < probs->ne[0]; ++k) { float p = get_f32_2d(probs, k, i); - printf(" %.2f", p); + LOG(" %.2f", p); } - printf("\n"); + LOG("\n"); } } -#ifdef __GNUC__ -#ifdef __MINGW32__ -__attribute__((format(gnu_printf, 1, 2))) -#else -__attribute__((format(printf, 1, 2))) -#endif -#endif -static std::string format(const char * fmt, ...) { - va_list ap, ap2; - va_start(ap, fmt); - va_copy(ap2, ap); - int size = vsnprintf(NULL, 0, fmt, ap); - GGML_ASSERT(size >= 0 && size < INT_MAX); - std::vector buf(size + 1); - int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2); - GGML_ASSERT(size2 == size); - va_end(ap2); - va_end(ap); - return std::string(buf.data(), size); -} - struct llama_file { // use FILE * so we don't have to re-open the file to mmap FILE * fp; @@ -549,8 +524,9 @@ static std::string llama_escape_whitespaces(const std::string & text) { return out.str(); } -static void load_vocab(const char *filename, Config *config, struct llama_vocab *vocab) { +static void load_vocab(const char * filename, const Config * config, struct llama_vocab * vocab) { if (is_ggml_file(filename)) { + LOG("%s: Loading vocabulary from gguf file %s\n", __func__, filename); struct ggml_context * ctx_data = NULL; struct gguf_init_params params = { @@ -578,6 +554,9 @@ static void load_vocab(const char *filename, Config *config, struct llama_vocab const int * toktypes = (const int * ) gguf_get_arr_data(ctx, toktype_idx); const uint32_t n_vocab = gguf_get_arr_n(ctx, token_idx); + if (n_vocab != static_cast(config->vocab_size)) { + die_fmt("vocab size mismatch: (gguf) %u != (llama2c) %d", n_vocab, config->vocab_size); + } vocab->id_to_token.resize(n_vocab); @@ -595,7 +574,7 @@ static void load_vocab(const char *filename, Config *config, struct llama_vocab gguf_free(ctx); } else { // assume llama2.c vocabulary - printf("Assuming llama2.c vocabulary since %s is not a gguf file\n", filename); + LOG("%s: Assuming llama2.c vocabulary since %s is not a gguf file\n", __func__, filename); llama_file file(filename, "rb"); if (!file.fp) { die_fmt("%s: %s", strerror(errno), filename); @@ -638,38 +617,15 @@ static void load_vocab(const char *filename, Config *config, struct llama_vocab } static void convert_weights_ak_to_gg(struct ggml_tensor * gg_weights, const float * karpathy_weights) { - int ct; - switch (ggml_n_dims(gg_weights)) { - case 1: - ct = 0; - for (int i0 = 0; i0 < gg_weights->ne[0]; i0++){ - float * ptr = (float *) ((char *) gg_weights->data + i0*gg_weights->nb[0]); - *ptr = karpathy_weights[ct]; - ct++; - } - break; - case 2: - ct = 0; - for (int i1 = 0; i1 < gg_weights->ne[1]; i1++) { - for (int i0 = 0; i0 < gg_weights->ne[0]; i0++) { - float * ptr = (float *) ((char *) gg_weights->data + i0*gg_weights->nb[0] + i1*gg_weights->nb[1]); - *ptr = karpathy_weights[ct]; - ct++; - } - } - break; - case 3: - ct = 0; - for (int i2 = 0; i2 < gg_weights->ne[2]; i2++) { - for (int i1 = 0; i1 < gg_weights->ne[1]; i1++) { - for (int i0 = 0; i0 < gg_weights->ne[0]; i0++) { - float * ptr = (float *) ((char *) gg_weights->data + i0*gg_weights->nb[0] + i1*gg_weights->nb[1] + i2*gg_weights->nb[2]); - *ptr = karpathy_weights[ct]; - ct++; - } - } - } - break; + int size = 1; + for (int dim = 0; dim < ggml_n_dims(gg_weights); ++dim) { + size *= gg_weights->ne[dim]; + } + for (int ct = 0; ct < size; ++ct) { + int64_t i0 = 0; int64_t i1 = 0; + int64_t i2 = 0; int64_t i3 = 0; + ggml_unravel_index(gg_weights, ct, &i0, &i1, &i2, &i3); + ggml_set_f32_nd(gg_weights, i0, i1, i2, i3, karpathy_weights[ct]); } } @@ -679,16 +635,18 @@ static void save_as_llama_model( // convert AK weights into GG weights one by one. // w->token_embedding_table -> model->tok_embeddings // float* -> struct ggml_tensor - convert_weights_ak_to_gg(model->tok_embeddings, w->token_embedding_table); - convert_weights_ak_to_gg(model->output, w->wcls ? w->wcls : w->token_embedding_table); + convert_weights_ak_to_gg(model->tok_embeddings, w->token_embedding_table.data()); + convert_weights_ak_to_gg(model->output, !w->wcls.empty() ? w->wcls.data() : w->token_embedding_table.data()); - convert_weights_ak_to_gg(model->norm, w->rms_final_weight); + convert_weights_ak_to_gg(model->norm, w->rms_final_weight.data()); //print_row(model->norm, 0); // for rms-att-weight int row_length = model->hparams.n_embd; int n_ff = model->hparams.n_ff; + const uint32_t n_multiqueries = model->hparams.n_head_kv <= 0 || model->hparams.n_head_kv >= model->hparams.n_head ? 1 : model->hparams.n_head / model->hparams.n_head_kv; + for (uint32_t i = 0; i < model->hparams.n_layer; ++i){ auto & layer = model->layers[i]; // 1d @@ -697,9 +655,10 @@ static void save_as_llama_model( // from 3d matrix layer x dim x dim to 2d matrix dim x dim convert_weights_ak_to_gg(layer.wq , &w->wq[i*row_length*row_length]); - convert_weights_ak_to_gg(layer.wk , &w->wk[i*row_length*row_length]); - convert_weights_ak_to_gg(layer.wv , &w->wv[i*row_length*row_length]); convert_weights_ak_to_gg(layer.wo , &w->wo[i*row_length*row_length]); + // from 3d matrix layer x dim x dim to 2d matrix dim x dim / n_multiqueries + convert_weights_ak_to_gg(layer.wk , &w->wk[i*row_length*row_length/n_multiqueries]); + convert_weights_ak_to_gg(layer.wv , &w->wv[i*row_length*row_length/n_multiqueries]); convert_weights_ak_to_gg(layer.w1 , &w->w1[i*row_length*n_ff]); convert_weights_ak_to_gg(layer.w2 , &w->w2[i*n_ff*row_length]); @@ -736,8 +695,8 @@ static void save_as_llama_model( gguf_set_val_u32(ctx, KV_EMBEDDING_LENGTH, model->hparams.n_embd); gguf_set_val_u32(ctx, KV_FEED_FORWARD_LENGTH, model->hparams.n_ff); gguf_set_val_u32(ctx, KV_ATTENTION_HEAD_COUNT, model->hparams.n_head); - // n_head_kv is optional, default to n_head - // gguf_set_val_u32(ctx, KV_ATTENTION_HEAD_COUNT_KV, ...); + gguf_set_val_u32(ctx, KV_ATTENTION_HEAD_COUNT, model->hparams.n_head); + gguf_set_val_u32(ctx, KV_ATTENTION_HEAD_COUNT_KV, model->hparams.n_head_kv); gguf_set_val_u32(ctx, KV_BLOCK_COUNT, model->hparams.n_layer); gguf_set_val_u32(ctx, KV_ROPE_DIMENSION_COUNT, model->hparams.n_rot); gguf_set_val_f32(ctx, KV_ATTENTION_LAYERNORM_RMS_EPS, 1e-5f); @@ -789,12 +748,12 @@ static void save_as_llama_model( static struct train_params get_default_train_params() { struct train_params params; - params.fn_vocab_model = "models/7B/ggml-model-f16.gguf"; + params.fn_vocab_model = "models/7B/ggml-model-f16.gguf"; params.fn_llama2c_output_model = "ak_llama_model.bin"; - params.fn_train_data = "shakespeare.txt"; - params.fn_checkpoint_in = "checkpoint.bin"; - params.fn_checkpoint_out = "checkpoint.bin"; - params.fn_model_out = "ggml-checkpoint-f32.bin"; + params.fn_train_data = "shakespeare.txt"; + params.fn_checkpoint_in = "checkpoint.bin"; + params.fn_checkpoint_out = "checkpoint.bin"; + params.fn_model_out = "ggml-checkpoint-f32.bin"; params.seed = -1; @@ -829,8 +788,8 @@ static struct train_params get_default_train_params() { params.adam_alpha = 1e-3f; params.adam_decay = 1e-3f; - params.mem_model_gb = 2; - params.mem_compute_gb = 24; + params.mem_model_gb = 2; + params.mem_compute_gb = 24; params.mem_compute0_gb = 8; params.mem_compute1_gb = 2; @@ -916,19 +875,30 @@ int main(int argc, char ** argv) { if (!params_parse(argc, argv, ¶ms)) { return 1; } + log_set_target(stdout); Config config; TransformerWeights weights = {}; { - FILE *file = fopen(params.fn_llama2c_model, "rb"); - if (!file) { printf("Unable to open the checkpoint file %s!\n", params.fn_llama2c_model); return 1; } + LOG("%s: Loading llama2c model from %s\n", __func__, params.fn_llama2c_model); + FILE * file = fopen(params.fn_llama2c_model, "rb"); + if (!file) { + LOG("%s: Unable to open the checkpoint file %s!\n", __func__, params.fn_llama2c_model); + return 1; + } // read in the config header - if(fread(&config, sizeof(Config), 1, file) != 1) { return 1; } + if (fread(&config, sizeof(Config), 1, file) != 1) { + LOG("%s: Unable to read llama2c config from %s!\n",__func__,params.fn_llama2c_model); + return 1; + } auto shared_weights = config.vocab_size > 0; config.vocab_size = abs(config.vocab_size); // read in the Transformer weights - malloc_weights(&weights, &config, shared_weights); - if(checkpoint_init_weights(&weights, &config, file, shared_weights)) { return 1; } + alloc_weights(&weights, &config, shared_weights); + if (checkpoint_init_weights(&weights, &config, file, shared_weights)) { + LOG("%s: Unable to initialize transformer weights from %s!",__func__,params.fn_llama2c_model); + return 1; + } fclose(file); } @@ -936,15 +906,18 @@ int main(int argc, char ** argv) { load_vocab(params.fn_vocab_model, &config, &vocab); struct my_llama_model model; - model.hparams.n_vocab = config.vocab_size; //llama_n_vocab(lctx); - model.hparams.n_ctx = params.n_ctx; - model.hparams.n_embd = config.dim; //params.n_embd; - model.hparams.n_ff = config.hidden_dim; - model.hparams.n_mult = 32;//params.n_mult; - model.hparams.n_head = config.n_heads; //params.n_head; - model.hparams.n_layer = config.n_layers; //params.n_layer; - model.hparams.n_rot = std::min((uint32_t)params.n_rotmax, model.hparams.n_embd / model.hparams.n_head); + model.hparams.n_vocab = config.vocab_size; //llama_n_vocab(lctx); + model.hparams.n_ctx = params.n_ctx; + model.hparams.n_embd = config.dim; //params.n_embd; + model.hparams.n_ff = config.hidden_dim; + model.hparams.n_mult = 32;//params.n_mult; + model.hparams.n_head = config.n_heads; //params.n_head; + model.hparams.n_head_kv = config.n_kv_heads; + model.hparams.n_layer = config.n_layers; //params.n_layer; + model.hparams.n_rot = std::min((uint32_t)params.n_rotmax, model.hparams.n_embd / model.hparams.n_head); + print_params(&model.hparams); + struct ggml_init_params lcparams; lcparams.mem_size = 1024ll*1024ll*1024ll*((size_t) params.mem_model_gb); lcparams.mem_buffer = NULL; @@ -956,7 +929,7 @@ int main(int argc, char ** argv) { model.name = basename(params.fn_llama2c_model); save_as_llama_model(&vocab, &model, &weights, params.fn_llama2c_output_model); - printf("Saving llama.c model file %s in ggml format at %s\n", params.fn_llama2c_model, params.fn_llama2c_output_model); + LOG("%s: Saving llama.c model file %s in ggml format at %s\n", __func__, params.fn_llama2c_model, params.fn_llama2c_output_model); ggml_free(model.ctx); return 0; diff --git a/examples/embedding/embedding.cpp b/examples/embedding/embedding.cpp index 7b436556280fe..91b575f88dfd1 100644 --- a/examples/embedding/embedding.cpp +++ b/examples/embedding/embedding.cpp @@ -62,6 +62,8 @@ int main(int argc, char ** argv) { } params.embedding = true; + // For non-causal models, batch size must be equal to ubatch size + params.n_ubatch = params.n_batch; print_build_info(); @@ -113,13 +115,22 @@ int main(int argc, char ** argv) { // tokenize the prompts and trim std::vector> inputs; for (const auto & prompt : prompts) { - auto inp = ::llama_tokenize(ctx, prompt, true); + auto inp = ::llama_tokenize(ctx, prompt, true, false); if (inp.size() > n_batch) { - inp.resize(n_batch); + fprintf(stderr, "%s: error: number of tokens in input line (%lld) exceeds batch size (%lld), increase batch size and re-run\n", + __func__, (long long int) inp.size(), (long long int) n_batch); + return 1; } inputs.push_back(inp); } + // add eos if not present + for (auto & inp : inputs) { + if (inp.empty() || inp.back() != llama_token_eos(model)) { + inp.push_back(llama_token_eos(model)); + } + } + // tokenization stats if (params.verbose_prompt) { for (int i = 0; i < (int) inputs.size(); i++) { @@ -168,15 +179,28 @@ int main(int argc, char ** argv) { float * out = emb + p * n_embd; batch_decode(ctx, batch, out, s, n_embd); - // print first 3 embeddings - for (int j = 0; j < std::min(3, n_prompts); j++) { - fprintf(stderr, "embedding %d: ", j); - for (int i = 0; i < n_embd; i++) { - fprintf(stderr, "%f ", emb[j * n_embd + i]); + // print the first part of the embeddings or for a single prompt, the full embedding + fprintf(stdout, "\n"); + for (int j = 0; j < n_prompts; j++) { + fprintf(stdout, "embedding %d: ", j); + for (int i = 0; i < (n_prompts > 1 ? std::min(16, n_embd) : n_embd); i++) { + fprintf(stdout, "%9.6f ", emb[j * n_embd + i]); + } + fprintf(stdout, "\n"); + } + + // print cosine similarity matrix + if (n_prompts > 1) { + fprintf(stdout, "\n"); + printf("cosine similarity matrix:\n\n"); + for (int i = 0; i < n_prompts; i++) { + for (int j = 0; j < n_prompts; j++) { + float sim = llama_embd_similarity_cos(emb + i * n_embd, emb + j * n_embd, n_embd); + fprintf(stdout, "%6.2f ", sim); + } + fprintf(stdout, "\n"); } - fprintf(stderr, "\n\n"); } - fprintf(stderr, "\n"); // clean up llama_print_timings(ctx); diff --git a/examples/gbnf-validator/CMakeLists.txt b/examples/gbnf-validator/CMakeLists.txt new file mode 100644 index 0000000000000..166e3ad2ae7dd --- /dev/null +++ b/examples/gbnf-validator/CMakeLists.txt @@ -0,0 +1,5 @@ +set(TARGET gbnf-validator) +add_executable(${TARGET} gbnf-validator.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common grammar-parser llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/gbnf-validator/gbnf-validator.cpp b/examples/gbnf-validator/gbnf-validator.cpp new file mode 100644 index 0000000000000..e4c0c1689c7a4 --- /dev/null +++ b/examples/gbnf-validator/gbnf-validator.cpp @@ -0,0 +1,132 @@ +#define LLAMA_API_INTERNAL + +#include "grammar-parser.h" +#include "ggml.h" +#include "llama.h" +#include "unicode.h" + +#include +#include +#include +#include + +static bool llama_sample_grammar_string(struct llama_grammar * grammar, const std::string & input_str, size_t & error_pos, std::string & error_msg) { + auto decoded = decode_utf8(input_str, {}); + const auto & code_points = decoded.first; + + size_t pos = 0; + for (auto it = code_points.begin(), end = code_points.end() - 1; it != end; ++it) { + auto prev_stacks = grammar->stacks; + grammar->stacks = llama_grammar_accept(grammar->rules, grammar->stacks, *it); + if (grammar->stacks.empty()) { + error_pos = pos; + error_msg = "Unexpected character '" + unicode_cpt_to_utf8(*it) + "'"; + grammar->stacks = prev_stacks; + return false; + } + ++pos; + } + + for (const auto & stack : grammar->stacks) { + if (stack.empty()) { + return true; + } + } + + error_pos = pos; + error_msg = "Unexpected end of input"; + return false; +} + +static void print_error_message(const std::string & input_str, size_t error_pos, const std::string & error_msg) { + fprintf(stdout, "Input string is invalid according to the grammar.\n"); + fprintf(stdout, "Error: %s at position %zu\n", error_msg.c_str(), error_pos); + fprintf(stdout, "\n"); + fprintf(stdout, "Input string:\n"); + fprintf(stdout, "%s", input_str.substr(0, error_pos).c_str()); + if (error_pos < input_str.size()) { + fprintf(stdout, "\033[1;31m%c", input_str[error_pos]); + if (error_pos+1 < input_str.size()) { + fprintf(stdout, "\033[0;31m%s", input_str.substr(error_pos+1).c_str()); + } + fprintf(stdout, "\033[0m\n"); + } +} + +int main(int argc, char** argv) { + if (argc != 3) { + fprintf(stdout, "Usage: %s \n", argv[0]); + return 1; + } + + const std::string grammar_filename = argv[1]; + const std::string input_filename = argv[2]; + + // Read the GBNF grammar file + FILE* grammar_file = fopen(grammar_filename.c_str(), "r"); + if (!grammar_file) { + fprintf(stdout, "Failed to open grammar file: %s\n", grammar_filename.c_str()); + return 1; + } + + fseek(grammar_file, 0, SEEK_END); + size_t grammar_size = ftell(grammar_file); + fseek(grammar_file, 0, SEEK_SET); + + std::string grammar_str(grammar_size, ' '); + fread(&grammar_str[0], 1, grammar_size, grammar_file); + fclose(grammar_file); + + // Parse the GBNF grammar + auto parsed_grammar = grammar_parser::parse(grammar_str.c_str()); + + // will be empty (default) if there are parse errors + if (parsed_grammar.rules.empty()) { + fprintf(stdout, "%s: failed to parse grammar\n", __func__); + return 1; + } + + // Ensure that there is a "root" node. + if (parsed_grammar.symbol_ids.find("root") == parsed_grammar.symbol_ids.end()) { + fprintf(stdout, "%s: grammar does not contain a 'root' symbol\n", __func__); + return 1; + } + + std::vector grammar_rules(parsed_grammar.c_rules()); + + // Create the LLAMA grammar + auto grammar = llama_grammar_init( + grammar_rules.data(), + grammar_rules.size(), parsed_grammar.symbol_ids.at("root")); + + // Read the input file + FILE* input_file = fopen(input_filename.c_str(), "r"); + if (!input_file) { + fprintf(stdout, "Failed to open input file: %s\n", input_filename.c_str()); + return 1; + } + + fseek(input_file, 0, SEEK_END); + size_t input_size = ftell(input_file); + fseek(input_file, 0, SEEK_SET); + + std::string input_str(input_size, ' '); + fread(&input_str[0], 1, input_size, input_file); + fclose(input_file); + + // Validate the input string against the grammar + size_t error_pos; + std::string error_msg; + bool is_valid = llama_sample_grammar_string(grammar, input_str, error_pos, error_msg); + + if (is_valid) { + fprintf(stdout, "Input string is valid according to the grammar.\n"); + } else { + print_error_message(input_str, error_pos, error_msg); + } + + // Clean up + llama_grammar_free(grammar); + + return 0; +} diff --git a/examples/gguf-split/CMakeLists.txt b/examples/gguf-split/CMakeLists.txt new file mode 100644 index 0000000000000..828e624352c8d --- /dev/null +++ b/examples/gguf-split/CMakeLists.txt @@ -0,0 +1,5 @@ +set(TARGET gguf-split) +add_executable(${TARGET} gguf-split.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/gguf-split/README.md b/examples/gguf-split/README.md new file mode 100644 index 0000000000000..ddb1f76497aed --- /dev/null +++ b/examples/gguf-split/README.md @@ -0,0 +1,9 @@ +## GGUF split Example + +CLI to split / merge GGUF files. + +**Command line options:** + +- `--split`: split GGUF to multiple GGUF, default operation. +- `--split-max-tensors`: maximum tensors in each split: default(128) +- `--merge`: merge multiple GGUF to a single GGUF. diff --git a/examples/gguf-split/gguf-split.cpp b/examples/gguf-split/gguf-split.cpp new file mode 100644 index 0000000000000..f89c56f172812 --- /dev/null +++ b/examples/gguf-split/gguf-split.cpp @@ -0,0 +1,553 @@ +#include "llama.h" +#include "common.h" + +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include + +#if defined(_WIN32) + #include + #ifndef PATH_MAX + #define PATH_MAX MAX_PATH + #endif + #include +#endif + +enum split_operation : uint8_t { + SPLIT_OP_SPLIT, + SPLIT_OP_MERGE, +}; + +struct split_params { + split_operation operation = SPLIT_OP_SPLIT; + size_t n_bytes_split = 0; + int n_split_tensors = 128; + std::string input; + std::string output; + bool dry_run = false; +}; + +static void split_print_usage(const char * executable) { + const split_params default_params; + printf("\n"); + printf("usage: %s [options] GGUF_IN GGUF_OUT\n", executable); + printf("\n"); + printf("Apply a GGUF operation on IN to OUT."); + printf("\n"); + printf("options:\n"); + printf(" -h, --help show this help message and exit\n"); + printf(" --version show version and build info\n"); + printf(" --split split GGUF to multiple GGUF (enabled by default)\n"); + printf(" --merge merge multiple GGUF to a single GGUF\n"); + printf(" --split-max-tensors max tensors in each split (default: %d)\n", default_params.n_split_tensors); + printf(" --split-max-size N(M|G) max size per split\n"); + printf(" --dry-run only print out a split plan and exit, without writing any new files\n"); + printf("\n"); +} + +// return convert string, for example "128M" or "4G" to number of bytes +static size_t split_str_to_n_bytes(std::string str) { + size_t n_bytes = 0; + int n; + if (str.back() == 'M') { + sscanf(str.c_str(), "%d", &n); + n_bytes = n * 1024 * 1024; // megabytes + } else if (str.back() == 'G') { + sscanf(str.c_str(), "%d", &n); + n_bytes = n * 1024 * 1024 * 1024; // gigabytes + } else { + throw std::invalid_argument("error: supported units are M (megabytes) or G (gigabytes), but got: " + std::string(1, str.back())); + } + if (n <= 0) { + throw std::invalid_argument("error: size must be a positive value"); + } + return n_bytes; +} + +static void split_params_parse_ex(int argc, const char ** argv, split_params & params) { + std::string arg; + const std::string arg_prefix = "--"; + bool invalid_param = false; + + int arg_idx = 1; + for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) { + arg = argv[arg_idx]; + if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) { + std::replace(arg.begin(), arg.end(), '_', '-'); + } + + bool arg_found = false; + bool is_op_set = false; + bool is_mode_set = false; + if (arg == "-h" || arg == "--help") { + split_print_usage(argv[0]); + exit(0); + } + if (arg == "--version") { + fprintf(stderr, "version: %d (%s)\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT); + fprintf(stderr, "built with %s for %s\n", LLAMA_COMPILER, LLAMA_BUILD_TARGET); + exit(0); + } + if (arg == "--dry-run") { + arg_found = true; + params.dry_run = true; + } + + if (is_op_set) { + throw std::invalid_argument("error: either --split or --merge can be specified, but not both"); + } + if (arg == "--merge") { + arg_found = true; + is_op_set = true; + params.operation = SPLIT_OP_MERGE; + } + if (arg == "--split") { + arg_found = true; + is_op_set = true; + params.operation = SPLIT_OP_SPLIT; + } + + if (is_mode_set) { + throw std::invalid_argument("error: either --split-max-tensors or --split-max-size can be specified, but not both"); + } + if (arg == "--split-max-tensors") { + if (++arg_idx >= argc) { + invalid_param = true; + break; + } + arg_found = true; + is_mode_set = true; + params.n_split_tensors = atoi(argv[arg_idx]); + } + if (arg == "--split-max-size") { + if (++arg_idx >= argc) { + invalid_param = true; + break; + } + arg_found = true; + is_mode_set = true; + params.n_bytes_split = split_str_to_n_bytes(argv[arg_idx]); + } + + if (!arg_found) { + throw std::invalid_argument("error: unknown argument: " + arg); + } + } + + if (invalid_param) { + throw std::invalid_argument("error: invalid parameter for argument: " + arg); + } + + if (argc - arg_idx < 2) { + throw std::invalid_argument("error: bad arguments"); + } + + params.input = argv[arg_idx++]; + params.output = argv[arg_idx++]; +} + +static bool split_params_parse(int argc, const char ** argv, split_params & params) { + bool result = true; + try { + split_params_parse_ex(argc, argv, params); + } + catch (const std::invalid_argument & ex) { + fprintf(stderr, "%s\n", ex.what()); + split_print_usage(argv[0]); + exit(EXIT_FAILURE); + } + return result; +} + +static void zeros(std::ofstream & file, size_t n) { + char zero = 0; + for (size_t i = 0; i < n; ++i) { + file.write(&zero, 1); + } +} + +struct split_strategy { + const split_params params; + std::ifstream & f_input; + struct gguf_context * ctx_gguf; + struct ggml_context * ctx_meta = NULL; + const int n_tensors; + + // one ctx_out per one output file + std::vector ctx_outs; + + // temporary buffer for reading in tensor data + std::vector read_buf; + + split_strategy(const split_params & params, + std::ifstream & f_input, + struct gguf_context * ctx_gguf, + struct ggml_context * ctx_meta) : + params(params), + f_input(f_input), + ctx_gguf(ctx_gguf), + ctx_meta(ctx_meta), + n_tensors(gguf_get_n_tensors(ctx_gguf)) { + + // because we need to know list of tensors for each file in advance, we will build all the ctx_out for all output splits + int i_split = -1; + struct gguf_context * ctx_out = NULL; + auto new_ctx_out = [&]() { + i_split++; + if (ctx_out != NULL) { + if (gguf_get_n_tensors(ctx_out) == 0) { + fprintf(stderr, "error: one of splits have 0 tensors. Maybe size or tensors limit is too small\n"); + exit(EXIT_FAILURE); + } + ctx_outs.push_back(ctx_out); + } + ctx_out = gguf_init_empty(); + // Save all metadata in first split only + if (i_split == 0) { + gguf_set_kv(ctx_out, ctx_gguf); + } + gguf_set_val_u16(ctx_out, LLM_KV_SPLIT_NO_STR, i_split); + gguf_set_val_u16(ctx_out, LLM_KV_SPLIT_COUNT_STR, 0); // placeholder + gguf_set_val_i32(ctx_out, LLM_KV_SPLIT_TENSORS_COUNT_STR, n_tensors); + }; + + // initialize ctx_out for the first split + new_ctx_out(); + + // process tensors one by one + size_t curr_tensors_size = 0; // current size by counting only tensors size (without metadata) + for (int i = 0; i < n_tensors; ++i) { + struct ggml_tensor * t = ggml_get_tensor(ctx_meta, gguf_get_tensor_name(ctx_gguf, i)); + // calculate the "imaginary" size = the current size + next tensor size + size_t n_bytes = GGML_PAD(ggml_nbytes(t), GGUF_DEFAULT_ALIGNMENT); + size_t next_tensors_size = curr_tensors_size + n_bytes; + if (should_split(i, next_tensors_size)) { + new_ctx_out(); + curr_tensors_size = n_bytes; + } else { + curr_tensors_size = next_tensors_size; + } + gguf_add_tensor(ctx_out, t); + } + + // push the last ctx_out + ctx_outs.push_back(ctx_out); + + // set the correct n_split for all ctx_out + for (auto & ctx : ctx_outs) { + gguf_set_val_u16(ctx, LLM_KV_SPLIT_COUNT_STR, ctx_outs.size()); + } + } + + ~split_strategy() { + for (auto & ctx_out : ctx_outs) { + gguf_free(ctx_out); + } + } + + bool should_split(int i_tensor, size_t next_size) { + if (params.n_bytes_split > 0) { + // split by max size per file + return next_size > params.n_bytes_split; + } else { + // split by number of tensors per file + return i_tensor > 0 && i_tensor < n_tensors && i_tensor % params.n_split_tensors == 0; + } + } + + void print_info() { + printf("n_split: %ld\n", ctx_outs.size()); + int i_split = 0; + for (auto & ctx_out : ctx_outs) { + // re-calculate the real gguf size for each split (= metadata size + total size of all tensors) + size_t total_size = gguf_get_meta_size(ctx_out); + for (int i = 0; i < gguf_get_n_tensors(ctx_out); ++i) { + struct ggml_tensor * t = ggml_get_tensor(ctx_meta, gguf_get_tensor_name(ctx_out, i)); + total_size += ggml_nbytes(t); + } + total_size = total_size / 1024 / 1024; // convert to megabytes + printf("split %05d: n_tensors = %d, total_size = %ldM\n", i_split + 1, gguf_get_n_tensors(ctx_out), total_size); + i_split++; + } + } + + void write() { + int i_split = 0; + int n_split = ctx_outs.size(); + for (auto & ctx_out : ctx_outs) { + // construct file path + char split_path[PATH_MAX] = {0}; + llama_split_path(split_path, sizeof(split_path), params.output.c_str(), i_split, n_split); + + // open the output file + printf("Writing file %s ... ", split_path); + fflush(stdout); + std::ofstream fout = std::ofstream(split_path, std::ios::binary); + fout.exceptions(std::ofstream::failbit); // fail fast on write errors + + // write metadata + std::vector data(gguf_get_meta_size(ctx_out)); + gguf_get_meta_data(ctx_out, data.data()); + fout.write((const char *)data.data(), data.size()); + + // write tensors + for (int i = 0; i < gguf_get_n_tensors(ctx_out); ++i) { + // read tensor meta and prepare buffer + const char * t_name = gguf_get_tensor_name(ctx_out, i); + struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name); + auto n_bytes = ggml_nbytes(t); + read_buf.resize(n_bytes); + + // calculate offset + auto i_tensor_in = gguf_find_tensor(ctx_gguf, t_name); // idx of tensor in the input file + auto offset = gguf_get_data_offset(ctx_gguf) + gguf_get_tensor_offset(ctx_gguf, i_tensor_in); + + // copy tensor from input to output file + copy_file_to_file(f_input, fout, offset, n_bytes); + zeros(fout, GGML_PAD(n_bytes, GGUF_DEFAULT_ALIGNMENT) - n_bytes); + } + + printf("done\n"); + // close the file + fout.close(); + i_split++; + } + } + + void copy_file_to_file(std::ifstream & f_in, std::ofstream & f_out, const size_t in_offset, const size_t len) { + // TODO: detect OS and use copy_file_range() here for better performance + if (read_buf.size() < len) { + read_buf.resize(len); + } + f_in.seekg(in_offset); + f_in.read((char *)read_buf.data(), len); + f_out.write((const char *)read_buf.data(), len); + } +}; + +static void gguf_split(const split_params & split_params) { + struct ggml_context * ctx_meta = NULL; + + struct gguf_init_params params = { + /*.no_alloc = */ true, + /*.ctx = */ &ctx_meta, + }; + + std::ifstream f_input(split_params.input.c_str(), std::ios::binary); + if (!f_input.is_open()) { + fprintf(stderr, "%s: failed to open input GGUF from %s\n", __func__, split_params.input.c_str()); + exit(EXIT_FAILURE); + } + + auto * ctx_gguf = gguf_init_from_file(split_params.input.c_str(), params); + if (!ctx_gguf) { + fprintf(stderr, "%s: failed to load input GGUF from %s\n", __func__, split_params.input.c_str()); + exit(EXIT_FAILURE); + } + + // prepare the strategy + split_strategy strategy(split_params, f_input, ctx_gguf, ctx_meta); + int n_split = strategy.ctx_outs.size(); + strategy.print_info(); + + if (!split_params.dry_run) { + // write all output splits + strategy.write(); + } + + // done, clean up + gguf_free(ctx_gguf); + f_input.close(); + + fprintf(stderr, "%s: %d gguf split written with a total of %d tensors.\n", + __func__, n_split, strategy.n_tensors); +} + +static void gguf_merge(const split_params & split_params) { + fprintf(stderr, "%s: %s -> %s\n", + __func__, split_params.input.c_str(), + split_params.output.c_str()); + int n_split = 1; + int total_tensors = 0; + + auto * ctx_out = gguf_init_empty(); + std::ofstream fout(split_params.output.c_str(), std::ios::binary); + fout.exceptions(std::ofstream::failbit); // fail fast on write errors + + std::vector read_data; + std::vector ctx_metas; + std::vector ctx_ggufs; + + char split_path[PATH_MAX] = {0}; + strncpy(split_path, split_params.input.c_str(), sizeof(split_path) - 1); + char split_prefix[PATH_MAX] = {0}; + + // First pass to find KV and tensors metadata + for (int i_split = 0; i_split < n_split; i_split++) { + struct ggml_context * ctx_meta = NULL; + + struct gguf_init_params params = { + /*.no_alloc = */ true, + /*.ctx = */ &ctx_meta, + }; + + if (i_split > 0) { + llama_split_path(split_path, sizeof(split_path), split_prefix, i_split, n_split); + } + fprintf(stderr, "%s: reading metadata %s ...", __func__, split_path); + + auto * ctx_gguf = gguf_init_from_file(split_path, params); + if (!ctx_gguf) { + fprintf(stderr, "\n%s: failed to load input GGUF from %s\n", __func__, split_params.input.c_str()); + exit(EXIT_FAILURE); + } + ctx_ggufs.push_back(ctx_gguf); + ctx_metas.push_back(ctx_meta); + + if (i_split == 0) { + auto key_n_split = gguf_find_key(ctx_gguf, LLM_KV_SPLIT_COUNT_STR); + if (key_n_split < 0) { + fprintf(stderr, + "\n%s: input file does not contain %s metadata\n", + __func__, + LLM_KV_SPLIT_COUNT_STR); + gguf_free(ctx_gguf); + ggml_free(ctx_meta); + gguf_free(ctx_out); + fout.close(); + exit(EXIT_FAILURE); + } + + n_split = gguf_get_val_u16(ctx_gguf, key_n_split); + if (n_split < 1) { + fprintf(stderr, + "\n%s: input file does not contain a valid split count %d\n", + __func__, + n_split); + gguf_free(ctx_gguf); + ggml_free(ctx_meta); + gguf_free(ctx_out); + fout.close(); + exit(EXIT_FAILURE); + } + + // Verify the file naming and extract split_prefix + if (!llama_split_prefix(split_prefix, sizeof (split_prefix), split_path, i_split, n_split)) { + fprintf(stderr, "\n%s: unexpected input file name: %s" + " i_split=%d" + " n_split=%d\n", __func__, + split_path, i_split, n_split); + gguf_free(ctx_gguf); + ggml_free(ctx_meta); + gguf_free(ctx_out); + fout.close(); + exit(EXIT_FAILURE); + } + + // Do not trigger merge if we try to merge again the output + gguf_set_val_u16(ctx_gguf, LLM_KV_SPLIT_COUNT_STR, 0); + + // Set metadata from the first split + gguf_set_kv(ctx_out, ctx_gguf); + } + + auto n_tensors = gguf_get_n_tensors(ctx_gguf); + for (int i_tensor = 0; i_tensor < n_tensors; i_tensor++) { + const char * t_name = gguf_get_tensor_name(ctx_gguf, i_tensor); + struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name); + gguf_add_tensor(ctx_out, t); + } + total_tensors += n_tensors; + + fprintf(stderr, "\033[3Ddone\n"); + } + + // placeholder for the meta data + { + auto meta_size = gguf_get_meta_size(ctx_out); + ::zeros(fout, meta_size); + } + + // Write tensors data + for (int i_split = 0; i_split < n_split; i_split++) { + llama_split_path(split_path, sizeof(split_path), split_prefix, i_split, n_split); + std::ifstream f_input(split_path, std::ios::binary); + if (!f_input.is_open()) { + fprintf(stderr, "%s: failed to open input GGUF from %s\n", __func__, split_path); + for (uint32_t i = 0; i < ctx_ggufs.size(); i++) { + gguf_free(ctx_ggufs[i]); + ggml_free(ctx_metas[i]); + } + gguf_free(ctx_out); + fout.close(); + exit(EXIT_FAILURE); + } + fprintf(stderr, "%s: writing tensors %s ...", __func__, split_path); + + auto * ctx_gguf = ctx_ggufs[i_split]; + auto * ctx_meta = ctx_metas[i_split]; + + auto n_tensors = gguf_get_n_tensors(ctx_gguf); + for (int i_tensor = 0; i_tensor < n_tensors; i_tensor++) { + const char * t_name = gguf_get_tensor_name(ctx_gguf, i_tensor); + struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name); + + auto n_bytes = ggml_nbytes(t); + + if (read_data.size() < n_bytes) { + read_data.resize(n_bytes); + } + + auto offset = gguf_get_data_offset(ctx_gguf) + gguf_get_tensor_offset(ctx_gguf, i_tensor); + f_input.seekg(offset); + f_input.read((char *)read_data.data(), n_bytes); + + // write tensor data + padding + fout.write((const char *)read_data.data(), n_bytes); + zeros(fout, GGML_PAD(n_bytes, GGUF_DEFAULT_ALIGNMENT) - n_bytes); + } + + gguf_free(ctx_gguf); + ggml_free(ctx_meta); + f_input.close(); + fprintf(stderr, "\033[3Ddone\n"); + } + + { + // go back to beginning of file and write the updated metadata + fout.seekp(0); + std::vector data(gguf_get_meta_size(ctx_out)); + gguf_get_meta_data(ctx_out, data.data()); + fout.write((const char *)data.data(), data.size()); + + fout.close(); + gguf_free(ctx_out); + } + + fprintf(stderr, "%s: %s merged from %d split with %d tensors.\n", + __func__, split_params.output.c_str(), n_split, total_tensors); +} + +int main(int argc, const char ** argv) { + split_params params; + split_params_parse(argc, argv, params); + + switch (params.operation) { + case SPLIT_OP_SPLIT: gguf_split(params); + break; + case SPLIT_OP_MERGE: gguf_merge(params); + break; + default: split_print_usage(argv[0]); + exit(EXIT_FAILURE); + } + + return 0; +} diff --git a/examples/gguf/gguf.cpp b/examples/gguf/gguf.cpp index e67be4fb2995e..5444503a5d218 100644 --- a/examples/gguf/gguf.cpp +++ b/examples/gguf/gguf.cpp @@ -211,6 +211,7 @@ static bool gguf_ex_read_1(const std::string & fname) { for (int j = 0; j < ggml_nelements(cur); ++j) { if (data[j] != 100 + i) { fprintf(stderr, "%s: tensor[%d]: data[%d] = %f\n", __func__, i, j, data[j]); + gguf_free(ctx); return false; } } diff --git a/examples/gritlm/README.md b/examples/gritlm/README.md new file mode 100644 index 0000000000000..64cc192040c43 --- /dev/null +++ b/examples/gritlm/README.md @@ -0,0 +1,62 @@ +## Generative Representational Instruction Tuning (GRIT) Example +[gritlm] a model which can generate embeddings as well as "normal" text +generation depending on the instructions in the prompt. + +* Paper: https://arxiv.org/pdf/2402.09906.pdf + +### Retrieval-Augmented Generation (RAG) use case +One use case for `gritlm` is to use it with RAG. If we recall how RAG works is +that we take documents that we want to use as context, to ground the large +language model (LLM), and we create token embeddings for them. We then store +these token embeddings in a vector database. + +When we perform a query, prompt the LLM, we will first create token embeddings +for the query and then search the vector database to retrieve the most +similar vectors, and return those documents so they can be passed to the LLM as +context. Then the query and the context will be passed to the LLM which will +have to _again_ create token embeddings for the query. But because gritlm is used +the first query can be cached and the second query tokenization generation does +not have to be performed at all. + +### Running the example +Download a Grit model: +```console +$ scripts/hf.sh --repo cohesionet/GritLM-7B_gguf --file gritlm-7b_q4_1.gguf +``` + +Run the example using the downloaded model: +```console +$ ./gritlm -m gritlm-7b_q4_1.gguf + +Cosine similarity between "Bitcoin: A Peer-to-Peer Electronic Cash System" and "A purely peer-to-peer version of electronic cash w" is: 0.605 +Cosine similarity between "Bitcoin: A Peer-to-Peer Electronic Cash System" and "All text-based language problems can be reduced to" is: 0.103 +Cosine similarity between "Generative Representational Instruction Tuning" and "A purely peer-to-peer version of electronic cash w" is: 0.112 +Cosine similarity between "Generative Representational Instruction Tuning" and "All text-based language problems can be reduced to" is: 0.547 + +Oh, brave adventurer, who dared to climb +The lofty peak of Mt. Fuji in the night, +When shadows lurk and ghosts do roam, +And darkness reigns, a fearsome sight. + +Thou didst set out, with heart aglow, +To conquer this mountain, so high, +And reach the summit, where the stars do glow, +And the moon shines bright, up in the sky. + +Through the mist and fog, thou didst press on, +With steadfast courage, and a steadfast will, +Through the darkness, thou didst not be gone, +But didst climb on, with a steadfast skill. + +At last, thou didst reach the summit's crest, +And gazed upon the world below, +And saw the beauty of the night's best, +And felt the peace, that only nature knows. + +Oh, brave adventurer, who dared to climb +The lofty peak of Mt. Fuji in the night, +Thou art a hero, in the eyes of all, +For thou didst conquer this mountain, so bright. +``` + +[gritlm]: https://github.com/ContextualAI/gritlm diff --git a/examples/gritlm/gritlm.cpp b/examples/gritlm/gritlm.cpp index 3d4b085d69b6f..52fd719b38ee5 100644 --- a/examples/gritlm/gritlm.cpp +++ b/examples/gritlm/gritlm.cpp @@ -6,22 +6,6 @@ // #define GRIT_DEBUG -static float dot_product(const std::vector & v1, const std::vector & v2) { - float dot = 0.0f; - for (uint64_t i = 0; i < v1.size(); ++i) { - dot += v1[i] * v2[i]; - } - return dot; -} - -static float norm(const std::vector & v) { - return std::sqrt(dot_product(v, v)); -} - -static float cosine_similarity(const std::vector & v1, const std::vector & v2) { - return dot_product(v1, v2) / (norm(v1) * norm(v2)); -} - static std::vector> encode(llama_context * ctx, const std::vector & sentences, const std::string & instruction) { std::vector> result; @@ -203,10 +187,12 @@ int main(int argc, char * argv[]) { const std::vector> d_rep = encode(ctx, documents, gritlm_instruction("")); const std::vector> q_rep = encode(ctx, queries, gritlm_instruction(instruction)); - const float cosine_sim_q0_d0 = cosine_similarity(q_rep[0], d_rep[0]); - const float cosine_sim_q0_d1 = cosine_similarity(q_rep[0], d_rep[1]); - const float cosine_sim_q1_d0 = cosine_similarity(q_rep[1], d_rep[0]); - const float cosine_sim_q1_d1 = cosine_similarity(q_rep[1], d_rep[1]); + const int n_embd = llama_n_embd(mdl); + + const float cosine_sim_q0_d0 = llama_embd_similarity_cos(q_rep[0].data(), d_rep[0].data(), n_embd); + const float cosine_sim_q0_d1 = llama_embd_similarity_cos(q_rep[0].data(), d_rep[1].data(), n_embd); + const float cosine_sim_q1_d0 = llama_embd_similarity_cos(q_rep[1].data(), d_rep[0].data(), n_embd); + const float cosine_sim_q1_d1 = llama_embd_similarity_cos(q_rep[1].data(), d_rep[1].data(), n_embd); std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[0].c_str(), documents[0].c_str(), cosine_sim_q0_d0); std::printf("Cosine similarity between \"%.50s\" and \"%.50s\" is: %.3f\n", queries[0].c_str(), documents[1].c_str(), cosine_sim_q0_d1); diff --git a/examples/imatrix/README.md b/examples/imatrix/README.md index 578e8fc27177a..458c01b8751f1 100644 --- a/examples/imatrix/README.md +++ b/examples/imatrix/README.md @@ -22,7 +22,7 @@ For faster computation, make sure to use GPU offloading via the `-ngl` argument ## Example ```bash -LLAMA_CUBLAS=1 make -j +LLAMA_CUDA=1 make -j # generate importance matrix (imatrix.dat) ./imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99 diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index ec108a5843568..2edd56da86438 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -51,11 +51,31 @@ class IMatrixCollector { void keep_imatrix(int ncall) const; }; +// remove any prefix and suffixes from the name +// CUDA0#blk.0.attn_k.weight#0 => blk.0.attn_k.weight +static std::string filter_tensor_name(const char * name) { + std::string wname; + const char * p = strchr(name, '#'); + if (p != NULL) { + p = p + 1; + const char * q = strchr(p, '#'); + if (q != NULL) { + wname = std::string(p, q - p); + } else { + wname = p; + } + } else { + wname = name; + } + return wname; +} + bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * user_data) { GGML_UNUSED(user_data); const struct ggml_tensor * src0 = t->src[0]; const struct ggml_tensor * src1 = t->src[1]; + std::string wname = filter_tensor_name(src0->name); // when ask is true, the scheduler wants to know if we are interested in data from this tensor // if we return true, a follow-up call will be made with ask=false in which we can do the actual collection @@ -63,7 +83,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * if (t->op == GGML_OP_MUL_MAT_ID) return true; // collect all indirect matrix multiplications if (t->op != GGML_OP_MUL_MAT) return false; if (src1->ne[1] < 16 || src1->type != GGML_TYPE_F32) return false; - if (!(strncmp(src0->name, "blk.", 4) == 0 || (m_params.collect_output_weight && strcmp(src0->name, "output.weight") == 0))) return false; + if (!(wname.substr(0, 4) == "blk." || (m_params.collect_output_weight && wname == "output.weight"))) return false; return true; } @@ -79,36 +99,40 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * const float * data = is_host ? (const float *) src1->data : m_src1_data.data(); + // this has been adapted to the new format of storing merged experts in a single 3d tensor + // ref: https://github.com/ggerganov/llama.cpp/pull/6387 if (t->op == GGML_OP_MUL_MAT_ID) { const int idx = ((int32_t *) t->op_params)[0]; - const int n_as = ((int32_t *) t->op_params)[1]; + const ggml_tensor * ids = t->src[2]; + const int n_as = src0->ne[2]; + + // the top-k selected expert ids are stored in the ids tensor + // for simplicity, always copy ids to host, because it is small + // take into account that ids is not contiguous! + GGML_ASSERT(ids->ne[1] == src1->ne[1]); + GGML_ASSERT(n_as*ggml_nrows(ids)*sizeof(int) == GGML_PAD(ggml_nbytes(ids), n_as*sizeof(int))); + m_ids.resize(ggml_nbytes(ids)/sizeof(int)); + ggml_backend_tensor_get(ids, m_ids.data(), 0, ggml_nbytes(ids)); - // the top-k selected expert ids are stored in the src0 tensor - // for simplicity, always copy src0 to host, because it is small - // take into account that src0 is not contiguous! - GGML_ASSERT(src0->ne[1] == src1->ne[1]); - GGML_ASSERT(n_as*ggml_nrows(src0)*sizeof(int) == GGML_PAD(ggml_nbytes(src0), n_as*sizeof(int))); - m_ids.resize(ggml_nbytes(src0)/sizeof(int)); - ggml_backend_tensor_get(src0, m_ids.data(), 0, ggml_nbytes(src0)); + auto & e = m_stats[wname]; + + ++e.ncall; + // NOTE: since we select top-k experts, the number of calls for the expert tensors will be k times larger + // using the following line, we can correct for that if needed by replacing the line above with: + //if (idx == t->src[0]->ne[0] - 1) ++e.ncall; // loop over all possible experts, regardless if they are used or not in the batch - // this is necessary to guarantee equal number of "ncall" for each tensor for (int ex = 0; ex < n_as; ++ex) { - src0 = t->src[2 + ex]; - auto& e = m_stats[src0->name]; + size_t e_start = ex*src1->ne[0]; if (e.values.empty()) { - e.values.resize(src1->ne[0], 0); + e.values.resize(src1->ne[0]*n_as, 0); } - else if (e.values.size() != (size_t)src1->ne[0]) { - fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", src0->name, (int)e.values.size(), (int)src1->ne[0]); + else if (e.values.size() != (size_t)src1->ne[0]*n_as) { + fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]*n_as); exit(1); //GGML_ASSERT(false); } - // NOTE: since we select top-k experts, the number of calls for the expert tensors will be k times larger - // using the following line, we can correct for that if needed - //if (idx == t->src[0]->ne[0] - 1) ++e.ncall; - ++e.ncall; if (m_params.verbosity > 1) { - printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, src0->name, ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); + printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); } for (int row = 0; row < (int)src1->ne[1]; ++row) { const int excur = m_ids[row*n_as + idx]; @@ -116,7 +140,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * if (excur != ex) continue; const float * x = data + row * src1->ne[0]; for (int j = 0; j < (int)src1->ne[0]; ++j) { - e.values[j] += x[j]*x[j]; + e.values[e_start + j] += x[j]*x[j]; } } if (e.ncall > m_last_call) { @@ -130,17 +154,17 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * } } } else { - auto& e = m_stats[src0->name]; + auto& e = m_stats[wname]; if (e.values.empty()) { e.values.resize(src1->ne[0], 0); } else if (e.values.size() != (size_t)src1->ne[0]) { - fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", src0->name, (int)e.values.size(), (int)src1->ne[0]); + fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]); exit(1); //GGML_ASSERT(false); } ++e.ncall; if (m_params.verbosity > 1) { - printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, src0->name, ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); + printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); } for (int row = 0; row < (int)src1->ne[1]; ++row) { const float * x = data + row * src1->ne[0]; @@ -404,6 +428,7 @@ static bool compute_imatrix(llama_context * ctx, const gpt_params & params, bool tokens[batch_start] = llama_token_bos(llama_get_model(ctx)); } + // TODO: use batch.logits to save computations instead of relying on logits_all == true if (llama_decode(ctx, llama_batch_get_one(tokens.data() + batch_start, batch_size, j * n_batch, 0))) { fprintf(stderr, "%s : failed to eval\n", __func__); return false; diff --git a/examples/json-schema-pydantic-example.py b/examples/json-schema-pydantic-example.py new file mode 100644 index 0000000000000..69ebfd4093824 --- /dev/null +++ b/examples/json-schema-pydantic-example.py @@ -0,0 +1,74 @@ +# Usage: +#! ./server -m some-model.gguf & +#! pip install pydantic +#! python json-schema-pydantic-example.py + +from pydantic import BaseModel, TypeAdapter +from annotated_types import MinLen +from typing import Annotated, List, Optional +import json, requests + +if True: + + def create_completion(*, response_model=None, endpoint="http://localhost:8080/v1/chat/completions", messages, **kwargs): + ''' + Creates a chat completion using an OpenAI-compatible endpoint w/ JSON schema support + (llama.cpp server, llama-cpp-python, Anyscale / Together...) + + The response_model param takes a type (+ supports Pydantic) and behaves just as w/ Instructor (see below) + ''' + if response_model: + type_adapter = TypeAdapter(response_model) + schema = type_adapter.json_schema() + messages = [{ + "role": "system", + "content": f"You respond in JSON format with the following schema: {json.dumps(schema, indent=2)}" + }] + messages + response_format={"type": "json_object", "schema": schema} + + data = requests.post(endpoint, headers={"Content-Type": "application/json"}, + json=dict(messages=messages, response_format=response_format, **kwargs)).json() + if 'error' in data: + raise Exception(data['error']['message']) + + content = data["choices"][0]["message"]["content"] + return type_adapter.validate_json(content) if type_adapter else content + +else: + + # This alternative branch uses Instructor + OpenAI client lib. + # Instructor support streamed iterable responses, retry & more. + # (see https://python.useinstructor.com/) + #! pip install instructor openai + import instructor, openai + client = instructor.patch( + openai.OpenAI(api_key="123", base_url="http://localhost:8080"), + mode=instructor.Mode.JSON_SCHEMA) + create_completion = client.chat.completions.create + + +if __name__ == '__main__': + + class QAPair(BaseModel): + question: str + concise_answer: str + justification: str + + class PyramidalSummary(BaseModel): + title: str + summary: str + question_answers: Annotated[List[QAPair], MinLen(2)] + sub_sections: Optional[Annotated[List['PyramidalSummary'], MinLen(2)]] + + print("# Summary\n", create_completion( + model="...", + response_model=PyramidalSummary, + messages=[{ + "role": "user", + "content": f""" + You are a highly efficient corporate document summarizer. + Create a pyramidal summary of an imaginary internal document about our company processes + (starting high-level, going down to each sub sections). + Keep questions short, and answers even shorter (trivia / quizz style). + """ + }])) diff --git a/examples/json-schema-to-grammar.py b/examples/json-schema-to-grammar.py index 6a977f031662e..91dd734cc26ff 100755 --- a/examples/json-schema-to-grammar.py +++ b/examples/json-schema-to-grammar.py @@ -1,8 +1,10 @@ #!/usr/bin/env python3 import argparse +import itertools import json import re import sys +from typing import Any, Dict, List, Set, Tuple, Union # whitespace is constrained to a single space char to prevent model "running away" in # whitespace. Also maybe improves generation quality? @@ -12,26 +14,54 @@ 'boolean': '("true" | "false") space', 'number': '("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? space', 'integer': '("-"? ([0-9] | [1-9] [0-9]*)) space', + 'value' : 'object | array | string | number | boolean', + 'object' : '"{" space ( string ":" space value ("," space string ":" space value)* )? "}" space', + 'array' : '"[" space ( value ("," space value)* )? "]" space', + 'uuid' : '"\\"" ' + ' "-" '.join('[0-9a-fA-F]' * n for n in [8, 4, 4, 4, 12]) + ' "\\"" space', 'string': r''' "\"" ( [^"\\] | "\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) - )* "\"" space ''', + )* "\"" space''', 'null': '"null" space', } +OBJECT_RULE_NAMES = ['object', 'array', 'string', 'number', 'boolean', 'null', 'value'] + +# TODO: support "uri", "email" string formats +DATE_RULES = { + 'date' : '[0-9] [0-9] [0-9] [0-9] "-" ( "0" [1-9] | "1" [0-2] ) "-" ( \"0\" [1-9] | [1-2] [0-9] | "3" [0-1] )', + 'time' : '([01] [0-9] | "2" [0-3]) ":" [0-5] [0-9] ":" [0-5] [0-9] ( "." [0-9] [0-9] [0-9] )? ( "Z" | ( "+" | "-" ) ( [01] [0-9] | "2" [0-3] ) ":" [0-5] [0-9] )', + 'date-time': 'date "T" time', + 'date-string': '"\\"" date "\\"" space', + 'time-string': '"\\"" time "\\"" space', + 'date-time-string': '"\\"" date-time "\\"" space', +} + +RESERVED_NAMES = set(["root", *PRIMITIVE_RULES.keys(), *DATE_RULES.keys()]) INVALID_RULE_CHARS_RE = re.compile(r'[^a-zA-Z0-9-]+') GRAMMAR_LITERAL_ESCAPE_RE = re.compile(r'[\r\n"]') -GRAMMAR_LITERAL_ESCAPES = {'\r': '\\r', '\n': '\\n', '"': '\\"'} +GRAMMAR_RANGE_LITERAL_ESCAPE_RE = re.compile(r'[\r\n"\]\-\\]') +GRAMMAR_LITERAL_ESCAPES = {'\r': '\\r', '\n': '\\n', '"': '\\"', '-': '\\-', ']': '\\]'} +NON_LITERAL_SET = set('|.()[]{}*+?') +ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = set('[]()|{}*+?') + +DATE_PATTERN = '[0-9]{4}-(0[1-9]|1[0-2])-([0-2][0-9]|3[0-1])' +TIME_PATTERN = '([01][0-9]|2[0-3])(:[0-5][0-9]){2}(\\.[0-9]{1,3})?(Z|[+-](([01][0-9]|2[0-3]):[0-5][0-9]))' # Cap millisecond precision w/ 3 digits class SchemaConverter: - def __init__(self, prop_order): + def __init__(self, *, prop_order, allow_fetch, dotall, raw_pattern): self._prop_order = prop_order + self._allow_fetch = allow_fetch + self._dotall = dotall + self._raw_pattern = raw_pattern self._rules = {'space': SPACE_RULE} + self._refs = {} + self._refs_being_resolved = set() def _format_literal(self, literal): escaped = GRAMMAR_LITERAL_ESCAPE_RE.sub( - lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)), json.dumps(literal) + lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)), literal ) return f'"{escaped}"' @@ -41,78 +71,420 @@ def _add_rule(self, name, rule): key = esc_name else: i = 0 - while f'{esc_name}{i}' in self._rules: + while f'{esc_name}{i}' in self._rules and self._rules[f'{esc_name}{i}'] != rule: i += 1 key = f'{esc_name}{i}' self._rules[key] = rule return key + def resolve_refs(self, schema: dict, url: str): + ''' + Resolves all $ref fields in the given schema, fetching any remote schemas, + replacing $ref with absolute reference URL and populating self._refs with the + respective referenced (sub)schema dictionaries. + ''' + def visit(n: dict): + if isinstance(n, list): + return [visit(x) for x in n] + elif isinstance(n, dict): + ref = n.get('$ref') + if ref is not None and ref not in self._refs: + if ref.startswith('https://'): + assert self._allow_fetch, 'Fetching remote schemas is not allowed (use --allow-fetch for force)' + import requests + + frag_split = ref.split('#') + base_url = frag_split[0] + + target = self._refs.get(base_url) + if target is None: + target = self.resolve_refs(requests.get(ref).json(), base_url) + self._refs[base_url] = target + + if len(frag_split) == 1 or frag_split[-1] == '': + return target + elif ref.startswith('#/'): + target = schema + ref = f'{url}{ref}' + n['$ref'] = ref + else: + raise ValueError(f'Unsupported ref {ref}') + + for sel in ref.split('#')[-1].split('/')[1:]: + assert target is not None and sel in target, f'Error resolving ref {ref}: {sel} not in {target}' + target = target[sel] + + self._refs[ref] = target + else: + for v in n.values(): + visit(v) + + return n + return visit(schema) + + def _generate_union_rule(self, name, alt_schemas): + return ' | '.join(( + self.visit(alt_schema, f'{name}{"-" if name else "alternative-"}{i}') + for i, alt_schema in enumerate(alt_schemas) + )) + + def _visit_pattern(self, pattern, name): + ''' + Transforms a regular expression pattern into a GBNF rule. + + Input: https://json-schema.org/understanding-json-schema/reference/regular_expressions + Output: https://github.com/ggerganov/llama.cpp/blob/master/grammars/README.md + + Unsupported features: negative/positive lookaheads, greedy/non-greedy modifiers. + + Mostly a 1:1 translation, except for {x} / {x,} / {x,y} quantifiers for which + we define sub-rules to keep the output lean. + ''' + + assert pattern.startswith('^') and pattern.endswith('$'), 'Pattern must start with "^" and end with "$"' + pattern = pattern[1:-1] + sub_rule_ids = {} + + i = 0 + length = len(pattern) + + def to_rule(s: Tuple[str, bool]) -> str: + (txt, is_literal) = s + return "\"" + txt + "\"" if is_literal else txt + + def transform() -> Tuple[str, bool]: + ''' + Parse a unit at index i (advancing it), and return its string representation + whether it's a literal. + ''' + nonlocal i + nonlocal pattern + nonlocal sub_rule_ids + + start = i + # For each component of this sequence, store its string representation and whether it's a literal. + # We only need a flat structure here to apply repetition operators to the last item, and + # to merge literals at the and (we're parsing grouped ( sequences ) recursively and don't treat '|' specially + # (GBNF's syntax is luckily very close to regular expressions!) + seq: list[Tuple[str, bool]] = [] + + def get_dot(): + if self._dotall: + rule = '[\\U00000000-\\U0010FFFF]' + else: + # Accept any character... except \n and \r line break chars (\x0A and \xOD) + rule = '[\\U00000000-\\x09\\x0B\\x0C\\x0E-\\U0010FFFF]' + return self._add_rule(f'dot', rule) + + def join_seq(): + nonlocal seq + ret = [] + for is_literal, g in itertools.groupby(seq, lambda x: x[1]): + if is_literal: + ret.append((''.join(x[0] for x in g), True)) + else: + ret.extend(g) + if len(ret) == 1: + return ret[0] + return (' '.join(to_rule(x) for x in seq), False) + + while i < length: + c = pattern[i] + if c == '.': + seq.append((get_dot(), False)) + i += 1 + elif c == '(': + i += 1 + if i < length: + assert pattern[i] != '?', f'Unsupported pattern syntax "{pattern[i]}" at index {i} of /{pattern}/' + seq.append((f'({to_rule(transform())})', False)) + elif c == ')': + i += 1 + assert start > 0 and pattern[start-1] == '(', f'Unbalanced parentheses; start = {start}, i = {i}, pattern = {pattern}' + return join_seq() + elif c == '[': + square_brackets = c + i += 1 + while i < length and pattern[i] != ']': + if pattern[i] == '\\': + square_brackets += pattern[i:i+2] + i += 2 + else: + square_brackets += pattern[i] + i += 1 + assert i < length, f'Unbalanced square brackets; start = {start}, i = {i}, pattern = {pattern}' + square_brackets += ']' + i += 1 + seq.append((square_brackets, False)) + elif c == '|': + seq.append(('|', False)) + i += 1 + elif c in ('*', '+', '?'): + seq[-1] = (to_rule(seq[-1]) + c, False) + i += 1 + elif c == '{': + curly_brackets = c + i += 1 + while i < length and pattern[i] != '}': + curly_brackets += pattern[i] + i += 1 + assert i < length, f'Unbalanced curly brackets; start = {start}, i = {i}, pattern = {pattern}' + curly_brackets += '}' + i += 1 + nums = [s.strip() for s in curly_brackets[1:-1].split(',')] + min_times = 0 + max_times = None + try: + if len(nums) == 1: + min_times = int(nums[0]) + max_times = min_times + else: + assert len(nums) == 2 + min_times = int(nums[0]) if nums[0] else 0 + max_times = int(nums[1]) if nums[1] else None + except ValueError: + raise ValueError(f'Invalid quantifier {curly_brackets} in /{pattern}/') + + (sub, sub_is_literal) = seq[-1] + + if min_times == 0 and max_times is None: + seq[-1] = (f'{sub}*', False) + elif min_times == 0 and max_times == 1: + seq[-1] = (f'{sub}?', False) + elif min_times == 1 and max_times is None: + seq[-1] = (f'{sub}+', False) + else: + if not sub_is_literal: + id = sub_rule_ids.get(sub) + if id is None: + id = self._add_rule(f'{name}-{len(sub_rule_ids) + 1}', sub) + sub_rule_ids[sub] = id + sub = id + + seq[-1] = ( + ' '.join( + ([f'"{sub[1:-1] * min_times}"'] if sub_is_literal else [sub] * min_times) + + ([f'{sub}?'] * (max_times - min_times) if max_times is not None else [f'{sub}*'])), + False + ) + else: + literal = '' + while i < length: + if pattern[i] == '\\' and i < length - 1: + next = pattern[i + 1] + if next in ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS: + i += 1 + literal += pattern[i] + i += 1 + else: + literal += pattern[i:i+2] + i += 2 + elif pattern[i] == '"' and not self._raw_pattern: + literal += '\\"' + i += 1 + elif pattern[i] not in NON_LITERAL_SET and \ + (i == length - 1 or literal == '' or pattern[i+1] == '.' or pattern[i+1] not in NON_LITERAL_SET): + literal += pattern[i] + i += 1 + else: + break + if literal: + seq.append((literal, True)) + + return join_seq() + + return self._add_rule( + name, + to_rule(transform()) if self._raw_pattern \ + else "\"\\\"\" " + to_rule(transform()) + " \"\\\"\" space") + + + def _resolve_ref(self, ref): + ref_name = ref.split('/')[-1] + if ref_name not in self._rules and ref not in self._refs_being_resolved: + self._refs_being_resolved.add(ref) + resolved = self._refs[ref] + ref_name = self.visit(resolved, ref_name) + self._refs_being_resolved.remove(ref) + return ref_name + + def _generate_constant_rule(self, value): + return self._format_literal(json.dumps(value)) + def visit(self, schema, name): schema_type = schema.get('type') - rule_name = name or 'root' + schema_format = schema.get('format') + rule_name = name + '-' if name in RESERVED_NAMES else name or 'root' - if 'oneOf' in schema or 'anyOf' in schema: - rule = ' | '.join(( - self.visit(alt_schema, f'{name}{"-" if name else ""}{i}') - for i, alt_schema in enumerate(schema.get('oneOf') or schema['anyOf']) - )) - return self._add_rule(rule_name, rule) + if (ref := schema.get('$ref')) is not None: + return self._add_rule(rule_name, self._resolve_ref(ref)) + + elif 'oneOf' in schema or 'anyOf' in schema: + return self._add_rule(rule_name, self._generate_union_rule(name, schema.get('oneOf') or schema['anyOf'])) + + elif isinstance(schema_type, list): + return self._add_rule(rule_name, self._generate_union_rule(name, [{'type': t} for t in schema_type])) elif 'const' in schema: - return self._add_rule(rule_name, self._format_literal(schema['const'])) + return self._add_rule(rule_name, self._generate_constant_rule(schema['const'])) elif 'enum' in schema: - rule = ' | '.join((self._format_literal(v) for v in schema['enum'])) + rule = ' | '.join((self._generate_constant_rule(v) for v in schema['enum'])) return self._add_rule(rule_name, rule) - elif schema_type == 'object' and 'properties' in schema: - # TODO: `required` keyword - prop_order = self._prop_order - prop_pairs = sorted( - schema['properties'].items(), - # sort by position in prop_order (if specified) then by key - key=lambda kv: (prop_order.get(kv[0], len(prop_order)), kv[0]), - ) + elif schema_type in (None, 'object') and \ + ('properties' in schema or \ + ('additionalProperties' in schema and schema['additionalProperties'] is not True)): + required = set(schema.get('required', [])) + properties = list(schema.get('properties', {}).items()) + return self._add_rule(rule_name, self._build_object_rule(properties, required, name, schema.get('additionalProperties'))) - rule = '"{" space' - for i, (prop_name, prop_schema) in enumerate(prop_pairs): - prop_rule_name = self.visit(prop_schema, f'{name}{"-" if name else ""}{prop_name}') - if i > 0: - rule += ' "," space' - rule += fr' {self._format_literal(prop_name)} space ":" space {prop_rule_name}' - rule += ' "}" space' + elif schema_type in (None, 'object') and 'allOf' in schema: + required = set() + properties = [] + hybrid_name = name + def add_component(comp_schema, is_required): + if (ref := comp_schema.get('$ref')) is not None: + comp_schema = self._refs[ref] - return self._add_rule(rule_name, rule) + if 'properties' in comp_schema: + for prop_name, prop_schema in comp_schema['properties'].items(): + properties.append((prop_name, prop_schema)) + if is_required: + required.add(prop_name) - elif schema_type == 'array' and 'items' in schema: - # TODO `prefixItems` keyword - item_rule_name = self.visit(schema['items'], f'{name}{"-" if name else ""}item') - list_item_operator = f'("," space {item_rule_name})' - successive_items = "" - min_items = schema.get("minItems", 0) - if min_items > 0: - first_item = f"({item_rule_name})" - successive_items = list_item_operator * (min_items - 1) - min_items -= 1 - else: - first_item = f"({item_rule_name})?" - max_items = schema.get("maxItems") - if max_items is not None and max_items > min_items: - successive_items += (list_item_operator + "?") * (max_items - min_items - 1) + for t in schema['allOf']: + if 'anyOf' in t: + for tt in t['anyOf']: + add_component(tt, is_required=False) + else: + add_component(t, is_required=True) + + return self._add_rule(rule_name, self._build_object_rule(properties, required, hybrid_name, additional_properties=[])) + + elif schema_type in (None, 'array') and ('items' in schema or 'prefixItems' in schema): + items = schema.get('items') or schema['prefixItems'] + if isinstance(items, list): + return self._add_rule( + rule_name, + '"[" space ' + + ' "," space '.join( + self.visit(item, f'{name}{"-" if name else ""}tuple-{i}') + for i, item in enumerate(items)) + + ' "]" space') else: - successive_items += list_item_operator + "*" - rule = f'"[" space {first_item} {successive_items} "]" space' - return self._add_rule(rule_name, rule) + item_rule_name = self.visit(items, f'{name}{"-" if name else ""}item') + list_item_operator = f'( "," space {item_rule_name} )' + successive_items = "" + min_items = schema.get("minItems", 0) + max_items = schema.get("maxItems") + if min_items > 0: + successive_items = list_item_operator * (min_items - 1) + min_items -= 1 + if max_items is not None and max_items > min_items: + successive_items += (list_item_operator + "?") * (max_items - min_items - 1) + else: + successive_items += list_item_operator + "*" + if min_items == 0: + rule = f'"[" space ( {item_rule_name} {successive_items} )? "]" space' + else: + rule = f'"[" space {item_rule_name} {successive_items} "]" space' + return self._add_rule(rule_name, rule) + + elif schema_type in (None, 'string') and 'pattern' in schema: + return self._visit_pattern(schema['pattern'], rule_name) + + elif schema_type in (None, 'string') and re.match(r'^uuid[1-5]?$', schema_format or ''): + return self._add_rule( + 'root' if rule_name == 'root' else schema_format, + PRIMITIVE_RULES['uuid'] + ) + + elif schema_type in (None, 'string') and schema_format in DATE_RULES: + for t, r in DATE_RULES.items(): + self._add_rule(t, r) + return schema_format + '-string' + + elif (schema_type == 'object') or (len(schema) == 0): + for n in OBJECT_RULE_NAMES: + self._add_rule(n, PRIMITIVE_RULES[n]) + return self._add_rule(rule_name, 'object') else: assert schema_type in PRIMITIVE_RULES, f'Unrecognized schema: {schema}' + # TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero return self._add_rule( 'root' if rule_name == 'root' else schema_type, PRIMITIVE_RULES[schema_type] ) + def _build_object_rule(self, properties: List[Tuple[str, Any]], required: Set[str], name: str, additional_properties: Union[bool, Any]): + prop_order = self._prop_order + # sort by position in prop_order (if specified) then by original order + sorted_props = [kv[0] for _, kv in sorted(enumerate(properties), key=lambda ikv: (prop_order.get(ikv[1][0], len(prop_order)), ikv[0]))] + + prop_kv_rule_names = {} + for prop_name, prop_schema in properties: + prop_rule_name = self.visit(prop_schema, f'{name}{"-" if name else ""}{prop_name}') + prop_kv_rule_names[prop_name] = self._add_rule( + f'{name}{"-" if name else ""}{prop_name}-kv', + fr'{self._format_literal(json.dumps(prop_name))} space ":" space {prop_rule_name}' + ) + required_props = [k for k in sorted_props if k in required] + optional_props = [k for k in sorted_props if k not in required] + + if additional_properties == True or isinstance(additional_properties, dict): + sub_name = f'{name}{"-" if name else ""}additional' + value_rule = self.visit({} if additional_properties == True else additional_properties, f'{sub_name}-value') + prop_kv_rule_names["*"] = self._add_rule( + f'{sub_name}-kv', + self._add_rule('string', PRIMITIVE_RULES['string']) + f' ":" space {value_rule}' + ) + optional_props.append("*") + + rule = '"{" space ' + rule += ' "," space '.join(prop_kv_rule_names[k] for k in required_props) + + if optional_props: + rule += ' (' + if required_props: + rule += ' "," space ( ' + + def get_recursive_refs(ks, first_is_optional): + [k, *rest] = ks + kv_rule_name = prop_kv_rule_names[k] + if k == '*': + res = self._add_rule( + f'{name}{"-" if name else ""}additional-kvs', + f'{kv_rule_name} ( "," space ' + kv_rule_name + ' )*' + ) + elif first_is_optional: + res = f'( "," space {kv_rule_name} )?' + else: + res = kv_rule_name + if len(rest) > 0: + res += ' ' + self._add_rule( + f'{name}{"-" if name else ""}{k}-rest', + get_recursive_refs(rest, first_is_optional=True) + ) + return res + + rule += ' | '.join( + get_recursive_refs(optional_props[i:], first_is_optional=False) + for i in range(len(optional_props)) + ) + if required_props: + rule += ' )' + rule += ' )?' + + rule += ' "}" space' + + return rule + def format_grammar(self): - return '\n'.join((f'{name} ::= {rule}' for name, rule in self._rules.items())) + return '\n'.join( + f'{name} ::= {rule}' + for name, rule in sorted(self._rules.items(), key=lambda kv: kv[0]) + ) def main(args_in = None): @@ -129,16 +501,47 @@ def main(args_in = None): type=lambda s: s.split(','), help=''' comma-separated property names defining the order of precedence for object properties; - properties not specified here are given lower precedence than those that are, and are - sorted alphabetically + properties not specified here are given lower precedence than those that are, and + are kept in their original order from the schema. Required properties are always + given precedence over optional properties. ''' ) + parser.add_argument( + '--allow-fetch', + action='store_true', + default=False, + help='Whether to allow fetching referenced schemas over HTTPS') + parser.add_argument( + '--dotall', + action='store_true', + default=False, + help='Whether to treat dot (".") as matching all chars including line breaks in regular expression patterns') + parser.add_argument( + '--raw-pattern', + action='store_true', + default=False, + help='Treats string patterns as raw patterns w/o quotes (or quote escapes)') + parser.add_argument('schema', help='file containing JSON schema ("-" for stdin)') args = parser.parse_args(args_in) - schema = json.load(sys.stdin if args.schema == '-' else open(args.schema)) - prop_order = {name: idx for idx, name in enumerate(args.prop_order)} - converter = SchemaConverter(prop_order) + if args.schema.startswith('https://'): + url = args.schema + import requests + schema = requests.get(url).json() + elif args.schema == '-': + url = 'stdin' + schema = json.load(sys.stdin) + else: + url = f'file://{args.schema}' + with open(args.schema) as f: + schema = json.load(f) + converter = SchemaConverter( + prop_order={name: idx for idx, name in enumerate(args.prop_order)}, + allow_fetch=args.allow_fetch, + dotall=args.dotall, + raw_pattern=args.raw_pattern) + schema = converter.resolve_refs(schema, url) converter.visit(schema, '') print(converter.format_grammar()) diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp index a19a9d665a3f1..fa106f142b720 100644 --- a/examples/llama-bench/llama-bench.cpp +++ b/examples/llama-bench/llama-bench.cpp @@ -8,6 +8,7 @@ #include #include #include +#include #include #include #include @@ -104,6 +105,7 @@ static std::string get_cpu_info() { } } } + fclose(f); } #endif // TODO: other platforms @@ -112,11 +114,11 @@ static std::string get_cpu_info() { static std::string get_gpu_info() { std::string id; -#ifdef GGML_USE_CUBLAS - int count = ggml_cuda_get_device_count(); +#ifdef GGML_USE_CUDA + int count = ggml_backend_cuda_get_device_count(); for (int i = 0; i < count; i++) { char buf[128]; - ggml_cuda_get_device_description(i, buf, sizeof(buf)); + ggml_backend_cuda_get_device_description(i, buf, sizeof(buf)); id += buf; if (i < count - 1) { id += "/"; @@ -248,6 +250,9 @@ static ggml_type ggml_type_from_name(const std::string & s) { if (s == "q5_1") { return GGML_TYPE_Q5_1; } + if (s == "iq4_nl") { + return GGML_TYPE_IQ4_NL; + } return GGML_TYPE_COUNT; } @@ -804,7 +809,7 @@ struct test { const std::string test::build_commit = LLAMA_COMMIT; const int test::build_number = LLAMA_BUILD_NUMBER; -const bool test::cuda = !!ggml_cpu_has_cublas(); +const bool test::cuda = !!ggml_cpu_has_cuda(); const bool test::opencl = !!ggml_cpu_has_clblast(); const bool test::vulkan = !!ggml_cpu_has_vulkan(); const bool test::kompute = !!ggml_cpu_has_kompute(); @@ -1123,15 +1128,19 @@ struct sql_printer : public printer { static void test_prompt(llama_context * ctx, int n_prompt, int n_past, int n_batch, int n_threads) { llama_set_n_threads(ctx, n_threads, n_threads); - //std::vector tokens(n_prompt, llama_token_bos(llama_get_model(ctx))); - //llama_decode(ctx, llama_batch_get_one(tokens.data(), n_prompt, n_past, 0)); - //GGML_UNUSED(n_batch); + const llama_model * model = llama_get_model(ctx); + const int32_t n_vocab = llama_n_vocab(model); + + std::vector tokens(n_batch); - std::vector tokens(n_batch, llama_token_bos(llama_get_model(ctx))); int n_processed = 0; while (n_processed < n_prompt) { int n_tokens = std::min(n_prompt - n_processed, n_batch); + tokens[0] = n_processed == 0 && llama_add_bos_token(model) ? llama_token_bos(model) : std::rand() % n_vocab; + for (int i = 1; i < n_tokens; i++) { + tokens[i] = std::rand() % n_vocab; + } llama_decode(ctx, llama_batch_get_one(tokens.data(), n_tokens, n_past + n_processed, 0)); n_processed += n_tokens; } @@ -1142,11 +1151,15 @@ static void test_prompt(llama_context * ctx, int n_prompt, int n_past, int n_bat static void test_gen(llama_context * ctx, int n_gen, int n_past, int n_threads) { llama_set_n_threads(ctx, n_threads, n_threads); - llama_token token = llama_token_bos(llama_get_model(ctx)); + const llama_model * model = llama_get_model(ctx); + const int32_t n_vocab = llama_n_vocab(model); + + llama_token token = llama_add_bos_token(model) ? llama_token_bos(model) : std::rand() % n_vocab; for (int i = 0; i < n_gen; i++) { llama_decode(ctx, llama_batch_get_one(&token, 1, n_past + i, 0)); llama_synchronize(ctx); + token = std::rand() % n_vocab; } } diff --git a/examples/llava/MobileVLM-README.md b/examples/llava/MobileVLM-README.md index 9eba791dadfef..96b048525239f 100644 --- a/examples/llava/MobileVLM-README.md +++ b/examples/llava/MobileVLM-README.md @@ -1,11 +1,13 @@ # MobileVLM -Currently this implementation supports [MobileVLM-v1.7](https://huggingface.co/mtgv/MobileVLM-1.7B) variants. +Currently this implementation supports [MobileVLM-1.7B](https://huggingface.co/mtgv/MobileVLM-1.7B) / [MobileVLM_V2-1.7B](https://huggingface.co/mtgv/MobileVLM_V2-1.7B) variants. for more information, please go to [Meituan-AutoML/MobileVLM](https://github.com/Meituan-AutoML/MobileVLM) The implementation is based on llava, and is compatible with llava and mobileVLM. The usage is basically same as llava. +Notice: The overall process of model inference for both **MobileVLM** and **MobileVLM_V2** models is the same, but the process of model conversion is a little different. Therefore, using **MobileVLM-1.7B** as an example, the different conversion step will be shown. + ## Usage Build with cmake or run `make llava-cli` to build it. @@ -34,7 +36,7 @@ git clone https://huggingface.co/openai/clip-vit-large-patch14-336 python ./examples/llava/llava-surgery.py -m path/to/MobileVLM-1.7B ``` -3. Use `convert-image-encoder-to-gguf.py` with `--projector-type ldp` to convert the LLaVA image encoder to GGUF: +3. Use `convert-image-encoder-to-gguf.py` with `--projector-type ldp` (for **V2** please use `--projector-type ldpv2`) to convert the LLaVA image encoder to GGUF: ```sh python ./examples/llava/convert-image-encoder-to-gguf \ @@ -44,6 +46,14 @@ python ./examples/llava/convert-image-encoder-to-gguf \ --projector-type ldp ``` +```sh +python ./examples/llava/convert-image-encoder-to-gguf \ + -m path/to/clip-vit-large-patch14-336 \ + --llava-projector path/to/MobileVLM-1.7B_V2/llava.projector \ + --output-dir path/to/MobileVLM-1.7B_V2 \ + --projector-type ldpv2 +``` + 4. Use `convert.py` to convert the LLaMA part of LLaVA to GGUF: ```sh @@ -68,7 +78,7 @@ cd examples/llava/android/build_64 ### run on Android refer to `android/adb_run.sh`, modify resources' `name` and `path` -## some result on Android with `Snapdragon 888` chip +## Some result on Android with `Snapdragon 888` chip ### case 1 **input** ```sh @@ -99,7 +109,6 @@ llama_print_timings: total time = 34731.93 ms --image /data/local/tmp/cat.jpeg \ -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: \nWhat is in the image? ASSISTANT:" ``` - **output** ```sh encode_image_with_clip: image encoded in 21149.51 ms by CLIP ( 146.87 ms per image patch) @@ -111,12 +120,82 @@ llama_print_timings: eval time = 1279.03 ms / 18 runs ( 71.06 m llama_print_timings: total time = 34570.79 ms ``` + +## Some result on Android with `Snapdragon 778G` chip +### MobileVLM-1.7B case +#### llava-cli release-b2005 +**input** +```sh +/data/local/tmp/llava-cli \ + -m /data/local/tmp/ggml-model-q4_k.gguf \ + --mmproj /data/local/tmp/mmproj-model-f16.gguf \ + -t 4 \ + --image /data/local/tmp/many_llamas.jpeg \ + -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: \nWhat's that? ASSISTANT:" +``` +**output** +```sh +encode_image_with_clip: image encoded in 18728.52 ms by CLIP ( 130.06 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that? ASSISTANT: + + A group of llamas are standing in a green pasture. + +llama_print_timings: load time = 20357.33 ms +llama_print_timings: sample time = 2.96 ms / 14 runs ( 0.21 ms per token, 4734.53 tokens per second) +llama_print_timings: prompt eval time = 8119.49 ms / 191 tokens ( 42.51 ms per token, 23.52 tokens per second) +llama_print_timings: eval time = 1005.75 ms / 14 runs ( 71.84 ms per token, 13.92 tokens per second) +llama_print_timings: total time = 28038.34 ms / 205 tokens +``` +#### llava-cli latest-version +**input** + +Just the same as above. + +**output**(seems to be much slower) +```sh +encode_image_with_clip: image embedding created: 144 tokens + +encode_image_with_clip: image encoded in 288268.88 ms by CLIP ( 2001.87 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that? ASSISTANT: + + It is a group of sheep standing together in a grass field. + +llama_print_timings: load time = 818120.91 ms +llama_print_timings: sample time = 3.44 ms / 14 runs ( 0.25 ms per token, 4067.40 tokens per second) +llama_print_timings: prompt eval time = 529274.69 ms / 191 tokens ( 2771.07 ms per token, 0.36 tokens per second) +llama_print_timings: eval time = 43894.02 ms / 13 runs ( 3376.46 ms per token, 0.30 tokens per second) +llama_print_timings: total time = 865441.76 ms / 204 tokens +``` +### MobileVLM_V2-1.7B case +#### llava-cli release-2005b +**input** + +Just the same as above. + +**output** +```sh +encode_image_with_clip: image encoded in 20609.61 ms by CLIP ( 143.12 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that? ASSISTANT: + + This image captures a lively scene of 20 llamas in motion on an expansive, grassy field. The llama is scattered across the landscape with some standing and others sitting down as if taking rest or observing their surroundings from different vantage points within this verdant setting. + +The background offers glimpses into a picturesque town nestled amidst hills under an overcast sky, adding depth to the scene while also emphasizing that distance between these llama and human-made structures like houses or roads in which they roam freely without any barriers around them. The image is framed by text at both right angles on white backgrounds against a contrasting blue backdrop with green foliage, further drawing attention to the llamas amidst their natural habitat while also inviting viewers into this picturesque landscape within town limits of Alta Llama + +llama_print_timings: load time = 22406.77 ms +llama_print_timings: sample time = 49.26 ms / 186 runs ( 0.26 ms per token, 3776.27 tokens per second) +llama_print_timings: prompt eval time = 9044.54 ms / 191 tokens ( 47.35 ms per token, 21.12 tokens per second) +llama_print_timings: eval time = 14497.49 ms / 186 runs ( 77.94 ms per token, 12.83 tokens per second) +llama_print_timings: total time = 44411.01 ms / 377 tokens +``` + ## Orin compile and run ### compile ```sh -make LLAMA_CUBLAS=1 CUDA_DOCKER_ARCH=sm_87 LLAMA_CUDA_F16=1 -j 32 +make LLAMA_CUDA=1 CUDA_DOCKER_ARCH=sm_87 LLAMA_CUDA_F16=1 -j 32 ``` - ### run on Orin ### case 1 **input** @@ -165,8 +244,121 @@ llama_print_timings: eval time = 166.65 ms / 11 runs ( 15.15 m llama_print_timings: total time = 1365.47 ms / 243 tokens ``` -## Minor shortcomings -The `n_patch` of output in `ldp` is 1/4 of the input. In order to implement quickly, we uniformly modified `clip_n_patches` function to a quarter. when counting the time consumption, the calculated time will be 4 times bigger than the real cost. +## Running on Intel(R) Core(TM) i7-10750H +### Operating system +Ubuntu22.04 +### compile +```sh +make -j32 +``` +### MobileVLM-1.7B case +**input** +```sh +-m /path/to/ggml-model-q4_k.gguf \ + --mmproj /path/to/mmproj-model-f16.gguf \ + --image /path/to/many_llamas.jpeg + -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: \nWhat's that? ASSISTANT:" \ +``` +**output** +```sh +encode_image_with_clip: image embedding created: 144 tokens + +encode_image_with_clip: image encoded in 2730.94 ms by CLIP ( 18.96 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that?ASSISTANT: + + A group of llamas are walking together in a field. + +llama_print_timings: load time = 5506.60 ms +llama_print_timings: sample time = 0.44 ms / 13 runs ( 0.03 ms per token, 29545.45 tokens per second) +llama_print_timings: prompt eval time = 2031.58 ms / 190 tokens ( 10.69 ms per token, 93.52 tokens per second) +llama_print_timings: eval time = 438.92 ms / 12 runs ( 36.58 ms per token, 27.34 tokens per second) +llama_print_timings: total time = 5990.25 ms / 202 tokens +``` + +### MobileVLM_V2-1.7B case +**input** + +Just the same as above. + +**ouput** +```sh +encode_image_with_clip: image embedding created: 144 tokens + +encode_image_with_clip: image encoded in 3223.89 ms by CLIP ( 22.39 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that?ASSISTANT: + + The image captures a tranquil scene in a park, where a group of approximately 20 llamas are gathered. The llamas, a mix of white and black, are standing in a line, their black and white patterns contrasting with the lush green grass of the park. The lamas are arranged in a line, suggesting a social order. + +The park itself is lush and green, with trees dotting the landscape in the background. A sign reading "Llamas Tico Ana" is also visible in the image, possibly indicating the location or the breed of the llamas. The image seems to be taken from a distance, providing a wide view of the scene and the surrounding environment. + +The llamas' positions relative to each other, the sign, and the trees create a harmonious composition. The image does not contain any discernible text. The overall scene is one of peace and natural beauty, with the llamas in their natural habitat, surrounded by the vibrant colors and lush greenery of the park. + +llama_print_timings: load time = 6642.61 ms +llama_print_timings: sample time = 8.15 ms / 223 runs ( 0.04 ms per token, 27358.61 tokens per second) +llama_print_timings: prompt eval time = 2475.07 ms / 190 tokens ( 13.03 ms per token, 76.77 tokens per second) +llama_print_timings: eval time = 8760.60 ms / 222 runs ( 39.46 ms per token, 25.34 tokens per second) +llama_print_timings: total time = 15513.95 ms / 412 tokens +``` + +## Run on Intel(R) Core(TM) Ultra7 115H +### operation system +Windows11 +### comiple +```sh +make -j32 +``` +### MobileVLM-1.7B case +**input** +```sh +-m /path/to/ggml-model-q4_k.gguf \ + --mmproj /path/to/tmp/mmproj-model-f16.gguf \ + -p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: \nWhat's that? ASSISTANT:" \ +``` +**output** +```sh +encode_image_with_clip: image encoded in 4902.81 ms by CLIP ( 34.05 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that? ASSISTANT: + + The image features a group of brown and white llamas standing in a grassy field. + +llama_print_timings: load time = 7441.06 ms +llama_print_timings: sample time = 0.72 ms / 19 runs ( 0.04 ms per token, 26279.39 tokens per second) +llama_print_timings: prompt eval time = 2090.71 ms / 191 tokens ( 10.95 ms per token, 91.36 tokens per second) +llama_print_timings: eval time = 512.35 ms / 18 runs ( 28.46 ms per token, 35.13 tokens per second) +llama_print_timings: total time = 7987.23 ms / 209 tokens +``` + +### MobileVLM_V2-1.7B case +**input** + +Just the same as above. + +**output** +```sh +encode_image_with_clip: image encoded in 4682.44 ms by CLIP ( 32.52 ms per image patch) +system_prompt: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: +user_prompt: \nWhat's that? ASSISTANT: + + This image captures a lively scene of a group of 14 llamas in a grassy field. The llamas, with their distinctive black and white coats, are standing and walking in a line, seemingly engaged in a social activity. One + of them, possibly the first in the line, has its back turned, perhaps observing something in the distance. + +The llama in the front of the line stands out due to its black and white coloring, which is quite unusual for llama patterns. The llama in the front also seems to be more aware of its surroundings, as it faces the camera, giving a sense of engagement with the viewer. + +The image is taken from the side of the llama, providing a clear view of the llama in the front and its companions. The lameness in the llama in + front is not visible, indicating that it might not be the main focus of the photo. + +The background of the image features a grassy field, with a fence and a tree visible in the distance. The tree appears to be bare, suggesting that it might be during a time of year when most trees are dormant or have shed their leaves. + + +llama_print_timings: load time = 7015.35 ms +llama_print_timings: sample time = 10.61 ms / 256 runs ( 0.04 ms per token, 24119.09 tokens per second) +llama_print_timings: prompt eval time = 2052.45 ms / 191 tokens ( 10.75 ms per token, 93.06 tokens per second) +llama_print_timings: eval time = 7259.43 ms / 255 runs ( 28.47 ms per token, 35.13 tokens per second) +llama_print_timings: total time = 14371.19 ms / 446 tokens +``` ## TODO @@ -181,5 +373,5 @@ The `n_patch` of output in `ldp` is 1/4 of the input. In order to implement quic ## contributor ```sh -zhangjidong05, yangyang260, huyiming03, chenxiaotao03 +zhangjidong05, yangyang260, huyiming03, chenxiaotao03, ZiangWu-77 ``` diff --git a/examples/llava/README.md b/examples/llava/README.md index 35e6d9e5d00f7..67cb0f22b7d95 100644 --- a/examples/llava/README.md +++ b/examples/llava/README.md @@ -63,12 +63,20 @@ Now both the LLaMA part and the image encoder is in the `llava-v1.5-7b` director ```console git clone https://huggingface.co/liuhaotian/llava-v1.6-vicuna-7b ``` -2) Use `llava-surgery-v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models: + +2) Install the required Python packages: + +```sh +pip install -r examples/llava/requirements.txt +``` + +3) Use `llava-surgery-v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models: ```console python examples/llava/llava-surgery-v2.py -C -m ../llava-v1.6-vicuna-7b/ ``` - you will find a llava.projector and a llava.clip file in your model directory -3) Copy the llava.clip file into a subdirectory (like vit), rename it to pytorch_model.bin and add a fitting vit configuration to the directory: + +4) Copy the llava.clip file into a subdirectory (like vit), rename it to pytorch_model.bin and add a fitting vit configuration to the directory: ```console mkdir vit cp ../llava-v1.6-vicuna-7b/llava.clip vit/pytorch_model.bin @@ -76,18 +84,18 @@ cp ../llava-v1.6-vicuna-7b/llava.projector vit/ curl -s -q https://huggingface.co/cmp-nct/llava-1.6-gguf/raw/main/config_vit.json -o vit/config.json ``` -4) Create the visual gguf model: +5) Create the visual gguf model: ```console python ./examples/llava/convert-image-encoder-to-gguf.py -m vit --llava-projector vit/llava.projector --output-dir vit --clip-model-is-vision ``` - This is similar to llava-1.5, the difference is that we tell the encoder that we are working with the pure vision model part of CLIP -5) Then convert the model to gguf format: +6) Then convert the model to gguf format: ```console python ./convert.py ../llava-v1.6-vicuna-7b/ --skip-unknown ``` -6) And finally we can run the llava-cli using the 1.6 model version: +7) And finally we can run the llava-cli using the 1.6 model version: ```console ./llava-cli -m ../llava-v1.6-vicuna-7b/ggml-model-f16.gguf --mmproj vit/mmproj-model-f16.gguf --image some-image.jpg -c 4096 ``` diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp index 6653b815d93a1..5954bf6cdec68 100644 --- a/examples/llava/clip.cpp +++ b/examples/llava/clip.cpp @@ -7,7 +7,7 @@ #include "ggml-alloc.h" #include "ggml-backend.h" -#ifdef GGML_USE_CUBLAS +#ifdef GGML_USE_CUDA #include "ggml-cuda.h" #endif @@ -119,6 +119,7 @@ static std::string format(const char * fmt, ...) { #define TN_LLAVA_PROJ "mm.%d.%s" #define TN_MVLM_PROJ_MLP "mm.model.mlp.%d.%s" #define TN_MVLM_PROJ_BLOCK "mm.model.mb_block.%d.block.%d.%s" +#define TN_MVLM_PROJ_PEG "mm.model.peg.%d.%s" #define TN_IMAGE_NEWLINE "model.image_newline" @@ -126,12 +127,14 @@ enum projector_type { PROJECTOR_TYPE_MLP, PROJECTOR_TYPE_MLP_NORM, PROJECTOR_TYPE_LDP, + PROJECTOR_TYPE_LDPV2, PROJECTOR_TYPE_UNKNOWN, }; static std::map PROJECTOR_TYPE_NAMES = { { PROJECTOR_TYPE_MLP, "mlp" }, { PROJECTOR_TYPE_LDP, "ldp" }, + { PROJECTOR_TYPE_LDPV2, "ldpv2"}, }; @@ -475,6 +478,14 @@ struct clip_vision_model { struct ggml_tensor * mm_model_block_2_block_2_0_w; struct ggml_tensor * mm_model_block_2_block_2_1_w; struct ggml_tensor * mm_model_block_2_block_2_1_b; + + // MobileVLM_V2 projection + struct ggml_tensor * mm_model_mlp_0_w; + struct ggml_tensor * mm_model_mlp_0_b; + struct ggml_tensor * mm_model_mlp_2_w; + struct ggml_tensor * mm_model_mlp_2_b; + struct ggml_tensor * mm_model_peg_0_w; + struct ggml_tensor * mm_model_peg_0_b; }; struct clip_ctx { @@ -497,7 +508,6 @@ struct clip_ctx { // memory buffers to evaluate the model ggml_backend_buffer_t params_buffer = NULL; - ggml_backend_buffer_t compute_buffer = NULL; ggml_backend_t backend = NULL; ggml_gallocr_t compute_alloc = NULL; @@ -808,6 +818,30 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 } embeddings = block_1; } + else if (ctx->proj_type == PROJECTOR_TYPE_LDPV2) + { + int n_patch = 24; + struct ggml_tensor * mlp_0 = ggml_mul_mat(ctx0, model.mm_model_mlp_0_w, embeddings); + mlp_0 = ggml_add(ctx0, mlp_0, model.mm_model_mlp_0_b); + mlp_0 = ggml_gelu(ctx0, mlp_0); + struct ggml_tensor * mlp_2 = ggml_mul_mat(ctx0, model.mm_model_mlp_2_w, mlp_0); + mlp_2 = ggml_add(ctx0, mlp_2, model.mm_model_mlp_2_b); + // mlp_2 ne = [2048, 576, 1, 1] + // // AVG Pool Layer 2*2, strides = 2 + mlp_2 = ggml_cont(ctx0, ggml_permute(ctx0, mlp_2, 1, 0, 2, 3)); + // mlp_2 ne = [576, 2048, 1, 1] + mlp_2 = ggml_reshape_4d(ctx0, mlp_2, n_patch, n_patch, mlp_2->ne[1], mlp_2->ne[2]); + // mlp_2 ne [24, 24, 2048, 1] + mlp_2 = ggml_pool_2d(ctx0, mlp_2, GGML_OP_POOL_AVG, 2, 2, 2, 2, 0, 0); + // weight ne = [3, 3, 2048, 1] + struct ggml_tensor * peg_0 = ggml_conv_depthwise_2d(ctx0, model.mm_model_peg_0_w, mlp_2, 1, 1, 1, 1, 1, 1); + peg_0 = ggml_cont(ctx0, ggml_permute(ctx0, peg_0, 1, 2, 0, 3)); + peg_0 = ggml_add(ctx0, peg_0, model.mm_model_peg_0_b); + mlp_2 = ggml_cont(ctx0, ggml_permute(ctx0, mlp_2, 1, 2, 0, 3)); + peg_0 = ggml_add(ctx0, peg_0, mlp_2); + peg_0 = ggml_reshape_3d(ctx0, peg_0, peg_0->ne[0], peg_0->ne[1] * peg_0->ne[2], peg_0->ne[3]); + embeddings = peg_0; + } else { GGML_ASSERT(false); } @@ -935,7 +969,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { } } -#ifdef GGML_USE_CUBLAS +#ifdef GGML_USE_CUDA new_clip->backend = ggml_backend_cuda_init(0); printf("%s: CLIP using CUDA backend\n", __func__); #endif @@ -995,6 +1029,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { if (!new_clip->ctx_data) { fprintf(stderr, "%s: ggml_init() failed\n", __func__); clip_free(new_clip); + gguf_free(ctx); return nullptr; } @@ -1002,6 +1037,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { if (!fin) { printf("cannot open model file for loading tensors\n"); clip_free(new_clip); + gguf_free(ctx); return nullptr; } @@ -1023,6 +1059,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { if (!fin) { printf("%s: failed to seek for tensor %s\n", __func__, name); clip_free(new_clip); + gguf_free(ctx); return nullptr; } int num_bytes = ggml_nbytes(cur); @@ -1175,7 +1212,18 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { vision_model.mm_model_block_2_block_2_0_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_BLOCK, 2, 2, "0.weight")); vision_model.mm_model_block_2_block_2_1_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_BLOCK, 2, 2, "1.weight")); vision_model.mm_model_block_2_block_2_1_b = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_BLOCK, 2, 2, "1.bias")); - } else { + } + else if (new_clip->proj_type == PROJECTOR_TYPE_LDPV2) + { + // MobilVLM_V2 projection + vision_model.mm_model_mlp_0_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 0, "weight")); + vision_model.mm_model_mlp_0_b = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 0, "bias")); + vision_model.mm_model_mlp_2_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 2, "weight")); + vision_model.mm_model_mlp_2_b = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_MLP, 2, "bias")); + vision_model.mm_model_peg_0_w = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_PEG, 0, "weight")); + vision_model.mm_model_peg_0_b = get_tensor(new_clip->ctx_data, format(TN_MVLM_PROJ_PEG, 0, "bias")); + } + else { std::string proj_type = PROJECTOR_TYPE_NAMES[new_clip->proj_type]; throw std::runtime_error(format("%s: don't support projector with: %s currently\n", __func__, proj_type.c_str())); } @@ -1232,16 +1280,16 @@ struct clip_image_f32 * clip_image_f32_init() { void clip_image_u8_free(struct clip_image_u8 * img) { delete img; } void clip_image_f32_free(struct clip_image_f32 * img) { delete img; } -void clip_image_u8_batch_free(struct clip_image_u8_batch & batch) { - if (batch.size > 0) { - delete[] batch.data; - batch.size = 0; +void clip_image_u8_batch_free(struct clip_image_u8_batch * batch) { + if (batch->size > 0) { + delete[] batch->data; + batch->size = 0; } } -void clip_image_f32_batch_free(struct clip_image_f32_batch & batch) { - if (batch.size > 0) { - delete[] batch.data; - batch.size = 0; +void clip_image_f32_batch_free(struct clip_image_f32_batch * batch) { + if (batch->size > 0) { + delete[] batch->data; + batch->size = 0; } } @@ -1494,7 +1542,7 @@ static std::vector divide_to_patches_u8(const clip_image_u8 & im // returns the normalized float tensor for llava-1.5, for spatial_unpad with anyres processing for llava-1.6 it returns the normalized image patch tensors as a vector // res_imgs memory is being allocated here, previous allocations will be freed if found -bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, clip_image_f32_batch & res_imgs) { +bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, clip_image_f32_batch * res_imgs) { bool pad_to_square = true; if (!ctx->has_vision_encoder) { printf("This gguf file seems to have no vision encoder\n"); @@ -1506,11 +1554,11 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, cli pad_to_square = false; } // free the previous res_imgs if any set - if (res_imgs.size > 0) { + if (res_imgs->size > 0) { clip_image_f32_batch_free(res_imgs); } - res_imgs.data = nullptr; - res_imgs.size = 0; + res_imgs->data = nullptr; + res_imgs->size = 0; // the logic below is to pad the shorter side to the longer side with a background color: rgb(122, 116, 104) // see https://github.com/haotian-liu/LLaVA/blob/e854a2bf85118c504f6f16bf5c3c7c92f8fa8c6b/llava/conversation.py#L113-L156 @@ -1565,11 +1613,11 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, cli bicubic_resize(*img, *image_original_resize, params.image_size, params.image_size); // in python this is "shortest_edge", but all CLIP are square patches.insert(patches.begin(), image_original_resize); // clip_image_f32_batch_init(patches.size()); - res_imgs.size = patches.size(); - res_imgs.data = new clip_image_f32[res_imgs.size]; + res_imgs->size = patches.size(); + res_imgs->data = new clip_image_f32[res_imgs->size]; int num=0; for (auto& patch : patches) { - normalize_image_u8_to_f32(patch, &res_imgs.data[num], ctx->image_mean, ctx->image_std); + normalize_image_u8_to_f32(patch, &res_imgs->data[num], ctx->image_mean, ctx->image_std); num++; } @@ -1657,9 +1705,9 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, cli // } // res_imgs.push_back(res); - res_imgs.size = 1; - res_imgs.data = new clip_image_f32[res_imgs.size]; - res_imgs.data[0] = *res; + res_imgs->size = 1; + res_imgs->data = new clip_image_f32[res_imgs->size]; + res_imgs->data[0] = *res; clip_image_f32_free(res); return true; @@ -1673,6 +1721,9 @@ void clip_free(clip_ctx * ctx) { ggml_free(ctx->ctx_data); gguf_free(ctx->ctx_gguf); + ggml_backend_buffer_free(ctx->params_buffer); + ggml_backend_free(ctx->backend); + ggml_gallocr_free(ctx->compute_alloc); delete ctx; } @@ -1705,7 +1756,7 @@ int clip_n_patches(const struct clip_ctx * ctx) { int n_patches = (params.image_size / params.patch_size) * (params.image_size / params.patch_size); - if (ctx->proj_type == PROJECTOR_TYPE_LDP) { + if (ctx->proj_type == PROJECTOR_TYPE_LDP || ctx->proj_type == PROJECTOR_TYPE_LDPV2) { n_patches /= 4; } @@ -1908,6 +1959,7 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i break; default: printf("Please use an input file in f32 or f16\n"); + gguf_free(ctx_out); return false; } @@ -1960,6 +2012,9 @@ int clip_n_mmproj_embd(const struct clip_ctx * ctx) { if (ctx->proj_type == PROJECTOR_TYPE_LDP) { return ctx->vision_model.mm_model_block_1_block_2_1_b->ne[0]; } + if (ctx->proj_type == PROJECTOR_TYPE_LDPV2) { + return ctx->vision_model.mm_model_peg_0_b->ne[0]; + } if (ctx->proj_type == PROJECTOR_TYPE_MLP) { return ctx->vision_model.mm_2_b->ne[0]; } diff --git a/examples/llava/clip.h b/examples/llava/clip.h index e5bd54924a9c8..45bdad6897658 100644 --- a/examples/llava/clip.h +++ b/examples/llava/clip.h @@ -60,8 +60,8 @@ CLIP_API struct clip_image_f32 * clip_image_f32_init(); CLIP_API void clip_image_u8_free (struct clip_image_u8 * img); CLIP_API void clip_image_f32_free(struct clip_image_f32 * img); -CLIP_API void clip_image_u8_batch_free (struct clip_image_u8_batch & batch); -CLIP_API void clip_image_f32_batch_free(struct clip_image_f32_batch & batch); +CLIP_API void clip_image_u8_batch_free (struct clip_image_u8_batch * batch); +CLIP_API void clip_image_f32_batch_free(struct clip_image_f32_batch * batch); CLIP_API bool clip_image_load_from_file(const char * fname, struct clip_image_u8 * img); @@ -69,7 +69,7 @@ CLIP_API bool clip_image_load_from_file(const char * fname, struct clip_image_u8 CLIP_API bool clip_image_load_from_bytes(const unsigned char * bytes, size_t bytes_length, struct clip_image_u8 * img); /** preprocess img and store the result in res_imgs, pad_to_square may be overriden to false depending on model configuration */ -CLIP_API bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, clip_image_f32_batch & res_imgs ); +CLIP_API bool clip_image_preprocess(struct clip_ctx * ctx, const struct clip_image_u8 * img, struct clip_image_f32_batch * res_imgs ); CLIP_API struct ggml_tensor * clip_get_newline_tensor(const struct clip_ctx * ctx); diff --git a/examples/llava/convert-image-encoder-to-gguf.py b/examples/llava/convert-image-encoder-to-gguf.py index c69f89ac2b60e..b00bf7c6d0b59 100644 --- a/examples/llava/convert-image-encoder-to-gguf.py +++ b/examples/llava/convert-image-encoder-to-gguf.py @@ -1,6 +1,7 @@ import argparse import os import json +import re import torch import numpy as np @@ -38,9 +39,11 @@ def should_skip_tensor(name: str, has_text: bool, has_vision: bool, has_llava: b def get_tensor_name(name: str) -> str: if "projection" in name: return name - if "mm_projector" in name: - return name.replace("model.mm_projector", "mm") + name = name.replace("model.mm_projector", "mm") + name = re.sub(r'mm\.mlp\.mlp', 'mm.model.mlp', name, count=1) + name = re.sub(r'mm\.peg\.peg', 'mm.model.peg', name, count=1) + return name return name.replace("text_model", "t").replace("vision_model", "v").replace("encoder.layers", "blk").replace("embeddings.", "").replace("_proj", "").replace("self_attn.", "attn_").replace("layer_norm", "ln").replace("layernorm", "ln").replace("mlp.fc1", "ffn_down").replace("mlp.fc2", "ffn_up").replace("embedding", "embd").replace("final", "post").replace("layrnorm", "ln") @@ -83,7 +86,7 @@ def bytes_to_unicode(): ap.add_argument("--clip-model-is-openclip", action="store_true", required=False, help="The clip model is from openclip (for ViT-SO400M type))") ap.add_argument("--llava-projector", help="Path to llava.projector file. If specified, save an image encoder for LLaVA models.") -ap.add_argument("--projector-type", help="Type of projector. Possible values: mlp, ldp", choices=["mlp", "ldp"], default="mlp") +ap.add_argument("--projector-type", help="Type of projector. Possible values: mlp, ldp, ldpv2", choices=["mlp", "ldp", "ldpv2"], default="mlp") ap.add_argument("-o", "--output-dir", help="Directory to save GGUF files. Default is the original model directory", default=None) # Example --image_mean 0.48145466 0.4578275 0.40821073 --image_std 0.26862954 0.26130258 0.27577711 # Example --image_mean 0.5 0.5 0.5 --image_std 0.5 0.5 0.5 diff --git a/examples/llava/llava.cpp b/examples/llava/llava.cpp index 9801281661b25..29764757aab5d 100644 --- a/examples/llava/llava.cpp +++ b/examples/llava/llava.cpp @@ -223,7 +223,7 @@ static bool encode_image_with_clip(clip_ctx * ctx_clip, int n_threads, const cli clip_image_f32_batch img_res_v; img_res_v.size = 0; img_res_v.data = nullptr; - if (!clip_image_preprocess(ctx_clip, img, img_res_v)) { + if (!clip_image_preprocess(ctx_clip, img, &img_res_v)) { fprintf(stderr, "%s: unable to preprocess image\n", __func__); delete[] img_res_v.data; return false; diff --git a/examples/llava/llava.h b/examples/llava/llava.h index 2d40f3f1d5f84..19212f6e9e9c5 100644 --- a/examples/llava/llava.h +++ b/examples/llava/llava.h @@ -29,9 +29,9 @@ struct llava_image_embed { }; /** sanity check for clip <-> llava embed size match */ -LLAVA_API bool llava_validate_embed_size(const llama_context * ctx_llama, const clip_ctx * ctx_clip); +LLAVA_API bool llava_validate_embed_size(const struct llama_context * ctx_llama, const struct clip_ctx * ctx_clip); -LLAVA_API bool llava_image_embed_make_with_clip_img(clip_ctx * ctx_clip, int n_threads, const clip_image_u8 * img, float ** image_embd_out, int * n_img_pos_out); +LLAVA_API bool llava_image_embed_make_with_clip_img(struct clip_ctx * ctx_clip, int n_threads, const struct clip_image_u8 * img, float ** image_embd_out, int * n_img_pos_out); /** build an image embed from image file bytes */ LLAVA_API struct llava_image_embed * llava_image_embed_make_with_bytes(struct clip_ctx * ctx_clip, int n_threads, const unsigned char * image_bytes, int image_bytes_length); diff --git a/examples/lookup/CMakeLists.txt b/examples/lookup/CMakeLists.txt index c060b8f56d436..b91633f63e4ee 100644 --- a/examples/lookup/CMakeLists.txt +++ b/examples/lookup/CMakeLists.txt @@ -3,3 +3,21 @@ add_executable(${TARGET} lookup.cpp) install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_11) + +set(TARGET lookup-create) +add_executable(${TARGET} lookup-create.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) + +set(TARGET lookup-merge) +add_executable(${TARGET} lookup-merge.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) + +set(TARGET lookup-stats) +add_executable(${TARGET} lookup-stats.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/lookup/lookup-create.cpp b/examples/lookup/lookup-create.cpp new file mode 100644 index 0000000000000..46a6bed078e71 --- /dev/null +++ b/examples/lookup/lookup-create.cpp @@ -0,0 +1,43 @@ +#include "ggml.h" +#include "llama.h" +#include "common.h" +#include "ngram-cache.h" + +#include +#include +#include +#include +#include +#include + +int main(int argc, char ** argv){ + gpt_params params; + + if (!gpt_params_parse(argc, argv, params)) { + return 1; + } + // init llama.cpp + llama_backend_init(); + llama_numa_init(params.numa); + + llama_model * model = NULL; + llama_context * ctx = NULL; + + // load the model + std::tie(model, ctx) = llama_init_from_gpt_params(params); + GGML_ASSERT(model != nullptr); + + // tokenize the prompt + const bool add_bos = llama_should_add_bos_token(model); + + std::vector inp; + inp = ::llama_tokenize(ctx, params.prompt, add_bos, true); + fprintf(stderr, "%s: tokenization done\n", __func__); + + + llama_ngram_cache ngram_cache; + llama_ngram_cache_update(ngram_cache, LLAMA_NGRAM_STATIC, LLAMA_NGRAM_STATIC, inp, inp.size(), true); + fprintf(stderr, "%s: hashing done, writing file to %s\n", __func__, params.lookup_cache_static.c_str()); + + llama_ngram_cache_save(ngram_cache, params.lookup_cache_static); +} diff --git a/examples/lookup/lookup-merge.cpp b/examples/lookup/lookup-merge.cpp new file mode 100644 index 0000000000000..07c93eb8d057b --- /dev/null +++ b/examples/lookup/lookup-merge.cpp @@ -0,0 +1,47 @@ +#include "ggml.h" +#include "llama.h" +#include "common.h" +#include "ngram-cache.h" + +#include +#include +#include +#include +#include +#include +#include + +static void print_usage() { + fprintf(stderr, "Merges multiple lookup cache files into a single one.\n"); + fprintf(stderr, "Usage: lookup-merge [--help] lookup_part_1.bin lookup_part_2.bin ... lookup_merged.bin\n"); +} + +int main(int argc, char ** argv){ + if (argc < 3) { + print_usage(); + exit(1); + } + + std::vector args; + args.resize(argc-1); + for (int i = 0; i < argc-1; ++i) { + args[i] = argv[i+1]; + if (args[i] == "-h" || args[i] == "--help") { + print_usage(); + exit(0); + } + } + + fprintf(stderr, "lookup-merge: loading file %s\n", args[0].c_str()); + llama_ngram_cache ngram_cache_merged = llama_ngram_cache_load(args[0]); + + for (size_t i = 1; i < args.size()-1; ++i) { + fprintf(stderr, "lookup-merge: loading file %s\n", args[i].c_str()); + llama_ngram_cache ngram_cache = llama_ngram_cache_load(args[i]); + + llama_ngram_cache_merge(ngram_cache_merged, ngram_cache); + } + + fprintf(stderr, "lookup-merge: saving file %s\n", args.back().c_str()); + llama_ngram_cache_save(ngram_cache_merged, args.back()); +} diff --git a/examples/lookup/lookup-stats.cpp b/examples/lookup/lookup-stats.cpp new file mode 100644 index 0000000000000..31f227773de6f --- /dev/null +++ b/examples/lookup/lookup-stats.cpp @@ -0,0 +1,163 @@ +#include "ggml.h" +#include "common.h" +#include "llama.h" +#include "log.h" +#include "ngram-cache.h" + +#include +#include +#include +#include +#include +#include +#include + +int main(int argc, char ** argv){ + gpt_params params; + + if (!gpt_params_parse(argc, argv, params)) { + return 1; + } + + const int n_draft = params.n_draft; + + // init llama.cpp + llama_backend_init(); + llama_numa_init(params.numa); + + llama_model * model = NULL; + llama_context * ctx = NULL; + + // load the model + std::tie(model, ctx) = llama_init_from_gpt_params(params); + llama_set_rng_seed(ctx, params.seed); + GGML_ASSERT(llama_n_vocab(model) < (1 << 16)); + + // tokenize the prompt + const bool add_bos = llama_should_add_bos_token(model); + LOG("add_bos tgt: %d\n", add_bos); + + std::vector inp; + inp = ::llama_tokenize(ctx, params.prompt, add_bos, true); + + llama_ngram_cache ngram_cache_context; + llama_ngram_cache ngram_cache_dynamic; + llama_ngram_cache ngram_cache_static; + int64_t t_draft_flat_us = 0; + int64_t t_draft_us = 0; + + { + const int64_t t_start_draft_us = ggml_time_us(); + + if (!params.lookup_cache_static.empty()) { + try { + ngram_cache_static = llama_ngram_cache_load(params.lookup_cache_static); + } catch (std::ifstream::failure const &) { + fprintf(stderr, "error: failed to open static lookup cache: %s", params.lookup_cache_static.c_str()); + exit(1); + } + } + + if (!params.lookup_cache_dynamic.empty()) { + try { + ngram_cache_dynamic = llama_ngram_cache_load(params.lookup_cache_dynamic); + } catch (std::ifstream::failure const &) {} // if the file does not exist it will simply be created at the end of the program + } + + t_draft_flat_us += ggml_time_us() - t_start_draft_us; + } + + const int n_input = inp.size(); + const int n_ctx = params.n_ctx; + + int n_drafted = 0; + int n_accept = 0; + + const int64_t t_start_ms = ggml_time_ms(); + + // Iterate over input tokens in chunks of size n_ctx. + // Each chunk is treated as if a sequential generation but with pre-determined tokens to ensure reproducibility. + for (int i_start = 0; i_start + n_ctx < n_input; i_start += n_ctx) { + const std::vector inp_slice(inp.begin() + i_start, inp.begin() + i_start + n_ctx); + std::vector pseudo_output; + pseudo_output.push_back(inp_slice[0]); + + while ((int) pseudo_output.size() < n_ctx) { + // Simulate drafting and decoding from draft: + std::vector draft; + draft.push_back(pseudo_output.back()); + + { + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_draft(pseudo_output, draft, n_draft, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, ngram_cache_context, ngram_cache_dynamic, ngram_cache_static); + t_draft_us += ggml_time_us() - t_start_draft_us; + } + + n_drafted += draft.size() - 1; + + for (size_t j = 1; j < draft.size() && (int) pseudo_output.size() < n_ctx; ++j) { + const llama_token ground_truth = inp_slice[pseudo_output.size()]; + const llama_token drafted = draft[j]; + + if (ground_truth != drafted) { + break; + } + + ++n_accept; + pseudo_output.push_back(ground_truth); + + { + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_update(ngram_cache_context, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, pseudo_output, 1, false); + t_draft_us += ggml_time_us() - t_start_draft_us; + } + } + + // After each simulated batch decoding simulate the sampling of a single token: + if ((int) pseudo_output.size() < n_ctx) { + pseudo_output.push_back(inp_slice[pseudo_output.size()]); + { + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_update(ngram_cache_context, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, pseudo_output, 1, false); + t_draft_us += ggml_time_us() - t_start_draft_us; + } + } + + draft.erase(draft.begin()); + + } + if (i_start > 0 && i_start / 100000 != (i_start - n_ctx) / 100000) { + const int64_t t_now_ms = ggml_time_ms(); + const int64_t eta_ms = (n_input - i_start) * (t_now_ms - t_start_ms) / i_start; + const int64_t eta_min = eta_ms / (60*1000); + const int64_t eta_s = (eta_ms - 60*1000*eta_min) / 1000; + + LOG_TEE("lookup-stats: %d/%d done, ETA: %02" PRId64 ":%02" PRId64 "\n", i_start, n_input, eta_min, eta_s); + } + + // After each chunk, update the dynamic ngram cache with the context ngram cache: + llama_ngram_cache_merge(ngram_cache_dynamic, ngram_cache_context); + ngram_cache_context.clear(); + } + + LOG_TEE("\n"); + + LOG_TEE("\n"); + LOG_TEE("n_draft = %d\n", n_draft); + LOG_TEE("n_predict = %d\n", n_input - n_input % n_ctx); + LOG_TEE("n_drafted = %d\n", n_drafted); + LOG_TEE("t_draft_flat = %.2f ms\n", t_draft_flat_us*1e-3); + LOG_TEE("t_draft = %.2f ms, %.2f us per token, %.2f tokens per second\n", + t_draft_us*1e-3, 1.0f*t_draft_us/n_drafted, n_drafted/(1e-6*t_draft_us)); + LOG_TEE("n_accept = %d\n", n_accept); + LOG_TEE("accept = %.3f%%\n", 100.0f * n_accept / n_drafted); + + llama_free(ctx); + llama_free_model(model); + + llama_backend_free(); + + fprintf(stderr, "\n\n"); + + return 0; +} diff --git a/examples/lookup/lookup.cpp b/examples/lookup/lookup.cpp index b53fae11045b8..2e8c35de31427 100644 --- a/examples/lookup/lookup.cpp +++ b/examples/lookup/lookup.cpp @@ -1,12 +1,15 @@ -#include "common.h" #include "ggml.h" #include "llama.h" +#include "common.h" +#include "ngram-cache.h" #include #include #include +#include #include #include +#include int main(int argc, char ** argv){ gpt_params params; @@ -15,11 +18,7 @@ int main(int argc, char ** argv){ return 1; } - // max/min n-grams size to search for in prompt - const int ngram_max = 4; - const int ngram_min = 1; - - // length of the candidate / draft sequence, if match is found + // max. number of additional tokens to draft if match is found const int n_draft = params.n_draft; const bool dump_kv_cache = params.dump_kv_cache; @@ -39,6 +38,8 @@ int main(int argc, char ** argv){ // load the model std::tie(model, ctx) = llama_init_from_gpt_params(params); + llama_set_rng_seed(ctx, params.seed); + GGML_ASSERT(llama_n_vocab(model) < (1 << 16)); // tokenize the prompt const bool add_bos = llama_should_add_bos_token(model); @@ -47,6 +48,35 @@ int main(int argc, char ** argv){ std::vector inp; inp = ::llama_tokenize(ctx, params.prompt, add_bos, true); + llama_ngram_cache ngram_cache_context; + llama_ngram_cache ngram_cache_dynamic; + llama_ngram_cache ngram_cache_static; + int64_t t_draft_flat_us = 0; + int64_t t_draft_us = 0; + + { + // Fill up context ngram cache with tokens from user input: + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_update(ngram_cache_context, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, inp, inp.size(), false); + + if (!params.lookup_cache_static.empty()) { + try { + ngram_cache_static = llama_ngram_cache_load(params.lookup_cache_static); + } catch (std::ifstream::failure const &) { + fprintf(stderr, "error: failed to open static lookup cache: %s", params.lookup_cache_static.c_str()); + exit(1); + } + } + + if (!params.lookup_cache_dynamic.empty()) { + try { + ngram_cache_dynamic = llama_ngram_cache_load(params.lookup_cache_dynamic); + } catch (std::ifstream::failure const &) {} // if the file does not exist it will simply be created at the end of the program + } + + t_draft_flat_us += ggml_time_us() - t_start_draft_us; + } + const int max_context_size = llama_n_ctx(ctx); const int max_tokens_list_size = max_context_size - 4; @@ -76,8 +106,6 @@ int main(int argc, char ** argv){ int n_drafted = 0; int n_accept = 0; - int64_t t_draft_us = 0; - int n_past = inp.size(); bool has_eos = false; @@ -129,6 +157,12 @@ int main(int argc, char ** argv){ ++n_past; ++i_dft; inp.push_back(id); + { + // Update context ngram cache with the newly accepted token: + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_update(ngram_cache_context, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, inp, 1, false); + t_draft_us += ggml_time_us() - t_start_draft_us; + } if (params.use_color) { // color accepted draft token @@ -149,6 +183,12 @@ int main(int argc, char ** argv){ draft.clear(); draft.push_back(id); inp.push_back(id); + { + // Update context ngram cache with the newly accepted token: + const int64_t t_start_draft_us = ggml_time_us(); + llama_ngram_cache_update(ngram_cache_context, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, inp, 1, false); + t_draft_us += ggml_time_us() - t_start_draft_us; + } break; } @@ -163,44 +203,19 @@ int main(int argc, char ** argv){ llama_batch_clear(batch_tgt); llama_batch_add(batch_tgt, draft[0], n_past, { 0 }, true); - // generate n_pred tokens through prompt lookup - auto prompt_lookup = [&]() -> void { - const int inp_size = inp.size(); - for (int ngram_size = ngram_max ; ngram_size > ngram_min; --ngram_size){ - const llama_token * ngram = &inp[inp_size - ngram_size]; - - for (int i = 0; i <= (int) inp_size - (ngram_size * 2); ++i) { - bool match = true; - for (int j = 0; j < ngram_size; ++j) { - if (inp[i + j] != ngram[j]) { - match = false; - break; - } - } - - if (match) { - const int startIdx = i + ngram_size; - const int endIdx = startIdx + n_draft; - if (endIdx < inp_size) { - for (int j = startIdx; j < endIdx; ++j) { - LOG(" - draft candidate %d: %d\n", j, inp[j]); - draft.push_back(inp[j]); - llama_batch_add(batch_tgt, inp[j], n_past + (j - startIdx) + 1, { 0 }, true); - ++n_drafted; - } - return; - } - } - } - } - return; - }; - + // Draft already contains a single token sampled from the model: + GGML_ASSERT(draft.size() == 1); + GGML_ASSERT(draft[0] == inp.back()); const int64_t t_start_draft_us = ggml_time_us(); - prompt_lookup(); + llama_ngram_cache_draft(inp, draft, n_draft, LLAMA_NGRAM_MIN, LLAMA_NGRAM_MAX, ngram_cache_context, ngram_cache_dynamic, ngram_cache_static); + + for (size_t i = 1; i < draft.size(); ++i) { + llama_batch_add(batch_tgt, draft[i], n_past + i, { 0 }, true); + } t_draft_us += ggml_time_us() - t_start_draft_us; + n_drafted += draft.size() - 1; llama_decode(ctx, batch_tgt); ++n_past; @@ -210,19 +225,24 @@ int main(int argc, char ** argv){ auto t_dec_end = ggml_time_us(); + // Update dynamic ngram cache with context ngram cache and save it to disk: + llama_ngram_cache_merge(ngram_cache_dynamic, ngram_cache_context); + llama_ngram_cache_save(ngram_cache_dynamic, params.lookup_cache_dynamic); + LOG_TEE("\n\n"); LOG_TEE("encoded %4d tokens in %8.3f seconds, speed: %8.3f t/s\n", n_input, (t_enc_end - t_enc_start) / 1e6f, inp.size() / ((t_enc_end - t_enc_start) / 1e6f)); LOG_TEE("decoded %4d tokens in %8.3f seconds, speed: %8.3f t/s\n", n_predict, (t_dec_end - t_dec_start) / 1e6f, n_predict / ((t_dec_end - t_dec_start) / 1e6f)); LOG_TEE("\n"); - LOG_TEE("n_draft = %d\n", n_draft); - LOG_TEE("n_predict = %d\n", n_predict); - LOG_TEE("n_drafted = %d\n", n_drafted); - LOG_TEE("t_draft = %.2f ms, %.2f us per token, %.2f tokens per second\n", + LOG_TEE("n_draft = %d\n", n_draft); + LOG_TEE("n_predict = %d\n", n_predict); + LOG_TEE("n_drafted = %d\n", n_drafted); + LOG_TEE("t_draft_flat = %.2f ms\n", t_draft_flat_us*1e-3); + LOG_TEE("t_draft = %.2f ms, %.2f us per token, %.2f tokens per second\n", t_draft_us*1e-3, 1.0f*t_draft_us/n_drafted, n_drafted/(1e-6*t_draft_us)); - LOG_TEE("n_accept = %d\n", n_accept); - LOG_TEE("accept = %.3f%%\n", 100.0f * n_accept / n_drafted); + LOG_TEE("n_accept = %d\n", n_accept); + LOG_TEE("accept = %.3f%%\n", 100.0f * n_accept / n_drafted); LOG_TEE("\ntarget:\n"); llama_print_timings(ctx); diff --git a/examples/main-cmake-pkg/README.md b/examples/main-cmake-pkg/README.md index 6d665f28fe9bd..f599fbaec46b5 100644 --- a/examples/main-cmake-pkg/README.md +++ b/examples/main-cmake-pkg/README.md @@ -8,7 +8,7 @@ Because this example is "outside of the source tree", it is important to first b ### Considerations -When hardware acceleration libraries are used (e.g. CUBlas, Metal, CLBlast, etc.), CMake must be able to locate the associated CMake package. In the example below, when building _main-cmake-pkg_ notice the `CMAKE_PREFIX_PATH` includes the Llama CMake package location _in addition to_ the CLBlast package—which was used when compiling _llama.cpp_. +When hardware acceleration libraries are used (e.g. CUDA, Metal, CLBlast, etc.), CMake must be able to locate the associated CMake package. In the example below, when building _main-cmake-pkg_ notice the `CMAKE_PREFIX_PATH` includes the Llama CMake package location _in addition to_ the CLBlast package—which was used when compiling _llama.cpp_. ### Build llama.cpp and install to C:\LlamaCPP directory diff --git a/examples/main/README.md b/examples/main/README.md index 7f84e42623274..bb696b5620198 100644 --- a/examples/main/README.md +++ b/examples/main/README.md @@ -67,6 +67,7 @@ main.exe -m models\7B\ggml-model.bin --ignore-eos -n -1 --random-prompt In this section, we cover the most commonly used options for running the `main` program with the LLaMA models: - `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`). +- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf). - `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses. - `-ins, --instruct`: Run the program in instruction mode, which is particularly useful when working with Alpaca models. - `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text. @@ -295,7 +296,9 @@ These options help improve the performance and memory usage of the LLaMA models. ### Batch Size -- `-b N, --batch-size N`: Set the batch size for prompt processing (default: 512). This large batch size benefits users who have BLAS installed and enabled it during the build. If you don't have BLAS enabled ("BLAS=0"), you can use a smaller number, such as 8, to see the prompt progress as it's evaluated in some situations. +- `-b N, --batch-size N`: Set the batch size for prompt processing (default: `2048`). This large batch size benefits users who have BLAS installed and enabled it during the build. If you don't have BLAS enabled ("BLAS=0"), you can use a smaller number, such as 8, to see the prompt progress as it's evaluated in some situations. + +- `-ub N`, `--ubatch-size N`: physical maximum batch size. This is for pipeline parallelization. Default: `512`. ### Prompt Caching @@ -315,8 +318,8 @@ These options provide extra functionality and customization when running the LLa - `-h, --help`: Display a help message showing all available options and their default values. This is particularly useful for checking the latest options and default values, as they can change frequently, and the information in this document may become outdated. - `--verbose-prompt`: Print the prompt before generating text. -- `-ngl N, --n-gpu-layers N`: When compiled with appropriate support (currently CLBlast or cuBLAS), this option allows offloading some layers to the GPU for computation. Generally results in increased performance. -- `-mg i, --main-gpu i`: When using multiple GPUs this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default GPU 0 is used. Requires cuBLAS. -- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance. Requires cuBLAS. +- `-ngl N, --n-gpu-layers N`: When compiled with GPU support, this option allows offloading some layers to the GPU for computation. Generally results in increased performance. +- `-mg i, --main-gpu i`: When using multiple GPUs this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default GPU 0 is used. +- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance. - `--lora FNAME`: Apply a LoRA (Low-Rank Adaptation) adapter to the model (implies --no-mmap). This allows you to adapt the pretrained model to specific tasks or domains. - `--lora-base FNAME`: Optional model to use as a base for the layers modified by the LoRA adapter. This flag is used in conjunction with the `--lora` flag, and specifies the base model for the adaptation. diff --git a/examples/main/main.cpp b/examples/main/main.cpp index 8293dfa5f224c..6e57514d54a50 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -236,7 +236,7 @@ int main(int argc, char ** argv) { // The file exists and is not empty session_tokens.resize(n_ctx); size_t n_token_count_out = 0; - if (!llama_load_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.capacity(), &n_token_count_out)) { + if (!llama_state_load_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.capacity(), &n_token_count_out)) { LOG_TEE("%s: error: failed to load session file '%s'\n", __func__, path_session.c_str()); return 1; } @@ -694,7 +694,7 @@ int main(int argc, char ** argv) { // optionally save the session on first sample (for faster prompt loading next time) if (!path_session.empty() && need_to_save_session && !params.prompt_cache_ro) { need_to_save_session = false; - llama_save_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size()); + llama_state_save_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size()); LOG("saved session to %s\n", path_session.c_str()); } @@ -936,7 +936,7 @@ int main(int argc, char ** argv) { if (!path_session.empty() && params.prompt_cache_all && !params.prompt_cache_ro) { LOG_TEE("\n%s: saving final output to session file '%s'\n", __func__, path_session.c_str()); - llama_save_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size()); + llama_state_save_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size()); } llama_print_timings(ctx); diff --git a/examples/parallel/parallel.cpp b/examples/parallel/parallel.cpp index 6c8a6661ebacc..c7a290371cdd5 100644 --- a/examples/parallel/parallel.cpp +++ b/examples/parallel/parallel.cpp @@ -134,7 +134,6 @@ int main(int argc, char ** argv) { llama_context * ctx = NULL; // load the target model - params.logits_all = true; std::tie(model, ctx) = llama_init_from_gpt_params(params); // load the prompts from an external file if there are any diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp index 322c0280d9aa1..d01b0fd9c0de9 100644 --- a/examples/perplexity/perplexity.cpp +++ b/examples/perplexity/perplexity.cpp @@ -381,6 +381,7 @@ static results_perplexity perplexity_v2(llama_context * ctx, const gpt_params & const int batch_size = std::min(end - batch_start, n_batch); //fprintf(stderr, " Batch %d: starts at %d, size is %d, n_past is %d\n",j,batch_start,batch_size,j * n_batch); + // TODO: use llama_batch.logits instead of relying on logits_all == true if (llama_decode(ctx, llama_batch_get_one(tokens.data() + batch_start, batch_size, j * n_batch, 0))) { //fprintf(stderr, "%s : failed to eval\n", __func__); return {tokens, -1, logit_history, prob_history}; @@ -553,6 +554,8 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par const int batch_start = start + j * n_batch; const int batch_size = std::min(end - batch_start, n_batch); + int n_outputs = 0; + batch.n_tokens = 0; for (int seq = 0; seq < n_seq_batch; seq++) { int seq_start = batch_start + seq*n_ctx; @@ -567,11 +570,13 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par for (int k = 0; k < batch_size; ++k) { const int idx = seq*n_ctx + k; - batch.token[idx] = tokens[seq_start + k]; - batch.pos[idx] = j*n_batch + k; - batch.n_seq_id[idx] = 1; - batch.seq_id[idx][0] = seq; - batch.logits[idx] = batch.pos[idx] >= first ? 1 : 0; + batch.token [idx] = tokens[seq_start + k]; + batch.pos [idx] = j*n_batch + k; + batch.n_seq_id[idx] = 1; + batch.seq_id [idx][0] = seq; + batch.logits [idx] = batch.pos[idx] >= first ? 1 : 0; + + n_outputs += batch.logits[idx] != 0; } batch.n_tokens += batch_size; @@ -584,9 +589,9 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par return {tokens, -1, logit_history, prob_history}; } - if (num_batches > 1) { + if (num_batches > 1 && n_outputs > 0) { const auto * batch_logits = llama_get_logits(ctx); - logits.insert(logits.end(), batch_logits, batch_logits + batch_size * n_vocab); + logits.insert(logits.end(), batch_logits, batch_logits + n_outputs * n_vocab); } } @@ -605,14 +610,15 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par } for (int seq = 0; seq < n_seq_batch; seq++) { - const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx); + const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx + first); + llama_token * tokens_data = tokens.data() + start + seq*n_ctx + first; if (!params.logits_file.empty()) { - process_logits(logits_stream, n_vocab, all_logits + first*n_vocab, + process_logits(logits_stream, n_vocab, all_logits, tokens_data, n_ctx - 1 - first, workers, log_probs, nll, nll2); } else { - process_logits(n_vocab, all_logits + first*n_vocab, + process_logits(n_vocab, all_logits, tokens_data, n_ctx - 1 - first, workers, nll, nll2, logit_history.data() + start + seq*n_ctx + first, @@ -653,6 +659,7 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par } static bool decode_helper(llama_context * ctx, llama_batch & batch, std::vector & batch_logits, int32_t n_batch, int32_t n_vocab) { + int prev_outputs = 0; for (int32_t i = 0; i < (int32_t) batch.n_tokens; i += n_batch) { const int32_t n_tokens = std::min(n_batch, (int32_t) (batch.n_tokens - i)); @@ -673,7 +680,14 @@ static bool decode_helper(llama_context * ctx, llama_batch & batch, std::vector< return false; } - memcpy(batch_logits.data() + i*n_vocab, llama_get_logits(ctx), n_tokens*n_vocab*sizeof(float)); + int n_outputs = 0; + for (int i = 0; i < n_tokens; ++i) { + n_outputs += batch_view.logits[i] != 0; + } + + memcpy(batch_logits.data() + prev_outputs*n_vocab, llama_get_logits(ctx), n_outputs*n_vocab*sizeof(float)); + + prev_outputs += n_outputs; } return true; @@ -780,7 +794,7 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { size_t ending_logprob_count[4]; double ending_logprob[4]; - size_t i_batch; // starting index in the llama_batch + size_t i_logits; // starting index of logits in the llama_batch size_t common_prefix; // max number of initial tokens that are the same in all sentences size_t required_tokens; // needed number of tokens to evaluate all 4 endings std::vector seq_tokens[4]; @@ -845,9 +859,10 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { const int max_tasks_per_batch = 32; const int max_seq = std::min(4*max_tasks_per_batch, (int) llama_n_seq_max(ctx)); - llama_batch batch = llama_batch_init(n_ctx, 0, max_seq); + llama_batch batch = llama_batch_init(n_ctx, 0, 4); std::vector tok_logits(n_vocab); + // TODO: this could be made smaller; it's currently the worst-case size std::vector batch_logits(n_vocab*n_ctx); std::vector> eval_pairs; @@ -858,16 +873,17 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { int n_cur = 0; size_t i1 = i0; - size_t i_batch = 0; // this tells us where in `llama_batch` we are currently + size_t i_logits = 0; // this tells us how many logits were needed before this point in the batch llama_batch_clear(batch); // batch as much tasks as possible into the available context - // each task has 4 unique seuqnce ids - one for each ending + // each task has 4 unique sequence ids - one for each ending // the common prefix is shared among the 4 sequences to save tokens // we extract logits only from the last common token and from all ending tokens of each sequence while (n_cur + (int) hs_data[i1].required_tokens <= n_ctx) { auto & hs_cur = hs_data[i1]; + int n_logits = 0; const int s0 = 4*(i1 - i0); if (s0 + 4 > max_seq) { @@ -875,18 +891,23 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { } for (size_t i = 0; i < hs_cur.common_prefix; ++i) { - llama_batch_add(batch, hs_cur.seq_tokens[0][i], i, { s0 + 0, s0 + 1, s0 + 2, s0 + 3}, false); + llama_batch_add(batch, hs_cur.seq_tokens[0][i], i, { s0 + 0, s0 + 1, s0 + 2, s0 + 3 }, false); } batch.logits[batch.n_tokens - 1] = true; // we need logits for the last token of the common prefix + n_logits += 1; for (int s = 0; s < 4; ++s) { - for (size_t i = hs_cur.common_prefix; i < hs_cur.seq_tokens[s].size(); ++i) { - llama_batch_add(batch, hs_cur.seq_tokens[s][i], i, { s0 + s }, true); + const size_t seq_tokens_size = hs_cur.seq_tokens[s].size(); + // TODO: don't evaluate the last token of each sequence + for (size_t i = hs_cur.common_prefix; i < seq_tokens_size; ++i) { + const bool needs_logits = i < seq_tokens_size - 1; + llama_batch_add(batch, hs_cur.seq_tokens[s][i], i, { s0 + s }, needs_logits); + n_logits += needs_logits; } } - hs_cur.i_batch = i_batch; - i_batch += hs_cur.required_tokens; + hs_cur.i_logits = i_logits; + i_logits += n_logits; n_cur += hs_data[i1].required_tokens; if (++i1 == hs_task_count) { @@ -912,12 +933,11 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { eval_pairs.clear(); for (size_t i = i0; i < i1; ++i) { auto & hs_cur = hs_data[i]; - size_t li = hs_cur.common_prefix; + size_t li = 1; // skip the last logit of the common prefix (computed separately below) for (int s = 0; s < 4; ++s) { for (size_t j = hs_cur.common_prefix; j < hs_cur.seq_tokens[s].size() - 1; j++) { - eval_pairs.emplace_back(hs_cur.i_batch + li++, hs_cur.seq_tokens[s][j + 1]); + eval_pairs.emplace_back(hs_cur.i_logits + li++, hs_cur.seq_tokens[s][j + 1]); } - ++li; } } // Then we do the actual calculation @@ -929,7 +949,8 @@ static void hellaswag_score(llama_context * ctx, const gpt_params & params) { for (size_t i = i0; i < i1; ++i) { auto & hs_cur = hs_data[i]; - std::memcpy(tok_logits.data(), batch_logits.data() + n_vocab*(hs_cur.i_batch + hs_cur.common_prefix - 1), n_vocab*sizeof(float)); + // get the logits of the last token of the common prefix + std::memcpy(tok_logits.data(), batch_logits.data() + n_vocab*hs_cur.i_logits, n_vocab*sizeof(float)); const auto first_probs = softmax(tok_logits); @@ -979,7 +1000,7 @@ struct winogrande_entry { std::array choices; int answer; - size_t i_batch; + size_t i_logits; size_t common_prefix; size_t required_tokens; size_t n_base1; // number of tokens for context + choice 1 @@ -1105,6 +1126,7 @@ static void winogrande_score(llama_context * ctx, const gpt_params & params) { task.common_prefix++; } + // TODO: the last token of each of the sequences don't need to be evaluated task.required_tokens = task.common_prefix + task.seq_tokens[0].size() - task.common_prefix + task.seq_tokens[1].size() - task.common_prefix; @@ -1122,9 +1144,10 @@ static void winogrande_score(llama_context * ctx, const gpt_params & params) { const int max_tasks_per_batch = 128; const int max_seq = std::min(2*max_tasks_per_batch, (int) llama_n_seq_max(ctx)); - llama_batch batch = llama_batch_init(n_ctx, 0, max_seq); + llama_batch batch = llama_batch_init(n_ctx, 0, 2); std::vector tok_logits(n_vocab); + // TODO: this could be made smaller; it's currently the worst-case size std::vector batch_logits(n_vocab*n_ctx); std::vector> eval_pairs; @@ -1138,29 +1161,33 @@ static void winogrande_score(llama_context * ctx, const gpt_params & params) { int n_cur = 0; size_t i1 = i0; - size_t i_batch = 0; + size_t i_logits = 0; llama_batch_clear(batch); while (n_cur + (int) data[i1].required_tokens <= n_ctx) { + int n_logits = 0; const int s0 = 2*(i1 - i0); if (s0 + 2 > max_seq) { break; } for (size_t i = 0; i < data[i1].common_prefix; ++i) { - llama_batch_add(batch, data[i1].seq_tokens[0][i], i, { s0 + 0, s0 + 1}, false); + llama_batch_add(batch, data[i1].seq_tokens[0][i], i, { s0 + 0, s0 + 1 }, false); } batch.logits[batch.n_tokens - 1] = true; + n_logits += 1; for (int s = 0; s < 2; ++s) { + // TODO: end before the last token, no need to predict past the end of the sequences for (size_t i = data[i1].common_prefix; i < data[i1].seq_tokens[s].size(); ++i) { llama_batch_add(batch, data[i1].seq_tokens[s][i], i, { s0 + s }, true); + n_logits += 1; } } - data[i1].i_batch = i_batch; - i_batch += data[i1].required_tokens; + data[i1].i_logits = i_logits; + i_logits += n_logits; n_cur += data[i1].required_tokens; if (++i1 == data.size()) { @@ -1191,15 +1218,16 @@ static void winogrande_score(llama_context * ctx, const gpt_params & params) { const auto& n_base1 = skip_choice ? task.n_base1 : task.common_prefix; const int last_1st = task.seq_tokens[0].size() - n_base1 > 1 ? 1 : 0; - size_t li = n_base1 - 1; + size_t li = n_base1 - task.common_prefix; for (size_t j = n_base1-1; j < task.seq_tokens[0].size()-1-last_1st; ++j) { - eval_pairs.emplace_back(task.i_batch + li++, task.seq_tokens[0][j+1]); + eval_pairs.emplace_back(task.i_logits + li++, task.seq_tokens[0][j+1]); } const auto& n_base2 = skip_choice ? task.n_base2 : task.common_prefix; const int last_2nd = task.seq_tokens[1].size() - n_base2 > 1 ? 1 : 0; - li = task.seq_tokens[0].size() - task.common_prefix + n_base2 - 1; + // FIXME: this uses the wrong first logits when not skipping the choice word + li = task.seq_tokens[0].size() - task.common_prefix + n_base2 - task.common_prefix; for (size_t j = n_base2-1; j < task.seq_tokens[1].size()-1-last_2nd; ++j) { - eval_pairs.emplace_back(task.i_batch + li++, task.seq_tokens[1][j+1]); + eval_pairs.emplace_back(task.i_logits + li++, task.seq_tokens[1][j+1]); } } compute_logprobs(batch_logits.data(), n_vocab, workers, eval_pairs, eval_results); @@ -1288,7 +1316,7 @@ struct multiple_choice_task { } // For evaluation - size_t i_batch; // starting index in the llama_batch + size_t i_logits; // starting index of logits in the llama_batch size_t common_prefix; // max number of initial tokens that are the same in all sentences size_t required_tokens; // needed number of tokens to evaluate all answers std::vector> seq_tokens; @@ -1367,7 +1395,7 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params std::vector task_pos(n_task); strstream.read((char *)task_pos.data(), task_pos.size()*sizeof(uint32_t)); if (strstream.fail()) { - printf("%s: failed to raad task positions from prompt\n", __func__); + printf("%s: failed to read task positions from prompt\n", __func__); return; } @@ -1448,7 +1476,7 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params return; } } else { - int n_dot = n_task/100; + int n_dot = std::max((int) n_task/100, 1); int i_task = 0; for (auto& task : tasks) { ++i_task; @@ -1492,17 +1520,18 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params int n_cur = 0; size_t i1 = i0; - size_t i_batch = 0; // this tells us where in `llama_batch` we are currently + size_t i_logits = 0; // this tells us how many logits were needed before this point in the batch llama_batch_clear(batch); // batch as much tasks as possible into the available context - // each task has 4 unique seuqnce ids - one for each ending + // each task has 4 unique sequence ids - one for each ending // the common prefix is shared among the 4 sequences to save tokens // we extract logits only from the last common token and from all ending tokens of each sequence int s0 = 0; while (n_cur + (int) tasks[i1].required_tokens <= n_ctx) { auto& cur_task = tasks[i1]; + int n_logits = 0; int num_answers = cur_task.seq_tokens.size(); if (s0 + num_answers > max_seq) { @@ -1519,17 +1548,22 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params llama_batch_add(batch, cur_task.seq_tokens[0][i], i, batch_indeces, false); } batch.logits[batch.n_tokens - 1] = true; // we need logits for the last token of the common prefix + n_logits += 1; for (int s = 0; s < int(cur_task.seq_tokens.size()); ++s) { - for (size_t i = cur_task.common_prefix; i < cur_task.seq_tokens[s].size(); ++i) { - llama_batch_add(batch, cur_task.seq_tokens[s][i], i, { s0 + s }, true); + const size_t seq_tokens_size = cur_task.seq_tokens[s].size(); + // TODO: don't evaluate the last token of each sequence + for (size_t i = cur_task.common_prefix; i < seq_tokens_size; ++i) { + const bool needs_logits = i < seq_tokens_size - 1; + llama_batch_add(batch, cur_task.seq_tokens[s][i], i, { s0 + s }, needs_logits); + n_logits += needs_logits; } } s0 += num_answers; - cur_task.i_batch = i_batch; - i_batch += cur_task.required_tokens; + cur_task.i_logits = i_logits; + i_logits += n_logits; n_cur += cur_task.required_tokens; if (++i1 == tasks.size()) { @@ -1555,12 +1589,11 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params eval_pairs.clear(); for (size_t i = i0; i < i1; ++i) { auto& cur_task = tasks[i]; - size_t li = cur_task.common_prefix; + size_t li = 1; // skip the last logit of the common prefix (computed separately below) for (int s = 0; s < int(cur_task.seq_tokens.size()); ++s) { for (size_t j = cur_task.common_prefix; j < cur_task.seq_tokens[s].size() - 1; j++) { - eval_pairs.emplace_back(cur_task.i_batch + li++, cur_task.seq_tokens[s][j + 1]); + eval_pairs.emplace_back(cur_task.i_logits + li++, cur_task.seq_tokens[s][j + 1]); } - ++li; } } // Then we do the actual calculation @@ -1579,7 +1612,8 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params //} //printf("\n common_prefix: %zu\n", cur_task.common_prefix); - std::memcpy(tok_logits.data(), batch_logits.data() + n_vocab*(cur_task.i_batch + cur_task.common_prefix - 1), n_vocab*sizeof(float)); + // get the logits of the last token of the common prefix + std::memcpy(tok_logits.data(), batch_logits.data() + n_vocab*cur_task.i_logits, n_vocab*sizeof(float)); const auto first_probs = softmax(tok_logits); @@ -1731,6 +1765,7 @@ static void kl_divergence(llama_context * ctx, const gpt_params & params) { tokens[batch_start] = llama_token_bos(llama_get_model(ctx)); } + // TODO: use llama_batch.logits instead of relying on logits_all == true if (llama_decode(ctx, llama_batch_get_one(tokens.data() + batch_start, batch_size, j * n_batch, 0))) { fprintf(stderr, "%s : failed to eval\n", __func__); return; diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 6ae5180cf2f7d..1fd6c67d78a8a 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -27,6 +27,7 @@ static const std::vector QUANT_OPTIONS = { { "IQ2_S", LLAMA_FTYPE_MOSTLY_IQ2_S, " 2.5 bpw quantization", }, { "IQ2_M", LLAMA_FTYPE_MOSTLY_IQ2_M, " 2.7 bpw quantization", }, { "IQ1_S", LLAMA_FTYPE_MOSTLY_IQ1_S, " 1.56 bpw quantization", }, + { "IQ1_M", LLAMA_FTYPE_MOSTLY_IQ1_M, " 1.75 bpw quantization", }, { "Q2_K", LLAMA_FTYPE_MOSTLY_Q2_K, " 2.63G, +0.6717 ppl @ LLaMA-v1-7B", }, { "Q2_K_S", LLAMA_FTYPE_MOSTLY_Q2_K_S, " 2.16G, +9.0634 ppl @ LLaMA-v1-7B", }, { "IQ3_XXS",LLAMA_FTYPE_MOSTLY_IQ3_XXS," 3.06 bpw quantization", }, @@ -88,13 +89,17 @@ static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftyp // [[noreturn]] static void usage(const char * executable) { - printf("usage: %s [--help] [--allow-requantize] [--leave-output-tensor] [--pure] [--imatrix] [--include-weights] [--exclude-weights] model-f32.gguf [model-quant.gguf] type [nthreads]\n\n", executable); + printf("usage: %s [--help] [--allow-requantize] [--leave-output-tensor] [--pure] [--imatrix] [--include-weights] [--exclude-weights] [--output-tensor-type] [--token-embedding-type] [--override-kv] model-f32.gguf [model-quant.gguf] type [nthreads]\n\n", executable); printf(" --allow-requantize: Allows requantizing tensors that have already been quantized. Warning: This can severely reduce quality compared to quantizing from 16bit or 32bit\n"); printf(" --leave-output-tensor: Will leave output.weight un(re)quantized. Increases model size but may also increase quality, especially when requantizing\n"); printf(" --pure: Disable k-quant mixtures and quantize all tensors to the same type\n"); printf(" --imatrix file_name: use data in file_name as importance matrix for quant optimizations\n"); printf(" --include-weights tensor_name: use importance matrix for this/these tensor(s)\n"); printf(" --exclude-weights tensor_name: use importance matrix for this/these tensor(s)\n"); + printf(" --output-tensor-type ggml_type: use this ggml_type for the output.weight tensor\n"); + printf(" --token-embedding-type ggml_type: use this ggml_type for the token embeddings tensor\n"); + printf(" --override-kv KEY=TYPE:VALUE\n"); + printf(" Advanced option to override model metadata by key in the quantized model. May be specified multiple times.\n"); printf("Note: --include-weights and --exclude-weights cannot be used together\n"); printf("\nAllowed quantization types:\n"); for (auto & it : QUANT_OPTIONS) { @@ -108,56 +113,60 @@ static void usage(const char * executable) { exit(1); } -static void load_imatrix(const std::string& imatrix_file, std::unordered_map>& imatrix_data) { +static void load_imatrix(const std::string & imatrix_file, std::unordered_map> & imatrix_data) { std::ifstream in(imatrix_file.c_str(), std::ios::binary); if (!in) { - printf("%s: failed to open %s\n",__func__,imatrix_file.c_str()); - return; + printf("%s: failed to open %s\n",__func__, imatrix_file.c_str()); + exit(1); } int n_entries; - in.read((char*)&n_entries, sizeof(n_entries)); + in.read((char *)&n_entries, sizeof(n_entries)); if (in.fail() || n_entries < 1) { printf("%s: no data in file %s\n", __func__, imatrix_file.c_str()); - return; + exit(1); } for (int i = 0; i < n_entries; ++i) { int len; in.read((char *)&len, sizeof(len)); std::vector name_as_vec(len+1); in.read((char *)name_as_vec.data(), len); if (in.fail()) { - printf("%s: failed reading name for entry %d from %s\n",__func__,i+1,imatrix_file.c_str()); - return; + printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str()); + exit(1); } name_as_vec[len] = 0; std::string name{name_as_vec.data()}; - auto& e = imatrix_data[std::move(name)]; + auto & e = imatrix_data[name]; int ncall; - in.read((char*)&ncall, sizeof(ncall)); + in.read((char *)&ncall, sizeof(ncall)); int nval; in.read((char *)&nval, sizeof(nval)); if (in.fail() || nval < 1) { - printf("%s: failed reading number of values for entry %d\n",__func__,i); + printf("%s: failed reading number of values for entry %d\n", __func__, i); imatrix_data = {}; - return; + exit(1); } e.resize(nval); - in.read((char*)e.data(), nval*sizeof(float)); + in.read((char *)e.data(), nval*sizeof(float)); if (in.fail()) { - printf("%s: failed reading data for entry %d\n",__func__,i); + printf("%s: failed reading data for entry %d\n", __func__, i); imatrix_data = {}; - return; + exit(1); } if (ncall > 0) { for (auto& v : e) v /= ncall; } + + if (getenv("LLAMA_TRACE")) { + printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), ncall, name.c_str()); + } } - printf("%s: loaded %d importance matrix entries from %s\n",__func__,int(imatrix_data.size()),imatrix_file.c_str()); + printf("%s: loaded %d importance matrix entries from %s\n", __func__, int(imatrix_data.size()), imatrix_file.c_str()); } -static void prepare_imatrix(const std::string& imatrix_file, - const std::vector& included_weights, - const std::vector& excluded_weights, - std::unordered_map>& imatrix_data) { +static void prepare_imatrix(const std::string & imatrix_file, + const std::vector & included_weights, + const std::vector & excluded_weights, + std::unordered_map> & imatrix_data) { if (!imatrix_file.empty()) { load_imatrix(imatrix_file, imatrix_data); } @@ -190,6 +199,55 @@ static void prepare_imatrix(const std::string& imatrix_file, } } +static ggml_type parse_ggml_type(const char * arg) { + ggml_type result = GGML_TYPE_COUNT; + for (int j = 0; j < GGML_TYPE_COUNT; ++j) { + auto type = ggml_type(j); + const auto * name = ggml_type_name(type); + if (name && strcmp(arg, name) == 0) { + result = type; break; + } + } + return result; +} + +static bool parse_kv_override(const char * data, std::vector & overrides) { + const char* sep = strchr(data, '='); + if (sep == nullptr || sep - data >= 128) { + fprintf(stderr, "%s: malformed KV override '%s'\n", __func__, data); + return false; + } + llama_model_kv_override kvo; + std::strncpy(kvo.key, data, sep - data); + kvo.key[sep - data] = 0; + sep++; + if (strncmp(sep, "int:", 4) == 0) { + sep += 4; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; + kvo.int_value = std::atol(sep); + } else if (strncmp(sep, "float:", 6) == 0) { + sep += 6; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; + kvo.float_value = std::atof(sep); + } else if (strncmp(sep, "bool:", 5) == 0) { + sep += 5; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; + if (std::strcmp(sep, "true") == 0) { + kvo.bool_value = true; + } else if (std::strcmp(sep, "false") == 0) { + kvo.bool_value = false; + } else { + fprintf(stderr, "%s: invalid boolean value for KV override '%s'\n", __func__, data); + return false; + } + } else { + fprintf(stderr, "%s: invalid type for KV override '%s'\n", __func__, data); + return false; + } + overrides.emplace_back(std::move(kvo)); + return true; +} + int main(int argc, char ** argv) { if (argc < 3) { usage(argv[0]); @@ -200,10 +258,27 @@ int main(int argc, char ** argv) { int arg_idx = 1; std::string imatrix_file; std::vector included_weights, excluded_weights; + std::vector kv_overrides; for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) { if (strcmp(argv[arg_idx], "--leave-output-tensor") == 0) { params.quantize_output_tensor = false; + } else if (strcmp(argv[arg_idx], "--output-tensor-type") == 0) { + if (arg_idx < argc-1) { + params.output_tensor_type = parse_ggml_type(argv[++arg_idx]); + } else { + usage(argv[0]); + } + } else if (strcmp(argv[arg_idx], "--token-embedding-type") == 0) { + if (arg_idx < argc-1) { + params.token_embedding_type = parse_ggml_type(argv[++arg_idx]); + } else { + usage(argv[0]); + } + } else if (strcmp(argv[arg_idx], "--override-kv") == 0) { + if (arg_idx == argc-1 || !parse_kv_override(argv[++arg_idx], kv_overrides)) { + usage(argv[0]); + } } else if (strcmp(argv[arg_idx], "--allow-requantize") == 0) { params.allow_requantize = true; } else if (strcmp(argv[arg_idx], "--pure") == 0) { @@ -244,6 +319,11 @@ int main(int argc, char ** argv) { if (!imatrix_data.empty()) { params.imatrix = &imatrix_data; } + if (!kv_overrides.empty()) { + kv_overrides.emplace_back(); + kv_overrides.back().key[0] = 0; + params.kv_overrides = &kv_overrides; + } llama_backend_init(); @@ -265,8 +345,7 @@ int main(int argc, char ** argv) { if (ftype_str == "COPY") { params.only_copy = true; } - } - else { + } else { fname_out = argv[arg_idx]; arg_idx++; @@ -297,10 +376,12 @@ int main(int argc, char ** argv) { if ((params.ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS || params.ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || params.ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || - params.ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S || params.ftype == LLAMA_FTYPE_MOSTLY_IQ1_S) && imatrix_data.empty()) { - fprintf(stderr, "\n===============================================================================================\n"); - fprintf(stderr, "Please do not use IQ1_S, IQ2_XXS, IQ2_XS or Q2_K_S quantization without an importance matrix\n"); - fprintf(stderr, "===============================================================================================\n\n\n"); + params.ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S || + params.ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || + params.ftype == LLAMA_FTYPE_MOSTLY_IQ1_M) && imatrix_data.empty()) { + fprintf(stderr, "\n==========================================================================================================\n"); + fprintf(stderr, "Please do not use IQ1_S, IQ1_M, IQ2_S, IQ2_XXS, IQ2_XS or Q2_K_S quantization without an importance matrix\n"); + fprintf(stderr, "==========================================================================================================\n\n\n"); return 1; } diff --git a/examples/regex-to-grammar.py b/examples/regex-to-grammar.py new file mode 100644 index 0000000000000..c98118e95a858 --- /dev/null +++ b/examples/regex-to-grammar.py @@ -0,0 +1,20 @@ +import json, subprocess, sys, os + +assert len(sys.argv) >= 2 +[_, pattern, *rest] = sys.argv + +print(subprocess.check_output( + [ + "python", + os.path.join( + os.path.dirname(os.path.realpath(__file__)), + "json-schema-to-grammar.py"), + *rest, + "-", + "--raw-pattern", + ], + text=True, + input=json.dumps({ + "type": "string", + "pattern": pattern, + }, indent=2))) diff --git a/examples/retrieval/CMakeLists.txt b/examples/retrieval/CMakeLists.txt new file mode 100644 index 0000000000000..eaabae08d5583 --- /dev/null +++ b/examples/retrieval/CMakeLists.txt @@ -0,0 +1,5 @@ +set(TARGET retrieval) +add_executable(${TARGET} retrieval.cpp) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_11) diff --git a/examples/retrieval/README.md b/examples/retrieval/README.md new file mode 100644 index 0000000000000..2b2595c468046 --- /dev/null +++ b/examples/retrieval/README.md @@ -0,0 +1,69 @@ +# llama.cpp/examples/retrieval + +Demonstration of simple retrieval technique based on cosine similarity + +More info: +https://github.com/ggerganov/llama.cpp/pull/6193 + +### How to use + +`retieval.cpp` has parameters of its own: +- `--context-file`: file to be embedded - state this option multiple times to embed multiple files +- `--chunk-size`: minimum size of each text chunk to be embedded +- `--chunk-separator`: STRING to divide chunks by. newline by default + +`retrieval` example can be tested as follows: + +```bash +make -j && ./retrieval --model ./models/bge-base-en-v1.5-f16.gguf --top-k 3 --context-file README.md --context-file License --chunk-size 100 --chunk-separator . +``` + +This chunks and embeds all given files and starts a loop requesting query inputs: + +``` +Enter query: +``` + +On each query input, top k chunks are shown along with file name, chunk position within file and original text: + +``` +Enter query: describe the mit license +batch_decode: n_tokens = 6, n_seq = 1 +Top 3 similar chunks: +filename: README.md +filepos: 119 +similarity: 0.762334 +textdata: +png) + +[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT) + +[Roadmap](https://github. +-------------------- +filename: License +filepos: 0 +similarity: 0.725146 +textdata: +MIT License + +Copyright (c) 2023 Georgi Gerganov + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. +-------------------- +filename: README.md +filepos: 9178 +similarity: 0.621722 +textdata: +com/cztomsik/ava) (MIT) +- [ptsochantaris/emeltal](https://github.com/ptsochantaris/emeltal) +- [pythops/tenere](https://github. +-------------------- +``` diff --git a/examples/retrieval/retrieval.cpp b/examples/retrieval/retrieval.cpp new file mode 100644 index 0000000000000..5ba71e76a93b4 --- /dev/null +++ b/examples/retrieval/retrieval.cpp @@ -0,0 +1,350 @@ +#include "common.h" +#include "llama.h" + +#include +#include + +struct retrieval_params { + std::vector context_files; // context files to embed + int32_t chunk_size = 64; // chunk size for context embedding + std::string chunk_separator = "\n"; // chunk separator for context embedding +}; + +static void retrieval_params_print_usage(int argc, char ** argv, gpt_params & gpt_params, retrieval_params & params) { + gpt_print_usage(argc, argv, gpt_params); + printf("retrieval options:\n"); + printf(" --context-file FNAME file containing context to embed.\n"); + printf(" specify multiple files by providing --context-file option multiple times.\n"); + printf(" --chunk-size N minimum length of embedded text chunk (default:%d)\n", params.chunk_size); + printf(" --chunk-separator STRING\n"); + printf(" string to separate chunks (default: \"\\n\")\n"); + printf("\n"); +} + +static void retrieval_params_parse(int argc, char ** argv, gpt_params & gpt_params, retrieval_params & retrieval_params) { + int i = 1; + std::string arg; + while (i < argc) { + arg = argv[i]; + bool invalid_gpt_param = false; + if(gpt_params_find_arg(argc, argv, argv[i], gpt_params, i, invalid_gpt_param)) { + if (invalid_gpt_param) { + fprintf(stderr, "error: invalid argument: %s\n", arg.c_str()); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + // option was parsed by gpt_params_find_arg + } else if (arg == "--context-file") { + if (++i >= argc) { + fprintf(stderr, "error: missing argument for --context-file\n"); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + std::ifstream file(argv[i]); + if (!file) { + fprintf(stderr, "error: failed to open file '%s'\n", argv[i]); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + // store the external file name in params + retrieval_params.context_files.push_back(argv[i]); + } else if (arg == "--chunk-size") { + if (++i >= argc) { + fprintf(stderr, "error: missing argument for --chunk-size\n"); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + retrieval_params.chunk_size = std::stoi(argv[i]); + } else if (arg == "--chunk-separator") { + if (++i >= argc) { + fprintf(stderr, "error: missing argument for --chunk-separator\n"); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + retrieval_params.chunk_separator = argv[i]; + } else { + // unknown argument + fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); + retrieval_params_print_usage(argc, argv, gpt_params, retrieval_params); + exit(1); + } + i++; + } +} + +struct chunk { + // filename + std::string filename; + // original file position + size_t filepos; + // original text data + std::string textdata = ""; + // tokenized text data + std::vector tokens; + // embedding + std::vector embedding; +}; + +// chunk file data to chunks of size >= chunk_size +// chunk_separator is the separator between chunks +static std::vector chunk_file(const std::string & filename, int chunk_size, const std::string & chunk_separator) { + std::vector chunks; + std::ifstream f(filename.c_str()); + + if (!f.is_open()) { + fprintf(stderr, "Error: could not open file %s\n", filename.c_str()); + return chunks; + } + + chunk current_chunk; + char buffer[1024]; + int64_t filepos = 0; + std::string current = ""; + while (f.read(buffer, 1024)) { + current += std::string(buffer, f.gcount()); + size_t pos; + while ((pos = current.find(chunk_separator)) != std::string::npos) { + current_chunk.textdata += current.substr(0, pos + chunk_separator.size()); + if ((int) current_chunk.textdata.size() > chunk_size) { + // save chunk + current_chunk.filepos = filepos; + current_chunk.filename = filename; + chunks.push_back(current_chunk); + // update filepos + filepos += (int) current_chunk.textdata.size(); + // reset current_chunk + current_chunk = chunk(); + } + current = current.substr(pos + chunk_separator.size()); + } + + } + // add leftover data to last chunk + if (current_chunk.textdata.size() > 0) { + if (chunks.empty()) { + current_chunk.filepos = filepos; + current_chunk.filename = filename; + chunks.push_back(current_chunk); + } else { + chunks.back().textdata += current_chunk.textdata; + } + } + f.close(); + return chunks; +} + +static void batch_add_seq(llama_batch & batch, const std::vector & tokens, int seq_id) { + for (size_t i = 0; i < tokens.size(); i++) { + llama_batch_add(batch, tokens[i], i, { seq_id }, i == tokens.size() - 1); + } +} + +static void batch_decode(llama_context * ctx, llama_batch & batch, float * output, int n_seq, int n_embd) { + // clear previous kv_cache values (irrelevant for embeddings) + llama_kv_cache_clear(ctx); + + // run model + fprintf(stderr, "%s: n_tokens = %d, n_seq = %d\n", __func__, batch.n_tokens, n_seq); + if (llama_decode(ctx, batch) < 0) { + fprintf(stderr, "%s : failed to decode\n", __func__); + } + + for (int i = 0; i < batch.n_tokens; i++) { + if (!batch.logits[i]) { + continue; + } + + // try to get sequence embeddings - supported only when pooling_type is not NONE + const float * embd = llama_get_embeddings_seq(ctx, batch.seq_id[i][0]); + if (embd == NULL) { + embd = llama_get_embeddings_ith(ctx, i); + if (embd == NULL) { + fprintf(stderr, "%s: failed to get embeddings for token %d\n", __func__, i); + continue; + } + } + + float * out = output + batch.seq_id[i][0] * n_embd; + llama_embd_normalize(embd, out, n_embd); + } +} + +int main(int argc, char ** argv) { + gpt_params params; + retrieval_params retrieval_params; + + retrieval_params_parse(argc, argv, params, retrieval_params); + + // For BERT models, batch size must be equal to ubatch size + params.n_ubatch = params.n_batch; + + if (retrieval_params.chunk_size <= 0) { + fprintf(stderr, "chunk_size must be positive\n"); + return 1; + } + if (retrieval_params.context_files.empty()) { + fprintf(stderr, "context_files must be specified\n"); + return 1; + } + params.embedding = true; + + print_build_info(); + + printf("processing files:\n"); + for (auto & context_file : retrieval_params.context_files) { + printf("%s\n", context_file.c_str()); + } + + std::vector chunks; + for (auto & context_file : retrieval_params.context_files) { + std::vector file_chunk = chunk_file(context_file, retrieval_params.chunk_size, retrieval_params.chunk_separator); + chunks.insert(chunks.end(), file_chunk.begin(), file_chunk.end()); + } + printf("Number of chunks: %ld\n", chunks.size()); + + llama_backend_init(); + llama_numa_init(params.numa); + + llama_model * model; + llama_context * ctx; + + // load the model + std::tie(model, ctx) = llama_init_from_gpt_params(params); + if (model == NULL) { + fprintf(stderr, "%s: error: unable to load model\n", __func__); + return 1; + } + + const int n_ctx_train = llama_n_ctx_train(model); + const int n_ctx = llama_n_ctx(ctx); + + if (n_ctx > n_ctx_train) { + fprintf(stderr, "%s: warning: model was trained on only %d context tokens (%d specified)\n", + __func__, n_ctx_train, n_ctx); + } + + // print system information + { + fprintf(stderr, "\n"); + fprintf(stderr, "%s\n", get_system_info(params).c_str()); + } + + // max batch size + const uint64_t n_batch = params.n_batch; + GGML_ASSERT(params.n_batch >= params.n_ctx); + + // tokenize the prompts and trim + for (auto & chunk : chunks) { + auto inp = ::llama_tokenize(ctx, chunk.textdata, true, false); + if (inp.size() > n_batch) { + fprintf(stderr, "%s: error: chunk size (%lld) exceeds batch size (%lld), increase batch size and re-run\n", + __func__, (long long int) inp.size(), (long long int) n_batch); + return 1; + } + // add eos if not present + if (inp.empty() || inp.back() != llama_token_eos(model)) { + inp.push_back(llama_token_eos(model)); + } + chunk.tokens = inp; + } + + // tokenization stats + if (params.verbose_prompt) { + for (int i = 0; i < (int) chunks.size(); i++) { + fprintf(stderr, "%s: prompt %d: '%s'\n", __func__, i, chunks[i].textdata.c_str()); + fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, chunks[i].tokens.size()); + for (int j = 0; j < (int) chunks[i].tokens.size(); j++) { + fprintf(stderr, "%6d -> '%s'\n", chunks[i].tokens[j], llama_token_to_piece(ctx, chunks[i].tokens[j]).c_str()); + } + fprintf(stderr, "\n\n"); + } + } + + // initialize batch + const int n_chunks = chunks.size(); + struct llama_batch batch = llama_batch_init(n_batch, 0, 1); + + // allocate output + const int n_embd = llama_n_embd(model); + std::vector embeddings(n_chunks * n_embd, 0); + float * emb = embeddings.data(); + + // break into batches + int p = 0; // number of prompts processed already + int s = 0; // number of prompts in current batch + for (int k = 0; k < n_chunks; k++) { + // clamp to n_batch tokens + auto & inp = chunks[k].tokens; + + const uint64_t n_toks = inp.size(); + + // encode if at capacity + if (batch.n_tokens + n_toks > n_batch) { + float * out = emb + p * n_embd; + batch_decode(ctx, batch, out, s, n_embd); + llama_batch_clear(batch); + p += s; + s = 0; + } + + // add to batch + batch_add_seq(batch, inp, s); + s += 1; + } + + // final batch + float * out = emb + p * n_embd; + batch_decode(ctx, batch, out, s, n_embd); + + // save embeddings to chunks + for (int i = 0; i < n_chunks; i++) { + chunks[i].embedding = std::vector(emb + i * n_embd, emb + (i + 1) * n_embd); + // clear tokens as they are no longer needed + chunks[i].tokens.clear(); + } + + // start loop, receive query and return top k similar chunks based on cosine similarity + std::string query; + while (true) { + printf("Enter query: "); + std::getline(std::cin, query); + std::vector query_tokens = llama_tokenize(ctx, query, true); + + struct llama_batch query_batch = llama_batch_init(n_batch, 0, 1); + batch_add_seq(query_batch, query_tokens, 0); + + std::vector query_emb(n_embd, 0); + batch_decode(ctx, query_batch, query_emb.data(), 1, n_embd); + + llama_batch_clear(query_batch); + + // compute cosine similarities + { + std::vector> similarities; + for (int i = 0; i < n_chunks; i++) { + float sim = llama_embd_similarity_cos(chunks[i].embedding.data(), query_emb.data(), n_embd); + similarities.push_back(std::make_pair(i, sim)); + } + + // sort similarities + std::sort(similarities.begin(), similarities.end(), [](const std::pair & a, const std::pair & b) { + return a.second > b.second; + }); + + printf("Top %d similar chunks:\n", params.sparams.top_k); + for (int i = 0; i < std::min(params.sparams.top_k, (int) chunks.size()); i++) { + printf("filename: %s\n", chunks[similarities[i].first].filename.c_str()); + printf("filepos: %lld\n", (long long int) chunks[similarities[i].first].filepos); + printf("similarity: %f\n", similarities[i].second); + printf("textdata:\n%s\n", chunks[similarities[i].first].textdata.c_str()); + printf("--------------------\n"); + } + } + } + + // clean up + llama_print_timings(ctx); + llama_free(ctx); + llama_free_model(model); + llama_backend_free(); +} diff --git a/examples/save-load-state/save-load-state.cpp b/examples/save-load-state/save-load-state.cpp index f91ab8bbcf078..c3782be64954d 100644 --- a/examples/save-load-state/save-load-state.cpp +++ b/examples/save-load-state/save-load-state.cpp @@ -25,6 +25,7 @@ int main(int argc, char ** argv) { std::string result0; std::string result1; + std::string result2; // init llama_model * model; @@ -45,8 +46,8 @@ int main(int argc, char ** argv) { // save state (rng, logits, embedding and kv_cache) to file { - std::vector state_mem(llama_get_state_size(ctx)); - const size_t written = llama_copy_state_data(ctx, state_mem.data()); + std::vector state_mem(llama_state_get_size(ctx)); + const size_t written = llama_state_get_data(ctx, state_mem.data()); FILE *fp_write = fopen("dump_state.bin", "wb"); fwrite(state_mem.data(), 1, written, fp_write); @@ -98,13 +99,13 @@ int main(int argc, char ** argv) { // load state (rng, logits, embedding and kv_cache) from file { - std::vector state_mem(llama_get_state_size(ctx2)); + std::vector state_mem(llama_state_get_size(ctx2)); FILE * fp_read = fopen("dump_state.bin", "rb"); const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read); fclose(fp_read); - if (read != llama_set_state_data(ctx2, state_mem.data())) { + if (read != llama_state_set_data(ctx2, state_mem.data())) { fprintf(stderr, "\n%s : failed to read state\n", __func__); llama_free(ctx2); llama_free_model(model); @@ -142,16 +143,104 @@ int main(int argc, char ** argv) { n_past += 1; } - printf("\n"); + printf("\n\n"); llama_free(ctx2); - llama_free_model(model); if (result0 != result1) { fprintf(stderr, "\n%s : error : the 2 generations are different\n", __func__); return 1; } + // make new context + auto* ctx3 = llama_new_context_with_model(model, llama_context_params_from_gpt_params(params)); + + printf("\nsingle seq run: %s", params.prompt.c_str()); + + // load state (rng, logits, embedding and kv_cache) from file + { + std::vector state_mem(llama_state_get_size(ctx3)); + + FILE * fp_read = fopen("dump_state.bin", "rb"); + const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read); + fclose(fp_read); + + if (read != llama_state_set_data(ctx3, state_mem.data())) { + fprintf(stderr, "\n%s : failed to read state\n", __func__); + llama_free(ctx3); + llama_free_model(model); + return 1; + } + + fprintf(stderr, "%s : deserialized state from %zd out of a maximum of %zd bytes\n", __func__, read, state_mem.size()); + } + + // restore state (last tokens) + n_past = n_past_saved; + + // save seq 0 and load into seq 1 + { + // save kv of seq 0 + std::vector seq_store(llama_state_seq_get_size(ctx3, 0)); + const size_t ncopy = llama_state_seq_get_data(ctx3, seq_store.data(), 0); + if (ncopy != seq_store.size()) { + fprintf(stderr, "\n%s : seq copy data length %zd does not match expected length %zd\n", __func__, ncopy, seq_store.size()); + llama_free(ctx3); + llama_free_model(model); + return 1; + } + fprintf(stderr, "%s : seq 0 copied, %zd bytes\n", __func__, ncopy); + + // erase whole kv + llama_kv_cache_clear(ctx3); + fprintf(stderr, "%s : kv cache cleared\n", __func__); + + // restore kv into seq 1 + const size_t nset = llama_state_seq_set_data(ctx3, seq_store.data(), 1); + if (nset != seq_store.size()) { + fprintf(stderr, "\n%s : seq set data length %zd does not match expected length %zd\n", __func__, nset, seq_store.size()); + llama_free(ctx3); + llama_free_model(model); + return 1; + } + fprintf(stderr, "%s : seq 1 restored, %zd bytes\n", __func__, nset); + } + + // third run with seq 1 instead of 0 + for (auto i = 0; i < params.n_predict; i++) { + auto * logits = llama_get_logits(ctx3); + auto n_vocab = llama_n_vocab(model); + std::vector candidates; + candidates.reserve(n_vocab); + for (llama_token token_id = 0; token_id < n_vocab; token_id++) { + candidates.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f}); + } + llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false }; + auto next_token = llama_sample_token(ctx3, &candidates_p); + auto next_token_str = llama_token_to_piece(ctx3, next_token); + + printf("%s", next_token_str.c_str()); + result2 += next_token_str; + + if (llama_decode(ctx3, llama_batch_get_one(&next_token, 1, n_past, 1))) { + fprintf(stderr, "\n%s : failed to evaluate\n", __func__); + llama_free(ctx3); + llama_free_model(model); + return 1; + } + n_past += 1; + } + + printf("\n"); + + llama_free(ctx3); + llama_free_model(model); + + if (result0 != result2) { + fprintf(stderr, "\n%s : error : the seq restore generation is different\n", __func__); + return 1; + } + fprintf(stderr, "\n%s : success\n", __func__); return 0; diff --git a/examples/server/CMakeLists.txt b/examples/server/CMakeLists.txt index f94de1e99b7e9..d2ee47d01d767 100644 --- a/examples/server/CMakeLists.txt +++ b/examples/server/CMakeLists.txt @@ -2,12 +2,16 @@ set(TARGET server) option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON) option(LLAMA_SERVER_SSL "Build SSL support for the server" OFF) include_directories(${CMAKE_CURRENT_SOURCE_DIR}) -add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h) +add_executable(${TARGET} + server.cpp + utils.hpp + httplib.h +) install(TARGETS ${TARGET} RUNTIME) target_compile_definitions(${TARGET} PRIVATE SERVER_VERBOSE=$ ) -target_link_libraries(${TARGET} PRIVATE common ${CMAKE_THREAD_LIBS_INIT}) +target_link_libraries(${TARGET} PRIVATE common json-schema-to-grammar ${CMAKE_THREAD_LIBS_INIT}) if (LLAMA_SERVER_SSL) find_package(OpenSSL REQUIRED) target_link_libraries(${TARGET} PRIVATE OpenSSL::SSL OpenSSL::Crypto) diff --git a/examples/server/README.md b/examples/server/README.md index 8f8454affaecd..a6fc92eaa9b29 100644 --- a/examples/server/README.md +++ b/examples/server/README.md @@ -16,48 +16,51 @@ The project is under active development, and we are [looking for feedback and co **Command line options:** -- `--threads N`, `-t N`: Set the number of threads to use during generation. -- `-tb N, --threads-batch N`: Set the number of threads to use during batch and prompt processing. If not specified, the number of threads will be set to the number of threads used for generation. -- `--threads-http N`: number of threads in the http server pool to process requests (default: `max(std::thread::hardware_concurrency() - 1, --parallel N + 2)`) +- `--threads N`, `-t N`: Set the number of threads to use during generation. Not used if model layers are offloaded to GPU. The server is using batching. This parameter is used only if one token is to be processed on CPU backend. +- `-tb N, --threads-batch N`: Set the number of threads to use during batch and prompt processing. If not specified, the number of threads will be set to the number of threads used for generation. Not used if model layers are offloaded to GPU. +- `--threads-http N`: Number of threads in the http server pool to process requests. Default: `max(std::thread::hardware_concurrency() - 1, --parallel N + 2)` - `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`). +- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file. Default: unused +- `-hfr REPO, --hf-repo REPO`: Hugging Face model repository. Default: unused +- `-hff FILE, --hf-file FILE`: Hugging Face model file. Default: unused - `-a ALIAS`, `--alias ALIAS`: Set an alias for the model. The alias will be returned in API responses. -- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of 4096. -- `-ngl N`, `--n-gpu-layers N`: When compiled with appropriate support (currently CLBlast or cuBLAS), this option allows offloading some layers to the GPU for computation. Generally results in increased performance. -- `-mg i, --main-gpu i`: When using multiple GPUs this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default GPU 0 is used. Requires cuBLAS. -- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance. Requires cuBLAS. -- `-b N`, `--batch-size N`: Set the batch size for prompt processing. Default: `512`. -- `--memory-f32`: Use 32-bit floats instead of 16-bit floats for memory key+value. Not recommended. +- `-c N`, `--ctx-size N`: Set the size of the prompt context. The default is `512`, but LLaMA models were built with a context of `2048`, which will provide better results for longer input/inference. The size may differ in other models, for example, baichuan models were build with a context of `4096`. +- `-ngl N`, `--n-gpu-layers N`: When compiled with GPU support, this option allows offloading some layers to the GPU for computation. Generally results in increased performance. +- `-mg i, --main-gpu i`: When using multiple GPUs, this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default, GPU `0` is used. +- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs, this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default, the data is split in proportion to VRAM, but this may not be optimal for performance. +- `-b N`, `--batch-size N`: Set the batch size for prompt processing. Default: `2048` +- `-ub N`, `--ubatch-size N`: Physical maximum batch size. Default: `512` - `--mlock`: Lock the model in memory, preventing it from being swapped out when memory-mapped. - `--no-mmap`: Do not memory-map the model. By default, models are mapped into memory, which allows the system to load only the necessary parts of the model as needed. -- `--numa STRATEGY`: Attempt one of the below optimization strategies that help on some NUMA systems +- `--numa STRATEGY`: Attempt one of the below optimization strategies that may help on some NUMA systems - `--numa distribute`: Spread execution evenly over all nodes - `--numa isolate`: Only spawn threads on CPUs on the node that execution started on -- `--numa numactl`: Use the CPU map provided by numactl -if run without this previously, it is recommended to drop the system page cache before using this -see https://github.com/ggerganov/llama.cpp/issues/1437 +- `--numa numactl`: Use the CPU map provided by numactl. If run without this previously, it is recommended to drop the system +page cache before using this. See https://github.com/ggerganov/llama.cpp/issues/1437 -- `--numa`: Attempt optimizations that help on some NUMA systems. +- `--numa`: Attempt optimizations that may help on some NUMA systems. - `--lora FNAME`: Apply a LoRA (Low-Rank Adaptation) adapter to the model (implies --no-mmap). This allows you to adapt the pretrained model to specific tasks or domains. - `--lora-base FNAME`: Optional model to use as a base for the layers modified by the LoRA adapter. This flag is used in conjunction with the `--lora` flag, and specifies the base model for the adaptation. -- `-to N`, `--timeout N`: Server read/write timeout in seconds. Default `600`. -- `--host`: Set the hostname or ip address to listen. Default `127.0.0.1`. -- `--port`: Set the port to listen. Default: `8080`. -- `--path`: path from which to serve static files (default: disabled) -- `--api-key`: Set an api key for request authorization. By default the server responds to every request. With an api key set, the requests must have the Authorization header set with the api key as Bearer token. May be used multiple times to enable multiple valid keys. -- `--api-key-file`: path to file containing api keys delimited by new lines. If set, requests must include one of the keys for access. May be used in conjunction with `--api-key`'s. -- `--embedding`: Enable embedding extraction, Default: disabled. -- `-np N`, `--parallel N`: Set the number of slots for process requests (default: 1) -- `-cb`, `--cont-batching`: enable continuous batching (a.k.a dynamic batching) (default: disabled) -- `-spf FNAME`, `--system-prompt-file FNAME` Set a file to load "a system prompt (initial prompt of all slots), this is useful for chat applications. [See more](#change-system-prompt-on-runtime) +- `-to N`, `--timeout N`: Server read/write timeout in seconds. Default `600` +- `--host`: Set the hostname or ip address to listen. Default `127.0.0.1` +- `--port`: Set the port to listen. Default: `8080` +- `--path`: Path from which to serve static files. Default: disabled +- `--api-key`: Set an api key for request authorization. By default, the server responds to every request. With an api key set, the requests must have the Authorization header set with the api key as Bearer token. May be used multiple times to enable multiple valid keys. +- `--api-key-file`: Path to file containing api keys delimited by new lines. If set, requests must include one of the keys for access. May be used in conjunction with `--api-key`s. +- `--embedding`: Enable embedding extraction. Default: disabled +- `-np N`, `--parallel N`: Set the number of slots for process requests. Default: `1` +- `-cb`, `--cont-batching`: Enable continuous batching (a.k.a dynamic batching). Default: disabled +- `-spf FNAME`, `--system-prompt-file FNAME` Set a file to load a system prompt (initial prompt of all slots). This is useful for chat applications. [See more](#change-system-prompt-on-runtime) - `--mmproj MMPROJ_FILE`: Path to a multimodal projector file for LLaVA. -- `--grp-attn-n`: Set the group attention factor to extend context size through self-extend(default: 1=disabled), used together with group attention width `--grp-attn-w` -- `--grp-attn-w`: Set the group attention width to extend context size through self-extend(default: 512), used together with group attention factor `--grp-attn-n` -- `-n N, --n-predict N`: Set the maximum tokens to predict (default: -1) +- `--grp-attn-n`: Set the group attention factor to extend context size through self-extend. Used together with group attention width `--grp-attn-w`. Default: `1`, which is disabled. +- `--grp-attn-w`: Set the group attention width to extend context size through self-extend. Used together with group attention factor `--grp-attn-n`. Default: `512` +- `-n N, --n-predict N`: Set the maximum tokens to predict. Default: `-1` - `--slots-endpoint-disable`: To disable slots state monitoring endpoint. Slots state may contain user data, prompts included. -- `--metrics`: enable prometheus `/metrics` compatible endpoint (default: disabled) -- `--chat-template JINJA_TEMPLATE`: Set custom jinja chat template. This parameter accepts a string, not a file name (default: template taken from model's metadata). We only support [some pre-defined templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) -- `--log-disable`: Output logs to stdout only, default: enabled. -- `--log-format FORMAT`: Define the log output to FORMAT: json or text (default: json) +- `--metrics`: enable prometheus `/metrics` compatible endpoint. Default: disabled +- `--slot-save-path PATH`: Specifies the path where the state of slots (the prompt cache) can be stored. If not provided, the slot management endpoints will be disabled. +- `--chat-template JINJA_TEMPLATE`: Set custom jinja chat template. This parameter accepts a string, not a file name. Default: template taken from model's metadata. We only support [some pre-defined templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) +- `--log-disable`: Output logs to stdout only, not to `llama.log`. Default: enabled +- `--log-format FORMAT`: Define the log output to FORMAT: json or text Default: `json` **If compiled with `LLAMA_SERVER_SSL=ON`** - `--ssl-key-file FNAME`: path to file a PEM-encoded SSL private key @@ -65,7 +68,7 @@ see https://github.com/ggerganov/llama.cpp/issues/1437 ## Build -server is build alongside everything else from the root of the project +`server` is built alongside everything else from the root of the project - Using `make`: @@ -81,7 +84,7 @@ server is build alongside everything else from the root of the project ## Build with SSL -server can also be built with SSL support using OpenSSL 3 +`server` can also be built with SSL support using OpenSSL 3 - Using `make`: @@ -131,7 +134,7 @@ docker run -p 8080:8080 -v /path/to/models:/models --gpus all ghcr.io/ggerganov/ ## Testing with CURL -Using [curl](https://curl.se/). On Windows `curl.exe` should be available in the base OS. +Using [curl](https://curl.se/). On Windows, `curl.exe` should be available in the base OS. ```sh curl --request POST \ @@ -155,7 +158,7 @@ mkdir llama-client cd llama-client ``` -Create a index.js file and put inside this: +Create a index.js file and put this inside: ```javascript const prompt = `Building a website can be done in 10 simple steps:`; @@ -186,8 +189,8 @@ node index.js - 503 -> `{"status": "loading model"}` if the model is still being loaded. - 500 -> `{"status": "error"}` if the model failed to load. - 200 -> `{"status": "ok", "slots_idle": 1, "slots_processing": 2 }` if the model is successfully loaded and the server is ready for further requests mentioned below. - - 200 -> `{"status": "no slot available", "slots_idle": 0, "slots_processing": 32}` if no slot are currently available. - - 503 -> `{"status": "no slot available", "slots_idle": 0, "slots_processing": 32}` if the query parameter `fail_on_no_slot` is provided and no slot are currently available. + - 200 -> `{"status": "no slot available", "slots_idle": 0, "slots_processing": 32}` if no slots are currently available. + - 503 -> `{"status": "no slot available", "slots_idle": 0, "slots_processing": 32}` if the query parameter `fail_on_no_slot` is provided and no slots are currently available. If the query parameter `include_slots` is passed, `slots` field will contain internal slots data except if `--slots-endpoint-disable` is set. @@ -201,75 +204,75 @@ node index.js - The model's `tokenizer.ggml.add_bos_token` metadata is `true` - The system prompt is empty - `temperature`: Adjust the randomness of the generated text (default: 0.8). + `temperature`: Adjust the randomness of the generated text. Default: `0.8` - `dynatemp_range`: Dynamic temperature range. The final temperature will be in the range of `[temperature - dynatemp_range; temperature + dynatemp_range]` (default: 0.0, 0.0 = disabled). + `dynatemp_range`: Dynamic temperature range. The final temperature will be in the range of `[temperature - dynatemp_range; temperature + dynatemp_range]` Default: `0.0`, which is disabled. - `dynatemp_exponent`: Dynamic temperature exponent (default: 1.0). + `dynatemp_exponent`: Dynamic temperature exponent. Default: `1.0` - `top_k`: Limit the next token selection to the K most probable tokens (default: 40). + `top_k`: Limit the next token selection to the K most probable tokens. Default: `40` - `top_p`: Limit the next token selection to a subset of tokens with a cumulative probability above a threshold P (default: 0.95). + `top_p`: Limit the next token selection to a subset of tokens with a cumulative probability above a threshold P. Default: `0.95` - `min_p`: The minimum probability for a token to be considered, relative to the probability of the most likely token (default: 0.05). + `min_p`: The minimum probability for a token to be considered, relative to the probability of the most likely token. Default: `0.05` - `n_predict`: Set the maximum number of tokens to predict when generating text. **Note:** May exceed the set limit slightly if the last token is a partial multibyte character. When 0, no tokens will be generated but the prompt is evaluated into the cache. (default: -1, -1 = infinity). + `n_predict`: Set the maximum number of tokens to predict when generating text. **Note:** May exceed the set limit slightly if the last token is a partial multibyte character. When 0, no tokens will be generated but the prompt is evaluated into the cache. Default: `-1`, where `-1` is infinity. `n_keep`: Specify the number of tokens from the prompt to retain when the context size is exceeded and tokens need to be discarded. - By default, this value is set to 0 (meaning no tokens are kept). Use `-1` to retain all tokens from the prompt. + By default, this value is set to `0`, meaning no tokens are kept. Use `-1` to retain all tokens from the prompt. `stream`: It allows receiving each predicted token in real-time instead of waiting for the completion to finish. To enable this, set to `true`. `stop`: Specify a JSON array of stopping strings. - These words will not be included in the completion, so make sure to add them to the prompt for the next iteration (default: []). + These words will not be included in the completion, so make sure to add them to the prompt for the next iteration. Default: `[]` - `tfs_z`: Enable tail free sampling with parameter z (default: 1.0, 1.0 = disabled). + `tfs_z`: Enable tail free sampling with parameter z. Default: `1.0`, which is disabled. - `typical_p`: Enable locally typical sampling with parameter p (default: 1.0, 1.0 = disabled). + `typical_p`: Enable locally typical sampling with parameter p. Default: `1.0`, which is disabled. - `repeat_penalty`: Control the repetition of token sequences in the generated text (default: 1.1). + `repeat_penalty`: Control the repetition of token sequences in the generated text. Default: `1.1` - `repeat_last_n`: Last n tokens to consider for penalizing repetition (default: 64, 0 = disabled, -1 = ctx-size). + `repeat_last_n`: Last n tokens to consider for penalizing repetition. Default: `64`, where `0` is disabled and `-1` is ctx-size. - `penalize_nl`: Penalize newline tokens when applying the repeat penalty (default: true). + `penalize_nl`: Penalize newline tokens when applying the repeat penalty. Default: `true` - `presence_penalty`: Repeat alpha presence penalty (default: 0.0, 0.0 = disabled). + `presence_penalty`: Repeat alpha presence penalty. Default: `0.0`, which is disabled. - `frequency_penalty`: Repeat alpha frequency penalty (default: 0.0, 0.0 = disabled); + `frequency_penalty`: Repeat alpha frequency penalty. Default: `0.0`, which is disabled. - `penalty_prompt`: This will replace the `prompt` for the purpose of the penalty evaluation. Can be either `null`, a string or an array of numbers representing tokens (default: `null` = use the original `prompt`). + `penalty_prompt`: This will replace the `prompt` for the purpose of the penalty evaluation. Can be either `null`, a string or an array of numbers representing tokens. Default: `null`, which is to use the original `prompt`. - `mirostat`: Enable Mirostat sampling, controlling perplexity during text generation (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0). + `mirostat`: Enable Mirostat sampling, controlling perplexity during text generation. Default: `0`, where `0` is disabled, `1` is Mirostat, and `2` is Mirostat 2.0. - `mirostat_tau`: Set the Mirostat target entropy, parameter tau (default: 5.0). + `mirostat_tau`: Set the Mirostat target entropy, parameter tau. Default: `5.0` - `mirostat_eta`: Set the Mirostat learning rate, parameter eta (default: 0.1). + `mirostat_eta`: Set the Mirostat learning rate, parameter eta. Default: `0.1` - `grammar`: Set grammar for grammar-based sampling (default: no grammar) + `grammar`: Set grammar for grammar-based sampling. Default: no grammar - `seed`: Set the random number generator (RNG) seed (default: -1, -1 = random seed). + `seed`: Set the random number generator (RNG) seed. Default: `-1`, which is a random seed. - `ignore_eos`: Ignore end of stream token and continue generating (default: false). + `ignore_eos`: Ignore end of stream token and continue generating. Default: `false` - `logit_bias`: Modify the likelihood of a token appearing in the generated text completion. For example, use `"logit_bias": [[15043,1.0]]` to increase the likelihood of the token 'Hello', or `"logit_bias": [[15043,-1.0]]` to decrease its likelihood. Setting the value to false, `"logit_bias": [[15043,false]]` ensures that the token `Hello` is never produced. The tokens can also be represented as strings, e.g. `[["Hello, World!",-0.5]]` will reduce the likelihood of all the individual tokens that represent the string `Hello, World!`, just like the `presence_penalty` does. (default: []). + `logit_bias`: Modify the likelihood of a token appearing in the generated text completion. For example, use `"logit_bias": [[15043,1.0]]` to increase the likelihood of the token 'Hello', or `"logit_bias": [[15043,-1.0]]` to decrease its likelihood. Setting the value to false, `"logit_bias": [[15043,false]]` ensures that the token `Hello` is never produced. The tokens can also be represented as strings, e.g. `[["Hello, World!",-0.5]]` will reduce the likelihood of all the individual tokens that represent the string `Hello, World!`, just like the `presence_penalty` does. Default: `[]` - `n_probs`: If greater than 0, the response also contains the probabilities of top N tokens for each generated token (default: 0) + `n_probs`: If greater than 0, the response also contains the probabilities of top N tokens for each generated token. Default: `0` - `min_keep`: If greater than 0, force samplers to return N possible tokens at minimum (default: 0) + `min_keep`: If greater than 0, force samplers to return N possible tokens at minimum. Default: `0` `image_data`: An array of objects to hold base64-encoded image `data` and its `id`s to be reference in `prompt`. You can determine the place of the image in the prompt as in the following: `USER:[img-12]Describe the image in detail.\nASSISTANT:`. In this case, `[img-12]` will be replaced by the embeddings of the image with id `12` in the following `image_data` array: `{..., "image_data": [{"data": "", "id": 12}]}`. Use `image_data` only with multimodal models, e.g., LLaVA. - `slot_id`: Assign the completion task to an specific slot. If is -1 the task will be assigned to a Idle slot (default: -1) + `id_slot`: Assign the completion task to an specific slot. If is -1 the task will be assigned to a Idle slot. Default: `-1` - `cache_prompt`: Re-use previously cached prompt from the last request if possible. This may prevent re-caching the prompt from scratch. (default: false) + `cache_prompt`: Re-use previously cached prompt from the last request if possible. This may prevent re-caching the prompt from scratch. Default: `false` `system_prompt`: Change the system prompt (initial prompt of all slots), this is useful for chat applications. [See more](#change-system-prompt-on-runtime) - `samplers`: The order the samplers should be applied in. An array of strings representing sampler type names. If a sampler is not set, it will not be used. If a sampler is specified more than once, it will be applied multiple times. (default: `["top_k", "tfs_z", "typical_p", "top_p", "min_p", "temperature"]` - these are all the available values) + `samplers`: The order the samplers should be applied in. An array of strings representing sampler type names. If a sampler is not set, it will not be used. If a sampler is specified more than once, it will be applied multiple times. Default: `["top_k", "tfs_z", "typical_p", "top_p", "min_p", "temperature"]` - these are all the available values. ### Result JSON -- Note: When using streaming mode (`stream`) only `content` and `stop` will be returned until end of completion. +- Note: When using streaming mode (`stream`), only `content` and `stop` will be returned until end of completion. - `completion_probabilities`: An array of token probabilities for each completion. The array's length is `n_predict`. Each item in the array has the following structure: @@ -283,7 +286,7 @@ node index.js }, { "prob": float, - "tok_str": "" + "tok_str": "" }, ... ] @@ -353,14 +356,14 @@ Notice that each `probs` is an array of length `n_probs`. - `assistant_name` - the required assistant name to generate the prompt in case you have specified a system prompt for all slots. - `user_name` - the required anti-prompt to generate the prompt in case you have specified a system prompt for all slots. -- `default_generation_settings` - the default generation settings for the `/completion` endpoint, has the same fields as the `generation_settings` response object from the `/completion` endpoint. +- `default_generation_settings` - the default generation settings for the `/completion` endpoint, which has the same fields as the `generation_settings` response object from the `/completion` endpoint. - `total_slots` - the total number of slots for process requests (defined by `--parallel` option) -- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only ChatML-tuned models, such as Dolphin, OpenOrca, OpenHermes, OpenChat-3.5, etc can be used with this endpoint. +- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only model with [supported chat template](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template) can be used optimally with this endpoint. By default, ChatML template will be used. *Options:* - See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such are `mirostat` are supported. + See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such as `mirostat` are supported. *Examples:* @@ -510,16 +513,67 @@ Available metrics: - `llamacpp:tokens_predicted_total`: Number of generation tokens processed. - `llamacpp:prompt_tokens_seconds`: Average prompt throughput in tokens/s. - `llamacpp:predicted_tokens_seconds`: Average generation throughput in tokens/s. -- `llamacpp:kv_cache_usage_ratio`: KV-cache usage. 1 means 100 percent usage. +- `llamacpp:kv_cache_usage_ratio`: KV-cache usage. `1` means 100 percent usage. - `llamacpp:kv_cache_tokens`: KV-cache tokens. -- `llamacpp:requests_processing`: Number of request processing. -- `llamacpp:requests_deferred`: Number of request deferred. +- `llamacpp:requests_processing`: Number of requests processing. +- `llamacpp:requests_deferred`: Number of requests deferred. + +- **POST** `/slots/{id_slot}?action=save`: Save the prompt cache of the specified slot to a file. + + *Options:* + + `filename`: Name of the file to save the slot's prompt cache. The file will be saved in the directory specified by the `--slot-save-path` server parameter. + +### Result JSON + +```json +{ + "id_slot": 0, + "filename": "slot_save_file.bin", + "n_saved": 1745, + "n_written": 14309796, + "timings": { + "save_ms": 49.865 + } +} +``` + +- **POST** `/slots/{id_slot}?action=restore`: Restore the prompt cache of the specified slot from a file. + + *Options:* + + `filename`: Name of the file to restore the slot's prompt cache from. The file should be located in the directory specified by the `--slot-save-path` server parameter. + +### Result JSON + +```json +{ + "id_slot": 0, + "filename": "slot_save_file.bin", + "n_restored": 1745, + "n_read": 14309796, + "timings": { + "restore_ms": 42.937 + } +} +``` + +- **POST** `/slots/{id_slot}?action=erase`: Erase the prompt cache of the specified slot. + +### Result JSON + +```json +{ + "id_slot": 0, + "n_erased": 1745 +} +``` ## More examples ### Change system prompt on runtime -To use the server example to serve multiple chat-type clients while keeping the same system prompt, you can utilize the option `system_prompt` to achieve that. This only needs to be done once to establish it. +To use the server example to serve multiple chat-type clients while keeping the same system prompt, you can utilize the option `system_prompt`. This only needs to be used once. `prompt`: Specify a context that you want all connecting clients to respect. @@ -558,11 +612,11 @@ bash chat.sh ### OAI-like API -The HTTP server supports OAI-like API: https://github.com/openai/openai-openapi +The HTTP `server` supports an OAI-like API: https://github.com/openai/openai-openapi ### API errors -Server returns error in the same format as OAI: https://github.com/openai/openai-openapi +`server` returns errors in the same format as OAI: https://github.com/openai/openai-openapi Example of an error: diff --git a/examples/server/bench/README.md b/examples/server/bench/README.md index a53ad64d7359b..23a3ec97523ef 100644 --- a/examples/server/bench/README.md +++ b/examples/server/bench/README.md @@ -2,13 +2,15 @@ Benchmark is using [k6](https://k6.io/). -##### Install k6 +##### Install k6 and sse extension -Follow instruction from: https://k6.io/docs/get-started/installation/ +SSE is not supported by default in k6, you have to build k6 with the [xk6-sse](https://github.com/phymbert/xk6-sse) extension. -Example for ubuntu: +Example: ```shell -snap install k6 +go install go.k6.io/xk6/cmd/xk6@latest +xk6 build master \ +--with github.com/phymbert/xk6-sse ``` #### Download a dataset @@ -46,7 +48,7 @@ server --host localhost --port 8080 \ For 500 chat completions request with 8 concurrent users during maximum 10 minutes, run: ```shell -k6 run script.js --duration 10m --iterations 500 --vus 8 +./k6 run script.js --duration 10m --iterations 500 --vus 8 ``` The benchmark values can be overridden with: @@ -86,3 +88,33 @@ K6 metrics might be compared against [server metrics](../README.md), with: ```shell curl http://localhost:8080/metrics ``` + +### Using the CI python script +The `bench.py` script does several steps: +- start the server +- define good variable for k6 +- run k6 script +- extract metrics from prometheus + +It aims to be used in the CI, but you can run it manually: + +```shell +LLAMA_SERVER_BIN_PATH=../../../cmake-build-release/bin/server python bench.py \ + --runner-label local \ + --name local \ + --branch `git rev-parse --abbrev-ref HEAD` \ + --commit `git rev-parse HEAD` \ + --scenario script.js \ + --duration 5m \ + --hf-repo ggml-org/models \ + --hf-file phi-2/ggml-model-q4_0.gguf \ + --model-path-prefix models \ + --parallel 4 \ + -ngl 33 \ + --batch-size 2048 \ + --ubatch-size 256 \ + --ctx-size 4096 \ + --n-prompts 200 \ + --max-prompt-tokens 256 \ + --max-tokens 256 +``` diff --git a/examples/server/bench/bench.py b/examples/server/bench/bench.py new file mode 100644 index 0000000000000..6ca637bddc3a1 --- /dev/null +++ b/examples/server/bench/bench.py @@ -0,0 +1,308 @@ +import argparse +import json +import os +import re +import signal +import socket +import subprocess +import sys +import threading +import time +import traceback +from contextlib import closing +from datetime import datetime + +import matplotlib +import matplotlib.dates +import matplotlib.pyplot as plt +import requests +from statistics import mean + + +def main(args_in: list[str] | None = None) -> None: + parser = argparse.ArgumentParser(description="Start server benchmark scenario") + parser.add_argument("--name", type=str, help="Bench name", required=True) + parser.add_argument("--runner-label", type=str, help="Runner label", required=True) + parser.add_argument("--branch", type=str, help="Branch name", default="detached") + parser.add_argument("--commit", type=str, help="Commit name", default="dirty") + parser.add_argument("--host", type=str, help="Server listen host", default="0.0.0.0") + parser.add_argument("--port", type=int, help="Server listen host", default="8080") + parser.add_argument("--model-path-prefix", type=str, help="Prefix where to store the model files", default="models") + parser.add_argument("--n-prompts", type=int, + help="SERVER_BENCH_N_PROMPTS: total prompts to randomly select in the benchmark", required=True) + parser.add_argument("--max-prompt-tokens", type=int, + help="SERVER_BENCH_MAX_PROMPT_TOKENS: maximum prompt tokens to filter out in the dataset", + required=True) + parser.add_argument("--max-tokens", type=int, + help="SERVER_BENCH_MAX_CONTEXT: maximum context size of the completions request to filter out in the dataset: prompt + predicted tokens", + required=True) + parser.add_argument("--hf-repo", type=str, help="Hugging Face model repository", required=True) + parser.add_argument("--hf-file", type=str, help="Hugging Face model file", required=True) + parser.add_argument("-ngl", "--n-gpu-layers", type=int, help="layers to the GPU for computation", required=True) + parser.add_argument("--ctx-size", type=int, help="Set the size of the prompt context", required=True) + parser.add_argument("--parallel", type=int, help="Set the number of slots for process requests", required=True) + parser.add_argument("--batch-size", type=int, help="Set the batch size for prompt processing", required=True) + parser.add_argument("--ubatch-size", type=int, help="physical maximum batch size", required=True) + parser.add_argument("--scenario", type=str, help="Scenario to run", required=True) + parser.add_argument("--duration", type=str, help="Bench scenario", required=True) + + args = parser.parse_args(args_in) + + start_time = time.time() + + # Start the server and performance scenario + try: + server_process = start_server(args) + except Exception: + print("bench: server start error :") + traceback.print_exc(file=sys.stdout) + sys.exit(1) + + # start the benchmark + try: + start_benchmark(args) + + iterations = 0 + with open("results.github.env", 'w') as github_env: + # parse output + with open('k6-results.json', 'r') as bench_results: + # Load JSON data from file + data = json.load(bench_results) + for metric_name in data['metrics']: + for metric_metric in data['metrics'][metric_name]: + value = data['metrics'][metric_name][metric_metric] + if isinstance(value, float) or isinstance(value, int): + value = round(value, 2) + data['metrics'][metric_name][metric_metric]=value + github_env.write( + f"{escape_metric_name(metric_name)}_{escape_metric_name(metric_metric)}={value}\n") + iterations = data['root_group']['checks']['success completion']['passes'] + + except Exception: + print("bench: error :") + traceback.print_exc(file=sys.stdout) + + # Stop the server + if server_process: + try: + print(f"bench: shutting down server pid={server_process.pid} ...") + if os.name == 'nt': + interrupt = signal.CTRL_C_EVENT + else: + interrupt = signal.SIGINT + server_process.send_signal(interrupt) + server_process.wait(0.5) + + except subprocess.TimeoutExpired: + print(f"server still alive after 500ms, force-killing pid={server_process.pid} ...") + server_process.kill() # SIGKILL + server_process.wait() + + while is_server_listening(args.host, args.port): + time.sleep(0.1) + + title = (f"llama.cpp {args.name} on {args.runner_label}\n " + f"duration={args.duration} {iterations} iterations") + xlabel = (f"{args.hf_repo}/{args.hf_file}\n" + f"parallel={args.parallel} ctx-size={args.ctx_size} ngl={args.n_gpu_layers} batch-size={args.batch_size} ubatch-size={args.ubatch_size} pp={args.max_prompt_tokens} pp+tg={args.max_tokens}\n" + f"branch={args.branch} commit={args.commit}") + + # Prometheus + end_time = time.time() + prometheus_metrics = {} + if is_server_listening("0.0.0.0", 9090): + metrics = ['prompt_tokens_seconds', 'predicted_tokens_seconds', + 'kv_cache_usage_ratio', 'requests_processing', 'requests_deferred'] + + for metric in metrics: + resp = requests.get(f"http://localhost:9090/api/v1/query_range", + params={'query': 'llamacpp:' + metric, 'start': start_time, 'end': end_time, 'step': 2}) + + with open(f"{metric}.json", 'w') as metric_json: + metric_json.write(resp.text) + + if resp.status_code != 200: + print(f"bench: unable to extract prometheus metric {metric}: {resp.text}") + else: + metric_data = resp.json() + values = metric_data['data']['result'][0]['values'] + timestamps, metric_values = zip(*values) + metric_values = [float(value) for value in metric_values] + prometheus_metrics[metric] = metric_values + timestamps_dt = [datetime.fromtimestamp(int(ts)) for ts in timestamps] + plt.figure(figsize=(16, 10), dpi=80) + plt.plot(timestamps_dt, metric_values, label=metric) + plt.xticks(rotation=0, fontsize=14, horizontalalignment='center', alpha=.7) + plt.yticks(fontsize=12, alpha=.7) + + ylabel = f"llamacpp:{metric}" + plt.title(title, + fontsize=14, wrap=True) + plt.grid(axis='both', alpha=.3) + plt.ylabel(ylabel, fontsize=22) + plt.xlabel(xlabel, fontsize=14, wrap=True) + plt.gca().xaxis.set_major_locator(matplotlib.dates.MinuteLocator()) + plt.gca().xaxis.set_major_formatter(matplotlib.dates.DateFormatter("%Y-%m-%d %H:%M:%S")) + plt.gcf().autofmt_xdate() + + # Remove borders + plt.gca().spines["top"].set_alpha(0.0) + plt.gca().spines["bottom"].set_alpha(0.3) + plt.gca().spines["right"].set_alpha(0.0) + plt.gca().spines["left"].set_alpha(0.3) + + # Save the plot as a jpg image + plt.savefig(f'{metric}.jpg', dpi=60) + plt.close() + + # Mermaid format in case images upload failed + with (open(f"{metric}.mermaid", 'w') as mermaid_f): + mermaid = ( + f"""--- +config: + xyChart: + titleFontSize: 12 + width: 900 + height: 600 + themeVariables: + xyChart: + titleColor: "#000000" +--- +xychart-beta + title "{title}" + y-axis "llamacpp:{metric}" + x-axis "llamacpp:{metric}" {int(min(timestamps))} --> {int(max(timestamps))} + line [{', '.join([str(round(float(value), 2)) for value in metric_values])}] + """) + mermaid_f.write(mermaid) + + # 140 chars max for commit status description + bench_results = { + "i": iterations, + "req": { + "p95": round(data['metrics']["http_req_duration"]["p(95)"], 2), + "avg": round(data['metrics']["http_req_duration"]["avg"], 2), + }, + "pp": { + "p95": round(data['metrics']["llamacpp_prompt_processing_second"]["p(95)"], 2), + "avg": round(data['metrics']["llamacpp_prompt_processing_second"]["avg"], 2), + "0": round(mean(prometheus_metrics['prompt_tokens_seconds']), 2), + }, + "tg": { + "p95": round(data['metrics']["llamacpp_tokens_second"]["p(95)"], 2), + "avg": round(data['metrics']["llamacpp_tokens_second"]["avg"], 2), + "0": round(mean(prometheus_metrics['predicted_tokens_seconds']), 2), + }, + } + with open("results.github.env", 'a') as github_env: + github_env.write(f"BENCH_RESULTS={json.dumps(bench_results, indent=None, separators=(',', ':') )}\n") + github_env.write(f"BENCH_ITERATIONS={iterations}\n") + + title = title.replace('\n', ' ') + xlabel = xlabel.replace('\n', ' ') + github_env.write(f"BENCH_GRAPH_TITLE={title}\n") + github_env.write(f"BENCH_GRAPH_XLABEL={xlabel}\n") + + +def start_benchmark(args): + k6_path = './k6' + if 'BENCH_K6_BIN_PATH' in os.environ: + k6_path = os.environ['BENCH_K6_BIN_PATH'] + k6_args = [ + 'run', args.scenario, + '--no-color', + ] + k6_args.extend(['--duration', args.duration]) + k6_args.extend(['--iterations', args.n_prompts]) + k6_args.extend(['--vus', args.parallel]) + k6_args.extend(['--summary-export', 'k6-results.json']) + args = f"SERVER_BENCH_N_PROMPTS={args.n_prompts} SERVER_BENCH_MAX_PROMPT_TOKENS={args.max_prompt_tokens} SERVER_BENCH_MAX_CONTEXT={args.max_tokens} " + args = args + ' '.join([str(arg) for arg in [k6_path, *k6_args]]) + print(f"bench: starting k6 with: {args}") + k6_completed = subprocess.run(args, shell=True, stdout=sys.stdout, stderr=sys.stderr) + if k6_completed.returncode != 0: + raise Exception("bench: unable to run k6") + + +def start_server(args): + server_process = start_server_background(args) + + attempts = 0 + max_attempts = 20 + if 'GITHUB_ACTIONS' in os.environ: + max_attempts *= 2 + + while not is_server_listening(args.host, args.port): + attempts += 1 + if attempts > max_attempts: + assert False, "server not started" + print(f"bench: waiting for server to start ...") + time.sleep(0.5) + + print("bench: server started.") + return server_process + + +def start_server_background(args): + # Start the server + server_path = '../../../build/bin/server' + if 'LLAMA_SERVER_BIN_PATH' in os.environ: + server_path = os.environ['LLAMA_SERVER_BIN_PATH'] + server_args = [ + '--host', args.host, + '--port', args.port, + ] + model_file = args.model_path_prefix + os.path.sep + args.hf_file + model_dir = os.path.dirname(model_file) + if not os.path.exists(model_dir): + os.makedirs(model_dir) + server_args.extend(['--model', model_file]) + server_args.extend(['--hf-repo', args.hf_repo]) + server_args.extend(['--hf-file', args.hf_file]) + server_args.extend(['--n-gpu-layers', args.n_gpu_layers]) + server_args.extend(['--ctx-size', args.ctx_size]) + server_args.extend(['--parallel', args.parallel]) + server_args.extend(['--batch-size', args.batch_size]) + server_args.extend(['--ubatch-size', args.ubatch_size]) + server_args.extend(['--n-predict', args.max_tokens * 2]) + server_args.extend(['--defrag-thold', "0.1"]) + server_args.append('--cont-batching') + server_args.append('--metrics') + server_args.extend(['--log-format', "text"]) + args = [str(arg) for arg in [server_path, *server_args]] + print(f"bench: starting server with: {' '.join(args)}") + pkwargs = { + 'stdout': subprocess.PIPE, + 'stderr': subprocess.PIPE + } + server_process = subprocess.Popen( + args, + **pkwargs) + + def server_log(in_stream, out_stream): + for line in iter(in_stream.readline, b''): + print(line.decode('utf-8'), end='', file=out_stream) + + thread_stdout = threading.Thread(target=server_log, args=(server_process.stdout, sys.stdout)) + thread_stdout.start() + thread_stderr = threading.Thread(target=server_log, args=(server_process.stderr, sys.stderr)) + thread_stderr.start() + + return server_process + + +def is_server_listening(server_fqdn, server_port): + with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock: + result = sock.connect_ex((server_fqdn, server_port)) + _is_server_listening = result == 0 + if _is_server_listening: + print(f"server is listening on {server_fqdn}:{server_port}...") + return _is_server_listening + + +def escape_metric_name(metric_name): + return re.sub('[^A-Z0-9]', '_', metric_name.upper()) + + +if __name__ == '__main__': + main() diff --git a/examples/server/bench/prometheus.yml b/examples/server/bench/prometheus.yml new file mode 100644 index 0000000000000..b15ee52443fe8 --- /dev/null +++ b/examples/server/bench/prometheus.yml @@ -0,0 +1,9 @@ +global: + scrape_interval: 10s + external_labels: + llamacpp: 'server' + +scrape_configs: + - job_name: 'llama.cpp server' + static_configs: + - targets: ['localhost:8080'] diff --git a/examples/server/bench/requirements.txt b/examples/server/bench/requirements.txt new file mode 100644 index 0000000000000..66ed226eda6f0 --- /dev/null +++ b/examples/server/bench/requirements.txt @@ -0,0 +1,2 @@ +matplotlib +requests diff --git a/examples/server/bench/script.js b/examples/server/bench/script.js index a4f5ac5ab22ad..c4c486cdf93d9 100644 --- a/examples/server/bench/script.js +++ b/examples/server/bench/script.js @@ -1,4 +1,4 @@ -import http from 'k6/http' +import sse from 'k6/x/sse' import {check, sleep} from 'k6' import {SharedArray} from 'k6/data' import {Counter, Rate, Trend} from 'k6/metrics' @@ -53,7 +53,9 @@ const data = new SharedArray('conversations', function () { const llamacpp_prompt_tokens = new Trend('llamacpp_prompt_tokens') const llamacpp_completion_tokens = new Trend('llamacpp_completion_tokens') + const llamacpp_tokens_second = new Trend('llamacpp_tokens_second') +const llamacpp_prompt_processing_second = new Trend('llamacpp_prompt_processing_second') const llamacpp_prompt_tokens_total_counter = new Counter('llamacpp_prompt_tokens_total_counter') const llamacpp_completion_tokens_total_counter = new Counter('llamacpp_completion_tokens_total_counter') @@ -86,35 +88,62 @@ export default function () { } ], "model": model, - "stream": false, + "stream": true, + "seed": 42, "max_tokens": max_tokens } - const body = JSON.stringify(payload) + const params = {method: 'POST', body: JSON.stringify(payload)}; + + const startTime = new Date() + let promptEvalEndTime = null + let prompt_tokens = 0 + let completions_tokens = 0 + let finish_reason = null + const res = sse.open(`${server_url}/chat/completions`, params, function (client) { + client.on('event', function (event) { + if (promptEvalEndTime == null) { + promptEvalEndTime = new Date() + } - let res = http.post(`${server_url}/chat/completions`, body, { - headers: {'Content-Type': 'application/json'}, - timeout: '300s' - }) + let chunk = JSON.parse(event.data) + let choice = chunk.choices[0] + if (choice.finish_reason) { + finish_reason = choice.finish_reason + } - check(res, {'success completion': (r) => r.status === 200}) + if (chunk.usage) { + prompt_tokens = chunk.usage.prompt_tokens + llamacpp_prompt_tokens.add(prompt_tokens) + llamacpp_prompt_tokens_total_counter.add(prompt_tokens) + + completions_tokens = chunk.usage.completion_tokens + llamacpp_completion_tokens.add(completions_tokens) + llamacpp_completion_tokens_total_counter.add(completions_tokens) + } + }) - if (res.status === 200) { - const completions = res.json() + client.on('error', function (e) { + console.log('An unexpected error occurred: ', e.error()); + throw e; + }) + }) - llamacpp_prompt_tokens.add(completions.usage.prompt_tokens) - llamacpp_prompt_tokens_total_counter.add(completions.usage.prompt_tokens) + check(res, {'success completion': (r) => r.status === 200}) - llamacpp_completion_tokens.add(completions.usage.completion_tokens) - llamacpp_completion_tokens_total_counter.add(completions.usage.completion_tokens) + const endTime = new Date() - llamacpp_completions_truncated_rate.add(completions.choices[0].finish_reason === 'length') - llamacpp_completions_stop_rate.add(completions.choices[0].finish_reason === 'stop') + const promptEvalTime = promptEvalEndTime - startTime + if (promptEvalTime > 0) { + llamacpp_prompt_processing_second.add(prompt_tokens / (promptEvalEndTime - startTime) * 1.e3) + } - llamacpp_tokens_second.add(completions.usage.total_tokens / res.timings.duration * 1.e3) - } else { - console.error(`response: ${res.body} request=${payload}`) + const completion_time = endTime - promptEvalEndTime + if (completions_tokens > 0 && completion_time > 0) { + llamacpp_tokens_second.add(completions_tokens / completion_time * 1.e3) } + llamacpp_completions_truncated_rate.add(finish_reason === 'length') + llamacpp_completions_stop_rate.add(finish_reason === 'stop') sleep(0.3) } diff --git a/examples/server/chat.mjs b/examples/server/chat.mjs index 219ebb51a1c9b..a79c8a3cd09c2 100644 --- a/examples/server/chat.mjs +++ b/examples/server/chat.mjs @@ -26,8 +26,9 @@ const propOrder = grammarJsonSchemaPropOrder let grammar = null if (grammarJsonSchemaFile) { - const schema = JSON.parse(readFileSync(grammarJsonSchemaFile, 'utf-8')) - const converter = new SchemaConverter(propOrder) + let schema = JSON.parse(readFileSync(grammarJsonSchemaFile, 'utf-8')) + const converter = new SchemaConverter({prop_order: propOrder, allow_fetch: true}) + schema = await converter.resolveRefs(schema, grammarJsonSchemaFile) converter.visit(schema, '') grammar = converter.formatGrammar() } diff --git a/examples/server/completion.js.hpp b/examples/server/completion.js.hpp index 10734091eeaf6..9a7f3986d4c07 100644 --- a/examples/server/completion.js.hpp +++ b/examples/server/completion.js.hpp @@ -43,444 +43,454 @@ unsigned char completion_js[] = { 0x7d, 0x29, 0x20, 0x7b, 0x0a, 0x20, 0x20, 0x6c, 0x65, 0x74, 0x20, 0x63, 0x6f, 0x6e, 0x74, 0x72, 0x6f, 0x6c, 0x6c, 0x65, 0x72, 0x20, 0x3d, 0x20, 0x63, 0x6f, 0x6e, 0x66, 0x69, 0x67, 0x2e, 0x63, 0x6f, 0x6e, 0x74, 0x72, - 0x6f, 0x6c, 0x6c, 0x65, 0x72, 0x3b, 0x0a, 0x0a, 0x20, 0x20, 0x69, 0x66, - 0x20, 0x28, 0x21, 0x63, 0x6f, 0x6e, 0x74, 0x72, 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0x20, 0x72, + 0x65, 0x74, 0x75, 0x72, 0x6e, 0x20, 0x67, 0x65, 0x6e, 0x65, 0x72, 0x61, + 0x74, 0x69, 0x6f, 0x6e, 0x5f, 0x73, 0x65, 0x74, 0x74, 0x69, 0x6e, 0x67, + 0x73, 0x3b, 0x0a, 0x7d, 0x0a }; -unsigned int completion_js_len = 5796; +unsigned int completion_js_len = 5909; diff --git a/examples/server/httplib.h b/examples/server/httplib.h index 28746000cddce..f360bd93ea098 100644 --- a/examples/server/httplib.h +++ b/examples/server/httplib.h @@ -1,14 +1,14 @@ // // httplib.h // -// Copyright (c) 2023 Yuji Hirose. All rights reserved. +// Copyright (c) 2024 Yuji Hirose. All rights reserved. // MIT License // #ifndef CPPHTTPLIB_HTTPLIB_H #define CPPHTTPLIB_HTTPLIB_H -#define CPPHTTPLIB_VERSION "0.12.2" +#define CPPHTTPLIB_VERSION "0.15.3" /* * Configuration @@ -82,6 +82,10 @@ #define CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 8192 #endif +#ifndef CPPHTTPLIB_RANGE_MAX_COUNT +#define CPPHTTPLIB_RANGE_MAX_COUNT 1024 +#endif + #ifndef CPPHTTPLIB_TCP_NODELAY #define CPPHTTPLIB_TCP_NODELAY false #endif @@ -160,10 +164,6 @@ using ssize_t = long; #define WSA_FLAG_NO_HANDLE_INHERIT 0x80 #endif -#ifndef strcasecmp -#define strcasecmp _stricmp -#endif // strcasecmp - using socket_t = SOCKET; #ifdef CPPHTTPLIB_USE_POLL #define poll(fds, nfds, timeout) WSAPoll(fds, nfds, timeout) @@ -172,9 +172,15 @@ using socket_t = SOCKET; #else // not _WIN32 #include -#ifndef _AIX +#if !defined(_AIX) && !defined(__MVS__) #include #endif +#ifdef __MVS__ +#include +#ifndef NI_MAXHOST +#define NI_MAXHOST 1025 +#endif +#endif #include #include #include @@ -187,6 +193,7 @@ using socket_t = SOCKET; #endif #include #include +#include #include #include #include @@ -207,6 +214,7 @@ using socket_t = int; #include #include #include +#include #include #include #include @@ -223,6 +231,9 @@ using socket_t = int; #include #include #include +#include +#include +#include #ifdef CPPHTTPLIB_OPENSSL_SUPPORT #ifdef _WIN32 @@ -237,7 +248,6 @@ using socket_t = int; #ifdef _MSC_VER #pragma comment(lib, "crypt32.lib") -#pragma comment(lib, "cryptui.lib") #endif #elif defined(CPPHTTPLIB_USE_CERTS_FROM_MACOSX_KEYCHAIN) && defined(__APPLE__) #include @@ -259,10 +269,8 @@ using socket_t = int; #include #include -#if OPENSSL_VERSION_NUMBER < 0x1010100fL -#error Sorry, OpenSSL versions prior to 1.1.1 are not supported -#elif OPENSSL_VERSION_NUMBER < 0x30000000L -#define SSL_get1_peer_certificate SSL_get_peer_certificate +#if OPENSSL_VERSION_NUMBER < 0x30000000L +#error Sorry, OpenSSL versions prior to 3.0.0 are not supported #endif #endif @@ -321,7 +329,7 @@ struct scope_exit { explicit scope_exit(std::function &&f) : exit_function(std::move(f)), execute_on_destruction{true} {} - scope_exit(scope_exit &&rhs) + scope_exit(scope_exit &&rhs) noexcept : exit_function(std::move(rhs.exit_function)), execute_on_destruction{rhs.execute_on_destruction} { rhs.release(); @@ -344,6 +352,81 @@ struct scope_exit { } // namespace detail +enum StatusCode { + // Information responses + Continue_100 = 100, + SwitchingProtocol_101 = 101, + Processing_102 = 102, + EarlyHints_103 = 103, + + // Successful responses + OK_200 = 200, + Created_201 = 201, + Accepted_202 = 202, + NonAuthoritativeInformation_203 = 203, + NoContent_204 = 204, + ResetContent_205 = 205, + PartialContent_206 = 206, + MultiStatus_207 = 207, + AlreadyReported_208 = 208, + IMUsed_226 = 226, + + // Redirection messages + MultipleChoices_300 = 300, + MovedPermanently_301 = 301, + Found_302 = 302, + SeeOther_303 = 303, + NotModified_304 = 304, + UseProxy_305 = 305, + unused_306 = 306, + TemporaryRedirect_307 = 307, + PermanentRedirect_308 = 308, + + // Client error responses + BadRequest_400 = 400, + Unauthorized_401 = 401, + PaymentRequired_402 = 402, + Forbidden_403 = 403, + NotFound_404 = 404, + MethodNotAllowed_405 = 405, + NotAcceptable_406 = 406, + ProxyAuthenticationRequired_407 = 407, + RequestTimeout_408 = 408, + Conflict_409 = 409, + Gone_410 = 410, + LengthRequired_411 = 411, + PreconditionFailed_412 = 412, + PayloadTooLarge_413 = 413, + UriTooLong_414 = 414, + UnsupportedMediaType_415 = 415, + RangeNotSatisfiable_416 = 416, + ExpectationFailed_417 = 417, + ImATeapot_418 = 418, + MisdirectedRequest_421 = 421, + UnprocessableContent_422 = 422, + Locked_423 = 423, + FailedDependency_424 = 424, + TooEarly_425 = 425, + UpgradeRequired_426 = 426, + PreconditionRequired_428 = 428, + TooManyRequests_429 = 429, + RequestHeaderFieldsTooLarge_431 = 431, + UnavailableForLegalReasons_451 = 451, + + // Server error responses + InternalServerError_500 = 500, + NotImplemented_501 = 501, + BadGateway_502 = 502, + ServiceUnavailable_503 = 503, + GatewayTimeout_504 = 504, + HttpVersionNotSupported_505 = 505, + VariantAlsoNegotiates_506 = 506, + InsufficientStorage_507 = 507, + LoopDetected_508 = 508, + NotExtended_510 = 510, + NetworkAuthenticationRequired_511 = 511, +}; + using Headers = std::multimap; using Params = std::multimap; @@ -373,17 +456,18 @@ class DataSink { DataSink &operator=(DataSink &&) = delete; std::function write; + std::function is_writable; std::function done; std::function done_with_trailer; std::ostream os; private: - class data_sink_streambuf : public std::streambuf { + class data_sink_streambuf final : public std::streambuf { public: explicit data_sink_streambuf(DataSink &sink) : sink_(sink) {} protected: - std::streamsize xsputn(const char *s, std::streamsize n) { + std::streamsize xsputn(const char *s, std::streamsize n) override { sink_.write(s, static_cast(n)); return n; } @@ -465,6 +549,7 @@ struct Request { MultipartFormDataMap files; Ranges ranges; Match matches; + std::unordered_map path_params; // for client ResponseHandler response_handler; @@ -476,8 +561,7 @@ struct Request { bool has_header(const std::string &key) const; std::string get_header_value(const std::string &key, size_t id = 0) const; - template - T get_header_value(const std::string &key, size_t id = 0) const; + uint64_t get_header_value_u64(const std::string &key, size_t id = 0) const; size_t get_header_value_count(const std::string &key) const; void set_header(const std::string &key, const std::string &val); @@ -509,14 +593,14 @@ struct Response { bool has_header(const std::string &key) const; std::string get_header_value(const std::string &key, size_t id = 0) const; - template - T get_header_value(const std::string &key, size_t id = 0) const; + uint64_t get_header_value_u64(const std::string &key, size_t id = 0) const; size_t get_header_value_count(const std::string &key) const; void set_header(const std::string &key, const std::string &val); - void set_redirect(const std::string &url, int status = 302); + void set_redirect(const std::string &url, int status = StatusCode::Found_302); void set_content(const char *s, size_t n, const std::string &content_type); void set_content(const std::string &s, const std::string &content_type); + void set_content(std::string &&s, const std::string &content_type); void set_content_provider( size_t length, const std::string &content_type, ContentProvider provider, @@ -573,15 +657,16 @@ class TaskQueue { TaskQueue() = default; virtual ~TaskQueue() = default; - virtual void enqueue(std::function fn) = 0; + virtual bool enqueue(std::function fn) = 0; virtual void shutdown() = 0; virtual void on_idle() {} }; -class ThreadPool : public TaskQueue { +class ThreadPool final : public TaskQueue { public: - explicit ThreadPool(size_t n) : shutdown_(false) { + explicit ThreadPool(size_t n, size_t mqr = 0) + : shutdown_(false), max_queued_requests_(mqr) { while (n) { threads_.emplace_back(worker(*this)); n--; @@ -591,13 +676,17 @@ class ThreadPool : public TaskQueue { ThreadPool(const ThreadPool &) = delete; ~ThreadPool() override = default; - void enqueue(std::function fn) override { + bool enqueue(std::function fn) override { { std::unique_lock lock(mutex_); + if (max_queued_requests_ > 0 && jobs_.size() >= max_queued_requests_) { + return false; + } jobs_.push_back(std::move(fn)); } cond_.notify_one(); + return true; } void shutdown() override { @@ -647,6 +736,7 @@ class ThreadPool : public TaskQueue { std::list> jobs_; bool shutdown_; + size_t max_queued_requests_ = 0; std::condition_variable cond_; std::mutex mutex_; @@ -658,6 +748,82 @@ using SocketOptions = std::function; void default_socket_options(socket_t sock); +const char *status_message(int status); + +std::string get_bearer_token_auth(const Request &req); + +namespace detail { + +class MatcherBase { +public: + virtual ~MatcherBase() = default; + + // Match request path and populate its matches and + virtual bool match(Request &request) const = 0; +}; + +/** + * Captures parameters in request path and stores them in Request::path_params + * + * Capture name is a substring of a pattern from : to /. + * The rest of the pattern is matched agains the request path directly + * Parameters are captured starting from the next character after + * the end of the last matched static pattern fragment until the next /. + * + * Example pattern: + * "/path/fragments/:capture/more/fragments/:second_capture" + * Static fragments: + * "/path/fragments/", "more/fragments/" + * + * Given the following request path: + * "/path/fragments/:1/more/fragments/:2" + * the resulting capture will be + * {{"capture", "1"}, {"second_capture", "2"}} + */ +class PathParamsMatcher final : public MatcherBase { +public: + PathParamsMatcher(const std::string &pattern); + + bool match(Request &request) const override; + +private: + static constexpr char marker = ':'; + // Treat segment separators as the end of path parameter capture + // Does not need to handle query parameters as they are parsed before path + // matching + static constexpr char separator = '/'; + + // Contains static path fragments to match against, excluding the '/' after + // path params + // Fragments are separated by path params + std::vector static_fragments_; + // Stores the names of the path parameters to be used as keys in the + // Request::path_params map + std::vector param_names_; +}; + +/** + * Performs std::regex_match on request path + * and stores the result in Request::matches + * + * Note that regex match is performed directly on the whole request. + * This means that wildcard patterns may match multiple path segments with /: + * "/begin/(.*)/end" will match both "/begin/middle/end" and "/begin/1/2/end". + */ +class RegexMatcher final : public MatcherBase { +public: + RegexMatcher(const std::string &pattern) : regex_(pattern) {} + + bool match(Request &request) const override; + +private: + std::regex regex_; +}; + +ssize_t write_headers(Stream &strm, const Headers &headers); + +} // namespace detail + class Server { public: using Handler = std::function; @@ -702,6 +868,7 @@ class Server { bool remove_mount_point(const std::string &mount_point); Server &set_file_extension_and_mimetype_mapping(const std::string &ext, const std::string &mime); + Server &set_default_file_mimetype(const std::string &mime); Server &set_file_request_handler(Handler handler); Server &set_error_handler(HandlerWithResponse handler); @@ -718,6 +885,8 @@ class Server { Server &set_socket_options(SocketOptions socket_options); Server &set_default_headers(Headers headers); + Server & + set_header_writer(std::function const &writer); Server &set_keep_alive_max_count(size_t count); Server &set_keep_alive_timeout(time_t sec); @@ -765,9 +934,14 @@ class Server { size_t payload_max_length_ = CPPHTTPLIB_PAYLOAD_MAX_LENGTH; private: - using Handlers = std::vector>; + using Handlers = + std::vector, Handler>>; using HandlersForContentReader = - std::vector>; + std::vector, + HandlerWithContentReader>>; + + static std::unique_ptr + make_matcher(const std::string &pattern); socket_t create_server_socket(const std::string &host, int port, int socket_flags, @@ -778,16 +952,16 @@ class Server { bool routing(Request &req, Response &res, Stream &strm); bool handle_file_request(const Request &req, Response &res, bool head = false); - bool dispatch_request(Request &req, Response &res, const Handlers &handlers); - bool - dispatch_request_for_content_reader(Request &req, Response &res, - ContentReader content_reader, - const HandlersForContentReader &handlers); + bool dispatch_request(Request &req, Response &res, + const Handlers &handlers) const; + bool dispatch_request_for_content_reader( + Request &req, Response &res, ContentReader content_reader, + const HandlersForContentReader &handlers) const; - bool parse_request_line(const char *s, Request &req); + bool parse_request_line(const char *s, Request &req) const; void apply_ranges(const Request &req, Response &res, - std::string &content_type, std::string &boundary); - bool write_response(Stream &strm, bool close_connection, const Request &req, + std::string &content_type, std::string &boundary) const; + bool write_response(Stream &strm, bool close_connection, Request &req, Response &res); bool write_response_with_content(Stream &strm, bool close_connection, const Request &req, Response &res); @@ -806,21 +980,23 @@ class Server { bool read_content_core(Stream &strm, Request &req, Response &res, ContentReceiver receiver, MultipartContentHeader multipart_header, - ContentReceiver multipart_receiver); + ContentReceiver multipart_receiver) const; virtual bool process_and_close_socket(socket_t sock); + std::atomic is_running_{false}; + std::atomic done_{false}; + struct MountPointEntry { std::string mount_point; std::string base_dir; Headers headers; }; std::vector base_dirs_; - - std::atomic is_running_{false}; - std::atomic done_{false}; std::map file_extension_and_mimetype_map_; + std::string default_file_mimetype_ = "application/octet-stream"; Handler file_request_handler_; + Handlers get_handlers_; Handlers post_handlers_; HandlersForContentReader post_handlers_for_content_reader_; @@ -831,18 +1007,22 @@ class Server { Handlers delete_handlers_; HandlersForContentReader delete_handlers_for_content_reader_; Handlers options_handlers_; + HandlerWithResponse error_handler_; ExceptionHandler exception_handler_; HandlerWithResponse pre_routing_handler_; Handler post_routing_handler_; - Logger logger_; Expect100ContinueHandler expect_100_continue_handler_; + Logger logger_; + int address_family_ = AF_UNSPEC; bool tcp_nodelay_ = CPPHTTPLIB_TCP_NODELAY; SocketOptions socket_options_ = default_socket_options; Headers default_headers_; + std::function header_writer_ = + detail::write_headers; }; enum class Error { @@ -860,17 +1040,19 @@ enum class Error { UnsupportedMultipartBoundaryChars, Compression, ConnectionTimeout, + ProxyConnection, // For internal use only SSLPeerCouldBeClosed_, }; -std::string to_string(const Error error); +std::string to_string(Error error); std::ostream &operator<<(std::ostream &os, const Error &obj); class Result { public: + Result() = default; Result(std::unique_ptr &&res, Error err, Headers &&request_headers = Headers{}) : res_(std::move(res)), err_(err), @@ -893,13 +1075,13 @@ class Result { bool has_request_header(const std::string &key) const; std::string get_request_header_value(const std::string &key, size_t id = 0) const; - template - T get_request_header_value(const std::string &key, size_t id = 0) const; + uint64_t get_request_header_value_u64(const std::string &key, + size_t id = 0) const; size_t get_request_header_value_count(const std::string &key) const; private: std::unique_ptr res_; - Error err_; + Error err_ = Error::Unknown; Headers request_headers_; }; @@ -1059,16 +1241,21 @@ class ClientImpl { bool send(Request &req, Response &res, Error &error); Result send(const Request &req); - size_t is_socket_open() const; + void stop(); - socket_t socket() const; + std::string host() const; + int port() const; - void stop(); + size_t is_socket_open() const; + socket_t socket() const; void set_hostname_addr_map(std::map addr_map); void set_default_headers(Headers headers); + void + set_header_writer(std::function const &writer); + void set_address_family(int family); void set_tcp_nodelay(bool on); void set_socket_options(SocketOptions socket_options); @@ -1117,6 +1304,7 @@ class ClientImpl { void set_ca_cert_path(const std::string &ca_cert_file_path, const std::string &ca_cert_dir_path = std::string()); void set_ca_cert_store(X509_STORE *ca_cert_store); + X509_STORE *create_ca_cert_store(const char *ca_cert, std::size_t size) const; #endif #ifdef CPPHTTPLIB_OPENSSL_SUPPORT @@ -1145,14 +1333,14 @@ class ClientImpl { // Also, shutdown_ssl and close_socket should also NOT be called concurrently // with a DIFFERENT thread sending requests using that socket. virtual void shutdown_ssl(Socket &socket, bool shutdown_gracefully); - void shutdown_socket(Socket &socket); + void shutdown_socket(Socket &socket) const; void close_socket(Socket &socket); bool process_request(Stream &strm, Request &req, Response &res, bool close_connection, Error &error); bool write_content_with_provider(Stream &strm, const Request &req, - Error &error); + Error &error) const; void copy_settings(const ClientImpl &rhs); @@ -1177,6 +1365,10 @@ class ClientImpl { // Default headers Headers default_headers_; + // Header writer + std::function header_writer_ = + detail::write_headers; + // Settings std::string client_cert_path_; std::string client_key_path_; @@ -1239,7 +1431,8 @@ class ClientImpl { Result send_(Request &&req); socket_t create_client_socket(Error &error) const; - bool read_response_line(Stream &strm, const Request &req, Response &res); + bool read_response_line(Stream &strm, const Request &req, + Response &res) const; bool write_request(Stream &strm, Request &req, bool close_connection, Error &error); bool redirect(Request &req, Response &res, Error &error); @@ -1258,7 +1451,7 @@ class ClientImpl { const std::string &content_type); ContentProviderWithoutLength get_multipart_content_provider( const std::string &boundary, const MultipartFormDataItems &items, - const MultipartFormDataProviderItems &provider_items); + const MultipartFormDataProviderItems &provider_items) const; std::string adjust_host_string(const std::string &host) const; @@ -1431,16 +1624,21 @@ class Client { bool send(Request &req, Response &res, Error &error); Result send(const Request &req); - size_t is_socket_open() const; + void stop(); - socket_t socket() const; + std::string host() const; + int port() const; - void stop(); + size_t is_socket_open() const; + socket_t socket() const; void set_hostname_addr_map(std::map addr_map); void set_default_headers(Headers headers); + void + set_header_writer(std::function const &writer); + void set_address_family(int family); void set_tcp_nodelay(bool on); void set_socket_options(SocketOptions socket_options); @@ -1497,6 +1695,7 @@ class Client { const std::string &ca_cert_dir_path = std::string()); void set_ca_cert_store(X509_STORE *ca_cert_store); + void load_ca_cert_store(const char *ca_cert, std::size_t size); long get_openssl_verify_result() const; @@ -1538,7 +1737,7 @@ class SSLServer : public Server { std::mutex ctx_mutex_; }; -class SSLClient : public ClientImpl { +class SSLClient final : public ClientImpl { public: explicit SSLClient(const std::string &host); @@ -1546,16 +1745,19 @@ class SSLClient : public ClientImpl { explicit SSLClient(const std::string &host, int port, const std::string &client_cert_path, - const std::string &client_key_path); + const std::string &client_key_path, + const std::string &private_key_password = std::string()); explicit SSLClient(const std::string &host, int port, X509 *client_cert, - EVP_PKEY *client_key); + EVP_PKEY *client_key, + const std::string &private_key_password = std::string()); ~SSLClient() override; bool is_valid() const override; void set_ca_cert_store(X509_STORE *ca_cert_store); + void load_ca_cert_store(const char *ca_cert, std::size_t size); long get_openssl_verify_result() const; @@ -1564,7 +1766,7 @@ class SSLClient : public ClientImpl { private: bool create_and_connect_socket(Socket &socket, Error &error) override; void shutdown_ssl(Socket &socket, bool shutdown_gracefully) override; - void shutdown_ssl_impl(Socket &socket, bool shutdown_socket); + void shutdown_ssl_impl(Socket &socket, bool shutdown_gracefully); bool process_socket(const Socket &socket, std::function callback) override; @@ -1608,15 +1810,9 @@ inline void duration_to_sec_and_usec(const T &duration, U callback) { callback(static_cast(sec), static_cast(usec)); } -template -inline T get_header_value(const Headers & /*headers*/, - const std::string & /*key*/, size_t /*id*/ = 0, - uint64_t /*def*/ = 0) {} - -template <> -inline uint64_t get_header_value(const Headers &headers, - const std::string &key, size_t id, - uint64_t def) { +inline uint64_t get_header_value_u64(const Headers &headers, + const std::string &key, size_t id, + uint64_t def) { auto rng = headers.equal_range(key); auto it = rng.first; std::advance(it, static_cast(id)); @@ -1628,14 +1824,14 @@ inline uint64_t get_header_value(const Headers &headers, } // namespace detail -template -inline T Request::get_header_value(const std::string &key, size_t id) const { - return detail::get_header_value(headers, key, id, 0); +inline uint64_t Request::get_header_value_u64(const std::string &key, + size_t id) const { + return detail::get_header_value_u64(headers, key, id, 0); } -template -inline T Response::get_header_value(const std::string &key, size_t id) const { - return detail::get_header_value(headers, key, id, 0); +inline uint64_t Response::get_header_value_u64(const std::string &key, + size_t id) const { + return detail::get_header_value_u64(headers, key, id, 0); } template @@ -1665,21 +1861,106 @@ inline ssize_t Stream::write_format(const char *fmt, const Args &...args) { inline void default_socket_options(socket_t sock) { int yes = 1; #ifdef _WIN32 - setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, reinterpret_cast(&yes), - sizeof(yes)); + setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, + reinterpret_cast(&yes), sizeof(yes)); setsockopt(sock, SOL_SOCKET, SO_EXCLUSIVEADDRUSE, - reinterpret_cast(&yes), sizeof(yes)); + reinterpret_cast(&yes), sizeof(yes)); #else #ifdef SO_REUSEPORT - setsockopt(sock, SOL_SOCKET, SO_REUSEPORT, reinterpret_cast(&yes), - sizeof(yes)); + setsockopt(sock, SOL_SOCKET, SO_REUSEPORT, + reinterpret_cast(&yes), sizeof(yes)); #else - setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, reinterpret_cast(&yes), - sizeof(yes)); + setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, + reinterpret_cast(&yes), sizeof(yes)); #endif #endif } +inline const char *status_message(int status) { + switch (status) { + case StatusCode::Continue_100: return "Continue"; + case StatusCode::SwitchingProtocol_101: return "Switching Protocol"; + case StatusCode::Processing_102: return "Processing"; + case StatusCode::EarlyHints_103: return "Early Hints"; + case StatusCode::OK_200: return "OK"; + case StatusCode::Created_201: return "Created"; + case StatusCode::Accepted_202: return "Accepted"; + case StatusCode::NonAuthoritativeInformation_203: + return "Non-Authoritative Information"; + case StatusCode::NoContent_204: return "No Content"; + case StatusCode::ResetContent_205: return "Reset Content"; + case StatusCode::PartialContent_206: return "Partial Content"; + case StatusCode::MultiStatus_207: return "Multi-Status"; + case StatusCode::AlreadyReported_208: return "Already Reported"; + case StatusCode::IMUsed_226: return "IM Used"; + case StatusCode::MultipleChoices_300: return "Multiple Choices"; + case StatusCode::MovedPermanently_301: return "Moved Permanently"; + case StatusCode::Found_302: return "Found"; + case StatusCode::SeeOther_303: return "See Other"; + case StatusCode::NotModified_304: return "Not Modified"; + case StatusCode::UseProxy_305: return "Use Proxy"; + case StatusCode::unused_306: return "unused"; + case StatusCode::TemporaryRedirect_307: return "Temporary Redirect"; + case StatusCode::PermanentRedirect_308: return "Permanent Redirect"; + case StatusCode::BadRequest_400: return "Bad Request"; + case StatusCode::Unauthorized_401: return "Unauthorized"; + case StatusCode::PaymentRequired_402: return "Payment Required"; + case StatusCode::Forbidden_403: return "Forbidden"; + case StatusCode::NotFound_404: return "Not Found"; + case StatusCode::MethodNotAllowed_405: return "Method Not Allowed"; + case StatusCode::NotAcceptable_406: return "Not Acceptable"; + case StatusCode::ProxyAuthenticationRequired_407: + return "Proxy Authentication Required"; + case StatusCode::RequestTimeout_408: return "Request Timeout"; + case StatusCode::Conflict_409: return "Conflict"; + case StatusCode::Gone_410: return "Gone"; + case StatusCode::LengthRequired_411: return "Length Required"; + case StatusCode::PreconditionFailed_412: return "Precondition Failed"; + case StatusCode::PayloadTooLarge_413: return "Payload Too Large"; + case StatusCode::UriTooLong_414: return "URI Too Long"; + case StatusCode::UnsupportedMediaType_415: return "Unsupported Media Type"; + case StatusCode::RangeNotSatisfiable_416: return "Range Not Satisfiable"; + case StatusCode::ExpectationFailed_417: return "Expectation Failed"; + case StatusCode::ImATeapot_418: return "I'm a teapot"; + case StatusCode::MisdirectedRequest_421: return "Misdirected Request"; + case StatusCode::UnprocessableContent_422: return "Unprocessable Content"; + case StatusCode::Locked_423: return "Locked"; + case StatusCode::FailedDependency_424: return "Failed Dependency"; + case StatusCode::TooEarly_425: return "Too Early"; + case StatusCode::UpgradeRequired_426: return "Upgrade Required"; + case StatusCode::PreconditionRequired_428: return "Precondition Required"; + case StatusCode::TooManyRequests_429: return "Too Many Requests"; + case StatusCode::RequestHeaderFieldsTooLarge_431: + return "Request Header Fields Too Large"; + case StatusCode::UnavailableForLegalReasons_451: + return "Unavailable For Legal Reasons"; + case StatusCode::NotImplemented_501: return "Not Implemented"; + case StatusCode::BadGateway_502: return "Bad Gateway"; + case StatusCode::ServiceUnavailable_503: return "Service Unavailable"; + case StatusCode::GatewayTimeout_504: return "Gateway Timeout"; + case StatusCode::HttpVersionNotSupported_505: + return "HTTP Version Not Supported"; + case StatusCode::VariantAlsoNegotiates_506: return "Variant Also Negotiates"; + case StatusCode::InsufficientStorage_507: return "Insufficient Storage"; + case StatusCode::LoopDetected_508: return "Loop Detected"; + case StatusCode::NotExtended_510: return "Not Extended"; + case StatusCode::NetworkAuthenticationRequired_511: + return "Network Authentication Required"; + + default: + case StatusCode::InternalServerError_500: return "Internal Server Error"; + } +} + +inline std::string get_bearer_token_auth(const Request &req) { + if (req.has_header("Authorization")) { + static std::string BearerHeaderPrefix = "Bearer "; + return req.get_header_value("Authorization") + .substr(BearerHeaderPrefix.length()); + } + return ""; +} + template inline Server & Server::set_read_timeout(const std::chrono::duration &duration) { @@ -1720,6 +2001,7 @@ inline std::string to_string(const Error error) { return "Unsupported HTTP multipart boundary characters"; case Error::Compression: return "Compression failed"; case Error::ConnectionTimeout: return "Connection timed out"; + case Error::ProxyConnection: return "Proxy connection failed"; case Error::Unknown: return "Unknown"; default: break; } @@ -1733,10 +2015,9 @@ inline std::ostream &operator<<(std::ostream &os, const Error &obj) { return os; } -template -inline T Result::get_request_header_value(const std::string &key, - size_t id) const { - return detail::get_header_value(request_headers_, key, id, 0); +inline uint64_t Result::get_request_header_value_u64(const std::string &key, + size_t id) const { + return detail::get_header_value_u64(request_headers_, key, id, 0); } template @@ -1790,7 +2071,7 @@ void hosted_at(const std::string &hostname, std::vector &addrs); std::string append_query_params(const std::string &path, const Params ¶ms); -std::pair make_range_header(Ranges ranges); +std::pair make_range_header(const Ranges &ranges); std::pair make_basic_authentication_header(const std::string &username, @@ -1810,6 +2091,9 @@ std::string trim_copy(const std::string &s); void split(const char *b, const char *e, char d, std::function fn); +void split(const char *b, const char *e, char d, size_t m, + std::function fn); + bool process_client_socket(socket_t sock, time_t read_timeout_sec, time_t read_timeout_usec, time_t write_timeout_sec, time_t write_timeout_usec, @@ -1844,7 +2128,7 @@ enum class EncodingType { None = 0, Gzip, Brotli }; EncodingType encoding_type(const Request &req, const Response &res); -class BufferStream : public Stream { +class BufferStream final : public Stream { public: BufferStream() = default; ~BufferStream() override = default; @@ -1884,19 +2168,19 @@ class decompressor { Callback callback) = 0; }; -class nocompressor : public compressor { +class nocompressor final : public compressor { public: - virtual ~nocompressor() = default; + ~nocompressor() override = default; bool compress(const char *data, size_t data_length, bool /*last*/, Callback callback) override; }; #ifdef CPPHTTPLIB_ZLIB_SUPPORT -class gzip_compressor : public compressor { +class gzip_compressor final : public compressor { public: gzip_compressor(); - ~gzip_compressor(); + ~gzip_compressor() override; bool compress(const char *data, size_t data_length, bool last, Callback callback) override; @@ -1906,10 +2190,10 @@ class gzip_compressor : public compressor { z_stream strm_; }; -class gzip_decompressor : public decompressor { +class gzip_decompressor final : public decompressor { public: gzip_decompressor(); - ~gzip_decompressor(); + ~gzip_decompressor() override; bool is_valid() const override; @@ -1923,7 +2207,7 @@ class gzip_decompressor : public decompressor { #endif #ifdef CPPHTTPLIB_BROTLI_SUPPORT -class brotli_compressor : public compressor { +class brotli_compressor final : public compressor { public: brotli_compressor(); ~brotli_compressor(); @@ -1935,7 +2219,7 @@ class brotli_compressor : public compressor { BrotliEncoderState *state_ = nullptr; }; -class brotli_decompressor : public decompressor { +class brotli_decompressor final : public decompressor { public: brotli_decompressor(); ~brotli_decompressor(); @@ -1972,6 +2256,29 @@ class stream_line_reader { std::string glowable_buffer_; }; +class mmap { +public: + mmap(const char *path); + ~mmap(); + + bool open(const char *path); + void close(); + + bool is_open() const; + size_t size() const; + const char *data() const; + +private: +#if defined(_WIN32) + HANDLE hFile_; + HANDLE hMapping_; +#else + int fd_; +#endif + size_t size_; + void *addr_; +}; + } // namespace detail // ---------------------------------------------------------------------------- @@ -2003,7 +2310,7 @@ inline bool from_hex_to_i(const std::string &s, size_t i, size_t cnt, val = 0; for (; cnt; i++, cnt--) { if (!s[i]) { return false; } - int v = 0; + auto v = 0; if (is_hex(s[i], v)) { val = val * 16 + v; } else { @@ -2014,7 +2321,7 @@ inline bool from_hex_to_i(const std::string &s, size_t i, size_t cnt, } inline std::string from_i_to_hex(size_t n) { - const char *charset = "0123456789abcdef"; + static const auto charset = "0123456789abcdef"; std::string ret; do { ret = charset[n & 15] + ret; @@ -2025,7 +2332,7 @@ inline std::string from_i_to_hex(size_t n) { inline size_t to_utf8(int code, char *buff) { if (code < 0x0080) { - buff[0] = (code & 0x7F); + buff[0] = static_cast(code & 0x7F); return 1; } else if (code < 0x0800) { buff[0] = static_cast(0xC0 | ((code >> 6) & 0x1F)); @@ -2064,8 +2371,8 @@ inline std::string base64_encode(const std::string &in) { std::string out; out.reserve(in.size()); - int val = 0; - int valb = -6; + auto val = 0; + auto valb = -6; for (auto c : in) { val = (val << 8) + static_cast(c); @@ -2112,6 +2419,11 @@ inline bool is_valid_path(const std::string &path) { // Read component auto beg = i; while (i < path.size() && path[i] != '/') { + if (path[i] == '\0') { + return false; + } else if (path[i] == '\\') { + return false; + } i++; } @@ -2196,7 +2508,7 @@ inline std::string decode_url(const std::string &s, for (size_t i = 0; i < s.size(); i++) { if (s[i] == '%' && i + 1 < s.size()) { if (s[i + 1] == 'u') { - int val = 0; + auto val = 0; if (from_hex_to_i(s, i + 2, 4, val)) { // 4 digits Unicode codes char buff[4]; @@ -2207,7 +2519,7 @@ inline std::string decode_url(const std::string &s, result += s[i]; } } else { - int val = 0; + auto val = 0; if (from_hex_to_i(s, i + 1, 2, val)) { // 2 digits hex codes result += static_cast(val); @@ -2260,16 +2572,30 @@ inline std::string trim_copy(const std::string &s) { return s.substr(r.first, r.second - r.first); } +inline std::string trim_double_quotes_copy(const std::string &s) { + if (s.length() >= 2 && s.front() == '"' && s.back() == '"') { + return s.substr(1, s.size() - 2); + } + return s; +} + inline void split(const char *b, const char *e, char d, std::function fn) { + return split(b, e, d, (std::numeric_limits::max)(), std::move(fn)); +} + +inline void split(const char *b, const char *e, char d, size_t m, + std::function fn) { size_t i = 0; size_t beg = 0; + size_t count = 1; while (e ? (b + i < e) : (b[i] != '\0')) { - if (b[i] == d) { + if (b[i] == d && count < m) { auto r = trim(b, e, beg, i); if (r.first < r.second) { fn(&b[r.first], &b[r.second]); } beg = i + 1; + count++; } i++; } @@ -2345,6 +2671,105 @@ inline void stream_line_reader::append(char c) { } } +inline mmap::mmap(const char *path) +#if defined(_WIN32) + : hFile_(NULL), hMapping_(NULL) +#else + : fd_(-1) +#endif + , + size_(0), addr_(nullptr) { + open(path); +} + +inline mmap::~mmap() { close(); } + +inline bool mmap::open(const char *path) { + close(); + +#if defined(_WIN32) + std::wstring wpath; + for (size_t i = 0; i < strlen(path); i++) { + wpath += path[i]; + } + + hFile_ = ::CreateFile2(wpath.c_str(), GENERIC_READ, FILE_SHARE_READ, + OPEN_EXISTING, NULL); + + if (hFile_ == INVALID_HANDLE_VALUE) { return false; } + + LARGE_INTEGER size{}; + if (!::GetFileSizeEx(hFile_, &size)) { return false; } + size_ = static_cast(size.QuadPart); + + hMapping_ = + ::CreateFileMappingFromApp(hFile_, NULL, PAGE_READONLY, size_, NULL); + + if (hMapping_ == NULL) { + close(); + return false; + } + + addr_ = ::MapViewOfFileFromApp(hMapping_, FILE_MAP_READ, 0, 0); +#else + fd_ = ::open(path, O_RDONLY); + if (fd_ == -1) { return false; } + + struct stat sb; + if (fstat(fd_, &sb) == -1) { + close(); + return false; + } + size_ = static_cast(sb.st_size); + + addr_ = ::mmap(NULL, size_, PROT_READ, MAP_PRIVATE, fd_, 0); +#endif + + if (addr_ == nullptr) { + close(); + return false; + } + + return true; +} + +inline bool mmap::is_open() const { return addr_ != nullptr; } + +inline size_t mmap::size() const { return size_; } + +inline const char *mmap::data() const { + return static_cast(addr_); +} + +inline void mmap::close() { +#if defined(_WIN32) + if (addr_) { + ::UnmapViewOfFile(addr_); + addr_ = nullptr; + } + + if (hMapping_) { + ::CloseHandle(hMapping_); + hMapping_ = NULL; + } + + if (hFile_ != INVALID_HANDLE_VALUE) { + ::CloseHandle(hFile_); + hFile_ = INVALID_HANDLE_VALUE; + } +#else + if (addr_ != nullptr) { + munmap(addr_, size_); + addr_ = nullptr; + } + + if (fd_ != -1) { + ::close(fd_); + fd_ = -1; + } +#endif + size_ = 0; +} inline int close_socket(socket_t sock) { #ifdef _WIN32 return closesocket(sock); @@ -2354,7 +2779,7 @@ inline int close_socket(socket_t sock) { } template inline ssize_t handle_EINTR(T fn) { - ssize_t res = false; + ssize_t res = 0; while (true) { res = fn(); if (res < 0 && errno == EINTR) { continue; } @@ -2399,7 +2824,7 @@ inline ssize_t select_read(socket_t sock, time_t sec, time_t usec) { return handle_EINTR([&]() { return poll(&pfd_read, 1, timeout); }); #else #ifndef _WIN32 - if (sock >= FD_SETSIZE) { return 1; } + if (sock >= FD_SETSIZE) { return -1; } #endif fd_set fds; @@ -2427,7 +2852,7 @@ inline ssize_t select_write(socket_t sock, time_t sec, time_t usec) { return handle_EINTR([&]() { return poll(&pfd_read, 1, timeout); }); #else #ifndef _WIN32 - if (sock >= FD_SETSIZE) { return 1; } + if (sock >= FD_SETSIZE) { return -1; } #endif fd_set fds; @@ -2458,7 +2883,7 @@ inline Error wait_until_socket_is_ready(socket_t sock, time_t sec, if (poll_res == 0) { return Error::ConnectionTimeout; } if (poll_res > 0 && pfd_read.revents & (POLLIN | POLLOUT)) { - int error = 0; + auto error = 0; socklen_t len = sizeof(error); auto res = getsockopt(sock, SOL_SOCKET, SO_ERROR, reinterpret_cast(&error), &len); @@ -2490,7 +2915,7 @@ inline Error wait_until_socket_is_ready(socket_t sock, time_t sec, if (ret == 0) { return Error::ConnectionTimeout; } if (ret > 0 && (FD_ISSET(sock, &fdsr) || FD_ISSET(sock, &fdsw))) { - int error = 0; + auto error = 0; socklen_t len = sizeof(error); auto res = getsockopt(sock, SOL_SOCKET, SO_ERROR, reinterpret_cast(&error), &len); @@ -2512,7 +2937,7 @@ inline bool is_socket_alive(socket_t sock) { return detail::read_socket(sock, &buf[0], sizeof(buf), MSG_PEEK) > 0; } -class SocketStream : public Stream { +class SocketStream final : public Stream { public: SocketStream(socket_t sock, time_t read_timeout_sec, time_t read_timeout_usec, time_t write_timeout_sec, time_t write_timeout_usec); @@ -2537,11 +2962,11 @@ class SocketStream : public Stream { size_t read_buff_off_ = 0; size_t read_buff_content_size_ = 0; - static const size_t read_buff_size_ = 1024 * 4; + static const size_t read_buff_size_ = 1024l * 4; }; #ifdef CPPHTTPLIB_OPENSSL_SUPPORT -class SSLSocketStream : public Stream { +class SSLSocketStream final : public Stream { public: SSLSocketStream(socket_t sock, SSL *ssl, time_t read_timeout_sec, time_t read_timeout_usec, time_t write_timeout_sec, @@ -2666,7 +3091,7 @@ socket_t create_socket(const std::string &host, const std::string &ip, int port, #ifndef _WIN32 if (hints.ai_family == AF_UNIX) { const auto addrlen = host.length(); - if (addrlen > sizeof(sockaddr_un::sun_path)) return INVALID_SOCKET; + if (addrlen > sizeof(sockaddr_un::sun_path)) { return INVALID_SOCKET; } auto sock = socket(hints.ai_family, hints.ai_socktype, hints.ai_protocol); if (sock != INVALID_SOCKET) { @@ -2735,17 +3160,27 @@ socket_t create_socket(const std::string &host, const std::string &ip, int port, #endif if (tcp_nodelay) { - int yes = 1; - setsockopt(sock, IPPROTO_TCP, TCP_NODELAY, reinterpret_cast(&yes), - sizeof(yes)); + auto yes = 1; +#ifdef _WIN32 + setsockopt(sock, IPPROTO_TCP, TCP_NODELAY, + reinterpret_cast(&yes), sizeof(yes)); +#else + setsockopt(sock, IPPROTO_TCP, TCP_NODELAY, + reinterpret_cast(&yes), sizeof(yes)); +#endif } if (socket_options) { socket_options(sock); } if (rp->ai_family == AF_INET6) { - int no = 0; - setsockopt(sock, IPPROTO_IPV6, IPV6_V6ONLY, reinterpret_cast(&no), - sizeof(no)); + auto no = 0; +#ifdef _WIN32 + setsockopt(sock, IPPROTO_IPV6, IPV6_V6ONLY, + reinterpret_cast(&no), sizeof(no)); +#else + setsockopt(sock, IPPROTO_IPV6, IPV6_V6ONLY, + reinterpret_cast(&no), sizeof(no)); +#endif } // bind or connect @@ -2804,7 +3239,7 @@ inline bool bind_ip_address(socket_t sock, const std::string &host) { return ret; } -#if !defined _WIN32 && !defined ANDROID && !defined _AIX +#if !defined _WIN32 && !defined ANDROID && !defined _AIX && !defined __MVS__ #define USE_IF2IP #endif @@ -2860,7 +3295,7 @@ inline socket_t create_client_socket( #ifdef USE_IF2IP auto ip_from_if = if2ip(address_family, intf); if (ip_from_if.empty()) { ip_from_if = intf; } - if (!bind_ip_address(sock2, ip_from_if.c_str())) { + if (!bind_ip_address(sock2, ip_from_if)) { error = Error::BindIPAddress; return false; } @@ -2888,13 +3323,14 @@ inline socket_t create_client_socket( #ifdef _WIN32 auto timeout = static_cast(read_timeout_sec * 1000 + read_timeout_usec / 1000); - setsockopt(sock2, SOL_SOCKET, SO_RCVTIMEO, (char *)&timeout, - sizeof(timeout)); + setsockopt(sock2, SOL_SOCKET, SO_RCVTIMEO, + reinterpret_cast(&timeout), sizeof(timeout)); #else timeval tv; tv.tv_sec = static_cast(read_timeout_sec); tv.tv_usec = static_cast(read_timeout_usec); - setsockopt(sock2, SOL_SOCKET, SO_RCVTIMEO, (char *)&tv, sizeof(tv)); + setsockopt(sock2, SOL_SOCKET, SO_RCVTIMEO, + reinterpret_cast(&tv), sizeof(tv)); #endif } { @@ -2902,13 +3338,14 @@ inline socket_t create_client_socket( #ifdef _WIN32 auto timeout = static_cast(write_timeout_sec * 1000 + write_timeout_usec / 1000); - setsockopt(sock2, SOL_SOCKET, SO_SNDTIMEO, (char *)&timeout, - sizeof(timeout)); + setsockopt(sock2, SOL_SOCKET, SO_SNDTIMEO, + reinterpret_cast(&timeout), sizeof(timeout)); #else timeval tv; tv.tv_sec = static_cast(write_timeout_sec); tv.tv_usec = static_cast(write_timeout_usec); - setsockopt(sock2, SOL_SOCKET, SO_SNDTIMEO, (char *)&tv, sizeof(tv)); + setsockopt(sock2, SOL_SOCKET, SO_SNDTIMEO, + reinterpret_cast(&tv), sizeof(tv)); #endif } @@ -3008,18 +3445,20 @@ inline constexpr unsigned int operator"" _t(const char *s, size_t l) { } // namespace udl -inline const char * +inline std::string find_content_type(const std::string &path, - const std::map &user_data) { + const std::map &user_data, + const std::string &default_content_type) { auto ext = file_extension(path); auto it = user_data.find(ext); - if (it != user_data.end()) { return it->second.c_str(); } + if (it != user_data.end()) { return it->second; } using udl::operator""_t; switch (str2tag(ext)) { - default: return nullptr; + default: return default_content_type; + case "css"_t: return "text/css"; case "csv"_t: return "text/csv"; case "htm"_t: @@ -3072,76 +3511,6 @@ find_content_type(const std::string &path, } } -inline const char *status_message(int status) { - switch (status) { - case 100: return "Continue"; - case 101: return "Switching Protocol"; - case 102: return "Processing"; - case 103: return "Early Hints"; - case 200: return "OK"; - case 201: return "Created"; - case 202: return "Accepted"; - case 203: return "Non-Authoritative Information"; - case 204: return "No Content"; - case 205: return "Reset Content"; - case 206: return "Partial Content"; - case 207: return "Multi-Status"; - case 208: return "Already Reported"; - case 226: return "IM Used"; - case 300: return "Multiple Choice"; - case 301: return "Moved Permanently"; - case 302: return "Found"; - case 303: return "See Other"; - case 304: return "Not Modified"; - case 305: return "Use Proxy"; - case 306: return "unused"; - case 307: return "Temporary Redirect"; - case 308: return "Permanent Redirect"; - case 400: return "Bad Request"; - case 401: return "Unauthorized"; - case 402: return "Payment Required"; - case 403: return "Forbidden"; - case 404: return "Not Found"; - case 405: return "Method Not Allowed"; - case 406: return "Not Acceptable"; - case 407: return "Proxy Authentication Required"; - case 408: return "Request Timeout"; - case 409: return "Conflict"; - case 410: return "Gone"; - case 411: return "Length Required"; - case 412: return "Precondition Failed"; - case 413: return "Payload Too Large"; - case 414: return "URI Too Long"; - case 415: return "Unsupported Media Type"; - case 416: return "Range Not Satisfiable"; - case 417: return "Expectation Failed"; - case 418: return "I'm a teapot"; - case 421: return "Misdirected Request"; - case 422: return "Unprocessable Entity"; - case 423: return "Locked"; - case 424: return "Failed Dependency"; - case 425: return "Too Early"; - case 426: return "Upgrade Required"; - case 428: return "Precondition Required"; - case 429: return "Too Many Requests"; - case 431: return "Request Header Fields Too Large"; - case 451: return "Unavailable For Legal Reasons"; - case 501: return "Not Implemented"; - case 502: return "Bad Gateway"; - case 503: return "Service Unavailable"; - case 504: return "Gateway Timeout"; - case 505: return "HTTP Version Not Supported"; - case 506: return "Variant Also Negotiates"; - case 507: return "Insufficient Storage"; - case 508: return "Loop Detected"; - case 510: return "Not Extended"; - case 511: return "Network Authentication Required"; - - default: - case 500: return "Internal Server Error"; - } -} - inline bool can_compress_content_type(const std::string &content_type) { using udl::operator""_t; @@ -3218,7 +3587,7 @@ inline bool gzip_compressor::compress(const char *data, size_t data_length, data += strm_.avail_in; auto flush = (last && data_length == 0) ? Z_FINISH : Z_NO_FLUSH; - int ret = Z_OK; + auto ret = Z_OK; std::array buff{}; do { @@ -3262,7 +3631,7 @@ inline bool gzip_decompressor::decompress(const char *data, size_t data_length, Callback callback) { assert(is_valid_); - int ret = Z_OK; + auto ret = Z_OK; do { constexpr size_t max_avail_in = @@ -3276,16 +3645,12 @@ inline bool gzip_decompressor::decompress(const char *data, size_t data_length, data += strm_.avail_in; std::array buff{}; - while (strm_.avail_in > 0) { + while (strm_.avail_in > 0 && ret == Z_OK) { strm_.avail_out = static_cast(buff.size()); strm_.next_out = reinterpret_cast(buff.data()); - auto prev_avail_in = strm_.avail_in; - ret = inflate(&strm_, Z_NO_FLUSH); - if (prev_avail_in - strm_.avail_in == 0) { return false; } - assert(ret != Z_STREAM_ERROR); switch (ret) { case Z_NEED_DICT: @@ -3298,7 +3663,7 @@ inline bool gzip_decompressor::decompress(const char *data, size_t data_length, } } - if (ret != Z_OK && ret != Z_STREAM_END) return false; + if (ret != Z_OK && ret != Z_STREAM_END) { return false; } } while (data_length > 0); @@ -3367,7 +3732,7 @@ inline bool brotli_decompressor::decompress(const char *data, return 0; } - const uint8_t *next_in = (const uint8_t *)data; + auto next_in = reinterpret_cast(data); size_t avail_in = data_length; size_t total_out; @@ -3437,6 +3802,9 @@ inline bool parse_header(const char *beg, const char *end, T fn) { } if (p < end) { + auto key_len = key_end - beg; + if (!key_len) { return false; } + auto key = std::string(beg, key_end); auto val = compare_case_ignore(key, "Location") ? std::string(p, end) @@ -3526,11 +3894,7 @@ inline bool read_content_without_length(Stream &strm, uint64_t r = 0; for (;;) { auto n = strm.read(buf, CPPHTTPLIB_RECV_BUFSIZ); - if (n < 0) { - return false; - } else if (n == 0) { - return true; - } + if (n <= 0) { return true; } if (!out(buf, static_cast(n), r, 0)) { return false; } r += static_cast(n); @@ -3566,7 +3930,7 @@ inline bool read_content_chunked(Stream &strm, T &x, if (!line_reader.getline()) { return false; } - if (strcmp(line_reader.ptr(), "\r\n")) { return false; } + if (strcmp(line_reader.ptr(), "\r\n") != 0) { return false; } if (!line_reader.getline()) { return false; } } @@ -3576,7 +3940,7 @@ inline bool read_content_chunked(Stream &strm, T &x, // Trailer if (!line_reader.getline()) { return false; } - while (strcmp(line_reader.ptr(), "\r\n")) { + while (strcmp(line_reader.ptr(), "\r\n") != 0) { if (line_reader.size() > CPPHTTPLIB_HEADER_MAX_LENGTH) { return false; } // Exclude line terminator @@ -3595,8 +3959,8 @@ inline bool read_content_chunked(Stream &strm, T &x, } inline bool is_chunked_transfer_encoding(const Headers &headers) { - return !strcasecmp(get_header_value(headers, "Transfer-Encoding", 0, ""), - "chunked"); + return compare_case_ignore( + get_header_value(headers, "Transfer-Encoding", 0, ""), "chunked"); } template @@ -3611,14 +3975,14 @@ bool prepare_content_receiver(T &x, int &status, #ifdef CPPHTTPLIB_ZLIB_SUPPORT decompressor = detail::make_unique(); #else - status = 415; + status = StatusCode::UnsupportedMediaType_415; return false; #endif } else if (encoding.find("br") != std::string::npos) { #ifdef CPPHTTPLIB_BROTLI_SUPPORT decompressor = detail::make_unique(); #else - status = 415; + status = StatusCode::UnsupportedMediaType_415; return false; #endif } @@ -3634,7 +3998,7 @@ bool prepare_content_receiver(T &x, int &status, }; return callback(std::move(out)); } else { - status = 500; + status = StatusCode::InternalServerError_500; return false; } } @@ -3662,7 +4026,7 @@ bool read_content(Stream &strm, T &x, size_t payload_max_length, int &status, } else if (!has_header(x.headers, "Content-Length")) { ret = read_content_without_length(strm, out); } else { - auto len = get_header_value(x.headers, "Content-Length"); + auto len = get_header_value_u64(x.headers, "Content-Length", 0, 0); if (len > payload_max_length) { exceed_payload_max_length = true; skip_content_with_length(strm, len); @@ -3672,7 +4036,10 @@ bool read_content(Stream &strm, T &x, size_t payload_max_length, int &status, } } - if (!ret) { status = exceed_payload_max_length ? 413 : 400; } + if (!ret) { + status = exceed_payload_max_length ? StatusCode::PayloadTooLarge_413 + : StatusCode::BadRequest_400; + } return ret; }); } // namespace detail @@ -3720,6 +4087,8 @@ inline bool write_content(Stream &strm, const ContentProvider &content_provider, return ok; }; + data_sink.is_writable = [&]() -> bool { return strm.is_writable(); }; + while (offset < end_offset && !is_shutting_down()) { if (!strm.is_writable()) { error = Error::Write; @@ -3764,6 +4133,8 @@ write_content_without_length(Stream &strm, return ok; }; + data_sink.is_writable = [&]() -> bool { return strm.is_writable(); }; + data_sink.done = [&](void) { data_available = false; }; while (data_available && !is_shutting_down()) { @@ -3814,6 +4185,8 @@ write_content_chunked(Stream &strm, const ContentProvider &content_provider, return ok; }; + data_sink.is_writable = [&]() -> bool { return strm.is_writable(); }; + auto done_with_trailer = [&](const Headers *trailer) { if (!ok) { return; } @@ -3898,7 +4271,8 @@ inline bool redirect(T &cli, Request &req, Response &res, new_req.path = path; new_req.redirect_count_ -= 1; - if (res.status == 303 && (req.method != "GET" && req.method != "HEAD")) { + if (res.status == StatusCode::SeeOther_303 && + (req.method != "GET" && req.method != "HEAD")) { new_req.method = "GET"; new_req.body.clear(); new_req.headers.clear(); @@ -3910,7 +4284,8 @@ inline bool redirect(T &cli, Request &req, Response &res, if (ret) { req = new_req; res = new_res; - res.location = location; + + if (res.location.empty()) { res.location = location; } } return ret; } @@ -3957,14 +4332,34 @@ inline bool parse_multipart_boundary(const std::string &content_type, if (pos == std::string::npos) { return false; } auto end = content_type.find(';', pos); auto beg = pos + strlen(boundary_keyword); - boundary = content_type.substr(beg, end - beg); - if (boundary.length() >= 2 && boundary.front() == '"' && - boundary.back() == '"') { - boundary = boundary.substr(1, boundary.size() - 2); - } + boundary = trim_double_quotes_copy(content_type.substr(beg, end - beg)); return !boundary.empty(); } +inline void parse_disposition_params(const std::string &s, Params ¶ms) { + std::set cache; + split(s.data(), s.data() + s.size(), ';', [&](const char *b, const char *e) { + std::string kv(b, e); + if (cache.find(kv) != cache.end()) { return; } + cache.insert(kv); + + std::string key; + std::string val; + split(b, e, '=', [&](const char *b2, const char *e2) { + if (key.empty()) { + key.assign(b2, e2); + } else { + val.assign(b2, e2); + } + }); + + if (!key.empty()) { + params.emplace(trim_double_quotes_copy((key)), + trim_double_quotes_copy((val))); + } + }); +} + #ifdef CPPHTTPLIB_NO_EXCEPTIONS inline bool parse_range_header(const std::string &s, Ranges &ranges) { #else @@ -3975,9 +4370,9 @@ inline bool parse_range_header(const std::string &s, Ranges &ranges) try { if (std::regex_match(s, m, re_first_range)) { auto pos = static_cast(m.position(1)); auto len = static_cast(m.length(1)); - bool all_valid_ranges = true; + auto all_valid_ranges = true; split(&s[pos], &s[pos + len], ',', [&](const char *b, const char *e) { - if (!all_valid_ranges) return; + if (!all_valid_ranges) { return; } static auto re_another_range = std::regex(R"(\s*(\d*)-(\d*))"); std::cmatch cm; if (std::regex_match(b, e, cm, re_another_range)) { @@ -4022,11 +4417,6 @@ class MultipartFormDataParser { bool parse(const char *buf, size_t n, const ContentReceiver &content_callback, const MultipartContentHeader &header_callback) { - // TODO: support 'filename*' - static const std::regex re_content_disposition( - R"~(^Content-Disposition:\s*form-data;\s*name="(.*?)"(?:;\s*filename="(.*?)")?(?:;\s*filename\*=\S+)?\s*$)~", - std::regex_constants::icase); - buf_append(buf, n); while (buf_size() > 0) { @@ -4059,18 +4449,54 @@ class MultipartFormDataParser { break; } - static const std::string header_name = "content-type:"; const auto header = buf_head(pos); - if (start_with_case_ignore(header, header_name)) { - file_.content_type = trim_copy(header.substr(header_name.size())); + + if (!parse_header(header.data(), header.data() + header.size(), + [&](std::string &&, std::string &&) {})) { + is_valid_ = false; + return false; + } + + static const std::string header_content_type = "Content-Type:"; + + if (start_with_case_ignore(header, header_content_type)) { + file_.content_type = + trim_copy(header.substr(header_content_type.size())); } else { + static const std::regex re_content_disposition( + R"~(^Content-Disposition:\s*form-data;\s*(.*)$)~", + std::regex_constants::icase); + std::smatch m; if (std::regex_match(header, m, re_content_disposition)) { - file_.name = m[1]; - file_.filename = m[2]; - } else { - is_valid_ = false; - return false; + Params params; + parse_disposition_params(m[1], params); + + auto it = params.find("name"); + if (it != params.end()) { + file_.name = it->second; + } else { + is_valid_ = false; + return false; + } + + it = params.find("filename"); + if (it != params.end()) { file_.filename = it->second; } + + it = params.find("filename*"); + if (it != params.end()) { + // Only allow UTF-8 enconnding... + static const std::regex re_rfc5987_encoding( + R"~(^UTF-8''(.+?)$)~", std::regex_constants::icase); + + std::smatch m2; + if (std::regex_match(it->second, m2, re_rfc5987_encoding)) { + file_.filename = decode_url(m2[1], false); // override... + } else { + is_valid_ = false; + return false; + } + } } } buf_erase(pos + crlf_.size()); @@ -4108,9 +4534,9 @@ class MultipartFormDataParser { buf_erase(crlf_.size()); state_ = 1; } else { - if (dash_crlf_.size() > buf_size()) { return true; } - if (buf_start_with(dash_crlf_)) { - buf_erase(dash_crlf_.size()); + if (dash_.size() > buf_size()) { return true; } + if (buf_start_with(dash_)) { + buf_erase(dash_.size()); is_valid_ = true; buf_erase(buf_size()); // Remove epilogue } else { @@ -4143,7 +4569,6 @@ class MultipartFormDataParser { const std::string dash_ = "--"; const std::string crlf_ = "\r\n"; - const std::string dash_crlf_ = "--\r\n"; std::string boundary_; std::string dash_boundary_crlf_; std::string crlf_dash_boundary_; @@ -4230,28 +4655,32 @@ inline std::string to_lower(const char *beg, const char *end) { return out; } -inline std::string make_multipart_data_boundary() { +inline std::string random_string(size_t length) { static const char data[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"; // std::random_device might actually be deterministic on some // platforms, but due to lack of support in the c++ standard library, // doing better requires either some ugly hacks or breaking portability. - std::random_device seed_gen; + static std::random_device seed_gen; // Request 128 bits of entropy for initialization - std::seed_seq seed_sequence{seed_gen(), seed_gen(), seed_gen(), seed_gen()}; - std::mt19937 engine(seed_sequence); + static std::seed_seq seed_sequence{seed_gen(), seed_gen(), seed_gen(), + seed_gen()}; - std::string result = "--cpp-httplib-multipart-data-"; + static std::mt19937 engine(seed_sequence); - for (auto i = 0; i < 16; i++) { + std::string result; + for (size_t i = 0; i < length; i++) { result += data[engine() % (sizeof(data) - 1)]; } - return result; } +inline std::string make_multipart_data_boundary() { + return "--cpp-httplib-multipart-data-" + detail::random_string(16); +} + inline bool is_multipart_boundary_chars_valid(const std::string &boundary) { auto valid = true; for (size_t i = 0; i < boundary.size(); i++) { @@ -4304,48 +4733,97 @@ serialize_multipart_formdata(const MultipartFormDataItems &items, body += item.content + serialize_multipart_formdata_item_end(); } - if (finish) body += serialize_multipart_formdata_finish(boundary); + if (finish) { body += serialize_multipart_formdata_finish(boundary); } return body; } -inline std::pair -get_range_offset_and_length(const Request &req, size_t content_length, - size_t index) { - auto r = req.ranges[index]; +inline bool range_error(Request &req, Response &res) { + if (!req.ranges.empty() && 200 <= res.status && res.status < 300) { + ssize_t contant_len = static_cast( + res.content_length_ ? res.content_length_ : res.body.size()); - if (r.first == -1 && r.second == -1) { - return std::make_pair(0, content_length); - } + ssize_t prev_first_pos = -1; + ssize_t prev_last_pos = -1; + size_t overwrapping_count = 0; - auto slen = static_cast(content_length); + // NOTE: The following Range check is based on '14.2. Range' in RFC 9110 + // 'HTTP Semantics' to avoid potential denial-of-service attacks. + // https://www.rfc-editor.org/rfc/rfc9110#section-14.2 - if (r.first == -1) { - r.first = (std::max)(static_cast(0), slen - r.second); - r.second = slen - 1; + // Too many ranges + if (req.ranges.size() > CPPHTTPLIB_RANGE_MAX_COUNT) { return true; } + + for (auto &r : req.ranges) { + auto &first_pos = r.first; + auto &last_pos = r.second; + + if (first_pos == -1 && last_pos == -1) { + first_pos = 0; + last_pos = contant_len; + } + + if (first_pos == -1) { + first_pos = contant_len - last_pos; + last_pos = contant_len - 1; + } + + if (last_pos == -1) { last_pos = contant_len - 1; } + + // Range must be within content length + if (!(0 <= first_pos && first_pos <= last_pos && + last_pos <= contant_len - 1)) { + return true; + } + + // Ranges must be in ascending order + if (first_pos <= prev_first_pos) { return true; } + + // Request must not have more than two overlapping ranges + if (first_pos <= prev_last_pos) { + overwrapping_count++; + if (overwrapping_count > 2) { return true; } + } + + prev_first_pos = (std::max)(prev_first_pos, first_pos); + prev_last_pos = (std::max)(prev_last_pos, last_pos); + } } - if (r.second == -1) { r.second = slen - 1; } + return false; +} + +inline std::pair +get_range_offset_and_length(Range r, size_t content_length) { + (void)(content_length); // patch to get rid of "unused parameter" on release build + assert(r.first != -1 && r.second != -1); + assert(0 <= r.first && r.first < static_cast(content_length)); + assert(r.first <= r.second && + r.second < static_cast(content_length)); + return std::make_pair(r.first, static_cast(r.second - r.first) + 1); } -inline std::string make_content_range_header_field(size_t offset, size_t length, - size_t content_length) { +inline std::string make_content_range_header_field( + const std::pair &offset_and_length, size_t content_length) { + auto st = offset_and_length.first; + auto ed = st + offset_and_length.second - 1; + std::string field = "bytes "; - field += std::to_string(offset); + field += std::to_string(st); field += "-"; - field += std::to_string(offset + length - 1); + field += std::to_string(ed); field += "/"; field += std::to_string(content_length); return field; } template -bool process_multipart_ranges_data(const Request &req, Response &res, +bool process_multipart_ranges_data(const Request &req, const std::string &boundary, const std::string &content_type, - SToken stoken, CToken ctoken, - Content content) { + size_t content_length, SToken stoken, + CToken ctoken, Content content) { for (size_t i = 0; i < req.ranges.size(); i++) { ctoken("--"); stoken(boundary); @@ -4356,50 +4834,51 @@ bool process_multipart_ranges_data(const Request &req, Response &res, ctoken("\r\n"); } - auto offsets = get_range_offset_and_length(req, res.body.size(), i); - auto offset = offsets.first; - auto length = offsets.second; + auto offset_and_length = + get_range_offset_and_length(req.ranges[i], content_length); ctoken("Content-Range: "); - stoken(make_content_range_header_field(offset, length, res.body.size())); + stoken(make_content_range_header_field(offset_and_length, content_length)); ctoken("\r\n"); ctoken("\r\n"); - if (!content(offset, length)) { return false; } + + if (!content(offset_and_length.first, offset_and_length.second)) { + return false; + } ctoken("\r\n"); } ctoken("--"); stoken(boundary); - ctoken("--\r\n"); + ctoken("--"); return true; } -inline bool make_multipart_ranges_data(const Request &req, Response &res, +inline void make_multipart_ranges_data(const Request &req, Response &res, const std::string &boundary, const std::string &content_type, + size_t content_length, std::string &data) { - return process_multipart_ranges_data( - req, res, boundary, content_type, + process_multipart_ranges_data( + req, boundary, content_type, content_length, [&](const std::string &token) { data += token; }, [&](const std::string &token) { data += token; }, [&](size_t offset, size_t length) { - if (offset < res.body.size()) { - data += res.body.substr(offset, length); - return true; - } - return false; + assert(offset + length <= content_length); + data += res.body.substr(offset, length); + return true; }); } -inline size_t -get_multipart_ranges_data_length(const Request &req, Response &res, - const std::string &boundary, - const std::string &content_type) { +inline size_t get_multipart_ranges_data_length(const Request &req, + const std::string &boundary, + const std::string &content_type, + size_t content_length) { size_t data_length = 0; process_multipart_ranges_data( - req, res, boundary, content_type, + req, boundary, content_type, content_length, [&](const std::string &token) { data_length += token.size(); }, [&](const std::string &token) { data_length += token.size(); }, [&](size_t /*offset*/, size_t length) { @@ -4411,13 +4890,13 @@ get_multipart_ranges_data_length(const Request &req, Response &res, } template -inline bool write_multipart_ranges_data(Stream &strm, const Request &req, - Response &res, - const std::string &boundary, - const std::string &content_type, - const T &is_shutting_down) { +inline bool +write_multipart_ranges_data(Stream &strm, const Request &req, Response &res, + const std::string &boundary, + const std::string &content_type, + size_t content_length, const T &is_shutting_down) { return process_multipart_ranges_data( - req, res, boundary, content_type, + req, boundary, content_type, content_length, [&](const std::string &token) { strm.write(token); }, [&](const std::string &token) { strm.write(token); }, [&](size_t offset, size_t length) { @@ -4426,18 +4905,6 @@ inline bool write_multipart_ranges_data(Stream &strm, const Request &req, }); } -inline std::pair -get_range_offset_and_length(const Request &req, const Response &res, - size_t index) { - auto r = req.ranges[index]; - - if (r.second == -1) { - r.second = static_cast(res.content_length_) - 1; - } - - return std::make_pair(r.first, r.second - r.first + 1); -} - inline bool expect_content(const Request &req) { if (req.method == "POST" || req.method == "PUT" || req.method == "PATCH" || req.method == "PRI" || req.method == "DELETE") { @@ -4471,7 +4938,7 @@ inline std::string message_digest(const std::string &s, const EVP_MD *algo) { std::stringstream ss; for (auto i = 0u; i < hash_length; ++i) { ss << std::hex << std::setw(2) << std::setfill('0') - << (unsigned int)hash[i]; + << static_cast(hash[i]); } return ss.str(); @@ -4564,7 +5031,7 @@ inline bool retrieve_root_certs_from_keychain(CFObjectPtr &certs) { inline bool add_certs_to_x509_store(CFArrayRef certs, X509_STORE *store) { auto result = false; - for (int i = 0; i < CFArrayGetCount(certs); ++i) { + for (auto i = 0; i < CFArrayGetCount(certs); ++i) { const auto cert = reinterpret_cast( CFArrayGetValueAtIndex(certs, i)); @@ -4707,7 +5174,7 @@ inline bool parse_www_authenticate(const Response &res, s = s.substr(pos + 1); auto beg = std::sregex_iterator(s.begin(), s.end(), re); for (auto i = beg; i != std::sregex_iterator(); ++i) { - auto m = *i; + const auto &m = *i; auto key = s.substr(static_cast(m.position(1)), static_cast(m.length(1))); auto val = m.length(2) > 0 @@ -4724,20 +5191,6 @@ inline bool parse_www_authenticate(const Response &res, return false; } -// https://stackoverflow.com/questions/440133/how-do-i-create-a-random-alpha-numeric-string-in-c/440240#answer-440240 -inline std::string random_string(size_t length) { - auto randchar = []() -> char { - const char charset[] = "0123456789" - "ABCDEFGHIJKLMNOPQRSTUVWXYZ" - "abcdefghijklmnopqrstuvwxyz"; - const size_t max_index = (sizeof(charset) - 1); - return charset[static_cast(std::rand()) % max_index]; - }; - std::string str(length, 0); - std::generate_n(str.begin(), length, randchar); - return str; -} - class ContentProviderAdapter { public: explicit ContentProviderAdapter( @@ -4782,7 +5235,7 @@ inline void hosted_at(const std::string &hostname, const auto &addr = *reinterpret_cast(rp->ai_addr); std::string ip; - int dummy = -1; + auto dummy = -1; if (detail::get_ip_and_port(addr, sizeof(struct sockaddr_storage), ip, dummy)) { addrs.push_back(ip); @@ -4802,10 +5255,11 @@ inline std::string append_query_params(const std::string &path, } // Header utilities -inline std::pair make_range_header(Ranges ranges) { +inline std::pair +make_range_header(const Ranges &ranges) { std::string field = "bytes="; auto i = 0; - for (auto r : ranges) { + for (const auto &r : ranges) { if (i != 0) { field += ", "; } if (r.first != -1) { field += std::to_string(r.first); } field += '-'; @@ -4924,7 +5378,7 @@ inline void Response::set_redirect(const std::string &url, int stat) { if (300 <= stat && stat < 400) { this->status = stat; } else { - this->status = 302; + this->status = StatusCode::Found_302; } } } @@ -4943,13 +5397,22 @@ inline void Response::set_content(const std::string &s, set_content(s.data(), s.size(), content_type); } +inline void Response::set_content(std::string &&s, + const std::string &content_type) { + body = std::move(s); + + auto rng = headers.equal_range("Content-Type"); + headers.erase(rng.first, rng.second); + set_header("Content-Type", content_type); +} + inline void Response::set_content_provider( size_t in_length, const std::string &content_type, ContentProvider provider, ContentProviderResourceReleaser resource_releaser) { set_header("Content-Type", content_type); content_length_ = in_length; if (in_length > 0) { content_provider_ = std::move(provider); } - content_provider_resource_releaser_ = resource_releaser; + content_provider_resource_releaser_ = std::move(resource_releaser); is_chunked_content_provider_ = false; } @@ -4959,7 +5422,7 @@ inline void Response::set_content_provider( set_header("Content-Type", content_type); content_length_ = 0; content_provider_ = detail::ContentProviderAdapter(std::move(provider)); - content_provider_resource_releaser_ = resource_releaser; + content_provider_resource_releaser_ = std::move(resource_releaser); is_chunked_content_provider_ = false; } @@ -4969,7 +5432,7 @@ inline void Response::set_chunked_content_provider( set_header("Content-Type", content_type); content_length_ = 0; content_provider_ = detail::ContentProviderAdapter(std::move(provider)); - content_provider_resource_releaser_ = resource_releaser; + content_provider_resource_releaser_ = std::move(resource_releaser); is_chunked_content_provider_ = true; } @@ -5010,7 +5473,7 @@ inline SocketStream::SocketStream(socket_t sock, time_t read_timeout_sec, write_timeout_sec_(write_timeout_sec), write_timeout_usec_(write_timeout_usec), read_buff_(read_buff_size_, 0) {} -inline SocketStream::~SocketStream() {} +inline SocketStream::~SocketStream() = default; inline bool SocketStream::is_readable() const { return select_read(sock_, read_timeout_sec_, read_timeout_usec_) > 0; @@ -5120,6 +5583,99 @@ inline socket_t BufferStream::socket() const { return 0; } inline const std::string &BufferStream::get_buffer() const { return buffer; } +inline PathParamsMatcher::PathParamsMatcher(const std::string &pattern) { + // One past the last ending position of a path param substring + std::size_t last_param_end = 0; + +#ifndef CPPHTTPLIB_NO_EXCEPTIONS + // Needed to ensure that parameter names are unique during matcher + // construction + // If exceptions are disabled, only last duplicate path + // parameter will be set + std::unordered_set param_name_set; +#endif + + while (true) { + const auto marker_pos = pattern.find(marker, last_param_end); + if (marker_pos == std::string::npos) { break; } + + static_fragments_.push_back( + pattern.substr(last_param_end, marker_pos - last_param_end)); + + const auto param_name_start = marker_pos + 1; + + auto sep_pos = pattern.find(separator, param_name_start); + if (sep_pos == std::string::npos) { sep_pos = pattern.length(); } + + auto param_name = + pattern.substr(param_name_start, sep_pos - param_name_start); + +#ifndef CPPHTTPLIB_NO_EXCEPTIONS + if (param_name_set.find(param_name) != param_name_set.cend()) { + std::string msg = "Encountered path parameter '" + param_name + + "' multiple times in route pattern '" + pattern + "'."; + throw std::invalid_argument(msg); + } +#endif + + param_names_.push_back(std::move(param_name)); + + last_param_end = sep_pos + 1; + } + + if (last_param_end < pattern.length()) { + static_fragments_.push_back(pattern.substr(last_param_end)); + } +} + +inline bool PathParamsMatcher::match(Request &request) const { + request.matches = std::smatch(); + request.path_params.clear(); + request.path_params.reserve(param_names_.size()); + + // One past the position at which the path matched the pattern last time + std::size_t starting_pos = 0; + for (size_t i = 0; i < static_fragments_.size(); ++i) { + const auto &fragment = static_fragments_[i]; + + if (starting_pos + fragment.length() > request.path.length()) { + return false; + } + + // Avoid unnecessary allocation by using strncmp instead of substr + + // comparison + if (std::strncmp(request.path.c_str() + starting_pos, fragment.c_str(), + fragment.length()) != 0) { + return false; + } + + starting_pos += fragment.length(); + + // Should only happen when we have a static fragment after a param + // Example: '/users/:id/subscriptions' + // The 'subscriptions' fragment here does not have a corresponding param + if (i >= param_names_.size()) { continue; } + + auto sep_pos = request.path.find(separator, starting_pos); + if (sep_pos == std::string::npos) { sep_pos = request.path.length(); } + + const auto ¶m_name = param_names_[i]; + + request.path_params.emplace( + param_name, request.path.substr(starting_pos, sep_pos - starting_pos)); + + // Mark everythin up to '/' as matched + starting_pos = sep_pos + 1; + } + // Returns false if the path is longer than the pattern + return starting_pos >= request.path.length(); +} + +inline bool RegexMatcher::match(Request &request) const { + request.path_params.clear(); + return std::regex_match(request.path, request.matches, regex_); +} + } // namespace detail // HTTP server implementation @@ -5131,69 +5687,72 @@ inline Server::Server() #endif } -inline Server::~Server() {} +inline Server::~Server() = default; + +inline std::unique_ptr +Server::make_matcher(const std::string &pattern) { + if (pattern.find("/:") != std::string::npos) { + return detail::make_unique(pattern); + } else { + return detail::make_unique(pattern); + } +} inline Server &Server::Get(const std::string &pattern, Handler handler) { - get_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + get_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } inline Server &Server::Post(const std::string &pattern, Handler handler) { - post_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + post_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } inline Server &Server::Post(const std::string &pattern, HandlerWithContentReader handler) { - post_handlers_for_content_reader_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + post_handlers_for_content_reader_.emplace_back(make_matcher(pattern), + std::move(handler)); return *this; } inline Server &Server::Put(const std::string &pattern, Handler handler) { - put_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + put_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } inline Server &Server::Put(const std::string &pattern, HandlerWithContentReader handler) { - put_handlers_for_content_reader_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + put_handlers_for_content_reader_.emplace_back(make_matcher(pattern), + std::move(handler)); return *this; } inline Server &Server::Patch(const std::string &pattern, Handler handler) { - patch_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + patch_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } inline Server &Server::Patch(const std::string &pattern, HandlerWithContentReader handler) { - patch_handlers_for_content_reader_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + patch_handlers_for_content_reader_.emplace_back(make_matcher(pattern), + std::move(handler)); return *this; } inline Server &Server::Delete(const std::string &pattern, Handler handler) { - delete_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + delete_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } inline Server &Server::Delete(const std::string &pattern, HandlerWithContentReader handler) { - delete_handlers_for_content_reader_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + delete_handlers_for_content_reader_.emplace_back(make_matcher(pattern), + std::move(handler)); return *this; } inline Server &Server::Options(const std::string &pattern, Handler handler) { - options_handlers_.push_back( - std::make_pair(std::regex(pattern), std::move(handler))); + options_handlers_.emplace_back(make_matcher(pattern), std::move(handler)); return *this; } @@ -5231,6 +5790,11 @@ Server::set_file_extension_and_mimetype_mapping(const std::string &ext, return *this; } +inline Server &Server::set_default_file_mimetype(const std::string &mime) { + default_file_mimetype_ = mime; + return *this; +} + inline Server &Server::set_file_request_handler(Handler handler) { file_request_handler_ = std::move(handler); return *this; @@ -5272,7 +5836,6 @@ inline Server &Server::set_logger(Logger logger) { inline Server & Server::set_expect_100_continue_handler(Expect100ContinueHandler handler) { expect_100_continue_handler_ = std::move(handler); - return *this; } @@ -5296,6 +5859,12 @@ inline Server &Server::set_default_headers(Headers headers) { return *this; } +inline Server &Server::set_header_writer( + std::function const &writer) { + header_writer_ = writer; + return *this; +} + inline Server &Server::set_keep_alive_max_count(size_t count) { keep_alive_max_count_ = count; return *this; @@ -5331,8 +5900,7 @@ inline Server &Server::set_payload_max_length(size_t length) { inline bool Server::bind_to_port(const std::string &host, int port, int socket_flags) { - if (bind_internal(host, port, socket_flags) < 0) return false; - return true; + return bind_internal(host, port, socket_flags) >= 0; } inline int Server::bind_to_any_port(const std::string &host, int socket_flags) { return bind_internal(host, 0, socket_flags); @@ -5366,7 +5934,7 @@ inline void Server::stop() { } } -inline bool Server::parse_request_line(const char *s, Request &req) { +inline bool Server::parse_request_line(const char *s, Request &req) const { auto len = strlen(s); if (len < 2 || s[len - 2] != '\r' || s[len - 1] != '\n') { return false; } len -= 2; @@ -5407,7 +5975,7 @@ inline bool Server::parse_request_line(const char *s, Request &req) { size_t count = 0; detail::split(req.target.data(), req.target.data() + req.target.size(), '?', - [&](const char *b, const char *e) { + 2, [&](const char *b, const char *e) { switch (count) { case 0: req.path = detail::decode_url(std::string(b, e), false); @@ -5430,7 +5998,10 @@ inline bool Server::parse_request_line(const char *s, Request &req) { } inline bool Server::write_response(Stream &strm, bool close_connection, - const Request &req, Response &res) { + Request &req, Response &res) { + // NOTE: `req.ranges` should be empty, otherwise it will be applied + // incorrectly to the error content. + req.ranges.clear(); return write_response_core(strm, close_connection, req, res, false); } @@ -5486,11 +6057,11 @@ inline bool Server::write_response_core(Stream &strm, bool close_connection, detail::BufferStream bstrm; if (!bstrm.write_format("HTTP/1.1 %d %s\r\n", res.status, - detail::status_message(res.status))) { + status_message(res.status))) { return false; } - if (!detail::write_headers(bstrm, res.headers)) { return false; } + if (!header_writer_(bstrm, res.headers)) { return false; } // Flush buffer auto &data = bstrm.get_buffer(); @@ -5508,7 +6079,6 @@ inline bool Server::write_response_core(Stream &strm, bool close_connection, if (write_content_with_provider(strm, req, res, boundary, content_type)) { res.content_provider_success_ = true; } else { - res.content_provider_success_ = false; ret = false; } } @@ -5533,15 +6103,16 @@ Server::write_content_with_provider(Stream &strm, const Request &req, return detail::write_content(strm, res.content_provider_, 0, res.content_length_, is_shutting_down); } else if (req.ranges.size() == 1) { - auto offsets = - detail::get_range_offset_and_length(req, res.content_length_, 0); - auto offset = offsets.first; - auto length = offsets.second; - return detail::write_content(strm, res.content_provider_, offset, length, - is_shutting_down); + auto offset_and_length = detail::get_range_offset_and_length( + req.ranges[0], res.content_length_); + + return detail::write_content(strm, res.content_provider_, + offset_and_length.first, + offset_and_length.second, is_shutting_down); } else { return detail::write_multipart_ranges_data( - strm, req, res, boundary, content_type, is_shutting_down); + strm, req, res, boundary, content_type, res.content_length_, + is_shutting_down); } } else { if (res.is_chunked_content_provider_) { @@ -5598,7 +6169,7 @@ inline bool Server::read_content(Stream &strm, Request &req, Response &res) { const auto &content_type = req.get_header_value("Content-Type"); if (!content_type.find("application/x-www-form-urlencoded")) { if (req.body.size() > CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH) { - res.status = 413; // NOTE: should be 414? + res.status = StatusCode::PayloadTooLarge_413; // NOTE: should be 414? return false; } detail::parse_query_text(req.body, req.params); @@ -5617,10 +6188,11 @@ inline bool Server::read_content_with_content_receiver( std::move(multipart_receiver)); } -inline bool Server::read_content_core(Stream &strm, Request &req, Response &res, - ContentReceiver receiver, - MultipartContentHeader multipart_header, - ContentReceiver multipart_receiver) { +inline bool +Server::read_content_core(Stream &strm, Request &req, Response &res, + ContentReceiver receiver, + MultipartContentHeader multipart_header, + ContentReceiver multipart_receiver) const { detail::MultipartFormDataParser multipart_form_data_parser; ContentReceiverWithProgress out; @@ -5628,7 +6200,7 @@ inline bool Server::read_content_core(Stream &strm, Request &req, Response &res, const auto &content_type = req.get_header_value("Content-Type"); std::string boundary; if (!detail::parse_multipart_boundary(content_type, boundary)) { - res.status = 400; + res.status = StatusCode::BadRequest_400; return false; } @@ -5664,7 +6236,7 @@ inline bool Server::read_content_core(Stream &strm, Request &req, Response &res, if (req.is_multipart_form_data()) { if (!multipart_form_data_parser.is_valid()) { - res.status = 400; + res.status = StatusCode::BadRequest_400; return false; } } @@ -5683,17 +6255,26 @@ inline bool Server::handle_file_request(const Request &req, Response &res, if (path.back() == '/') { path += "index.html"; } if (detail::is_file(path)) { - detail::read_file(path, res.body); - auto type = - detail::find_content_type(path, file_extension_and_mimetype_map_); - if (type) { res.set_header("Content-Type", type); } for (const auto &kv : entry.headers) { - res.set_header(kv.first.c_str(), kv.second); + res.set_header(kv.first, kv.second); } - res.status = req.has_header("Range") ? 206 : 200; + + auto mm = std::make_shared(path.c_str()); + if (!mm->is_open()) { return false; } + + res.set_content_provider( + mm->size(), + detail::find_content_type(path, file_extension_and_mimetype_map_, + default_file_mimetype_), + [mm](size_t offset, size_t length, DataSink &sink) -> bool { + sink.write(mm->data() + offset, length); + return true; + }); + if (!head && file_request_handler_) { file_request_handler_(req, res); } + return true; } } @@ -5789,13 +6370,14 @@ inline bool Server::listen_internal() { #ifdef _WIN32 auto timeout = static_cast(read_timeout_sec_ * 1000 + read_timeout_usec_ / 1000); - setsockopt(sock, SOL_SOCKET, SO_RCVTIMEO, (char *)&timeout, - sizeof(timeout)); + setsockopt(sock, SOL_SOCKET, SO_RCVTIMEO, + reinterpret_cast(&timeout), sizeof(timeout)); #else timeval tv; tv.tv_sec = static_cast(read_timeout_sec_); tv.tv_usec = static_cast(read_timeout_usec_); - setsockopt(sock, SOL_SOCKET, SO_RCVTIMEO, (char *)&tv, sizeof(tv)); + setsockopt(sock, SOL_SOCKET, SO_RCVTIMEO, + reinterpret_cast(&tv), sizeof(tv)); #endif } { @@ -5803,17 +6385,22 @@ inline bool Server::listen_internal() { #ifdef _WIN32 auto timeout = static_cast(write_timeout_sec_ * 1000 + write_timeout_usec_ / 1000); - setsockopt(sock, SOL_SOCKET, SO_SNDTIMEO, (char *)&timeout, - sizeof(timeout)); + setsockopt(sock, SOL_SOCKET, SO_SNDTIMEO, + reinterpret_cast(&timeout), sizeof(timeout)); #else timeval tv; tv.tv_sec = static_cast(write_timeout_sec_); tv.tv_usec = static_cast(write_timeout_usec_); - setsockopt(sock, SOL_SOCKET, SO_SNDTIMEO, (char *)&tv, sizeof(tv)); + setsockopt(sock, SOL_SOCKET, SO_SNDTIMEO, + reinterpret_cast(&tv), sizeof(tv)); #endif } - task_queue->enqueue([this, sock]() { process_and_close_socket(sock); }); + if (!task_queue->enqueue( + [this, sock]() { process_and_close_socket(sock); })) { + detail::shutdown_socket(sock); + detail::close_socket(sock); + } } task_queue->shutdown(); @@ -5829,7 +6416,7 @@ inline bool Server::routing(Request &req, Response &res, Stream &strm) { } // File handler - bool is_head_request = req.method == "HEAD"; + auto is_head_request = req.method == "HEAD"; if ((req.method == "GET" || is_head_request) && handle_file_request(req, res, is_head_request)) { return true; @@ -5895,17 +6482,17 @@ inline bool Server::routing(Request &req, Response &res, Stream &strm) { return dispatch_request(req, res, patch_handlers_); } - res.status = 400; + res.status = StatusCode::BadRequest_400; return false; } inline bool Server::dispatch_request(Request &req, Response &res, - const Handlers &handlers) { + const Handlers &handlers) const { for (const auto &x : handlers) { - const auto &pattern = x.first; + const auto &matcher = x.first; const auto &handler = x.second; - if (std::regex_match(req.path, req.matches, pattern)) { + if (matcher->match(req)) { handler(req, res); return true; } @@ -5915,18 +6502,18 @@ inline bool Server::dispatch_request(Request &req, Response &res, inline void Server::apply_ranges(const Request &req, Response &res, std::string &content_type, - std::string &boundary) { + std::string &boundary) const { if (req.ranges.size() > 1) { - boundary = detail::make_multipart_data_boundary(); - auto it = res.headers.find("Content-Type"); if (it != res.headers.end()) { content_type = it->second; res.headers.erase(it); } - res.headers.emplace("Content-Type", - "multipart/byteranges; boundary=" + boundary); + boundary = detail::make_multipart_data_boundary(); + + res.set_header("Content-Type", + "multipart/byteranges; boundary=" + boundary); } auto type = detail::encoding_type(req, res); @@ -5937,16 +6524,17 @@ inline void Server::apply_ranges(const Request &req, Response &res, if (req.ranges.empty()) { length = res.content_length_; } else if (req.ranges.size() == 1) { - auto offsets = - detail::get_range_offset_and_length(req, res.content_length_, 0); - auto offset = offsets.first; - length = offsets.second; + auto offset_and_length = detail::get_range_offset_and_length( + req.ranges[0], res.content_length_); + + length = offset_and_length.second; + auto content_range = detail::make_content_range_header_field( - offset, length, res.content_length_); + offset_and_length, res.content_length_); res.set_header("Content-Range", content_range); } else { - length = detail::get_multipart_ranges_data_length(req, res, boundary, - content_type); + length = detail::get_multipart_ranges_data_length( + req, boundary, content_type, res.content_length_); } res.set_header("Content-Length", std::to_string(length)); } else { @@ -5965,28 +6553,22 @@ inline void Server::apply_ranges(const Request &req, Response &res, if (req.ranges.empty()) { ; } else if (req.ranges.size() == 1) { - auto offsets = - detail::get_range_offset_and_length(req, res.body.size(), 0); - auto offset = offsets.first; - auto length = offsets.second; + auto offset_and_length = + detail::get_range_offset_and_length(req.ranges[0], res.body.size()); + auto offset = offset_and_length.first; + auto length = offset_and_length.second; + auto content_range = detail::make_content_range_header_field( - offset, length, res.body.size()); + offset_and_length, res.body.size()); res.set_header("Content-Range", content_range); - if (offset < res.body.size()) { - res.body = res.body.substr(offset, length); - } else { - res.body.clear(); - res.status = 416; - } + + assert(offset + length <= res.body.size()); + res.body = res.body.substr(offset, length); } else { std::string data; - if (detail::make_multipart_ranges_data(req, res, boundary, content_type, - data)) { - res.body.swap(data); - } else { - res.body.clear(); - res.status = 416; - } + detail::make_multipart_ranges_data(req, res, boundary, content_type, + res.body.size(), data); + res.body.swap(data); } if (type != detail::EncodingType::None) { @@ -6025,12 +6607,12 @@ inline void Server::apply_ranges(const Request &req, Response &res, inline bool Server::dispatch_request_for_content_reader( Request &req, Response &res, ContentReader content_reader, - const HandlersForContentReader &handlers) { + const HandlersForContentReader &handlers) const { for (const auto &x : handlers) { - const auto &pattern = x.first; + const auto &matcher = x.first; const auto &handler = x.second; - if (std::regex_match(req.path, req.matches, pattern)) { + if (matcher->match(req)) { handler(req, res, content_reader); return true; } @@ -6050,15 +6632,10 @@ Server::process_request(Stream &strm, bool close_connection, if (!line_reader.getline()) { return false; } Request req; - Response res; + Response res; res.version = "HTTP/1.1"; - - for (const auto &header : default_headers_) { - if (res.headers.find(header.first) == res.headers.end()) { - res.headers.insert(header); - } - } + res.headers = default_headers_; #ifdef _WIN32 // TODO: Increase FD_SETSIZE statically (libzmq), dynamically (MySQL). @@ -6068,7 +6645,7 @@ Server::process_request(Stream &strm, bool close_connection, if (strm.socket() >= FD_SETSIZE) { Headers dummy; detail::read_headers(strm, dummy); - res.status = 500; + res.status = StatusCode::InternalServerError_500; return write_response(strm, close_connection, req, res); } #endif @@ -6078,14 +6655,14 @@ Server::process_request(Stream &strm, bool close_connection, if (line_reader.size() > CPPHTTPLIB_REQUEST_URI_MAX_LENGTH) { Headers dummy; detail::read_headers(strm, dummy); - res.status = 414; + res.status = StatusCode::UriTooLong_414; return write_response(strm, close_connection, req, res); } // Request line and headers if (!parse_request_line(line_reader.ptr(), req) || !detail::read_headers(strm, req.headers)) { - res.status = 400; + res.status = StatusCode::BadRequest_400; return write_response(strm, close_connection, req, res); } @@ -6109,7 +6686,7 @@ Server::process_request(Stream &strm, bool close_connection, if (req.has_header("Range")) { const auto &range_header_value = req.get_header_value("Range"); if (!detail::parse_range_header(range_header_value, req.ranges)) { - res.status = 416; + res.status = StatusCode::RangeNotSatisfiable_416; return write_response(strm, close_connection, req, res); } } @@ -6117,22 +6694,22 @@ Server::process_request(Stream &strm, bool close_connection, if (setup_request) { setup_request(req); } if (req.get_header_value("Expect") == "100-continue") { - auto status = 100; + int status = StatusCode::Continue_100; if (expect_100_continue_handler_) { status = expect_100_continue_handler_(req, res); } switch (status) { - case 100: - case 417: + case StatusCode::Continue_100: + case StatusCode::ExpectationFailed_417: strm.write_format("HTTP/1.1 %d %s\r\n\r\n", status, - detail::status_message(status)); + status_message(status)); break; default: return write_response(strm, close_connection, req, res); } } - // Rounting - bool routed = false; + // Routing + auto routed = false; #ifdef CPPHTTPLIB_NO_EXCEPTIONS routed = routing(req, res, strm); #else @@ -6144,7 +6721,7 @@ Server::process_request(Stream &strm, bool close_connection, exception_handler_(req, res, ep); routed = true; } else { - res.status = 500; + res.status = StatusCode::InternalServerError_500; std::string val; auto s = e.what(); for (size_t i = 0; s[i]; i++) { @@ -6162,17 +6739,29 @@ Server::process_request(Stream &strm, bool close_connection, exception_handler_(req, res, ep); routed = true; } else { - res.status = 500; + res.status = StatusCode::InternalServerError_500; res.set_header("EXCEPTION_WHAT", "UNKNOWN"); } } #endif - if (routed) { - if (res.status == -1) { res.status = req.ranges.empty() ? 200 : 206; } + if (res.status == -1) { + res.status = req.ranges.empty() ? StatusCode::OK_200 + : StatusCode::PartialContent_206; + } + + if (detail::range_error(req, res)) { + res.body.clear(); + res.content_length_ = 0; + res.content_provider_ = nullptr; + res.status = StatusCode::RangeNotSatisfiable_416; + return write_response(strm, close_connection, req, res); + } + return write_response_with_content(strm, close_connection, req, res); } else { - if (res.status == -1) { res.status = 404; } + if (res.status == -1) { res.status = StatusCode::NotFound_404; } + return write_response(strm, close_connection, req, res); } } @@ -6272,7 +6861,7 @@ inline socket_t ClientImpl::create_client_socket(Error &error) const { // Check is custom IP specified for host_ std::string ip; auto it = addr_map_.find(host_); - if (it != addr_map_.end()) ip = it->second; + if (it != addr_map_.end()) { ip = it->second; } return detail::create_client_socket( host_, ip, port_, address_family_, tcp_nodelay_, socket_options_, @@ -6297,7 +6886,7 @@ inline void ClientImpl::shutdown_ssl(Socket & /*socket*/, socket_requests_are_from_thread_ == std::this_thread::get_id()); } -inline void ClientImpl::shutdown_socket(Socket &socket) { +inline void ClientImpl::shutdown_socket(Socket &socket) const { if (socket.sock == INVALID_SOCKET) { return; } detail::shutdown_socket(socket.sock); } @@ -6322,7 +6911,7 @@ inline void ClientImpl::close_socket(Socket &socket) { } inline bool ClientImpl::read_response_line(Stream &strm, const Request &req, - Response &res) { + Response &res) const { std::array buf{}; detail::stream_line_reader line_reader(strm, buf.data(), buf.size()); @@ -6330,9 +6919,9 @@ inline bool ClientImpl::read_response_line(Stream &strm, const Request &req, if (!line_reader.getline()) { return false; } #ifdef CPPHTTPLIB_ALLOW_LF_AS_LINE_TERMINATOR - const static std::regex re("(HTTP/1\\.[01]) (\\d{3})(?: (.*?))?\r\n"); -#else const static std::regex re("(HTTP/1\\.[01]) (\\d{3})(?: (.*?))?\r?\n"); +#else + const static std::regex re("(HTTP/1\\.[01]) (\\d{3})(?: (.*?))?\r\n"); #endif std::cmatch m; @@ -6344,7 +6933,7 @@ inline bool ClientImpl::read_response_line(Stream &strm, const Request &req, res.reason = std::string(m[3]); // Ignore '100 Continue' - while (res.status == 100) { + while (res.status == StatusCode::Continue_100) { if (!line_reader.getline()) { return false; } // CRLF if (!line_reader.getline()) { return false; } // next response line @@ -6492,15 +7081,31 @@ inline bool ClientImpl::handle_request(Stream &strm, Request &req, if (!ret) { return false; } + if (res.get_header_value("Connection") == "close" || + (res.version == "HTTP/1.0" && res.reason != "Connection established")) { + // TODO this requires a not-entirely-obvious chain of calls to be correct + // for this to be safe. + + // This is safe to call because handle_request is only called by send_ + // which locks the request mutex during the process. It would be a bug + // to call it from a different thread since it's a thread-safety issue + // to do these things to the socket if another thread is using the socket. + std::lock_guard guard(socket_mutex_); + shutdown_ssl(socket_, true); + shutdown_socket(socket_); + close_socket(socket_); + } + if (300 < res.status && res.status < 400 && follow_location_) { req = req_save; ret = redirect(req, res, error); } #ifdef CPPHTTPLIB_OPENSSL_SUPPORT - if ((res.status == 401 || res.status == 407) && + if ((res.status == StatusCode::Unauthorized_401 || + res.status == StatusCode::ProxyAuthenticationRequired_407) && req.authorization_count_ < 5) { - auto is_proxy = res.status == 407; + auto is_proxy = res.status == StatusCode::ProxyAuthenticationRequired_407; const auto &username = is_proxy ? proxy_digest_auth_username_ : digest_auth_username_; const auto &password = @@ -6571,7 +7176,7 @@ inline bool ClientImpl::redirect(Request &req, Response &res, Error &error) { } else { if (next_scheme == "https") { #ifdef CPPHTTPLIB_OPENSSL_SUPPORT - SSLClient cli(next_host.c_str(), next_port); + SSLClient cli(next_host, next_port); cli.copy_settings(*this); if (ca_cert_store_) { cli.set_ca_cert_store(ca_cert_store_); } return detail::redirect(cli, req, res, path, location, error); @@ -6579,7 +7184,7 @@ inline bool ClientImpl::redirect(Request &req, Response &res, Error &error) { return false; #endif } else { - ClientImpl cli(next_host.c_str(), next_port); + ClientImpl cli(next_host, next_port); cli.copy_settings(*this); return detail::redirect(cli, req, res, path, location, error); } @@ -6588,7 +7193,7 @@ inline bool ClientImpl::redirect(Request &req, Response &res, Error &error) { inline bool ClientImpl::write_content_with_provider(Stream &strm, const Request &req, - Error &error) { + Error &error) const { auto is_shutting_down = []() { return false; }; if (req.is_chunked_content_provider_) { @@ -6616,32 +7221,32 @@ inline bool ClientImpl::write_request(Stream &strm, Request &req, // Prepare additional headers if (close_connection) { if (!req.has_header("Connection")) { - req.headers.emplace("Connection", "close"); + req.set_header("Connection", "close"); } } if (!req.has_header("Host")) { if (is_ssl()) { if (port_ == 443) { - req.headers.emplace("Host", host_); + req.set_header("Host", host_); } else { - req.headers.emplace("Host", host_and_port_); + req.set_header("Host", host_and_port_); } } else { if (port_ == 80) { - req.headers.emplace("Host", host_); + req.set_header("Host", host_); } else { - req.headers.emplace("Host", host_and_port_); + req.set_header("Host", host_and_port_); } } } - if (!req.has_header("Accept")) { req.headers.emplace("Accept", "*/*"); } + if (!req.has_header("Accept")) { req.set_header("Accept", "*/*"); } #ifndef CPPHTTPLIB_NO_DEFAULT_USER_AGENT if (!req.has_header("User-Agent")) { auto agent = std::string("cpp-httplib/") + CPPHTTPLIB_VERSION; - req.headers.emplace("User-Agent", agent); + req.set_header("User-Agent", agent); } #endif @@ -6650,23 +7255,23 @@ inline bool ClientImpl::write_request(Stream &strm, Request &req, if (!req.is_chunked_content_provider_) { if (!req.has_header("Content-Length")) { auto length = std::to_string(req.content_length_); - req.headers.emplace("Content-Length", length); + req.set_header("Content-Length", length); } } } else { if (req.method == "POST" || req.method == "PUT" || req.method == "PATCH") { - req.headers.emplace("Content-Length", "0"); + req.set_header("Content-Length", "0"); } } } else { if (!req.has_header("Content-Type")) { - req.headers.emplace("Content-Type", "text/plain"); + req.set_header("Content-Type", "text/plain"); } if (!req.has_header("Content-Length")) { auto length = std::to_string(req.body.size()); - req.headers.emplace("Content-Length", length); + req.set_header("Content-Length", length); } } @@ -6706,7 +7311,7 @@ inline bool ClientImpl::write_request(Stream &strm, Request &req, const auto &path = url_encode_ ? detail::encode_url(req.path) : req.path; bstrm.write_format("%s %s HTTP/1.1\r\n", req.method.c_str(), path.c_str()); - detail::write_headers(bstrm, req.headers); + header_writer_(bstrm, req.headers); // Flush buffer auto &data = bstrm.get_buffer(); @@ -6734,12 +7339,10 @@ inline std::unique_ptr ClientImpl::send_with_content_provider( ContentProvider content_provider, ContentProviderWithoutLength content_provider_without_length, const std::string &content_type, Error &error) { - if (!content_type.empty()) { - req.headers.emplace("Content-Type", content_type); - } + if (!content_type.empty()) { req.set_header("Content-Type", content_type); } #ifdef CPPHTTPLIB_ZLIB_SUPPORT - if (compress_) { req.headers.emplace("Content-Encoding", "gzip"); } + if (compress_) { req.set_header("Content-Encoding", "gzip"); } #endif #ifdef CPPHTTPLIB_ZLIB_SUPPORT @@ -6800,10 +7403,9 @@ inline std::unique_ptr ClientImpl::send_with_content_provider( req.content_provider_ = detail::ContentProviderAdapter( std::move(content_provider_without_length)); req.is_chunked_content_provider_ = true; - req.headers.emplace("Transfer-Encoding", "chunked"); + req.set_header("Transfer-Encoding", "chunked"); } else { req.body.assign(body, content_length); - ; } } @@ -6864,7 +7466,8 @@ inline bool ClientImpl::process_request(Stream &strm, Request &req, } // Body - if ((res.status != 204) && req.method != "HEAD" && req.method != "CONNECT") { + if ((res.status != StatusCode::NoContent_204) && req.method != "HEAD" && + req.method != "CONNECT") { auto redirect = 300 < res.status && res.status < 400 && follow_location_; if (req.response_handler && !redirect) { @@ -6909,24 +7512,6 @@ inline bool ClientImpl::process_request(Stream &strm, Request &req, } } - if (res.get_header_value("Connection") == "close" || - (res.version == "HTTP/1.0" && res.reason != "Connection established")) { - // TODO this requires a not-entirely-obvious chain of calls to be correct - // for this to be safe. Maybe a code refactor (such as moving this out to - // the send function and getting rid of the recursiveness of the mutex) - // could make this more obvious. - - // This is safe to call because process_request is only called by - // handle_request which is only called by send, which locks the request - // mutex during the process. It would be a bug to call it from a different - // thread since it's a thread-safety issue to do these things to the socket - // if another thread is using the socket. - std::lock_guard guard(socket_mutex_); - shutdown_ssl(socket_, true); - shutdown_socket(socket_); - close_socket(socket_); - } - // Log if (logger_) { logger_(req, res); } @@ -6935,13 +7520,14 @@ inline bool ClientImpl::process_request(Stream &strm, Request &req, inline ContentProviderWithoutLength ClientImpl::get_multipart_content_provider( const std::string &boundary, const MultipartFormDataItems &items, - const MultipartFormDataProviderItems &provider_items) { - size_t cur_item = 0, cur_start = 0; + const MultipartFormDataProviderItems &provider_items) const { + size_t cur_item = 0; + size_t cur_start = 0; // cur_item and cur_start are copied to within the std::function and maintain // state between successive calls return [&, cur_item, cur_start](size_t offset, DataSink &sink) mutable -> bool { - if (!offset && items.size()) { + if (!offset && !items.empty()) { sink.os << detail::serialize_multipart_formdata(items, boundary, false); return true; } else if (cur_item < provider_items.size()) { @@ -6954,12 +7540,13 @@ inline ContentProviderWithoutLength ClientImpl::get_multipart_content_provider( } DataSink cur_sink; - bool has_data = true; + auto has_data = true; cur_sink.write = sink.write; cur_sink.done = [&]() { has_data = false; }; - if (!provider_items[cur_item].provider(offset - cur_start, cur_sink)) + if (!provider_items[cur_item].provider(offset - cur_start, cur_sink)) { return false; + } if (!has_data) { sink.os << detail::serialize_multipart_formdata_item_end(); @@ -7078,14 +7665,15 @@ inline Result ClientImpl::Get(const std::string &path, const Params ¶ms, if (params.empty()) { return Get(path, headers); } std::string path_with_query = append_query_params(path, params); - return Get(path_with_query.c_str(), headers, progress); + return Get(path_with_query, headers, std::move(progress)); } inline Result ClientImpl::Get(const std::string &path, const Params ¶ms, const Headers &headers, ContentReceiver content_receiver, Progress progress) { - return Get(path, params, headers, nullptr, content_receiver, progress); + return Get(path, params, headers, nullptr, std::move(content_receiver), + std::move(progress)); } inline Result ClientImpl::Get(const std::string &path, const Params ¶ms, @@ -7094,12 +7682,13 @@ inline Result ClientImpl::Get(const std::string &path, const Params ¶ms, ContentReceiver content_receiver, Progress progress) { if (params.empty()) { - return Get(path, headers, response_handler, content_receiver, progress); + return Get(path, headers, std::move(response_handler), + std::move(content_receiver), std::move(progress)); } std::string path_with_query = append_query_params(path, params); - return Get(path_with_query.c_str(), headers, response_handler, - content_receiver, progress); + return Get(path_with_query, headers, std::move(response_handler), + std::move(content_receiver), std::move(progress)); } inline Result ClientImpl::Head(const std::string &path) { @@ -7201,7 +7790,7 @@ inline Result ClientImpl::Post(const std::string &path, const Headers &headers, const auto &content_type = detail::serialize_multipart_formdata_get_content_type(boundary); const auto &body = detail::serialize_multipart_formdata(items, boundary); - return Post(path, headers, body, content_type.c_str()); + return Post(path, headers, body, content_type); } inline Result ClientImpl::Post(const std::string &path, const Headers &headers, @@ -7214,7 +7803,7 @@ inline Result ClientImpl::Post(const std::string &path, const Headers &headers, const auto &content_type = detail::serialize_multipart_formdata_get_content_type(boundary); const auto &body = detail::serialize_multipart_formdata(items, boundary); - return Post(path, headers, body, content_type.c_str()); + return Post(path, headers, body, content_type); } inline Result @@ -7423,9 +8012,7 @@ inline Result ClientImpl::Delete(const std::string &path, req.headers = headers; req.path = path; - if (!content_type.empty()) { - req.headers.emplace("Content-Type", content_type); - } + if (!content_type.empty()) { req.set_header("Content-Type", content_type); } req.body.assign(body, content_length); return send_(std::move(req)); @@ -7458,13 +8045,6 @@ inline Result ClientImpl::Options(const std::string &path, return send_(std::move(req)); } -inline size_t ClientImpl::is_socket_open() const { - std::lock_guard guard(socket_mutex_); - return socket_.is_open(); -} - -inline socket_t ClientImpl::socket() const { return socket_.sock; } - inline void ClientImpl::stop() { std::lock_guard guard(socket_mutex_); @@ -7488,6 +8068,17 @@ inline void ClientImpl::stop() { close_socket(socket_); } +inline std::string ClientImpl::host() const { return host_; } + +inline int ClientImpl::port() const { return port_; } + +inline size_t ClientImpl::is_socket_open() const { + std::lock_guard guard(socket_mutex_); + return socket_.is_open(); +} + +inline socket_t ClientImpl::socket() const { return socket_.sock; } + inline void ClientImpl::set_connection_timeout(time_t sec, time_t usec) { connection_timeout_sec_ = sec; connection_timeout_usec_ = usec; @@ -7536,6 +8127,11 @@ inline void ClientImpl::set_default_headers(Headers headers) { default_headers_ = std::move(headers); } +inline void ClientImpl::set_header_writer( + std::function const &writer) { + header_writer_ = writer; +} + inline void ClientImpl::set_address_family(int family) { address_family_ = family; } @@ -7575,9 +8171,7 @@ inline void ClientImpl::set_proxy_digest_auth(const std::string &username, proxy_digest_auth_username_ = username; proxy_digest_auth_password_ = password; } -#endif -#ifdef CPPHTTPLIB_OPENSSL_SUPPORT inline void ClientImpl::set_ca_cert_path(const std::string &ca_cert_file_path, const std::string &ca_cert_dir_path) { ca_cert_file_path_ = ca_cert_file_path; @@ -7589,9 +8183,34 @@ inline void ClientImpl::set_ca_cert_store(X509_STORE *ca_cert_store) { ca_cert_store_ = ca_cert_store; } } -#endif -#ifdef CPPHTTPLIB_OPENSSL_SUPPORT +inline X509_STORE *ClientImpl::create_ca_cert_store(const char *ca_cert, + std::size_t size) const { + auto mem = BIO_new_mem_buf(ca_cert, static_cast(size)); + if (!mem) { return nullptr; } + + auto inf = PEM_X509_INFO_read_bio(mem, nullptr, nullptr, nullptr); + if (!inf) { + BIO_free_all(mem); + return nullptr; + } + + auto cts = X509_STORE_new(); + if (cts) { + for (auto i = 0; i < static_cast(sk_X509_INFO_num(inf)); i++) { + auto itmp = sk_X509_INFO_value(inf, i); + if (!itmp) { continue; } + + if (itmp->x509) { X509_STORE_add_cert(cts, itmp->x509); } + if (itmp->crl) { X509_STORE_add_crl(cts, itmp->crl); } + } + } + + sk_X509_INFO_pop_free(inf, X509_INFO_free); + BIO_free_all(mem); + return cts; +} + inline void ClientImpl::enable_server_certificate_verification(bool enabled) { server_certificate_verification_ = enabled; } @@ -7655,7 +8274,7 @@ bool ssl_connect_or_accept_nonblocking(socket_t sock, SSL *ssl, U ssl_connect_or_accept, time_t timeout_sec, time_t timeout_usec) { - int res = 0; + auto res = 0; while ((res = ssl_connect_or_accept(ssl)) != 1) { auto err = SSL_get_error(ssl, res); switch (err) { @@ -7718,7 +8337,7 @@ inline SSLSocketStream::SSLSocketStream(socket_t sock, SSL *ssl, SSL_clear_mode(ssl, SSL_MODE_AUTO_RETRY); } -inline SSLSocketStream::~SSLSocketStream() {} +inline SSLSocketStream::~SSLSocketStream() = default; inline bool SSLSocketStream::is_readable() const { return detail::select_read(sock_, read_timeout_sec_, read_timeout_usec_) > 0; @@ -7736,7 +8355,7 @@ inline ssize_t SSLSocketStream::read(char *ptr, size_t size) { auto ret = SSL_read(ssl_, ptr, static_cast(size)); if (ret < 0) { auto err = SSL_get_error(ssl_, ret); - int n = 1000; + auto n = 1000; #ifdef _WIN32 while (--n >= 0 && (err == SSL_ERROR_WANT_READ || (err == SSL_ERROR_SYSCALL && @@ -7769,7 +8388,7 @@ inline ssize_t SSLSocketStream::write(const char *ptr, size_t size) { auto ret = SSL_write(ssl_, ptr, static_cast(handle_size)); if (ret < 0) { auto err = SSL_get_error(ssl_, ret); - int n = 1000; + auto n = 1000; #ifdef _WIN32 while (--n >= 0 && (err == SSL_ERROR_WANT_WRITE || (err == SSL_ERROR_SYSCALL && @@ -7822,10 +8441,10 @@ inline SSLServer::SSLServer(const char *cert_path, const char *private_key_path, SSL_CTX_set_min_proto_version(ctx_, TLS1_1_VERSION); - // add default password callback before opening encrypted private key if (private_key_password != nullptr && (private_key_password[0] != '\0')) { - SSL_CTX_set_default_passwd_cb_userdata(ctx_, - (char *)private_key_password); + SSL_CTX_set_default_passwd_cb_userdata( + ctx_, + reinterpret_cast(const_cast(private_key_password))); } if (SSL_CTX_use_certificate_chain_file(ctx_, cert_path) != 1 || @@ -7927,16 +8546,23 @@ inline SSLClient::SSLClient(const std::string &host, int port) inline SSLClient::SSLClient(const std::string &host, int port, const std::string &client_cert_path, - const std::string &client_key_path) + const std::string &client_key_path, + const std::string &private_key_password) : ClientImpl(host, port, client_cert_path, client_key_path) { ctx_ = SSL_CTX_new(TLS_client_method()); detail::split(&host_[0], &host_[host_.size()], '.', [&](const char *b, const char *e) { - host_components_.emplace_back(std::string(b, e)); + host_components_.emplace_back(b, e); }); if (!client_cert_path.empty() && !client_key_path.empty()) { + if (!private_key_password.empty()) { + SSL_CTX_set_default_passwd_cb_userdata( + ctx_, reinterpret_cast( + const_cast(private_key_password.c_str()))); + } + if (SSL_CTX_use_certificate_file(ctx_, client_cert_path.c_str(), SSL_FILETYPE_PEM) != 1 || SSL_CTX_use_PrivateKey_file(ctx_, client_key_path.c_str(), @@ -7948,16 +8574,23 @@ inline SSLClient::SSLClient(const std::string &host, int port, } inline SSLClient::SSLClient(const std::string &host, int port, - X509 *client_cert, EVP_PKEY *client_key) + X509 *client_cert, EVP_PKEY *client_key, + const std::string &private_key_password) : ClientImpl(host, port) { ctx_ = SSL_CTX_new(TLS_client_method()); detail::split(&host_[0], &host_[host_.size()], '.', [&](const char *b, const char *e) { - host_components_.emplace_back(std::string(b, e)); + host_components_.emplace_back(b, e); }); if (client_cert != nullptr && client_key != nullptr) { + if (!private_key_password.empty()) { + SSL_CTX_set_default_passwd_cb_userdata( + ctx_, reinterpret_cast( + const_cast(private_key_password.c_str()))); + } + if (SSL_CTX_use_certificate(ctx_, client_cert) != 1 || SSL_CTX_use_PrivateKey(ctx_, client_key) != 1) { SSL_CTX_free(ctx_); @@ -7989,6 +8622,11 @@ inline void SSLClient::set_ca_cert_store(X509_STORE *ca_cert_store) { } } +inline void SSLClient::load_ca_cert_store(const char *ca_cert, + std::size_t size) { + set_ca_cert_store(ClientImpl::create_ca_cert_store(ca_cert, size)); +} + inline long SSLClient::get_openssl_verify_result() const { return verify_result_; } @@ -8003,14 +8641,14 @@ inline bool SSLClient::create_and_connect_socket(Socket &socket, Error &error) { inline bool SSLClient::connect_with_proxy(Socket &socket, Response &res, bool &success, Error &error) { success = true; - Response res2; + Response proxy_res; if (!detail::process_client_socket( socket.sock, read_timeout_sec_, read_timeout_usec_, write_timeout_sec_, write_timeout_usec_, [&](Stream &strm) { Request req2; req2.method = "CONNECT"; req2.path = host_and_port_; - return process_request(strm, req2, res2, false, error); + return process_request(strm, req2, proxy_res, false, error); })) { // Thread-safe to close everything because we are assuming there are no // requests in flight @@ -8021,12 +8659,12 @@ inline bool SSLClient::connect_with_proxy(Socket &socket, Response &res, return false; } - if (res2.status == 407) { + if (proxy_res.status == StatusCode::ProxyAuthenticationRequired_407) { if (!proxy_digest_auth_username_.empty() && !proxy_digest_auth_password_.empty()) { std::map auth; - if (detail::parse_www_authenticate(res2, auth, true)) { - Response res3; + if (detail::parse_www_authenticate(proxy_res, auth, true)) { + proxy_res = Response(); if (!detail::process_client_socket( socket.sock, read_timeout_sec_, read_timeout_usec_, write_timeout_sec_, write_timeout_usec_, [&](Stream &strm) { @@ -8037,7 +8675,7 @@ inline bool SSLClient::connect_with_proxy(Socket &socket, Response &res, req3, auth, 1, detail::random_string(10), proxy_digest_auth_username_, proxy_digest_auth_password_, true)); - return process_request(strm, req3, res3, false, error); + return process_request(strm, req3, proxy_res, false, error); })) { // Thread-safe to close everything because we are assuming there are // no requests in flight @@ -8048,17 +8686,28 @@ inline bool SSLClient::connect_with_proxy(Socket &socket, Response &res, return false; } } - } else { - res = res2; - return false; } } + // If status code is not 200, proxy request is failed. + // Set error to ProxyConnection and return proxy response + // as the response of the request + if (proxy_res.status != StatusCode::OK_200) { + error = Error::ProxyConnection; + res = std::move(proxy_res); + // Thread-safe to close everything because we are assuming there are + // no requests in flight + shutdown_ssl(socket, true); + shutdown_socket(socket); + close_socket(socket); + return false; + } + return true; } inline bool SSLClient::load_certs() { - bool ret = true; + auto ret = true; std::call_once(initialize_cert_, [&]() { std::lock_guard guard(ctx_mutex_); @@ -8134,7 +8783,11 @@ inline bool SSLClient::initialize_ssl(Socket &socket, Error &error) { return true; }, [&](SSL *ssl2) { - SSL_set_tlsext_host_name(ssl2, host_.c_str()); + // NOTE: Direct call instead of using the OpenSSL macro to suppress + // -Wold-style-cast warning + // SSL_set_tlsext_host_name(ssl2, host_.c_str()); + SSL_ctrl(ssl2, SSL_CTRL_SET_TLSEXT_HOSTNAME, TLSEXT_NAMETYPE_host_name, + static_cast(const_cast(host_.c_str()))); return true; }); @@ -8208,8 +8861,8 @@ SSLClient::verify_host_with_subject_alt_name(X509 *server_cert) const { auto type = GEN_DNS; - struct in6_addr addr6; - struct in_addr addr; + struct in6_addr addr6 {}; + struct in_addr addr {}; size_t addr_len = 0; #ifndef __MINGW32__ @@ -8234,8 +8887,9 @@ SSLClient::verify_host_with_subject_alt_name(X509 *server_cert) const { for (decltype(count) i = 0; i < count && !dsn_matched; i++) { auto val = sk_GENERAL_NAME_value(alt_names, i); if (val->type == type) { - auto name = (const char *)ASN1_STRING_get0_data(val->d.ia5); - auto name_len = (size_t)ASN1_STRING_length(val->d.ia5); + auto name = + reinterpret_cast(ASN1_STRING_get0_data(val->d.ia5)); + auto name_len = static_cast(ASN1_STRING_length(val->d.ia5)); switch (type) { case GEN_DNS: dsn_matched = check_host_name(name, name_len); break; @@ -8253,7 +8907,8 @@ SSLClient::verify_host_with_subject_alt_name(X509 *server_cert) const { if (dsn_matched || ip_matched) { ret = true; } } - GENERAL_NAMES_free((STACK_OF(GENERAL_NAME) *)alt_names); + GENERAL_NAMES_free(const_cast( + reinterpret_cast(alt_names))); return ret; } @@ -8282,7 +8937,7 @@ inline bool SSLClient::check_host_name(const char *pattern, std::vector pattern_components; detail::split(&pattern[0], &pattern[pattern_len], '.', [&](const char *b, const char *e) { - pattern_components.emplace_back(std::string(b, e)); + pattern_components.emplace_back(b, e); }); if (host_components_.size() != pattern_components.size()) { return false; } @@ -8361,7 +9016,7 @@ inline Client::Client(const std::string &host, int port, : cli_(detail::make_unique(host, port, client_cert_path, client_key_path)) {} -inline Client::~Client() {} +inline Client::~Client() = default; inline bool Client::is_valid() const { return cli_ != nullptr && cli_->is_valid(); @@ -8421,19 +9076,20 @@ inline Result Client::Get(const std::string &path, const Headers &headers, } inline Result Client::Get(const std::string &path, const Params ¶ms, const Headers &headers, Progress progress) { - return cli_->Get(path, params, headers, progress); + return cli_->Get(path, params, headers, std::move(progress)); } inline Result Client::Get(const std::string &path, const Params ¶ms, const Headers &headers, ContentReceiver content_receiver, Progress progress) { - return cli_->Get(path, params, headers, content_receiver, progress); + return cli_->Get(path, params, headers, std::move(content_receiver), + std::move(progress)); } inline Result Client::Get(const std::string &path, const Params ¶ms, const Headers &headers, ResponseHandler response_handler, ContentReceiver content_receiver, Progress progress) { - return cli_->Get(path, params, headers, response_handler, content_receiver, - progress); + return cli_->Get(path, params, headers, std::move(response_handler), + std::move(content_receiver), std::move(progress)); } inline Result Client::Head(const std::string &path) { return cli_->Head(path); } @@ -8665,12 +9321,16 @@ inline bool Client::send(Request &req, Response &res, Error &error) { inline Result Client::send(const Request &req) { return cli_->send(req); } +inline void Client::stop() { cli_->stop(); } + +inline std::string Client::host() const { return cli_->host(); } + +inline int Client::port() const { return cli_->port(); } + inline size_t Client::is_socket_open() const { return cli_->is_socket_open(); } inline socket_t Client::socket() const { return cli_->socket(); } -inline void Client::stop() { cli_->stop(); } - inline void Client::set_hostname_addr_map(std::map addr_map) { cli_->set_hostname_addr_map(std::move(addr_map)); @@ -8680,6 +9340,11 @@ inline void Client::set_default_headers(Headers headers) { cli_->set_default_headers(std::move(headers)); } +inline void Client::set_header_writer( + std::function const &writer) { + cli_->set_header_writer(writer); +} + inline void Client::set_address_family(int family) { cli_->set_address_family(family); } @@ -8754,7 +9419,9 @@ inline void Client::enable_server_certificate_verification(bool enabled) { } #endif -inline void Client::set_logger(Logger logger) { cli_->set_logger(logger); } +inline void Client::set_logger(Logger logger) { + cli_->set_logger(std::move(logger)); +} #ifdef CPPHTTPLIB_OPENSSL_SUPPORT inline void Client::set_ca_cert_path(const std::string &ca_cert_file_path, @@ -8770,6 +9437,10 @@ inline void Client::set_ca_cert_store(X509_STORE *ca_cert_store) { } } +inline void Client::load_ca_cert_store(const char *ca_cert, std::size_t size) { + set_ca_cert_store(cli_->create_ca_cert_store(ca_cert, size)); +} + inline long Client::get_openssl_verify_result() const { if (is_ssl_) { return static_cast(*cli_).get_openssl_verify_result(); diff --git a/examples/server/index.html.hpp b/examples/server/index.html.hpp index 20551520e29cd..122d3ff999f04 100644 --- a/examples/server/index.html.hpp +++ b/examples/server/index.html.hpp @@ -307,2485 +307,2577 @@ unsigned char index_html[] = { 0x6c, 0x2c, 0x20, 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0x20, 0x79, 0x69, 0x65, 0x6c, 0x64, 0x20, 0x5b, 0x6c, + 0x61, 0x73, 0x74, 0x4b, 0x65, 0x79, 0x2c, 0x20, 0x67, 0x72, 0x6f, 0x75, + 0x70, 0x5d, 0x3b, 0x0a, 0x20, 0x20, 0x7d, 0x0a, 0x7d, 0x0a }; -unsigned int json_schema_to_grammar_mjs_len = 3695; +unsigned int json_schema_to_grammar_mjs_len = 19690; diff --git a/examples/server/public/completion.js b/examples/server/public/completion.js index 835ce6e68422a..987b9a3b891d0 100644 --- a/examples/server/public/completion.js +++ b/examples/server/public/completion.js @@ -21,6 +21,7 @@ let generation_settings = null; // export async function* llama(prompt, params = {}, config = {}) { let controller = config.controller; + const api_url = config.api_url || ""; if (!controller) { controller = new AbortController(); @@ -28,7 +29,7 @@ export async function* llama(prompt, params = {}, config = {}) { const completionParams = { ...paramDefaults, ...params, prompt }; - const response = await fetch("/completion", { + const response = await fetch(`${api_url}/completion`, { method: 'POST', body: JSON.stringify(completionParams), headers: { @@ -193,9 +194,10 @@ export const llamaComplete = async (params, controller, callback) => { } // Get the model info from the server. This is useful for getting the context window and so on. -export const llamaModelInfo = async () => { +export const llamaModelInfo = async (config = {}) => { if (!generation_settings) { - const props = await fetch("/props").then(r => r.json()); + const api_url = config.api_url || ""; + const props = await fetch(`${api_url}/props`).then(r => r.json()); generation_settings = props.default_generation_settings; } return generation_settings; diff --git a/examples/server/public/index.html b/examples/server/public/index.html index 84038ddcefb43..9fe61eb1b1b13 100644 --- a/examples/server/public/index.html +++ b/examples/server/public/index.html @@ -199,10 +199,10 @@ -