Add sampling to vlm pipeline by Sampler

.github/workflows/causal_lm_cpp.yml

@@ -709,7 +709,8 @@ jobs:
           python -m pip install -U "optimum<1.23" --no-dependencies
           source ./ov/setupvars.sh
           optimum-cli export openvino -m openbmb/MiniCPM-V-2_6 MiniCPM-V-2_6 --trust-remote-code
-          wget https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11 --output-document cat.jpg
+          mkdir cat_img
+          wget https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11 --output-document cat_img/cat.jpg
       - name: Generate reference
         shell: python
         run: |
@@ -739,6 +740,11 @@ jobs:
           source ./ov/setupvars.sh
           && timeout 120s ./build/samples/cpp/visual_language_chat/visual_language_chat ./MiniCPM-V-2_6/ lines.png
           <<< $'What is unusual on this image?' | tee cpp.txt
+      - name: Run visual_language_chat C++ sample with dir - MiniCPM-V-2_6
+        run: >
+          source ./ov/setupvars.sh
+          && timeout 120s ./build/samples/cpp/visual_language_chat/visual_language_chat ./MiniCPM-V-2_6/ cat_img
+          <<< $'What is unusual on this image?' | tee cpp.txt
       - run: diff cpp.txt ref.txt
       - name: Download and convert LLaVa 1.5 model and an image
         run: |
@@ -767,7 +773,7 @@ jobs:
           source ./ov/setupvars.sh
           export PYTHONPATH=./build/:$PYTHONPATH
           printf 'What is on the image?\nWhat is special on the image?\n' > ./input.txt
-          timeout 120s python ./samples/python/visual_language_chat/visual_language_chat.py ./MiniCPM-V-2_6/ cat.jpg < input.txt > ./pred.txt
+          timeout 120s python ./samples/python/visual_language_chat/visual_language_chat.py ./miniCPM-V-2_6/ cat_img/cat.jpg < input.txt > ./pred.txt
 
   cpp-continuous-batching-ubuntu:
     runs-on: ubuntu-20.04-8-cores

samples/cpp/visual_language_chat/load_image.cpp

@@ -6,6 +6,28 @@
 #include "stb_image.h"
 #include "load_image.hpp"
 
+namespace fs = std::filesystem;
+
+std::vector<ov::Tensor> utils::load_images(const std::filesystem::path& input_path) {
+    std::vector<ov::Tensor> images;
+    if (!input_path.empty() && fs::exists(input_path)) {
+        if (fs::is_directory(input_path)) {
+            for (const auto& dir_entry : fs::directory_iterator(input_path)) {
+                ov::Tensor image = utils::load_image(dir_entry.path());
+                images.push_back(std::move(image));
+            }
+        } else if (fs::is_regular_file(input_path)) {
+            ov::Tensor image = utils::load_image(input_path);
+            images.push_back(std::move(image));
+        }
+    }
+
+    if (images.empty())
+        throw std::runtime_error(std::string{"No images were found in path "} + input_path.string());
+
+    return images;
+}
+
 ov::Tensor utils::load_image(const std::filesystem::path& image_path) {
     int x = 0, y = 0, channels_in_file = 0;
     constexpr int desired_channels = 3;

samples/cpp/visual_language_chat/load_image.hpp

@@ -9,4 +9,5 @@
 
 namespace utils {
 ov::Tensor load_image(const std::filesystem::path& image_path);
+std::vector<ov::Tensor> load_images(const std::filesystem::path& image_path);
 }

samples/cpp/visual_language_chat/visual_language_chat.cpp

@@ -3,6 +3,7 @@
 
 #include "load_image.hpp"
 #include <openvino/genai/visual_language/pipeline.hpp>
+#include <filesystem>
 #include <openvino/runtime/intel_gpu/properties.hpp>
 
 bool print_subword(std::string&& subword) {
@@ -11,9 +12,14 @@ bool print_subword(std::string&& subword) {
 
 int main(int argc, char* argv[]) try {
     if (3 != argc) {
-        throw std::runtime_error(std::string{"Usage "} + argv[0] + " <MODEL_DIR> <IMAGE_FILE>");
+        throw std::runtime_error(std::string{"Usage "} + argv[0] + " <MODEL_DIR> <IMAGE_FILE OR DIR_WITH_IMAGES>");
     }
-    ov::Tensor image = utils::load_image(argv[2]);
+
+    std::vector<ov::Tensor> images = utils::load_images(argv[2]);
+
+    ov::genai::GenerationConfig generation_config;
+    generation_config.max_new_tokens = 30;
+
     std::string device = "CPU";  // GPU can be used as well
     ov::AnyMap enable_compile_cache;
     if ("GPU" == device) {
@@ -26,16 +32,18 @@ int main(int argc, char* argv[]) try {
 
     pipe.start_chat();
     std::cout << "question:\n";
+
     std::getline(std::cin, prompt);
-    pipe.generate(
-        prompt,
-        ov::genai::image(image),
-        ov::genai::streamer(print_subword)
-    );
+    pipe.generate(prompt,
+                  ov::genai::images(images),
+                  ov::genai::generation_config(generation_config),
+                  ov::genai::streamer(print_subword));
     std::cout << "\n----------\n"
         "question:\n";
     while (std::getline(std::cin, prompt)) {
-        pipe.generate(prompt, ov::genai::streamer(print_subword));
+        pipe.generate(prompt,
+                      ov::genai::generation_config(generation_config),
+                      ov::genai::streamer(print_subword));
         std::cout << "\n----------\n"
             "question:\n";
     }

src/cpp/src/sampler.cpp

@@ -230,6 +230,22 @@ Sampler::GroupBeamSearcher::GroupBeamSearcher(SequenceGroup::Ptr sequence_group,
     }
 }
 
+
+std::vector<int32_t> Sampler::GroupBeamSearcher::get_beam_idxs() {
+    std::vector<int32_t> next_beams;
+
+    for (Group& group : m_groups) {
+        if (!group.done) {
+            for (Beam& beam : group.ongoing) {
+                next_beams.push_back(beam.m_global_beam_idx);
+            }
+        }
+    }
+
+    return next_beams;
+}
+
+
 void Sampler::GroupBeamSearcher::select_next_tokens(const ov::Tensor& logits, SamplerOutput& sampler_output) {
     assert(m_parameters.num_beams % m_parameters.num_beam_groups == 0 &&
         "number of beams should be divisible by number of groups");
@@ -581,6 +597,15 @@ void register_new_token(const Token& sampled_token_id,
     }
 };
 
+std::vector<int32_t> Sampler::get_beam_idxs(SequenceGroup::CPtr sequence_group) {
+    size_t request_id = sequence_group->get_request_id();
+    auto beam_searcher = m_beam_search_info.find(request_id);
+    if (m_beam_search_info.find(request_id) == m_beam_search_info.end()) {
+        return std::vector<int32_t>(sequence_group->num_running_seqs(), 0);
+    }
+    return beam_searcher->second.get_beam_idxs();
+}
+
 std::list<uint64_t>
 create_n_forked_sequences(SequenceGroup::Ptr sequence_group,
                           LogitProcessor& logit_processor,

src/cpp/src/sampler.hpp

@@ -65,6 +65,7 @@ class Sampler {
     SamplerOutput sample(std::vector<SequenceGroup::Ptr> & sequence_groups, ov::Tensor logits, bool is_validation_mode_enabled = false);
     void set_seed(size_t seed) { rng_engine.seed(seed); }
     void clear_beam_search_info(uint64_t request_id);
+    std::vector<int32_t> get_beam_idxs(SequenceGroup::CPtr sequence_group);
 };
 
 class Sampler::GroupBeamSearcher {
@@ -109,5 +110,6 @@ class Sampler::GroupBeamSearcher {
 
     void select_next_tokens(const ov::Tensor& logits, SamplerOutput& sampler_output);
     void finalize(SamplerOutput& sampler_output);
+    std::vector<int32_t> get_beam_idxs();
 };
 }