From 29d8c70106091cfb9a5c418fd4e33c6f207d6ebb Mon Sep 17 00:00:00 2001 From: Charles Frye Date: Sun, 17 Nov 2024 22:18:54 -0800 Subject: [PATCH 1/2] removes old examples, updates cli, removes unused files --- .../stable_diffusion/demo_images/dog.png | Bin 660518 -> 0 bytes 06_gpu_and_ml/stable_diffusion/foo.json | 1 - .../stable_diffusion/huggingface_token.png | Bin 173342 -> 0 bytes .../stable_diffusion/stable_diffusion_cli.py | 81 ++++++- .../stable_diffusion_latencies.png | Bin 320562 -> 0 bytes .../stable_diffusion_montage.png | Bin 3003990 -> 0 bytes .../stable_diffusion_turbo_input.png | Bin 660518 -> 0 bytes .../stable_diffusion_turbo_output.png | Bin 347714 -> 0 bytes .../stable_diffusion/stable_diffusion_xl.py | 220 ------------------ .../stable_diffusion_xl_lightning.py | 165 ------------- .../stable_diffusion_xl_turbo.py | 132 ----------- 11 files changed, 74 insertions(+), 525 deletions(-) delete mode 100644 06_gpu_and_ml/stable_diffusion/demo_images/dog.png delete mode 100644 06_gpu_and_ml/stable_diffusion/foo.json delete mode 100644 06_gpu_and_ml/stable_diffusion/huggingface_token.png delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_latencies.png delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_montage.png delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_turbo_input.png delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_turbo_output.png delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_xl.py delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_xl_lightning.py delete mode 100644 06_gpu_and_ml/stable_diffusion/stable_diffusion_xl_turbo.py diff --git a/06_gpu_and_ml/stable_diffusion/demo_images/dog.png b/06_gpu_and_ml/stable_diffusion/demo_images/dog.png deleted file mode 100644 index 022c2d13a1b7d79a979ccd6a51b80c1181d06478..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 660518 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b/06_gpu_and_ml/stable_diffusion/stable_diffusion_cli.py @@ -2,6 +2,7 @@ # output-directory: "/tmp/stable-diffusion" # args: ["--prompt", "A 1600s oil painting of the New York City skyline"] # tags: ["use-case-image-video-3d"] +# deploy: true # --- # # Run Stable Diffusion 3.5 Large Turbo from the command line @@ -47,19 +48,20 @@ .pip_install( "accelerate==0.33.0", "diffusers==0.31.0", + "fastapi[standard]==0.115.4", "huggingface-hub[hf_transfer]==0.25.2", "sentencepiece==0.2.0", "torch==2.5.1", "torchvision==0.20.1", "transformers~=4.44.0", ) - .entrypoint([]) # deactivate default entrypoint to reduce log verbosity .env({"HF_HUB_ENABLE_HF_TRANSFER": "1"}) # faster downloads ) with image.imports(): import diffusers import torch + from fastapi import Response # ## Implementing SD3.5 Large Turbo inference on Modal @@ -67,9 +69,14 @@ # that ensures models are downloaded when we `build` our container image (just like our dependencies) # and that models are loaded and then moved to the GPU when a new container starts. -# The `run_inference` function just wraps a `diffusers` pipeline. +# The `run` function just wraps a `diffusers` pipeline. # It sends the output image back to the client as bytes. +# We also include a `web` wrapper that makes it possible +# to trigger inference via an API call. +# See the `/docs` route of the URL ending in `inference-web.modal.run` +# that appears when you deploy the app for details. + model_id = "adamo1139/stable-diffusion-3.5-large-turbo-ungated" model_revision_id = "9ad870ac0b0e5e48ced156bb02f85d324b7275d2" @@ -79,7 +86,7 @@ gpu="H100", timeout=10 * MINUTES, ) -class StableDiffusion: +class Inference: @modal.build() @modal.enter() def initialize(self): @@ -94,7 +101,7 @@ def move_to_gpu(self): self.pipe.to("cuda") @modal.method() - def run_inference( + def run( self, prompt: str, batch_size: int = 4, seed: int = None ) -> list[bytes]: seed = seed if seed is not None else random.randint(0, 2**32 - 1) @@ -116,8 +123,17 @@ def run_inference( torch.cuda.empty_cache() # reduce fragmentation return image_output + @modal.web_endpoint(docs=True) + def web(self, prompt: str, seed: int = None): + return Response( + content=self.run.local( # run in the same container + prompt, batch_size=1, seed=seed + )[0], + media_type="image/png", + ) + -# ## Generating images from the command line +# ## Generating Stable Diffusion images from the command line # This is the command we'll use to generate images. It takes a text `prompt`, # a `batch_size` that determines the number of images to generate per prompt, @@ -144,11 +160,11 @@ def entrypoint( output_dir = Path("/tmp/stable-diffusion") output_dir.mkdir(exist_ok=True, parents=True) - sd = StableDiffusion() + inference_service = Inference() for sample_idx in range(samples): start = time.time() - images = sd.run_inference.remote(prompt, batch_size, seed) + images = inference_service.run.remote(prompt, batch_size, seed) duration = time.time() - start print(f"Run {sample_idx+1} took {duration:.3f}s") if sample_idx: @@ -169,5 +185,56 @@ def entrypoint( output_path.write_bytes(image_bytes) +# ## Generating Stable Diffusion images in a web UI + +# Here we ship a simple web application that exposes a front-end (written in Alpine.js) for +# our image generation backend. + +# The `Inference` class will serve multiple users from its own shared pool of warm GPU containers automatically. + +# We can deploy this with `modal deploy stable_diffusion_cli.py`. + +frontend_path = Path(__file__).parent / "frontend" + +web_image = modal.Image.debian_slim(python_version="3.12").pip_install( + "jinja2", "fastapi[standard]==0.115.4" +) + + +@app.function( + image=web_image, + mounts=[modal.Mount.from_local_dir(frontend_path, remote_path="/assets")], + allow_concurrent_inputs=1000, +) +@modal.asgi_app() +def ui(): + import fastapi.staticfiles + from fastapi import FastAPI, Request + from fastapi.templating import Jinja2Templates + + web_app = FastAPI() + templates = Jinja2Templates(directory="/assets") + + @web_app.get("/") + async def read_root(request: Request): + return templates.TemplateResponse( + "index.html", + { + "request": request, + "inference_url": Inference.web.web_url, + "model_name": "Stable Diffusion 3.5 Large Turbo", + "default_prompt": "A cinematic shot of a baby raccoon wearing an intricate italian priest robe.", + }, + ) + + web_app.mount( + "/static", + fastapi.staticfiles.StaticFiles(directory="/assets"), + name="static", + ) + + return web_app + + def slugify(s: str) -> str: return "".join(c if c.isalnum() else "-" for c in s).strip("-") diff --git a/06_gpu_and_ml/stable_diffusion/stable_diffusion_latencies.png b/06_gpu_and_ml/stable_diffusion/stable_diffusion_latencies.png deleted file mode 100644 index 1a70edc1f76e6562a590fb5d19b123fba0167f05..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 320562 zcmeFa_g|J*);&y;F-~GMu>c~VM(H91R1~CWf+AgtC`E`=QA+440*S^#S3p2%hAN66 zUFsc`UIi48B9SWI6ane&yY{WgJipBQ54_{&nHdXkU)MSN?7j9{YoEvasD{$&uQz?o z#>Tc<`G}%68ynA7Hnuh2{rgM&&E=+}|Hl7FJ0CjXtYdHK>~_l0f=&ID^Dj2`&NkMj zTU{+2oviKcc8N)eNs4Yg?d<%ElZ?2y?LS{2X76YvF7$SzDSpUTzZ}tbVq-HpO#k_8 zLD**;@qQ&v2vdoFUQ(=A-LZ&6`n`twHL6&u)B=pI$vu4PM)@&-hbmBVutyta94hmn|diU4e2jj&axqEue1ly~9XX$F?>iVWQ?d;NT z1Jd=(NV#23ZL*_#*+WaqU{_E2GFWdb0 zrTPC&*lehj9*A6j{``6Fi`mvq0xc51)#_eb!z(q%HCgT3CH2c+e}?3m1#XseKi`^Af9cEBn|ftLZhT&T^G3dM 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