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Don't update base conda, x_m_e_a call toggle, drop conda cache
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‎Dockerfile‎

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@@ -30,9 +30,7 @@ WORKDIR /api
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# We need python 3.9 or 3.10 for xformers
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# Yes, we install pytorch twice... will switch base image in future
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RUN mkdir -p /opt/conda/pkgs
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COPY /conda-pkgs/* /opt/conda/pkgs/
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RUN conda update -n base -c defaults conda
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# RUN conda update -n base -c defaults conda
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RUN conda create -n xformers python=3.10
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SHELL ["/opt/conda/bin/conda", "run", "--no-capture-output", "-n", "xformers", "/bin/bash", "-c"]
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RUN python --version

‎app.py‎

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@@ -273,12 +273,27 @@ def inference(all_inputs: dict) -> dict:
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mask = mask.repeat(8, axis=0).repeat(8, axis=1)
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model_inputs["mask_image"] = PIL.Image.fromarray(mask)
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x_m_e_a = call_inputs.get("xformers_memory_efficient_attention", None)
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if x_m_e_a == None:
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pipeline.enable_xformers_memory_efficient_attention() # default on
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elif x_m_e_a == True:
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pipeline.enable_xformers_memory_efficient_attention()
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elif x_m_e_a == False:
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pipeline.disable_xformers_memory_efficient_attention()
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else:
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return {
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"$error": {
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"code": "INVALID_XFORMERS_MEMORY_EFFICIENT_ATTENTION_VALUE",
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"message": f'Model "{model_id}" not available on this container which hosts "{MODEL_ID}"',
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"requested": x_m_e_a,
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"available": [True, False],
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}
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}
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# Run the model
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# with autocast("cuda"):
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# image = pipeline(**model_inputs).images[0]
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pipeline.enable_xformers_memory_efficient_attention()
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with torch.inference_mode():
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# autocast im2img and inpaint which are broken in 0.4.0, 0.4.1
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# still broken in 0.5.1

‎conda-pkgs/.gitignore‎

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This file was deleted.

‎conda-pkgs/README.md‎

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‎test.py‎

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@@ -119,6 +119,7 @@ def runTest(name, banana):
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"MODEL_ID": "runwayml/stable-diffusion-v1-5",
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"PIPELINE": "StableDiffusionPipeline",
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"SCHEDULER": "LMS",
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# "xformers_memory_efficient_attention": False,
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},
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},
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)

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