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smaller base image, conda-pkg cache, move triton to requirements
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‎Dockerfile‎

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# xformers available precompiled for:
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# Python 3.9 or 3.10, CUDA 11.3 or 11.6, and PyTorch 1.12.1
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# https://github.com/facebookresearch/xformers/#getting-started
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FROM pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime as base
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#FROM pytorch/pytorch:1.12.1-cuda11.3-cudnn8-runtime as base
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#FROM nvcr.io/nvidia/pytorch:22.08-py3 as base
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FROM continuumio/miniconda3:4.12.0 as base
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ENV DEBIAN_FRONTEND=noninteractive
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RUN mkdir -p /root/.cache/pip
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COPY root-cache/pip /root/.cache/pip
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#RUN apt-get install gnupg2
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#RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
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RUN apt-get update && apt-get install -yqq git
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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 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
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RUN conda install -c pytorch -c conda-forge cudatoolkit=11.6 pytorch=1.12.1
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RUN conda install xformers -c xformers/label/dev
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RUN pip install triton==2.0.0.dev20221105
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# Install python packages
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RUN mkdir -p /root/.cache/pip
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COPY root-cache/pip /root/.cache/pip
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RUN pip3 install --upgrade pip
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ADD requirements.txt requirements.txt
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RUN pip3 install -r requirements.txt

‎conda-pkgs/.gitignore‎

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*
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*/
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!.gitignore
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!README.md

‎conda-pkgs/README.md‎

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See ../root-cache/README.md

‎requirements.txt‎

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numpy==1.23.4
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scikit-image==0.19.3
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accelerate==0.13.2
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triton==2.0.0.dev20221105

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