mirror of https://github.com/open-mmlab/mmyolo.git
35 lines
1.2 KiB
Docker
35 lines
1.2 KiB
Docker
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ARG PYTORCH="1.9.0"
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ARG CUDA="11.1"
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ARG CUDNN="8"
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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6+PTX"
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ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
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ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
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RUN rm /etc/apt/sources.list.d/cuda.list \
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&& rm /etc/apt/sources.list.d/nvidia-ml.list \
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&& apt-key del 7fa2af80 \
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&& apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub \
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&& apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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# (Optional)
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# RUN sed -i 's/http:\/\/archive.ubuntu.com\/ubuntu\//http:\/\/mirrors.aliyun.com\/ubuntu\//g' /etc/apt/sources.list
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RUN apt-get update \
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&& apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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# Install MMEngine , MMCV and MMDet
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RUN pip install openmim
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RUN mim install mmengine "mmcv>=2.0.0rc1" "mmdet>=3.0.0rc0"
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# Install MMYOLO
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RUN conda clean --all
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RUN git clone https://github.com/open-mmlab/mmyolo.git /mmyolo
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WORKDIR /mmyolo
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ENV FORCE_CUDA="1"
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RUN mim install -e .
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