93 lines
4.1 KiB
Plaintext
93 lines
4.1 KiB
Plaintext
ARG CUDA_VERSION="11.8.0"
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ARG CUDNN_VERSION="8"
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ARG UBUNTU_VERSION="22.04"
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ARG MAX_JOBS=4
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ARG TARGETARCH
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FROM nvidia/cuda:$CUDA_VERSION-cudnn$CUDNN_VERSION-devel-ubuntu$UBUNTU_VERSION AS base-builder
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ENV PATH="/root/miniconda3/bin:${PATH}"
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ARG TARGETARCH
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ARG PYTHON_VERSION="3.11"
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ARG PYTORCH_VERSION="2.1.2"
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ARG CUDA="128"
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ARG TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 9.0+PTX"
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ENV PYTHON_VERSION=$PYTHON_VERSION
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ENV TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends \
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wget git build-essential ninja-build git-lfs libaio-dev pkg-config \
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ibverbs-providers ibverbs-utils infiniband-diags \
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librdmacm-dev librdmacm1 rdmacm-utils slurm-wlm \
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&& rm -rf /var/cache/apt/archives \
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&& rm -rf /var/lib/apt/lists/* \
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&& if [ "$TARGETARCH" = "amd64" ]; then \
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MINICONDA_ARCH="x86_64"; \
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elif [ "$TARGETARCH" = "arm64" ]; then \
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MINICONDA_ARCH="aarch64"; \
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else \
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echo "Unsupported architecture: $TARGETARCH"; exit 1; \
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fi \
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&& wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-${MINICONDA_ARCH}.sh \
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&& mkdir /root/.conda \
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&& bash Miniconda3-latest-Linux-${MINICONDA_ARCH}.sh -b \
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&& rm -f Miniconda3-latest-Linux-${MINICONDA_ARCH}.sh \
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&& conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main \
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&& conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r \
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&& conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}"
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ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}"
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WORKDIR /workspace
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RUN python3 -m pip install --upgrade pip && pip3 install -U packaging==26.0 setuptools==75.8.0 wheel psutil && \
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python3 -m pip install --no-cache-dir -U torch==${PYTORCH_VERSION}+cu${CUDA} torchvision --extra-index-url https://download.pytorch.org/whl/cu$CUDA && \
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python3 -m pip cache purge
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RUN if [ "$CUDA" != "130" ] ; then \
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CAUSAL_CONV1D_FORCE_CXX11_ABI=TRUE CAUSAL_CONV1D_FORCE_BUILD=TRUE python3 -m pip install --no-cache-dir "causal_conv1d @ git+https://github.com/Dao-AILab/causal-conv1d.git@v1.5.4"; \
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python3 -m pip install --no-cache-dir "mamba_ssm @ git+https://github.com/state-spaces/mamba.git@main"; \
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python3 -m pip cache purge; \
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fi
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RUN git lfs install --skip-repo && \
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pip3 install awscli && \
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# The base image ships with `pydantic==1.8.2` which is not working
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pip3 install -U --no-cache-dir pydantic==1.10.10 && \
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pip3 cache purge
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RUN case "$PYTORCH_VERSION" in \
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2.9.[0-9]*) \
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if [ "$CUDA" = "128" ]; then \
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if [ "$TARGETARCH" = "amd64" ]; then \
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WHL_FILE="flash_attn-2.8.3+cu128torch2.9-cp311-cp311-linux_x86_64.whl"; \
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WHL_VERSION="v0.5.4"; \
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elif [ "$TARGETARCH" = "arm64" ]; then \
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WHL_FILE="flash_attn-2.8.3+cu128torch2.9-cp311-cp311-linux_aarch64.whl"; \
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WHL_VERSION="v0.6.4"; \
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else \
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echo "Unsupported architecture: $TARGETARCH"; exit 1; \
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fi; \
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wget -nv https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/${WHL_VERSION}/${WHL_FILE}; \
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pip3 install --no-cache-dir ${WHL_FILE}; \
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rm ${WHL_FILE}; \
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elif [ "$CUDA" = "130" ]; then \
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if [ "$TARGETARCH" = "amd64" ]; then \
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WHL_FILE="flash_attn-2.8.3+cu130torch2.9-cp311-cp311-linux_x86_64.whl"; \
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WHL_VERSION="v0.5.4"; \
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elif [ "$TARGETARCH" = "arm64" ]; then \
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WHL_FILE="flash_attn-2.8.3+cu130torch2.9-cp311-cp311-linux_aarch64.whl"; \
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WHL_VERSION="v0.6.4"; \
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else \
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echo "Unsupported architecture: $TARGETARCH"; exit 1; \
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fi; \
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wget -nv https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/${WHL_VERSION}/${WHL_FILE}; \
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pip3 install --no-cache-dir ${WHL_FILE}; \
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rm ${WHL_FILE}; \
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fi \
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;; \
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esac
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