| ARG CUDA_VERSION="11.8.0" | |
| ARG CUDNN_VERSION="8" | |
| ARG UBUNTU_VERSION="22.04" | |
| ARG MAX_JOBS=4 | |
| FROM nvidia/cuda:$CUDA_VERSION-cudnn$CUDNN_VERSION-devel-ubuntu$UBUNTU_VERSION as base-builder | |
| ENV PATH="/root/miniconda3/bin:${PATH}" | |
| ARG PYTHON_VERSION="3.9" | |
| ARG PYTORCH_VERSION="2.0.1" | |
| ARG CUDA="118" | |
| ARG TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 9.0+PTX" | |
| ENV PYTHON_VERSION=$PYTHON_VERSION | |
| ENV TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST | |
| RUN apt-get update \ | |
| && apt-get install -y wget git build-essential ninja-build git-lfs libaio-dev && rm -rf /var/lib/apt/lists/* \ | |
| && wget \ | |
| https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \ | |
| && mkdir /root/.conda \ | |
| && bash Miniconda3-latest-Linux-x86_64.sh -b \ | |
| && rm -f Miniconda3-latest-Linux-x86_64.sh \ | |
| && conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}" | |
| ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}" | |
| WORKDIR /workspace | |
| RUN python3 -m pip install --upgrade pip && pip3 install packaging && \ | |
| python3 -m pip install --no-cache-dir -U torch==${PYTORCH_VERSION}+cu${CUDA} deepspeed-kernels --extra-index-url https://download.pytorch.org/whl/cu$CUDA | |
| RUN git lfs install --skip-repo && \ | |
| pip3 install awscli && \ | |
| # The base image ships with `pydantic==1.8.2` which is not working | |
| pip3 install -U --no-cache-dir pydantic==1.10.10 | |