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axolotl/docker/Dockerfile-uv-base

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ARG CUDA_VERSION="12.6.3"
ARG CUDNN_VERSION=""
ARG UBUNTU_VERSION="22.04"
ARG MAX_JOBS=4
FROM nvidia/cuda:$CUDA_VERSION-cudnn$CUDNN_VERSION-devel-ubuntu$UBUNTU_VERSION AS base-builder
ARG PYTHON_VERSION="3.11"
ARG PYTORCH_VERSION="2.6.0"
ARG CUDA="126"
ARG TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 9.0+PTX"
ENV PYTHON_VERSION=$PYTHON_VERSION
ENV TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST
ENV UV_TORCH_BACKEND="cu${CUDA}"
RUN apt-get update \
&& apt-get install -y wget git build-essential ninja-build git-lfs libaio-dev pkg-config curl && rm -rf /var/lib/apt/lists/* \
&& git lfs install --skip-repo \
&& curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.local/bin:${PATH}"
RUN uv python install ${PYTHON_VERSION}
WORKDIR /workspace
RUN uv venv --no-project --relocatable axolotl-venv
ENV PATH="/workspace/axolotl-venv/bin:${PATH}"
RUN uv pip install packaging setuptools wheel psutil \
&& uv pip install torch==${PYTORCH_VERSION} torchvision \
&& uv pip install --no-build-isolation "causal_conv1d @ git+https://github.com/Dao-AILab/causal-conv1d.git@main" \
&& uv pip install "mamba_ssm @ git+https://github.com/state-spaces/mamba.git@main" \
&& uv pip install awscli pydantic
RUN if [ "$PYTORCH_VERSION" = "2.9.0" ] && [ "$CUDA" = "128" ] ; then \
wget https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.4.17/flash_attn-2.8.3+cu128torch2.9-cp311-cp311-linux_x86_64.whl; \
uv pip install --no-cache-dir flash_attn-2.8.3+cu128torch2.9-cp311-cp311-linux_x86_64.whl; \
rm flash_attn-2.8.3+cu128torch2.9-cp311-cp311-linux_x86_64.whl; \
fi