Dockerfile.cuda12

# Use the latest CUDA 12 runtime as base image
FROM nvidia/cuda:12.3.1-devel-ubuntu22.04

# Set the working directory in the container
WORKDIR /workdir

ARG MINIFORGE_NAME=Miniforge3
ARG MINIFORGE_VERSION=23.3.1-1
ARG TARGETPLATFORM

ENV CONDA_DIR=/opt/conda
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
ENV PATH=${CONDA_DIR}/bin:${PATH}

# 1. Install just enough for conda to work
# 2. Keep $HOME clean (no .wget-hsts file), since HSTS isn't useful in this context
# 3. Install miniforge from GitHub releases
# 4. Apply some cleanup tips from https://jcrist.github.io/conda-docker-tips.html
#    Particularly, we remove pyc and a files. The default install has no js, we can skip that
# 5. Activate base by default when running as any *non-root* user as well
#    Good security practice requires running most workloads as non-root
#    This makes sure any non-root users created also have base activated
#    for their interactive shells.
# 6. Activate base by default when running as root as well
#    The root user is already created, so won't pick up changes to /etc/skel
RUN apt-get update > /dev/null && \
    apt-get install --no-install-recommends --yes \
        wget bzip2 ca-certificates \
        git \
        tini \
        > /dev/null && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/* && \
    wget --no-hsts --quiet https://github.com/conda-forge/miniforge/releases/download/${MINIFORGE_VERSION}/${MINIFORGE_NAME}-${MINIFORGE_VERSION}-Linux-$(uname -m).sh -O /tmp/miniforge.sh && \
    /bin/bash /tmp/miniforge.sh -b -p ${CONDA_DIR} && \
    rm /tmp/miniforge.sh && \
    conda clean --tarballs --index-cache --packages --yes && \
    find ${CONDA_DIR} -follow -type f -name '*.a' -delete && \
    find ${CONDA_DIR} -follow -type f -name '*.pyc' -delete && \
    conda clean --force-pkgs-dirs --all --yes  && \
    echo ". ${CONDA_DIR}/etc/profile.d/conda.sh && conda activate base" >> /etc/skel/.bashrc && \
    echo ". ${CONDA_DIR}/etc/profile.d/conda.sh && conda activate base" >> ~/.bashrc

# Install pytorch with CUDA
RUN --mount=type=cache,target=/opt/conda/pkgs mamba install -y pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia

# Install onnxruntime with CUDA
RUN --mount=type=cache,target=/opt/conda/pkgs mamba install -y onnxruntime=*=*cuda*

# Install audio-separator
RUN --mount=type=cache,target=/opt/conda/pkgs mamba install -y audio-separator