Dockerfile

FROM nvidia/cuda:12.2.0-devel-ubuntu22.04

RUN useradd -m -u 1000 user
ENV PATH=/opt/conda/bin:$PATH


RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
        build-essential \
        ca-certificates \
        ccache \
        curl \
        python3 \
        python3-pip \
        git && \
        rm -rf /var/lib/apt/lists/*

# Install conda
# translating Docker's TARGETPLATFORM into mamba arches
RUN case ${TARGETPLATFORM} in \
         "linux/arm64")  MAMBA_ARCH=aarch64  ;; \
         *)              MAMBA_ARCH=x86_64   ;; \
    esac && \
    curl -fsSL -v -o ~/mambaforge.sh -O  "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh"
RUN chmod +x ~/mambaforge.sh && \
    bash ~/mambaforge.sh -b -p /opt/conda && \
    rm ~/mambaforge.sh

# Install pytorch
# On arm64 we exit with an error code
RUN case ${TARGETPLATFORM} in \
         "linux/arm64")  exit 1 ;; \
         *)              /opt/conda/bin/conda update -y conda &&  \
                         /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" "pytorch=$PYTORCH_VERSION" "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)"  ;; \
    esac && \
    /opt/conda/bin/conda clean -ya


COPY ./requirements.txt requirements.txt

RUN pip install --no-cache-dir --upgrade -r requirements.txt
RUN git clone -b energy_star_dev https://github.com/huggingface/optimum-benchmark.git /optimum-benchmark && cd optimum-benchmark && pip install -e .

USER user
WORKDIR /app

# Expose the secret token at buildtime and use its value as git remote URL
RUN --mount=type=secret,id=BULK_ENERGY_TOKEN,mode=0444,required=true \
 git init && \
 git remote add origin $(cat /run/secrets/BULK_ENERGY_TOKEN)


COPY --chown=user . /app
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]