ApplioRVC-Inference / Dockerfile
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FROM ubuntu:20.04 as base
FROM base as base-amd64
ENV NVARCH x86_64
ENV NVIDIA_REQUIRE_CUDA "cuda>=11.8 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=tesla,driver>=515,driver<516 brand=unknown,driver>=515,driver<516 brand=nvidia,driver>=515,driver<516 brand=nvidiartx,driver>=515,driver<516 brand=geforce,driver>=515,driver<516 brand=geforcertx,driver>=515,driver<516 brand=quadro,driver>=515,driver<516 brand=quadrortx,driver>=515,driver<516 brand=titan,driver>=515,driver<516 brand=titanrtx,driver>=515,driver<516"
ENV NV_CUDA_CUDART_VERSION 11.8.89-1
ENV NV_CUDA_COMPAT_PACKAGE cuda-compat-11-8
FROM base as base-arm64
ENV NVARCH sbsa
ENV NVIDIA_REQUIRE_CUDA "cuda>=11.8"
ENV NV_CUDA_CUDART_VERSION 11.8.89-1
FROM base-${TARGETARCH}
ARG TARGETARCH
LABEL maintainer "NVIDIA CORPORATION <[email protected]>"
RUN apt-get update && apt-get install -y --no-install-recommends \
gnupg2 curl ca-certificates && \
curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH}/3bf863cc.pub | apt-key add - && \
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list && \
apt-get purge --autoremove -y curl \
&& rm -rf /var/lib/apt/lists/*
ENV CUDA_VERSION 11.8.0
# For libraries in the cuda-compat-* package: https://docs.nvidia.com/cuda/eula/index.html#attachment-a
RUN apt-get update && apt-get install -y --no-install-recommends \
cuda-cudart-11-8=${NV_CUDA_CUDART_VERSION} \
${NV_CUDA_COMPAT_PACKAGE} \
&& rm -rf /var/lib/apt/lists/*
# Required for nvidia-docker v1
RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf \
&& echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
COPY NGC-DL-CONTAINER-LICENSE /
# nvidia-container-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
WORKDIR /app
COPY ./requirements.txt /app/requirements.txt
COPY ./packages.txt /app/packages.txt
RUN pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
RUN apt-get update && xargs -r -a /app/packages.txt apt-get install -y && rm -rf /var/lib/apt/lists/*
RUN pip3 install --no-cache-dir -r /app/requirements.txt
# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user
# Switch to the "user" user
USER user
# Set home to the user's home directory
ENV HOME=/home/user \
PATH=/home/user/.local/bin:$PATH
# Set the working directory to the user's home directory
WORKDIR $HOME/app
# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app
EXPOSE 8501
CMD streamlit run app.py --server.maxUploadSize 1024 --server.enableWebsocketCompression=false --server.enableXsrfProtection=false