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# Use the official PyTorch Docker image as a base (includes CUDA and PyTorch) | |
FROM pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtime | |
# Install required dependencies (add any additional system dependencies you need) | |
RUN apt update && apt install -y ffmpeg | |
# Create a non-root user with a home directory | |
RUN useradd -m -u 1000 user | |
# Switch to the new non-root user | |
USER user | |
# Set environment variables for the new user | |
ENV HOME=/home/user \ | |
PATH=/home/user/.local/bin:$PATH | |
# Set a working directory | |
WORKDIR $HOME/app | |
# Set the TRANSFORMERS_CACHE directory to be within the user's home directory | |
ENV TRANSFORMERS_CACHE=$HOME/cache | |
# Copy the app code and set ownership to the non-root user | |
COPY --chown=user . $HOME/app | |
# Install Python dependencies in the virtual environment | |
RUN python -m venv /home/user/venv | |
ENV PATH="/home/user/venv/bin:$PATH" | |
# Install pip dependencies within the virtual environment | |
COPY requirements.txt . | |
RUN pip install --upgrade pip | |
RUN pip install -r requirements.txt | |
# Run the training script | |
CMD ["python", "app.py"] | |