Dockerfile.cuda

# Use NVIDIA CUDA base image
FROM nvidia/cuda:11.8.0-runtime-ubuntu22.04

# Set the working directory in the container
WORKDIR /app

# Install Python and system dependencies
RUN apt-get update && apt-get install -y \
    python3 \
    python3-pip \
    git \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install PyTorch with CUDA support
RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip3 install --no-cache-dir -r package/requirements.txt

# Install the local package
RUN pip3 install -e package

# Make port 8888 available to the world outside this container
EXPOSE 8888

# Create a non-root user and switch to it
RUN useradd -m jupyter
USER jupyter

# Run Jupyter when the container launches
CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--port=8888", "--no-browser", "--allow-root"]