What does it mean when CUDA version is not available and torch.cuda.is_available returns False while using GPU in a Docker container?

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This means that there is no CUDA library installed in the Docker container, which is required for GPU acceleration. As a result, the torch.cuda.is_available function returns False, indicating that PyTorch is unable to detect the presence of a GPU. To use a GPU, you need to install the CUDA library in the Docker container.