debug:pytorch

Debug PyTorch issues systematically. Use when encountering tensor errors, CUDA out-of-memory errors, gradient problems like NaN loss or exploding gradients, shape mismatches between layers, device conflicts between CPU and GPU, autograd graph issues, DataLoader problems, dtype mismatches, or training instabilities in deep learning workflows.