Appendix C: Full torch API Reference Crosswalk

“All the power. One list.”

Module	Link	Description
torch.Tensor	https://pytorch.org/docs/stable/tensors.html	Core data structure
torch.nn	https://pytorch.org/docs/stable/nn.html	Layers, loss functions, model building
torch.nn.functional	https://pytorch.org/docs/stable/nn.functional.html	Stateless functional ops
torch.autograd	https://pytorch.org/docs/stable/autograd.html	Gradient tracking, custom ops
torch.cuda	https://pytorch.org/docs/stable/cuda.html	GPU support, memory info
torch.utils.data	https://pytorch.org/docs/stable/data.html	Dataset, DataLoader, Samplers
torch.special	https://pytorch.org/docs/stable/special.html	Advanced math functions (gamma, digamma, etc.)
torch.fft	https://pytorch.org/docs/stable/fft.html	Frequency transforms (fft, rfft, fft2, etc.)
torch.linalg	https://pytorch.org/docs/stable/linalg.html	Modern linear algebra tools
torch.profiler	https://pytorch.org/docs/stable/profiler.html	CPU/GPU performance profiling
torch.onnx	https://pytorch.org/docs/stable/onnx.html	Exporting to ONNX format
torch.jit	https://pytorch.org/docs/stable/jit.html	Scripting & tracing models for speed/export
torchvision.transforms	https://pytorch.org/vision/stable/transforms.html	Image preprocessing
torch.utils.tensorboard	https://pytorch.org/docs/stable/tensorboard.html	Training visualizations