How does PyTorch handle in-memory tensor storage and strides?

Tensors use a storage buffer and stride metadata to map indices to memory.

PyTorch tensors are views over a 1D storage array. Strides define how to move in memory for each dimension, enabling efficient reshaping without copying data.