Strides

This podcast episode thoroughly explores the concept of strides in PyTorch, delving into their importance in representing multidimensional tensor data, their role in creating views and performance optimization, and their limitations in handling non-contiguous inputs. It also discusses the concepts of strided tensors, memory formats, and the distinction between channels first and channels last memory formats, highlighting the benefits and challenges associated with each.