The whole of PyTorch on one page: eight floors beneath three lines of code

The whole of PyTorch on one page

A navigational map of PyTorch internals. The author breaks `loss.backward()` into eight floors: Python calls, compiled shared libraries, the C++ boundary, the dispatcher, down to GPU kernels and memory allocators. Every key number comes from a runnable script—e.g., `libtorch_cpu.dylib` weighs 206.5 MB. The post doesn't detail specific operators, but lays out a full 11-part syllabus covering tensors, autograd, the compiler, and distributed deployment. Treat it as an index; the real depth arrives in later parts.

Why it matters: A well-structured map for a series on PyTorch internals, breaking loss.backward() into eight layers with clear chapter signposts — useful navigation for readers who want to go deep. But as a map entry it lacks concrete operator details or a counterintuitive finding, so it land...