>how much Python spaghetti probably tanks OpenAI's and other "big ML" shops' infra when they should've trusted in zero copy solutions
Probably not all that much. All of the Python numeric computing frameworks (Numpy, PyTorch, TensorFlow, etc.) are basically just wrappers for lower level C++/C/Fortran code. Unless you’re doing something boneheaded and converting framework-native tensors to Python objects, passing tensors around within a framework essentially just passes a pointer around, which has marginal overhead even when encapsulated in a bloated Python object.
Probably not all that much. All of the Python numeric computing frameworks (Numpy, PyTorch, TensorFlow, etc.) are basically just wrappers for lower level C++/C/Fortran code. Unless you’re doing something boneheaded and converting framework-native tensors to Python objects, passing tensors around within a framework essentially just passes a pointer around, which has marginal overhead even when encapsulated in a bloated Python object.
Indeed, a huge number of PyTorch operations are explicitly zero copy: https://pytorch.org/docs/stable/tensor_view.html