Description
Tensor reshaping and reduction patterns can be expressed consistently across PyTorch, TensorFlow, JAX, and other array stacks. Machine-learning developers use it to make model code shorter and clearer. Shape mistakes can silently change model behavior, so tests around tensor dimensions still matter.