1-liner for viewing the shape of all local Tensors in Python (gist.github.com)

Using torch and numpy a lot I find myself perplexed about the shape of some torch.Tensors, particularly if they have a non-obvious set of dimensions (e.g a batch dimension or something). I reach for this one-liner pretty regularly so perhaps it can be of use to others:)

Here's an example output:

  Array Shapes:
  ==================================================
  attention1          : Tensor : (8, 8921, 251)
  m                   : Tensor : (8, 8921, 50)
  ŷ0                  : Tensor : (8, 8921, 50)
  ŷ1                  : Tensor : (8, 8921)
  ŷ2                  : Tensor : (8, 8921)
  random_np_arr       : ndarray: (2, 3)

And the code:

  print(f"\nArray Shapes:\n{'':=>50}"); [print(f"{k:<20}: {str(type(v).__name__):<7}:",  tuple(v.shape)) for k, v in locals().items() if hasattr(v, "shape") and not hasattr(getattr(v, "shape", None), "__call__")]  # Exclude the 'numpy' import, the `shape` func. isn't relevant

(semi-golfed to be able to easily run in a `breakpoint()`)