TorchSnooper v0.3

Containers are now represented recursively.

Example code:

import torch
import torchsnooper

@torchsnooper.snoop()
def f():
    return [{'key': torch.zeros(5, 6, 7)}]

f()

Output from TorchSnooper v0.2

14:17:49.646680 call         5 def f():
14:17:49.646778 line         6     return [{'key': torch.zeros(5, 6, 7)}]
14:17:49.646973 return       6     return [{'key': torch.zeros(5, 6, 7)}]
Return value:.. [{'key': tensor([[[0., 0., 0., 0., 0., 0., 0.], ...., 0.],         [0., 0., 0., 0., 0., 0., 0.]]])}]

Output from TorchSnooper v0.3

14:16:33.205156 call         5 def f():
14:16:33.205261 line         6     return [{'key': torch.zeros(5, 6, 7)}]
14:16:33.205427 return       6     return [{'key': torch.zeros(5, 6, 7)}]
Return value:.. [{'key': tensor<(5, 6, 7), float32, cpu>}]