Support Torch.Tensor in the variable explorer

Problem Description

I’m a pytorch user, and I’m always thinking that type torch.Tensor might be represented in a proper way. What torch.Tensor type data need is just ‘.numpy()’ to be converted to numpy array objects.

So, is it possible to apply simple scripts for the unsupported data types inside of Variable explorer?(i.e. If Variable explorer saw Tensor type objects, then a corresponding function/method for the type is applied and show the result of it on Variable explorer with distinguishable color.)

def type_conversion(data: torch.Tensor):
  if isinstance(data, torch.Tensor):
    return data.numpy()
  return None

Package Versions

• Spyder: 3.2.8
• Python: 3.6.4
• Qt:
• PyQt:
• Operating System: macOS 10.13.4

Dependencies

IPython >=4.0    :  6.3.1 (OK)
cython >=0.21    :  0.28.2 (OK)
jedi >=0.9.0     :  0.12.0 (OK)
nbconvert >=4.0  :  5.3.1 (OK)
numpy >=1.7      :  1.14.1 (OK)
pandas >=0.13.1  :  0.22.0 (OK)
psutil >=0.3     :  5.4.5 (OK)
pycodestyle >=2.3:  2.4.0 (OK)
pyflakes >=0.6.0 :  1.6.0 (OK)
pygments >=2.0   :  2.2.0 (OK)
pylint >=0.25    :  1.8.4 (OK)
qtconsole >=4.2.0:  4.3.1 (OK)
rope >=0.9.4     :  0.10.7 (OK)
sphinx >=0.6.6   :  1.7.4 (OK)
sympy >=0.7.3    :  1.1.1 (OK)

[ccordoba12]

Sorry, there are not updates about this. We’ll try to do that in the coming months.

[sanchit88]

Hi Spyder team, any update on this matter? Like current developments or even if supporting Pytorch tensors in the debugger and in the variable explorer is a priority? It would be really helpful. Thanks.