Deep copy error on modules implementing MessagePassing

🐛 Bug

Since pytorch_geometric version 1.4 modules derived from the class MessagePassing cannot be deep copied (no issues with older versions).

To Reproduce

Just run the following lines (same issue occurring with any other layer derived from MessagePassing)

import copy
import torch_geometric
gconv = torch_geometric.nn.GCNConv(1,1)
copy.deepcopy(gconv)

which produce:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/conda/lib/python3.6/copy.py", line 180, in deepcopy
    y = _reconstruct(x, memo, *rv)
  File "/opt/conda/lib/python3.6/copy.py", line 280, in _reconstruct
    state = deepcopy(state, memo)
  File "/opt/conda/lib/python3.6/copy.py", line 150, in deepcopy
    y = copier(x, memo)
  File "/opt/conda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
    y[deepcopy(key, memo)] = deepcopy(value, memo)
  File "/opt/conda/lib/python3.6/copy.py", line 169, in deepcopy
    rv = reductor(4)
TypeError: can't pickle mappingproxy objects

Expected behavior

Should have produced a new deep copy of the object instead.

Environment

Nvidia DGX station

Virtual environment with:

• torch 1.4
• torch_geometric 1.4.1

Additional context

A deep copy is necessary in order to copy models or parts of models whose weighs are later altered.

[rusty1s]

Fixed with 1.4.2.

[tjiagoM]

Awesome!! 😄