TypeError: can't pickle Environment objects when num_workers > 0 for LSUN

The program fails to create an iterator for a DataLoader object when the used dataset is LSUN and the amount of workers is greater than zero. I do not have such an error when work with other datasets. Something tells me that the issue might be caused by lmdb. I run on Windows 10, CUDA 10.

Code:

import torch.utils.data
import torchvision.datasets as dset
import torchvision.transforms as transforms

dataset = dset.LSUN(root='D:/bedroom_train_lmdb', classes=['bedroom_train'],
                            transform=transforms.Compose([
                                transforms.Resize((64, 64)),
                                transforms.ToTensor(),
                                transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
                            ]))

dataloader = torch.utils.data.DataLoader(dataset, batch_size=128,
                                             shuffle=True, num_workers=4)

for data in dataloader:
    print(data)

Error:

Traceback (most recent call last):
  File "C:/Users/x/.PyCharm2018.3/config/scratches/scratch.py", line 15, in <module>
    for data in dataloader:
  File "C:\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 819, in __iter__
    return _DataLoaderIter(self)
  File "C:\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 560, in __init__
    w.start()
  File "C:\Anaconda3\lib\multiprocessing\process.py", line 112, in start
    self._popen = self._Popen(self)
  File "C:\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "C:\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
    return Popen(process_obj)
  File "C:\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
    reduction.dump(process_obj, to_child)
  File "C:\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
TypeError: can't pickle Environment objects

Start with the LSUN dataset and DataLoader multiprocessing paths implicated by the traceback, especially iterator creation and Windows process startup. Reproduce the example with LSUN and num_workers=4, compare it with another dataset, and inspect the dataset state passed to workers. Done means LSUN iteration works on Windows with workers greater than zero and the behavior is covered by a regression test.