perming-1.9.1

Upgraded Details:

• configured criterion of common/Binarier from BCELoss to CrossEntropyLoss, make annotated cases in tests executable.
• drop BCELoss in the allowed criterion to avoid users manually set torch.nn.Sigmoid() with outputs in train_val module.

Binarier Configuration:

import perming
# main = perming.Box(23, 2, (50,), batch_size=8, activation='relu', inplace_on=True, solver='adam', learning_rate_init=0.01)
main = perming.Binarier(23, (50,), batch_size=8, activation='relu', solver='adam', learning_rate_init=0.01)

download:

!pip install perming==1.9.1 # in jupyter
pip install perming==1.9.1 # in cmd