(torch)如何构造一种forward 和backward 不同的layer
在BNN中,往往训练阶段较为复杂,而inference phase is simple.
So how can we build a layer with complex training progress and simple inference algorithm?
n1 = nn.Linear(4,5) n1.train() print(n1.__dict__) n1.eval() print(n1.__dict__)
The different phase has its corresponding __dict__