| import torch.nn as nn | |
| class Sequential2(nn.Sequential): | |
| """An alternative sequential container to nn.Sequential, | |
| which accepts an arbitrary number of input arguments. | |
| """ | |
| def forward(self, *inputs): | |
| for module in self._modules.values(): | |
| if isinstance(inputs, tuple): | |
| inputs = module(*inputs) | |
| else: | |
| inputs = module(inputs) | |
| return inputs | |