| 9 | from torchinfo import summary |
| 10 | |
| 11 | class Encoder(torch.nn.Module): |
| 12 | def __init__(self,in_features = 784,out_features = 128): |
| 13 | super(Encoder, self).__init__() |
| 14 | self.encoder = torch.nn.Sequential( |
| 15 | torch.nn.Linear(in_features=in_features, out_features=512), |
| 16 | torch.nn.ReLU(), |
| 17 | |
| 18 | torch.nn.Linear(in_features=512, out_features=256), |
| 19 | torch.nn.ReLU(), |
| 20 | |
| 21 | torch.nn.Linear(in_features=256, out_features=out_features), |
| 22 | ) |
| 23 | def forward(self,x): |
| 24 | x = x.view(-1,784) |
| 25 | out = self.encoder(x) |
| 26 | return out |
| 27 | |
| 28 | if __name__ == '__main__': |
| 29 | model = Encoder(in_features=784,out_features=128) |
no outgoing calls
no test coverage detected