(self,input,label)
| 70 | ) |
| 71 | ) |
| 72 | def forward(self,input,label): |
| 73 | x = self.conv_layer_1(input) |
| 74 | y = self.conv_layer_2(label) |
| 75 | x = torch.cat([x,y], dim = 1) |
| 76 | x = self.conv_layer_3(x) |
| 77 | x = self.conv_layer_4(x) |
| 78 | out = torch.tanh(self.final_conv_layer(x)) |
| 79 | return out |
| 80 | |
| 81 | class Discriminator(torch.nn.Module): |
| 82 | def __init__(self,img_channels = 1,out_channels = 1,d = 128): |
nothing calls this directly
no outgoing calls
no test coverage detected