Dear all,

I want to reconstruct a synapse in the first layer of full-connection, which shows in Fig. Could you help me.

If I understand your use case correctly, you would like to transform the left layer to the right one.

In that case I assume the left layer is defined as `nn.Linear(784, 1, bias=False)`

and you could replace it with:

```
class MyModel(nn.Module):
def __init__(self):
super(MyModel, self).__init__()
self.fc1a = nn.Linear(392, 1, bias=False)
self.fc1b = nn.Linear(392, 1, bias=False)
self.fc2 = nn.Linear(2, 1, bias=False)
def forward(self, xa, xb):
xa = self.fc1a(xa)
xb = self.fc1b(xb)
x = torch.cat((xa, xb), dim=1)
x = self.fc2(x)
return x
model = MyModel()
batch_size = 2
xa = torch.randn(batch_size, 392)
xb = torch.randn(batch_size, 392)
out = model(xa, xb)
```

Note that I haven’t added any activation functions etc. as it’s unclear from the figure, if this is desired.

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