siamese_model.py
class SiameseNetwork(nn.Module):
    def __init__(self):
        super(SiameseNetwork, self).__init__()

        self.cnn = nn.Sequential(
            nn.Conv2d(1, 64, kernel_size=5, stride=1, padding=2),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(2, stride=2),

            nn.Conv2d(64, 128, kernel_size=5, stride=1, padding=2),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(2, stride=2),

            nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(2, stride=2)
        )

        self.fc = nn.Sequential(
            nn.Linear(256 * 3 * 3, 1024),
            nn.ReLU(inplace=True),

            nn.Linear(1024, 256),
            nn.ReLU(inplace=True),

            nn.Linear(256, 2)
        )

    def forward_once(self, x):
        output = self.cnn(x)
        output = output.view(output.size()[0], -1)
        output = self.fc(output)
        return output

    def forward(self, inputA, inputB):
        outputA = self.forward_once(inputA)
        outputB = self.forward_once(inputB)
        return outputA, outputB

A CNN sub-network

A Fully connected sub-network

Embeddings

for both images