def forward(self, x):
        """
        Returns output tensor after passing input `x` to the neural network.

        Parameters
        ----------
            x : tensor
                input to the UNet.

        Returns
        -------
            tensor
                output of the UNet.
        """


        x  = F.leaky_relu(self.conv1(x), negative_slope = 0.1)
        s1 = F.leaky_relu(self.conv2(x), negative_slope = 0.1)
        s2 = self.down1(s1)
        s3 = self.down2(s2)
        s4 = self.down3(s3)
        s5 = self.down4(s4)
        x  = self.down5(s5)
        x  = self.up1(x, s5)
        x  = self.up2(x, s4)
        x  = self.up3(x, s3)
        x  = self.up4(x, s2)
        x  = self.up5(x, s1)
        x  = F.leaky_relu(self.conv3(x), negative_slope = 0.1)
        return x

        Returns output tensor after passing input `x` to the neural network.

        Parameters
        ----------
            x : tensor
                input to the UNet.

        Returns
        -------
            tensor
                output of the UNet.
        
model.py