def forward(self, x):
            """
            Forward function to evaluate the model
            :param x: Input to the model
            :return: Prediction of the model
            """
            x = self.conv(x)
            x = self.relu(x)
            x = x.reshape(-1, 1600)
            x = self.fullyconnected(x)
            if not from_logits:
                x = torch.nn.functional.softmax(x, dim=1)
            return x

            Forward function to evaluate the model
            :param x: Input to the model
            :return: Prediction of the model
            
tests/utils.py