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, 1296)
                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