def forward()

in models/vision_transformer.py [0:0]

• 9 lines of code
• 3 McCabe index (conditional complexity)

    def forward(self, x):
        x = self.conv(x)  # extract patches
        x = x.flatten(2)  # flatten the patches into a single dimension
        x = x.transpose(1, 2)  # transpose to (batch_size, num_patches, hidden_dim)

        # Add CLS token (according to original ViT Paper) and position embeddings
        if self.cls_flag:
            cls_token = self.cls_token.expand(x.shape[0], -1, -1)
            x = torch.cat((cls_token, x), dim=1)
        x = x + self.position_embedding
        return x