srvcodes / continual_learning_with_vit Goto Github PK

 self.conv_layers = nn.Sequential(
            *[nn.Sequential(
                nn.Conv2d(in_channels=n_filter_list[i],
                          out_channels=n_filter_list[i + 1],
                          kernel_size=3,  # hardcoding for now because that's what the paper used
                          stride=2,  # hardcoding for now because that's what the paper used
                          padding=1),  # hardcoding for now because that's what the paper used
            )
                for i in range(len(n_filter_list)-1)
            ])

self.conv_layers = nn.Sequential(
            *[nn.Sequential
                (
                    nn.Conv2d(in_channels=n_filter_list[i],
                            out_channels=n_filter_list[i + 1],
                            kernel_size=3,  # hardcoding for now because that's what the paper used
                            stride=2,  # hardcoding for now because that's what the paper used
                            padding=1),  # hardcoding for now because that's what the paper used
                    nn.BatchNorm2d(n_filter_list[i + 1]),
                    nn.ReLU(inplace=True)
                )
                for i in range(len(n_filter_list)-1)
            ])