def forward(self, x):
        x = self.forward_features(x)
        x = self.global_pool(x)
        # both classifier and block drop?
        # if self.drop_rate > 0.:
        #     x = F.dropout(x, p=self.drop_rate, training=self.training)
        x = self.classifier(x)
        return x