def forward(self, x): x = self.features(x) # 1x1024x7x7 if not self.training and self.test_time_tool: x = F.avg_pool2d(x, kernel_size=7, stride=1) x = self.classifier(x) x = adaptive_avgmax_pool2d( out, pool_type='avgmax') # something wrong here abt dimension else: x = adaptive_avgmax_pool2d(x, pool_type='avg') x = self.classifier(x) return x
def classifier(self, x): x = self._classifier(x) if not self.training: x = adaptive_avgmax_pool2d(x, pool_type='avgmax') return x.view(x.size(0), -1)