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)
