def train(self, mode=True):
    super(HighResolutionNet, self).train(mode)
    if (mode and self.norm_eval):
        for m in self.modules():
            if isinstance(m, nn.BatchNorm2d):
                m.eval()
def train(self, mode=True):
    super(HighResolutionNet, self).train(mode)
    if (mode and self.norm_eval):
        for m in self.modules():
            if isinstance(m, nn.BatchNorm2d):
                m.eval()