def train(self, mode=True):
        """Convert the model into training mode will keeping the normalization
        layer freezed."""
        super(HRNet, self).train(mode)
        if mode and self.norm_eval:
            for m in self.modules():
                # trick: eval have effect on BatchNorm only
                if isinstance(m, _BatchNorm):
                    m.eval()
Convert the model into training mode will keeping the normalization
        layer freezed.
ControlNet-v1-1-nightly/annotator/uniformer/mmseg/models/backbones/hrnet.py