code: def __init__(
      self,
      num_features,
      eps=1e-05,
      momentum=0.1,
      affine=True,
      track_running_stats=True,
  ):
      momentum = 1 - momentum
      weight_attr = None
      bias_attr = None
      if not affine:
          weight_attr = paddle.ParamAttr(learning_rate=0.0)
          bias_attr = paddle.ParamAttr(learning_rate=0.0)
      super().__init__(
          num_features,
          momentum=momentum,
          epsilon=eps,
          weight_attr=weight_attr,
          bias_attr=bias_attr,
          use_global_stats=track_running_stats,
      )
  
file_path: PaddleOCR/ppocr/modeling/heads/gcn.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new BatchNorm1D object from inherited base classes: nn with example: obj = BatchNorm1D(num_features, eps, momentum, affine, track_running_stats)