code: def __init__(
      self,
      input_size,
      eps=1e-05,
      momentum=0.9,
      weight_attr=None,
      bias_attr=None,
      data_format="NCL",
      use_global_stats=None,
  ):
      super(BatchNorm1d, self).__init__()
  
      self.norm = nn.BatchNorm1D(
          input_size,
          epsilon=eps,
          momentum=momentum,
          weight_attr=weight_attr,
          bias_attr=bias_attr,
          data_format=data_format,
          use_global_stats=use_global_stats,
      )
  
imports: import math
  import os
  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(input_size, eps, momentum, weight_attr, bias_attr, data_format, use_global_stats)