class_docstr: A batch normalization layer for node-level features.
  
  Args:
      layer_config (LayerConfig): The configuration of the layer.
class_docstr_tok: ["A","batch","normalization","layer","for","node-level","features",".","Args",":","layer_config","(","LayerConfig",")",":","The","configuration","of","the","layer","."]
code: def __init__(self, layer_config: LayerConfig):
      super().__init__()
      self.bn = torch.nn.BatchNorm1d(
          layer_config.dim_in,
          eps=layer_config.bn_eps,
          momentum=layer_config.bn_mom,
      )
  
imports: import copy
  from dataclasses import dataclass, replace
  import torch
  import torch.nn.functional
  import torch_geometric
  import torch_geometric.graphgym.models.act
  import torch_geometric.graphgym.register
  from torch_geometric.graphgym.contrib.layer.generalconv import GeneralConvLayer, GeneralEdgeConvLayer
  from torch_geometric.graphgym.register import register_layer
  from torch_geometric.nn import Linear
label_desc: Use image node_id 1 to create a new BatchNorm1dNode object from inherited base classes: torch.nn with example: obj = BatchNorm1dNode(layer_config)