code: def __init__(
      self,
      nodes_per_layer,
      importance_sampling=True,
      weight="w",
      out_weight="edge_weights",
      replace=False,
  ):
      super().__init__()
      self.nodes_per_layer = nodes_per_layer
      self.importance_sampling = importance_sampling
      self.edge_weight = weight
      self.output_weight = out_weight
      self.replace = replace
  
file_path: dgl/examples/pytorch/labor/ladies_sampler.py
imports: import dgl
  import dgl.function
  import torch
label_desc: Use image node_id 1 to create a new LadiesSampler object from inherited base classes: dgl.dataloading with example: obj = LadiesSampler(nodes_per_layer, importance_sampling, weight, out_weight, replace)