class_docstr: A general wrapper class for a stacking multiple NN layers.
  
  Args:
      name (str): The registered name of the layer.
      layer_config (LayerConfig): The configuration of the layer.
      **kwargs (optional): Additional keyword arguments.
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code: def __init__(self, name, layer_config: LayerConfig, **kwargs):
      super().__init__()
      if layer_config.dim_inner:
          dim_inner = layer_config.dim_out
      else:
          dim_inner = layer_config.dim_inner
  
      for i in range(layer_config.num_layers):
          d_in = layer_config.dim_in if i == 0 else dim_inner
          d_out = (
              layer_config.dim_out
              if i == layer_config.num_layers - 1
              else dim_inner
          )
          has_act = (
              layer_config.final_act
              if i == layer_config.num_layers - 1
              else True
          )
          inter_layer_config = copy.deepcopy(layer_config)
          inter_layer_config.dim_in = d_in
          inter_layer_config.dim_out = d_out
          inter_layer_config.has_act = has_act
          layer = GeneralLayer(name, inter_layer_config, **kwargs)
          self.add_module(f"Layer_{i}", layer)
  
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 GeneralMultiLayer object from inherited base classes: torch.nn with example: obj = GeneralMultiLayer(name, layer_config)