class_docstr: A general wrapper for layers.
  
  Args:
      name (str): The registered name of the layer.
      layer_config (LayerConfig): The configuration of the layer.
      **kwargs (optional): Additional keyword arguments.
class_docstr_tok: ["A","general","wrapper","for","layers",".","Args",":","name","(","str",")",":","The","registered","name","of","the","layer",".","layer_config","(","LayerConfig",")",":","The","configuration","of","the","layer",".","*","*","kwargs","(","optional",")",":","Additional","keyword","arguments","."]
code: def forward(self, batch):
      batch = self.layer(batch)
      if isinstance(batch, torch.Tensor):
          batch = self.post_layer(batch)
          if self.has_l2norm:
              batch = F.normalize(batch, p=2, dim=1)
      else:
          batch.x = self.post_layer(batch.x)
          if self.has_l2norm:
              batch.x = F.normalize(batch.x, p=2, dim=1)
      return batch
  
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 2 for calling the GeneralLayer obj's underlying member method code with example usage: obj.forward(batch) and returns: batch