class_docstr: A basic MLP model.
  
  Args:
      layer_config (LayerConfig): The configuration of the layer.
      **kwargs (optional): Additional keyword arguments.
class_docstr_tok: ["A","basic","MLP","model",".","Args",":","layer_config","(","LayerConfig",")",":","The","configuration","of","the","layer",".","*","*","kwargs","(","optional",")",":","Additional","keyword","arguments","."]
code: def forward(self, batch):
      if isinstance(batch, torch.Tensor):
          batch = self.model(batch)
      else:
          batch.x = self.model(batch.x)
      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 MLP obj's underlying member method code with example usage: obj.forward(batch) and returns: batch