class_docstr: Description
  -----------
  An MLP module.
  
  Parameters
  ----------
  input_d : int
      Number of input features.
  output_d : int
      Number of output features.
  hidden_d : int
      Size of hidden layers.
  num_layers : int
      Number of mlp layers.
  dropout : float
      The dropout rate in mlp layers.
  norm : str
      The type of norm layers inside mlp layers. Can be ``'batch'``, ``'layer'`` or ``'none'``.
  init_activate : bool
      If add a relu at the beginning.
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docstr: reset mlp parameters using xavier_norm
docstr_tok: ["reset","mlp","parameters","using","xavier_norm"]
code: def reset_params(self):
      """reset mlp parameters using xavier_norm"""
      for layer in self.layers:
          nn.init.xavier_normal_(layer.weight.data)
          nn.init.constant_(layer.bias.data, 0)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ....None import function
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.reset_params() without return types