class_docstr: The MLP-Mixer module.
  
  Args:
      num_tokens (int): Number of tokens/patches in each sample.
      in_channels (int): Input channels.
      out_channels (int): Output channels.
      dropout (float, optional): Dropout probability. (default: :obj:`0.0`)
code: def reset_parameters(self):
      self.token_norm.reset_parameters()
      self.token_lin1.reset_parameters()
      self.token_lin2.reset_parameters()
      self.channel_norm.reset_parameters()
      self.channel_lin1.reset_parameters()
      self.channel_lin2.reset_parameters()
      self.head_norm.reset_parameters()
      self.head_lin.reset_parameters()
  
imports: import numpy
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch.nn import LayerNorm, Linear
  from torch_geometric.nn import TemporalEncoding
  from torch_geometric.utils import scatter, to_dense_batch
label_desc: Use image node_id 2 for calling the _MLPMixer obj's underlying member method code with example usage: obj.reset_parameters() without return types