code: def __init__(self, hidden_size, num_inputs, dropout):
      super().__init__()
      self.joint_grn = GRN(
          input_size=hidden_size * num_inputs,
          hidden_size=hidden_size,
          output_size=num_inputs,
          context_hidden_size=hidden_size,
      )
      self.var_grns = nn.ModuleList(
          [
              GRN(
                  input_size=hidden_size,
                  hidden_size=hidden_size,
                  dropout=dropout,
              )
              for _ in range(num_inputs)
          ]
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.nn import LayerNorm
  import logging
  import warnings
  from typing import Tuple, Optional
  from ..losses.pytorch import MAE
  from ..common._base_windows import BaseWindows
label_desc: Use image node_id 1 to create a new VariableSelectionNetwork object from inherited base classes: nn with example: obj = VariableSelectionNetwork(hidden_size, num_inputs, dropout)