code: def __init__(
      self,
      d_hidden: int,
      n_vars: int,
      dropout: float = 0.0,
      add_static: bool = False,
      **kwargs,
  ) -> None:
      super().__init__(**kwargs)
      self.d_hidden = d_hidden
      self.n_vars = n_vars
      self.add_static = add_static
  
      with self.name_scope():
          self.weight_network = GatedResidualNetwork(
              d_hidden=self.d_hidden,
              d_input=self.d_hidden * self.n_vars,
              d_output=self.n_vars,
              d_static=self.d_hidden if add_static else None,
              dropout=dropout,
          )
          self.variable_network = []
          for n in range(self.n_vars):
              var_net = GatedResidualNetwork(
                  d_hidden=self.d_hidden,
                  dropout=dropout,
              )
              self.register_child(var_net, name=f"var_{n+1}")
              self.variable_network.append(var_net)
  
imports: import math
  from typing import List, Optional, Tuple
  from mxnet import init
  from mxnet.gluon import HybridBlock, nn, rnn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
label_desc: Use image node_id 1 to create a new VariableSelectionNetwork object from inherited base classes: HybridBlock with example: obj = VariableSelectionNetwork(d_hidden, n_vars, dropout, add_static)