code: def __init__(self, hidden_size, num_static_vars, dropout):
      super().__init__()
      self.vsn = VariableSelectionNetwork(
          hidden_size=hidden_size,
          num_inputs=num_static_vars,
          dropout=dropout,
      )
      self.context_grns = nn.ModuleList(
          [
              GRN(
                  input_size=hidden_size,
                  hidden_size=hidden_size,
                  dropout=dropout,
              )
              for _ in range(4)
          ]
      )
  
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 StaticCovariateEncoder object from inherited base classes: nn with example: obj = StaticCovariateEncoder(hidden_size, num_static_vars, dropout)