code: def __init__(
      self,
      prediction_length: int,
      context_length: int,
      input_size: int = 1,
      hidden_layer_size: int = 100,
      num_layers: int = 2,
  ) -> None:
      super().__init__()
  
      self.prediction_length = prediction_length
      self.context_length = context_length
      # self.criterion = nn.MSELoss(reduction='none')
      self.criterion = nn.SmoothL1Loss(reduction="none")
      self.hidden_layer_size = hidden_layer_size
      self.num_layers = num_layers
      self.lstm = nn.LSTM(input_size, hidden_layer_size, num_layers)
      self.linear = nn.Linear(hidden_layer_size, prediction_length)
  
file_path: gluonts/src/gluonts/nursery/SCott/model/lstm/lstm_network.py
imports: from typing import List
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new LSTMNetworkBase object from inherited base classes: nn with example: obj = LSTMNetworkBase(prediction_length, context_length, input_size, hidden_layer_size, num_layers)