code: def __init__(
      self, dimension: int, num_layers: int = 2, skip: bool = True
  ):
      super().__init__()
      self.skip = skip
      self.lstm = nn.LSTM(dimension, dimension, num_layers)
  
imports: from torch import nn
label_desc: Use image node_id 1 to create a new StreamableLSTM object from inherited base classes: nn with example: obj = StreamableLSTM(dimension, num_layers, skip)