code: def __init__(
      self,
      activation_function=tf.nn.relu,
      number_of_lstm_cells: int = 256,
      scheme: MiddlewareScheme = MiddlewareScheme.Medium,
      batchnorm: bool = False,
      dropout_rate: float = 0.0,
      name="middleware_lstm_embedder",
      dense_layer=Dense,
      is_training=False,
  ):
      super().__init__(
          activation_function=activation_function,
          batchnorm=batchnorm,
          dropout_rate=dropout_rate,
          scheme=scheme,
          name=name,
          dense_layer=dense_layer,
          is_training=is_training,
      )
      self.return_type = Middleware_LSTM_Embedding
      self.number_of_lstm_cells = number_of_lstm_cells
      self.layers = []
  
file_path: coach/rl_coach/architectures/tensorflow_components/middlewares/lstm_middleware.py
imports: import numpy
  import tensorflow
  from rl_coach.architectures.tensorflow_components.layers import Dense
  from rl_coach.architectures.tensorflow_components.middlewares.middleware import Middleware
  from rl_coach.base_parameters import MiddlewareScheme
  from rl_coach.core_types import Middleware_LSTM_Embedding
  from rl_coach.utils import force_list
label_desc: Use image node_id 1 to create a new LSTMMiddleware object from inherited base classes: Middleware with example: obj = LSTMMiddleware(activation_function, number_of_lstm_cells, scheme, batchnorm, dropout_rate, name, dense_layer, is_training)