code: def __init__(
      self,
      filters,
      kernel_size,
      strides=1,
      padding="valid",
      data_format=None,
      dilation_rate=1,
      activation="tanh",
      recurrent_activation="sigmoid",
      use_bias=True,
      kernel_initializer="glorot_uniform",
      recurrent_initializer="orthogonal",
      bias_initializer="zeros",
      unit_forget_bias=True,
      kernel_regularizer=None,
      recurrent_regularizer=None,
      bias_regularizer=None,
      activity_regularizer=None,
      kernel_constraint=None,
      recurrent_constraint=None,
      bias_constraint=None,
      dropout=0.0,
      recurrent_dropout=0.0,
      seed=None,
      return_sequences=False,
      return_state=False,
      go_backwards=False,
      stateful=False,
      **kwargs,
  ):
      super().__init__(
          rank=2,
          filters=filters,
          kernel_size=kernel_size,
          strides=strides,
          padding=padding,
          data_format=data_format,
          dilation_rate=dilation_rate,
          activation=activation,
          recurrent_activation=recurrent_activation,
          use_bias=use_bias,
          kernel_initializer=kernel_initializer,
          recurrent_initializer=recurrent_initializer,
          bias_initializer=bias_initializer,
          unit_forget_bias=unit_forget_bias,
          kernel_regularizer=kernel_regularizer,
          recurrent_regularizer=recurrent_regularizer,
          bias_regularizer=bias_regularizer,
          activity_regularizer=activity_regularizer,
          kernel_constraint=kernel_constraint,
          recurrent_constraint=recurrent_constraint,
          bias_constraint=bias_constraint,
          return_sequences=return_sequences,
          return_state=return_state,
          go_backwards=go_backwards,
          stateful=stateful,
          dropout=dropout,
          recurrent_dropout=recurrent_dropout,
          seed=seed,
          **kwargs,
      )
  
imports: from keras.api_export import keras_export
  from keras.layers.rnn.conv_lstm import ConvLSTM
label_desc: Use image node_id 1 to create a new ConvLSTM2D object from inherited base classes: ConvLSTM with example: obj = ConvLSTM2D(filters, kernel_size, strides, padding, data_format, dilation_rate, activation, recurrent_activation, use_bias, kernel_initializer, recurrent_initializer, bias_initializer, unit_forget_bias, kernel_regularizer, recurrent_regularizer, bias_regularizer, activity_regularizer, kernel_constraint, recurrent_constraint, bias_constraint, dropout, recurrent_dropout, seed, return_sequences, return_state, go_backwards, stateful)