code: def __init__(
      self,
      on_epoch_begin=None,
      on_epoch_end=None,
      on_train_begin=None,
      on_train_end=None,
      on_train_batch_begin=None,
      on_train_batch_end=None,
      **kwargs,
  ):
      super().__init__()
      self.__dict__.update(kwargs)
      if on_epoch_begin is not None:
          self.on_epoch_begin = on_epoch_begin
      if on_epoch_end is not None:
          self.on_epoch_end = on_epoch_end
      if on_train_begin is not None:
          self.on_train_begin = on_train_begin
      if on_train_end is not None:
          self.on_train_end = on_train_end
      if on_train_batch_begin is not None:
          self.on_train_batch_begin = on_train_batch_begin
      if on_train_batch_end is not None:
          self.on_train_batch_end = on_train_batch_end
  
imports: from keras.api_export import keras_export
  from keras.callbacks.callback import Callback
label_desc: Use image node_id 1 to create a new LambdaCallback object from inherited base classes: Callback with example: obj = LambdaCallback(on_epoch_begin, on_epoch_end, on_train_begin, on_train_end, on_train_batch_begin, on_train_batch_end)