class_docstr: Provides an interface to easily define a callback from lambdas or functions.
  
  Args:
      kwargs: The arguments of this class are keyword arguments with the same names as the methods in the
          :class:`~poutyne.Callback` class. The values are lambdas or functions taking the same arguments as the
          corresponding methods in :class:`~poutyne.Callback`.
  
  See:
      :class:`~poutyne.Callback`
  
  Example:
      .. code-block:: python
  
          from poutyne import LambdaCallback
          callbacks = [LambdaCallback(
              on_epoch_end=lambda epoch_number, logs: print(f"Epoch {epoch_number} end"),
              on_train_end=lambda logs: print("Training ended")
          )]
          model.fit(...., callbacks=callbacks)
code: def __init__(
      self,
      *,
      on_epoch_begin=None,
      on_epoch_end=None,
      on_train_batch_begin=None,
      on_train_batch_end=None,
      on_valid_batch_begin=None,
      on_valid_batch_end=None,
      on_test_batch_begin=None,
      on_test_batch_end=None,
      on_predict_batch_begin=None,
      on_predict_batch_end=None,
      on_train_begin=None,
      on_train_end=None,
      on_valid_begin=None,
      on_valid_end=None,
      on_test_begin=None,
      on_test_end=None,
      on_predict_begin=None,
      on_predict_end=None,
      on_backward_end=None,
  ):
      # pylint: disable=too-many-locals
      super().__init__()
      self._on_epoch_begin = self._set_lambda_for_none(on_epoch_begin)
      self._on_epoch_end = self._set_lambda_for_none(on_epoch_end)
      self._on_train_batch_begin = self._set_lambda_for_none(
          on_train_batch_begin
      )
      self._on_train_batch_end = self._set_lambda_for_none(
          on_train_batch_end
      )
      self._on_valid_batch_begin = self._set_lambda_for_none(
          on_valid_batch_begin
      )
      self._on_valid_batch_end = self._set_lambda_for_none(
          on_valid_batch_end
      )
      self._on_test_batch_begin = self._set_lambda_for_none(
          on_test_batch_begin
      )
      self._on_test_batch_end = self._set_lambda_for_none(
          on_test_batch_end
      )
      self._on_predict_batch_begin = self._set_lambda_for_none(
          on_predict_batch_begin
      )
      self._on_predict_batch_end = self._set_lambda_for_none(
          on_predict_batch_end
      )
      self._on_train_begin = self._set_lambda_for_none(on_train_begin)
      self._on_train_end = self._set_lambda_for_none(on_train_end)
      self._on_valid_begin = self._set_lambda_for_none(on_valid_begin)
      self._on_valid_end = self._set_lambda_for_none(on_valid_end)
      self._on_test_begin = self._set_lambda_for_none(on_test_begin)
      self._on_test_end = self._set_lambda_for_none(on_test_end)
      self._on_predict_begin = self._set_lambda_for_none(
          on_predict_begin
      )
      self._on_predict_end = self._set_lambda_for_none(on_predict_end)
      self._on_backward_end = self._set_lambda_for_none(on_backward_end)
  
imports: from typing import Dict
  from poutyne.framework.callbacks.callbacks import Callback
label_desc: Use image node_id 1 to create a new LambdaCallback object from inherited base classes: Callback with example: obj = LambdaCallback()