tf.keras.callbacks.CallbackList Container abstracting a list of callbacks.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.keras.callbacks.CallbackList  
tf.keras.callbacks.CallbackList(
    callbacks=None, add_history=False, add_progbar=False, model=None, **params
)

 


 Arguments
  callbacks   List of Callback instances.  
  add_history   Whether a History callback should be added, if one does not already exist in the callbacks list.  
  add_progbar   Whether a ProgbarLogger callback should be added, if one does not already exist in the callbacks list.  
  model   The Model these callbacks are used with.  
  **params   If provided, parameters will be passed to each Callback via Callback.set_params.    Methods append View source 
append(
    callback
)
 on_batch_begin View source 
on_batch_begin(
    batch, logs=None
)
 on_batch_end View source 
on_batch_end(
    batch, logs=None
)
 on_epoch_begin View source 
on_epoch_begin(
    epoch, logs=None
)
 Calls the on_epoch_begin methods of its callbacks. This function should only be called during TRAIN mode.
 


 Arguments
  epoch   Integer, index of epoch.  
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_epoch_end View source 
on_epoch_end(
    epoch, logs=None
)
 Calls the on_epoch_end methods of its callbacks. This function should only be called during TRAIN mode.
 


 Arguments
  epoch   Integer, index of epoch.  
  logs   Dict, metric results for this training epoch, and for the validation epoch if validation is performed. Validation result keys are prefixed with val_.    on_predict_batch_begin View source 
on_predict_batch_begin(
    batch, logs=None
)
 Calls the on_predict_batch_begin methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict, contains the return value of model.predict_step, it typically returns a dict with a key 'outputs' containing the model's outputs.    on_predict_batch_end View source 
on_predict_batch_end(
    batch, logs=None
)
 Calls the on_predict_batch_end methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict. Aggregated metric results up until this batch.    on_predict_begin View source 
on_predict_begin(
    logs=None
)
 Calls the 'on_predict_begin` methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_predict_end View source 
on_predict_end(
    logs=None
)
 Calls the on_predict_end methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_test_batch_begin View source 
on_test_batch_begin(
    batch, logs=None
)
 Calls the on_test_batch_begin methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict, contains the return value of model.test_step. Typically, the values of the Model's metrics are returned. Example: {'loss': 0.2, 'accuracy': 0.7}.    on_test_batch_end View source 
on_test_batch_end(
    batch, logs=None
)
 Calls the on_test_batch_end methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict. Aggregated metric results up until this batch.    on_test_begin View source 
on_test_begin(
    logs=None
)
 Calls the on_test_begin methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_test_end View source 
on_test_end(
    logs=None
)
 Calls the on_test_end methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_train_batch_begin View source 
on_train_batch_begin(
    batch, logs=None
)
 Calls the on_train_batch_begin methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict, contains the return value of model.train_step. Typically, the values of the Model's metrics are returned. Example: {'loss': 0.2, 'accuracy': 0.7}.    on_train_batch_end View source 
on_train_batch_end(
    batch, logs=None
)
 Calls the on_train_batch_end methods of its callbacks.
 


 Arguments
  batch   Integer, index of batch within the current epoch.  
  logs   Dict. Aggregated metric results up until this batch.    on_train_begin View source 
on_train_begin(
    logs=None
)
 Calls the on_train_begin methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    on_train_end View source 
on_train_end(
    logs=None
)
 Calls the on_train_end methods of its callbacks.
 


 Arguments
  logs   Dict. Currently no data is passed to this argument for this method but that may change in the future.    set_model View source 
set_model(
    model
)
 set_params View source 
set_params(
    params
)
 __iter__ View source 
__iter__()