Abstract base class used to build new callbacks.
callback_tuner(tuner, trial)tuner object
trial ID
None
Attributes: params: dict. Training parameters (eg. verbosity, batch size, number of epochs...). model: instance of `keras.models.Model`. Reference of the model being trained. validation_data: Deprecated. Do not use. The `logs` dictionary that callback methods take as argument will contain keys for quantities relevant to the current batch or epoch. Currently, the `.fit()` method of the `Model` class will include the following quantities in the `logs` that it passes to its callbacks: on_epoch_end: logs include `acc` and `loss`, and optionally include `val_loss` (if validation is enabled in `fit`), and `val_acc` (if validation and accuracy monitoring are enabled). on_batch_begin: logs include `size`, the number of samples in the current batch. on_batch_end: logs include `loss`, and optionally `acc` (if accuracy monitoring is enabled).
params: dict. Training parameters (eg. verbosity, batch size, number of epochs...). model: instance of `keras.models.Model`. Reference of the model being trained. validation_data: Deprecated. Do not use.