View source: R/tuner_callback.R
callback_tuner | R Documentation |
Abstract base class used to build new callbacks.
callback_tuner(tuner, trial)
tuner |
tuner object |
trial |
trial ID |
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).
None
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.
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