validation_split=validation_split)
// Initialize the hyper_graph.
self._meta_build(dataset)
// Initialize the Tuner.
// The hypermodel needs input_shape, which can only be known after
// preprocessing. So we preprocess the dataset once to get the input_shape,
// so that the hypermodel can be built in the initializer of the Tuner, which
// does not access the dataset.
hp = kerastuner.HyperParameters()
preprocess_graph, keras_graph = self.hyper_graph.build_graphs(hp)
preprocess_graph.preprocess(
dataset=dataset,
validation_data=validation_data,
fit=True)
self.tuner = self.tuner(
hyper_graph=self.hyper_graph,
hypermodel=keras_graph,
fit_on_val_data=self._split_dataset,
overwrite=self.overwrite,
After Change
validation_split=validation_split)
// Initialize the hyper_graph.
hyper_graph = self._meta_build(dataset)
// Process the args.
if callbacks is None:
callbacks = []
