def __init__(self, num_classes: Optional[int] = None, multi_label: bool = False, loss: types.LossType = None, metrics: Optional[types.MetricsType] = None, project_name: str = 'image_classifier', max_trials: int = 100, directory: Union[str, Path, None] = None, objective: str = 'val_loss', overwrite: bool = True, seed: Optional[int] = None, **kwargs): super().__init__(outputs=hypermodels.ClassificationHead( num_classes=num_classes, multi_label=multi_label, loss=loss, metrics=metrics), max_trials=max_trials, directory=directory, project_name=project_name, objective=objective, tuner=task_specific.ImageClassifierTuner, overwrite=overwrite, seed=seed, **kwargs)
def __init__(self, column_names=None, column_types=None, num_classes=None, multi_label=False, loss=None, metrics=None, name='structured_data_classifier', max_trials=100, directory=None, objective='val_accuracy', overwrite=True, seed=None): super().__init__(outputs=hypermodels.ClassificationHead( num_classes=num_classes, multi_label=multi_label, loss=loss, metrics=metrics), column_names=column_names, column_types=column_types, max_trials=max_trials, directory=directory, name=name, objective=objective, tuner=greedy.Greedy, overwrite=overwrite, seed=seed)
def __init__(self, num_classes=None, multi_label=False, loss=None, metrics=None, name='text_classifier', max_trials=100, directory=None, objective='val_loss', overwrite=True, seed=None): super().__init__( outputs=hypermodels.ClassificationHead(num_classes=num_classes, multi_label=multi_label, loss=loss, metrics=metrics), max_trials=max_trials, directory=directory, name=name, objective=objective, tuner=greedy.Greedy, overwrite=overwrite, seed=seed)
def __init__(self, num_classes: Optional[int] = None, multi_label: bool = False, loss: utils.AcceptableLoss = None, metrics: utils.AcceptableMetrics = None, name: str = 'text_classifier', max_trials: int = 100, directory: Union[str, pathlib.Path, None] = None, objective: str = 'val_loss', overwrite: bool = True, seed: Optional[int] = None): super().__init__(outputs=hypermodels.ClassificationHead( num_classes=num_classes, multi_label=multi_label, loss=loss, metrics=metrics), max_trials=max_trials, directory=directory, name=name, objective=objective, tuner=task_specific.TextClassifierTuner, overwrite=overwrite, seed=seed)
def __init__(self, num_classes: Optional[int] = None, multi_label: bool = False, loss: Union[str, Callable, None] = None, metrics: Optional[List[Union[str, Callable]]] = None, name: str = 'image_classifier', max_trials: int = 100, directory: Optional[str] = None, objective: str = 'val_loss', overwrite: bool = True, seed: Optional[int] = None): super().__init__(outputs=hypermodels.ClassificationHead( num_classes=num_classes, multi_label=multi_label, loss=loss, metrics=metrics), max_trials=max_trials, directory=directory, name=name, objective=objective, tuner=task_specific.ImageClassifierTuner, overwrite=overwrite, seed=seed)