def __init__(self,
json_decoder: JSONDataBodyDecoder,
wrapped: BaseStep,
json_encoder: JSONDataResponseEncoder,
route='/'):
Pipeline.__init__(self, [json_decoder, wrapped, json_encoder])
self.route: str = route
def __init__(
self,
pipeline: Union[BaseStep, NamedTupleList],
validation_size: float = 0.0,
batch_size: int = None,
batch_metrics: Dict[str, Callable] = None,
shuffle_in_each_epoch_at_train: bool = True,
seed: int = None,
n_epochs: int = 1,
epochs_metrics: Dict[str, Callable] = None,
scoring_function: Callable = None,
metrics_plotting_step: BaseStep = None,
cache_folder: str = None,
print_epoch_metrics=False,
print_batch_metrics=False
):
if epochs_metrics is None:
epochs_metrics = {}
if batch_metrics is None:
batch_metrics = {}
self.final_scoring_metric = scoring_function
self.epochs_metrics = epochs_metrics
self.n_epochs = n_epochs
self.shuffle_in_each_epoch_at_train = shuffle_in_each_epoch_at_train
self.batch_size = batch_size
self.batch_metrics = batch_metrics
self.validation_size = validation_size
self.metrics_plotting_step = metrics_plotting_step
self.print_batch_metrics = print_batch_metrics
self.print_epoch_metrics = print_epoch_metrics
wrapped = pipeline
wrapped = self._create_mini_batch_pipeline(wrapped)
if shuffle_in_each_epoch_at_train:
wrapped = TrainShuffled(wrapped=wrapped, seed=seed)
wrapped = self._create_validation_split(wrapped)
wrapped = self._create_epoch_repeater(wrapped)
BaseStep.__init__(self)
Pipeline.__init__(self, [wrapped], cache_folder=cache_folder)
def __init__(self, steps: NamedTupleList):
Pipeline.__init__(self, steps)
self.teared_down = False
def __init__(self, wrapped, seed=None):
Pipeline.__init__(self,
[TrainOnlyWrapper(DataShuffler(seed=seed)), wrapped])
