`matchzoo.datasets.toy`¶

Package Contents¶

class matchzoo.datasets.toy.BaseTask(losses=None, metrics=None)¶

Bases: abc.ABC

Base Task, shouldn’t be used directly.

TYPE = base¶

losses¶

Losses used in the task.

Type:	return

metrics¶

Metrics used in the task.

Type:	return

output_shape :tuple¶

output shape of a single sample of the task.

Type:	return

output_dtype¶

output data type for specific task.

Type:	return

_convert(self, identifiers, parse)¶

_assure_losses(self)¶

_assure_metrics(self)¶

classmethod list_available_losses(cls)¶

Returns:	a list of available losses.

classmethod list_available_metrics(cls)¶

Returns:	a list of available metrics.

matchzoo.datasets.toy.load_data(stage: str = 'train', task: typing.Union[str, BaseTask] = 'ranking', return_classes: bool = False) → typing.Union[matchzoo.DataPack, typing.Tuple[matchzoo.DataPack, list]]¶

Load toy data.

Parameters:	stage – One of train, dev, and test. task – Could be one of ranking, classification or a `matchzoo.engine.BaseTask` instance. return_classes – True to return classes for classification task, False otherwise.
Returns:	A DataPack unless task is classificiation and return_classes is True: a tuple of (DataPack, classes) in that case.

Example

>>> import matchzoo as mz
>>> stages = 'train', 'dev', 'test'
>>> tasks = 'ranking', 'classification'
>>> for stage in stages:
...     for task in tasks:
...         _ = mz.datasets.toy.load_data(stage, task)

matchzoo.datasets.toy.load_embedding()¶

matchzoo.datasets.toy¶

Package Contents¶

`matchzoo.datasets.toy`¶