`matchzoo.utils.parse`¶

Module Contents¶

matchzoo.utils.parse.activation¶

matchzoo.utils.parse.loss¶

matchzoo.utils.parse.optimizer¶

matchzoo.utils.parse._parse(identifier: typing.Union[str, typing.Type[nn.Module], nn.Module], dictionary: nn.ModuleDict, target: str) → nn.Module¶

Parse loss and activation.

Parameters:	identifier – activation identifier, one of - String: name of a activation - Torch Modele subclass - Torch Module instance (it will be returned unchanged). dictionary – nn.ModuleDict instance. Map string identifier to nn.Module instance.
Returns:	A `nn.Module` instance

matchzoo.utils.parse.parse_activation(identifier: typing.Union[str, typing.Type[nn.Module], nn.Module]) → nn.Module¶

Retrieves a torch Module instance.

Parameters:	identifier – activation identifier, one of - String: name of a activation - Torch Modele subclass - Torch Module instance (it will be returned unchanged).
Returns:	A `nn.Module` instance

Examples::

>>> from torch import nn
>>> from matchzoo.utils import parse_activation

Use str as activation:

>>> activation = parse_activation('relu')
>>> type(activation)
<class 'torch.nn.modules.activation.ReLU'>

Use torch.nn.Module subclasses as activation:

>>> type(parse_activation(nn.ReLU))
<class 'torch.nn.modules.activation.ReLU'>

Use torch.nn.Module instances as activation:

>>> type(parse_activation(nn.ReLU()))
<class 'torch.nn.modules.activation.ReLU'>

matchzoo.utils.parse.parse_loss(identifier: typing.Union[str, typing.Type[nn.Module], nn.Module], task: typing.Optional[str] = None) → nn.Module¶

Retrieves a torch Module instance.

Parameters:	identifier – loss identifier, one of - String: name of a loss - Torch Module subclass - Torch Module instance (it will be returned unchanged). task – Task type for determining specific loss.
Returns:	A `nn.Module` instance

Examples::

>>> from torch import nn
>>> from matchzoo.utils import parse_loss

Use str as loss:

>>> loss = parse_loss('mse')
>>> type(loss)
<class 'torch.nn.modules.loss.MSELoss'>

Use torch.nn.Module subclasses as loss:

>>> type(parse_loss(nn.MSELoss))
<class 'torch.nn.modules.loss.MSELoss'>

Use torch.nn.Module instances as loss:

>>> type(parse_loss(nn.MSELoss()))
<class 'torch.nn.modules.loss.MSELoss'>

matchzoo.utils.parse._parse_metric(metric: typing.Union[str, typing.Type[BaseMetric], BaseMetric], Metrix: typing.Type[BaseMetric]) → BaseMetric¶

Parse metric.

Parameters:	metrc – Input metric in any form. Metrix – Base Metric class. Either `matchzoo.engine.base_metric.RankingMetric` or `matchzoo.engine.base_metric.ClassificationMetric`.
Returns:	A `BaseMetric` instance

matchzoo.utils.parse.parse_metric(metric: typing.Union[str, typing.Type[BaseMetric], BaseMetric], task: str) → BaseMetric¶

Parse input metric in any form into a BaseMetric instance.

Parameters:	metric – Input metric in any form. task – Task type for determining specific metric.
Returns:	A `BaseMetric` instance

Examples::

>>> from matchzoo import metrics
>>> from matchzoo.utils import parse_metric

Use str as MatchZoo metrics:

>>> mz_metric = parse_metric('map', 'ranking')
>>> type(mz_metric)
<class 'matchzoo.metrics.mean_average_precision.MeanAveragePrecision'>

Use matchzoo.engine.BaseMetric subclasses as MatchZoo metrics:

>>> type(parse_metric(metrics.AveragePrecision, 'ranking'))
<class 'matchzoo.metrics.average_precision.AveragePrecision'>

Use matchzoo.engine.BaseMetric instances as MatchZoo metrics:

>>> type(parse_metric(metrics.AveragePrecision(), 'ranking'))
<class 'matchzoo.metrics.average_precision.AveragePrecision'>

matchzoo.utils.parse.parse_optimizer(identifier: typing.Union[str, typing.Type[optim.Optimizer]]) → optim.Optimizer¶

Parse input metric in any form into a Optimizer class.

Parameters:	optimizer – Input optimizer in any form.
Returns:	A `Optimizer` class

Examples::

>>> from torch import optim
>>> from matchzoo.utils import parse_optimizer

Use str as optimizer:

>>> parse_optimizer('adam')
<class 'torch.optim.adam.Adam'>

Use torch.optim.Optimizer subclasses as optimizer:

>>> parse_optimizer(optim.Adam)
<class 'torch.optim.adam.Adam'>

matchzoo.utils.parse¶

Module Contents¶

`matchzoo.utils.parse`¶