SingleSWD

Inheritance Diagram

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class ashpy.metrics.sliced_wasserstein_metric.SingleSWD(model_selection_operator=<built-in function lt>, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.1.3/docs/source/log', level_of_pyramid=0, real_or_fake='fake')

Bases: ashpy.metrics.metric.Metric

SlicedWassersteinDistance for a certain level of the pyramid.

Methods

__init__([model_selection_operator, logdir, …])	Initialize the Metric.
update_state(context, score)	Update the internal state of the metric, using the information from the context object.

Attributes

best_folder	Retrieve the folder used to save the best model when doing model selection.
best_model_sel_file	Retrieve the path to JSON file containing the measured performance of the best model.
logdir	Retrieve the log directory.
metric	Retrieve the tf.keras.metrics.Metric object.
model_selection_operator	Retrieve the operator used for model selection.
name	Retrieve the metric name.

__init__(model_selection_operator=<built-in function lt>, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.1.3/docs/source/log', level_of_pyramid=0, real_or_fake='fake')

Initialize the Metric.

Parameters

• model_selection_operator (typing.Callable) –

  The operation that will be used when model_selection is triggered to compare the metrics, used by the update_state. Any typing.Callable behaving like an operator is accepted.

  Note

  Model selection is done ONLY if an operator is specified here.

• logdir (str) – Path to the log dir, defaults to a log folder in the current directory.

• level_of_pyramid (int) – Level of the pyramid related to this metric

• real_or_fake (str) – string identifying this metric (real or fake distance)

Return type

None

update_state(context, score)

Update the internal state of the metric, using the information from the context object.

Parameters

context (ashpy.contexts.GANContext) – An AshPy Context Object that carries all the information the Metric needs.

Return type

None