sliced_wasserstein_metric¶
Sliced Wasserstein Distance metric.
Classes
SlicedWassersteinDistance for a certain level of the pyramid. |
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Sliced Wasserstein Distance. |
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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')[source]¶ Bases:
ashpy.metrics.metric.Metric
SlicedWassersteinDistance for a certain level of the pyramid.
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__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')[source]¶ 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 anoperator
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
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-
class
ashpy.metrics.sliced_wasserstein_metric.
SlicedWassersteinDistance
(model_selection_operator=<built-in function lt>, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.1.3/docs/source/log', resolution=128, resolution_min=16, patches_per_image=64, patch_size=7, random_sampling_count=1, random_projection_dim=147, use_svd=False)[source]¶ Bases:
ashpy.metrics.metric.Metric
Sliced Wasserstein Distance. Used as metric in Progressive Growing of GANs 1.
- 1
Progressive Growing of GANs https://arxiv.org/abs/1710.10196
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__init__
(model_selection_operator=<built-in function lt>, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.1.3/docs/source/log', resolution=128, resolution_min=16, patches_per_image=64, patch_size=7, random_sampling_count=1, random_projection_dim=147, use_svd=False)[source]¶ 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 anoperator
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.
resolution (int) – Image Resolution, defaults to 128
resolution_min (int) – Min Resolution achieved by the metric
patches_per_image (int) – Number of patches to extract per image per Laplacian level.
patch_size (int) – Width of a square patch.
random_sampling_count (int) – Number of random projections to average.
random_projection_dim (int) – Dimension of the random projection space.
use_svd (bool) – experimental method to compute a more accurate distance.
- Return type
None
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model_selection
(checkpoint, global_step)[source]¶ Perform model selection for each sub-metric
- Return type
None