Module: tfmot.sparsity.keras
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Module containing sparsity code built on Keras abstractions.
Classes
class ConstantSparsity
: Pruning schedule with constant sparsity(%) throughout training.
class PolynomialDecay
: Pruning Schedule with a PolynomialDecay function.
class PrunableLayer
: Abstract Base Class for making your own keras layer prunable.
class PruneForLatencyOnXNNPack
: Specifies to prune only 1x1 Conv2D layers in the model.
class PruningPolicy
: Specifies what layers to prune in the model.
class PruningSchedule
: Specifies when to prune layer and the sparsity(%) at each training step.
class PruningSummaries
: A Keras callback for adding pruning summaries to tensorboard.
class UpdatePruningStep
: Keras callback which updates pruning wrappers with the optimizer step.
Functions
prune_low_magnitude(...)
: Modify a tf.keras layer or model to be pruned during training.
prune_scope(...)
: Provides a scope in which Pruned layers and models can be deserialized.
strip_pruning(...)
: Strip pruning wrappers from the model.
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Last updated 2023-05-26 UTC.
[null,null,["Last updated 2023-05-26 UTC."],[],[],null,["# Module: tfmot.sparsity.keras\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/model-optimization/blob/v0.7.5/tensorflow_model_optimization/python/core/api/sparsity/keras/__init__.py) |\n\nModule containing sparsity code built on Keras abstractions.\n\nClasses\n-------\n\n[`class ConstantSparsity`](../../tfmot/sparsity/keras/ConstantSparsity): Pruning schedule with constant sparsity(%) throughout training.\n\n[`class PolynomialDecay`](../../tfmot/sparsity/keras/PolynomialDecay): Pruning Schedule with a PolynomialDecay function.\n\n[`class PrunableLayer`](../../tfmot/sparsity/keras/PrunableLayer): Abstract Base Class for making your own keras layer prunable.\n\n[`class PruneForLatencyOnXNNPack`](../../tfmot/sparsity/keras/PruneForLatencyOnXNNPack): Specifies to prune only 1x1 Conv2D layers in the model.\n\n[`class PruningPolicy`](../../tfmot/sparsity/keras/PruningPolicy): Specifies what layers to prune in the model.\n\n[`class PruningSchedule`](../../tfmot/sparsity/keras/PruningSchedule): Specifies when to prune layer and the sparsity(%) at each training step.\n\n[`class PruningSummaries`](../../tfmot/sparsity/keras/PruningSummaries): A Keras callback for adding pruning summaries to tensorboard.\n\n[`class UpdatePruningStep`](../../tfmot/sparsity/keras/UpdatePruningStep): Keras callback which updates pruning wrappers with the optimizer step.\n\nFunctions\n---------\n\n[`prune_low_magnitude(...)`](../../tfmot/sparsity/keras/prune_low_magnitude): Modify a tf.keras layer or model to be pruned during training.\n\n[`prune_scope(...)`](../../tfmot/sparsity/keras/prune_scope): Provides a scope in which Pruned layers and models can be deserialized.\n\n[`strip_pruning(...)`](../../tfmot/sparsity/keras/strip_pruning): Strip pruning wrappers from the model."]]