tfmot.sparsity.keras.ConstantSparsity

Pruning schedule with constant sparsity(%) throughout training.

tfmot.sparsity.keras.ConstantSparsity(
    target_sparsity, begin_step, end_step=-1, frequency=100
)

Used in the guide
Sparsity and cluster preserving quantization aware training (PCQAT) Keras example Pruning preserving quantization aware training (PQAT) Keras example Sparsity preserving clustering Keras example Sparse weights using structural pruning

Args
`target_sparsity`	A scalar float representing the target sparsity value.
`begin_step`	Step at which to begin pruning.
`end_step`	Step at which to end pruning. `-1` by default. `-1` implies continuing to prune till the end of training.
`frequency`	Only apply pruning every `frequency` steps.

Methods

@classmethod
from_config(
    config
)

Instantiates a PruningSchedule from its config.

Args
`config`	Output of `get_config()`.

Returns
A `PruningSchedule` instance.

get_config()

__call__(
    step
)

Returns the sparsity(%) to be applied.

If the returned sparsity(%) is 0, pruning is ignored for the step.

Args
`step`	Current step in graph execution.

Returns
Sparsity (%) that should be applied to the weights for the step.