tfmot.clustering.keras.strip_clustering  |  TensorFlow Model Optimization (original) (raw)

tfmot.clustering.keras.strip_clustering

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Strips clustering wrappers from the model.

tfmot.clustering.keras.strip_clustering(
    model
)

Used in the notebooks

Used in the guide
Weight clustering in Keras example Cluster preserving quantization aware training (CQAT) Keras example Sparsity and cluster preserving quantization aware training (PCQAT) Keras example Sparsity preserving clustering Keras example

Once a model has been clustered, this method can be used to restore the original model with the clustered weights.

Only sequential and functional models are supported for now.

Arguments
model A tf.keras.Model instance with clustered layers.
Returns
A keras model with clustering wrappers removed.
Raises
ValueError if the model is not a tf.keras.Model instance.
NotImplementedError if the model is a subclass model.

Usage:

orig_model = tf.keras.Model(inputs, outputs)
clustered_model = cluster_weights(orig_model)
exported_model = strip_clustering(clustered_model)

The exported_model and the orig_model have the same structure.

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Last updated 2023-05-26 UTC.