tf.keras.Quantizer

tf.keras.Quantizer(
    output_dtype='int8'
)

Methods

from_config

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@classmethod
from_config(
    config
)

Creates a quantizer from its config.

This method is the reverse of get_config, capable of instantiating the same quantizer from the config dictionary.

This method is used by Keras model_to_estimator, saving and loading models to HDF5 formats, Keras model cloning, some visualization utilities, and exporting models to and from JSON.

get_config

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get_config()

Returns the config of the quantizer.

An quantizer config is a Python dictionary (serializable) containing all configuration parameters of the quantizer. The same quantizer can be reinstantiated later (without any saved state) from this configuration.

This method is optional if you are just training and executing models, exporting to and from SavedModels, or using weight checkpoints.

This method is required for Keras model_to_estimator, saving and loading models to HDF5 formats, Keras model cloning, some visualization utilities, and exporting models to and from JSON.

__call__

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__call__(
    x
)

Compute a quantized output from an input tensor.