official/projects/qat/nlp/quantization/helper.py
# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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"""Quantization helpers."""
import tensorflow_model_optimization as tfmot
class LayerQuantizerHelper(object):
"""Helper class that handles quantizers."""
def __init__(self, *args, **kwargs):
self._quantizers = {}
self._quantizer_vars = {}
super().__init__(*args, **kwargs)
def _all_value_quantizer(self):
return tfmot.quantization.keras.quantizers.AllValuesQuantizer(
num_bits=8, per_axis=False, symmetric=False, narrow_range=False)
def _moving_average_quantizer(self):
return tfmot.quantization.keras.quantizers.MovingAverageQuantizer(
num_bits=8, per_axis=False, symmetric=False, narrow_range=False)
def _add_quantizer(self, name, all_value_quantizer=False):
if all_value_quantizer:
self._quantizers[name] = self._all_value_quantizer()
else:
self._quantizers[name] = self._moving_average_quantizer()
def _apply_quantizer(self, name, inputs, training, **kwargs):
return self._quantizers[name](
inputs, training, self._quantizer_vars[name], **kwargs)
def _build_quantizer_vars(self):
for name in self._quantizers:
self._quantizer_vars[name] = self._quantizers[name].build(
tensor_shape=None, name=name, layer=self)