#!/usr/bin/env python
# ******************************************************************************
# Copyright 2022 Brainchip Holdings Ltd.
#
# 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
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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"""
Recording utilities.
"""
__all__ = ["record_quantization_variables"]
import tensorflow as tf
from ..layers import recording
from .random import generate_keras_random_samples
[docs]
def record_quantization_variables(model):
"""Helper method to record quantization objects in the graph.
Passing a dummy sample through the model in recording mode, this triggers the
recording of all dynamic quantization objects.
Args:
model (keras.Model): model for which objects need to be recorded.
"""
with recording(True):
# Build a tf.function to run in graph mode
model_func = tf.function(model)
# Create sample and pass it through the model to calibrate variables
batch_size = model.input.shape[0] or 1
sample = generate_keras_random_samples(model, batch_size)
model_func(sample)