mirror of https://github.com/tensorflow/models.git
55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
# Copyright 2025 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
|
|
#
|
|
# 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
|
|
# limitations under the License.
|
|
|
|
"""Tests for helper."""
|
|
import numpy as np
|
|
import tensorflow as tf, tf_keras
|
|
|
|
import tensorflow_model_optimization as tfmot
|
|
from official.projects.qat.vision.quantization import helper
|
|
|
|
|
|
class HelperTest(tf.test.TestCase):
|
|
|
|
def create_simple_model(self):
|
|
return tf_keras.models.Sequential([
|
|
tf_keras.layers.Dense(8, input_shape=(16,)),
|
|
])
|
|
|
|
def test_copy_original_weights_for_simple_model_with_custom_weights(self):
|
|
one_model = self.create_simple_model()
|
|
one_weights = [np.ones_like(weight) for weight in one_model.get_weights()]
|
|
one_model.set_weights(one_weights)
|
|
|
|
qat_model = tfmot.quantization.keras.quantize_model(
|
|
self.create_simple_model())
|
|
zero_weights = [np.zeros_like(weight) for weight in qat_model.get_weights()]
|
|
qat_model.set_weights(zero_weights)
|
|
|
|
helper.copy_original_weights(one_model, qat_model)
|
|
|
|
qat_model_weights = qat_model.get_weights()
|
|
count = 0
|
|
for idx, weight in enumerate(qat_model.weights):
|
|
if not helper.is_quantization_weight_name(weight.name):
|
|
self.assertAllEqual(
|
|
qat_model_weights[idx], np.ones_like(qat_model_weights[idx]))
|
|
count += 1
|
|
self.assertLen(one_model.weights, count)
|
|
self.assertGreater(len(qat_model.weights), len(one_model.weights))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
tf.test.main()
|