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# Lint as: python2, python3
# Copyright 2019 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.
# ==============================================================================
"""Test for Utility functions."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from six.moves import range
import tensorflow.compat.v1 as tf
from object_detection.tpu_exporters import utils
class UtilsTest(tf.test.TestCase):
def testBfloat16ToFloat32(self):
bfloat16_tensor = tf.random.uniform([2, 3], dtype=tf.bfloat16)
float32_tensor = utils.bfloat16_to_float32(bfloat16_tensor)
self.assertEqual(float32_tensor.dtype, tf.float32)
def testOtherDtypesNotConverted(self):
int32_tensor = tf.ones([2, 3], dtype=tf.int32)
converted_tensor = utils.bfloat16_to_float32(int32_tensor)
self.assertEqual(converted_tensor.dtype, tf.int32)
def testBfloat16ToFloat32Nested(self):
tensor_dict = {
'key1': tf.random.uniform([2, 3], dtype=tf.bfloat16),
'key2': [
tf.random.uniform([1, 2], dtype=tf.bfloat16) for _ in range(3)
],
'key3': tf.ones([2, 3], dtype=tf.int32),
}
tensor_dict = utils.bfloat16_to_float32_nested(tensor_dict)
self.assertEqual(tensor_dict['key1'].dtype, tf.float32)
for t in tensor_dict['key2']:
self.assertEqual(t.dtype, tf.float32)
self.assertEqual(tensor_dict['key3'].dtype, tf.int32)
if __name__ == '__main__':
tf.test.main()
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