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chore: import upstream snapshot with attribution
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Python

# Copyright 2020 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 test_util.py."""
from tensorflow.lite.python import test_util as tflite_test_util
from tensorflow.python.framework import test_util
from tensorflow.python.platform import gfile
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import test
class TestUtilTest(test_util.TensorFlowTestCase):
def testBuiltinOp(self):
model_path = resource_loader.get_path_to_datafile('../testdata/add.bin')
op_set = tflite_test_util.get_ops_list(gfile.GFile(model_path, 'rb').read())
self.assertCountEqual(op_set, ['ADD'])
def testFlexOp(self):
model_path = resource_loader.get_path_to_datafile(
'../testdata/softplus_flex.bin')
op_set = tflite_test_util.get_ops_list(gfile.GFile(model_path, 'rb').read())
self.assertCountEqual(op_set, ['FlexSoftplus'])
if __name__ == '__main__':
test.main()