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official/projects/pruning/configs/image_classification_test.py
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A. Unique TensorFlower
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09 фев 2026, 19:00
09 фев 2026, 19:00
799b0af
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# Copyright 2026 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 image_classification.""" # pylint: disable=unused-import from absl.testing import parameterized import tensorflow as tf, tf_keras from official import vision from official.core import config_definitions as cfg from official.core import exp_factory from official.projects.pruning.configs import image_classification as pruning_exp_cfg from official.vision.configs import image_classification as exp_cfg class ImageClassificationConfigTest(tf.test.TestCase, parameterized.TestCase): @parameterized.parameters( ('resnet_imagenet_pruning',), ('mobilenet_imagenet_pruning'), ) def test_image_classification_configs(self, config_name): config = exp_factory.get_exp_config(config_name) self.assertIsInstance(config, cfg.ExperimentConfig) self.assertIsInstance(config.task, exp_cfg.ImageClassificationTask) self.assertIsInstance(config.task, pruning_exp_cfg.ImageClassificationTask) self.assertIsInstance(config.task.pruning, pruning_exp_cfg.PruningConfig) self.assertIsInstance(config.task.model, exp_cfg.ImageClassificationModel) self.assertIsInstance(config.task.train_data, exp_cfg.DataConfig) config.validate() config.task.train_data.is_training = None with self.assertRaises(KeyError): config.validate() if __name__ == '__main__': tf.test.main()