# Copyright 2022 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 SimCLR config.""" from absl.testing import parameterized import tensorflow as tf from official.core import config_definitions as cfg from official.core import exp_factory from official.projects.simclr.common import registry_imports # pylint: disable=unused-import from official.projects.simclr.configs import simclr as exp_cfg class SimCLRConfigTest(tf.test.TestCase, parameterized.TestCase): @parameterized.parameters( 'simclr_pretraining_imagenet', 'simclr_finetuning_imagenet') def test_simclr_configs(self, config_name): config = exp_factory.get_exp_config(config_name) self.assertIsInstance(config, cfg.ExperimentConfig) if config_name == 'simclr_pretrain_imagenet': self.assertIsInstance(config.task, exp_cfg.SimCLRPretrainTask) elif config_name == 'simclr_finetuning_imagenet': self.assertIsInstance(config.task, exp_cfg.SimCLRFinetuneTask) self.assertIsInstance(config.task.model, exp_cfg.SimCLRModel) self.assertIsInstance(config.task.train_data, exp_cfg.DataConfig) config.task.train_data.is_training = None with self.assertRaises(KeyError): config.validate() if __name__ == '__main__': tf.test.main()