# Copyright 2023 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 official.nlp.configs.encoders.""" import os import tensorflow as tf, tf_keras from official.modeling import hyperparams from official.nlp.configs import encoders from official.nlp.modeling import networks from official.projects.teams import teams class EncodersTest(tf.test.TestCase): def test_encoder_from_yaml(self): config = encoders.EncoderConfig( type="bert", bert=encoders.BertEncoderConfig(num_layers=1)) encoder = encoders.build_encoder(config) ckpt = tf.train.Checkpoint(encoder=encoder) ckpt_path = ckpt.save(self.get_temp_dir() + "/ckpt") params_save_path = os.path.join(self.get_temp_dir(), "params.yaml") hyperparams.save_params_dict_to_yaml(config, params_save_path) retored_cfg = encoders.EncoderConfig.from_yaml(params_save_path) retored_encoder = encoders.build_encoder(retored_cfg) status = tf.train.Checkpoint(encoder=retored_encoder).restore(ckpt_path) status.assert_consumed() def test_build_teams(self): config = encoders.EncoderConfig( type="any", any=teams.TeamsEncoderConfig(num_layers=1)) encoder = encoders.build_encoder(config) self.assertIsInstance(encoder, networks.EncoderScaffold) self.assertIsInstance(encoder.embedding_network, networks.PackedSequenceEmbedding) if __name__ == "__main__": tf.test.main()