def test_save_load(deepspeech: DeepSpeech, config: Configuration, config_path: str, alphabet_path: str, model_dir: str): weights_path = os.path.join(model_dir, 'weights.hdf5') model_weights = deepspeech.model.get_weights() deepspeech.save(weights_path) new_deepspeech = DeepSpeech.construct(config_path, alphabet_path) new_deepspeech.model = deepspeech.get_model(**config.model, is_gpu=False, random_state=123) new_model_weights = new_deepspeech.model.get_weights() assert not is_same(model_weights, new_model_weights) new_deepspeech.load(weights_path) new_model_weights = new_deepspeech.model.get_weights() assert is_same(model_weights, new_model_weights)
def test_compile_model(config: Configuration): model = DeepSpeech.get_model(**config.model, is_gpu=False) optimizer = DeepSpeech.get_optimizer(**config.optimizer) loss = DeepSpeech.get_loss() compiled_model = DeepSpeech.compile_model(model, optimizer, loss, gpus=[]) assert compiled_model._is_compiled
def test_get_decoder(config: Configuration, alphabet: Alphabet): model = DeepSpeech.get_model(**config.model, is_gpu=False) decoder = DeepSpeech.get_decoder(alphabet=alphabet, model=model, **config.decoder) assert callable(decoder)
def test_get_model(config: Configuration): model = DeepSpeech.get_model(**config.model, is_gpu=False) assert type(model) == Model new_model = DeepSpeech.get_model(**config.model, is_gpu=False) assert is_same(model.get_weights(), new_model.get_weights()) # Test random seed