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