def test_train_align_nnet(basic_corpus_dir, large_prosodylab_format_directory,
sick_dict_path, generated_dir,
large_dataset_dictionary):
args = DummyArgs()
args.artificial_neural_net = True
args.debug = True
args.output_model_path = None
args.corpus_directory = basic_corpus_dir
args.dictionary_path = large_dataset_dictionary
args.output_directory = os.path.join(generated_dir,
'nnet_basic_output_selftrained')
train_and_align_corpus(args)
def test_align_single_speaker_prosodylab(
single_speaker_prosodylab_format_directory, large_dataset_dictionary,
prosodylab_output_directory, prosodylab_output_model_path):
corpus_dir = single_speaker_prosodylab_format_directory
dict_path = large_dataset_dictionary
output_directory = prosodylab_output_directory
output_model_path = prosodylab_output_model_path
args = DummyArgs()
args.num_jobs = 2
args.fast = True
train_and_align_corpus(corpus_dir, dict_path, output_directory, '',
output_model_path, args)
def test_nnet_export_model(large_prosodylab_format_directory, config_directory,
generated_dir, large_dataset_dictionary, temp_dir):
args = DummyArgs()
args.debug = True
args.clean = True
args.config_path = os.path.join(config_directory, 'long_nnet_train.yaml')
args.output_model_path = os.path.join(generated_dir, 'nnet_test_model.zip')
args.corpus_directory = large_prosodylab_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = os.path.join(
generated_dir, 'nnet_basic_output_selftrained_outputting_model3')
args.temp_directory = temp_dir
train_and_align_corpus(args)
def test_train_single_speaker_prosodylab(
single_speaker_prosodylab_format_directory, large_dataset_dictionary,
prosodylab_output_directory, prosodylab_output_model_path):
args = DummyArgs()
args.num_jobs = 2
args.fast = True
args.corpus_directory = single_speaker_prosodylab_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = prosodylab_output_directory
args.output_model_path = prosodylab_output_model_path
train_and_align_corpus(args, skip_input=True)
# assert_export_exist(single_speaker_prosodylab_format_directory, prosodylab_output_directory)
assert (os.path.exists(args.output_model_path))
def test_train_large_textgrid(large_textgrid_format_directory,
large_dataset_dictionary,
textgrid_output_directory,
textgrid_output_model_path):
args = DummyArgs()
args.num_jobs = 2
args.fast = True
args.corpus_directory = large_textgrid_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = textgrid_output_directory
args.output_model_path = textgrid_output_model_path
train_and_align_corpus(args, skip_input=True)
# assert_export_exist(large_textgrid_format_directory, textgrid_output_directory)
assert (os.path.exists(args.output_model_path))
def test_train_large_textgrid(large_textgrid_format_directory,
large_dataset_dictionary,
textgrid_output_directory,
textgrid_output_model_path):
corpus_dir = large_textgrid_format_directory
dict_path = large_dataset_dictionary
output_directory = textgrid_output_directory
output_model_path = textgrid_output_model_path
args = DummyArgs()
args.num_jobs = 2
args.fast = True
train_and_align_corpus(corpus_dir, dict_path, output_directory, '',
output_model_path, args)
#assert_export_exist(large_textgrid_format_directory, textgrid_output_directory)
assert (os.path.exists(output_model_path))
def test_train_single_speaker_prosodylab(
single_speaker_prosodylab_format_directory, large_dataset_dictionary,
prosodylab_output_directory, prosodylab_output_model_path, temp_dir,
basic_train_config):
args = DummyArgs()
args.num_jobs = 2
args.clean = True
args.temp_directory = temp_dir
args.corpus_directory = single_speaker_prosodylab_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = prosodylab_output_directory
args.output_model_path = prosodylab_output_model_path
args.config_path = basic_train_config
train_and_align_corpus(args)
# assert_export_exist(single_speaker_prosodylab_format_directory, prosodylab_output_directory)
assert (os.path.exists(args.output_model_path))
def test_train_large_textgrid(large_textgrid_format_directory,
large_dataset_dictionary,
textgrid_output_directory,
textgrid_output_model_path, temp_dir,
basic_train_config):
args = DummyArgs()
args.num_jobs = 2
args.clean = True
args.corpus_directory = large_textgrid_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = textgrid_output_directory
args.output_model_path = textgrid_output_model_path
args.temp_directory = temp_dir
args.config_path = basic_train_config
train_and_align_corpus(args)
# assert_export_exist(large_textgrid_format_directory, textgrid_output_directory)
assert (os.path.exists(args.output_model_path))
def test_train_large_prosodylab(large_prosodylab_format_directory,
large_dataset_dictionary,
prosodylab_output_directory,
prosodylab_output_model_path, temp_dir):
args = DummyArgs()
args.num_jobs = 2
args.fast = True
args.corpus_directory = large_prosodylab_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = prosodylab_output_directory
args.output_model_path = prosodylab_output_model_path
args.temp_directory = temp_dir
train_and_align_corpus(args, skip_input=True)
# assert_export_exist(large_prosodylab_format_directory, prosodylab_output_directory)
assert (os.path.exists(args.output_model_path))
args.clean = False
train_and_align_corpus(args, skip_input=True)
def test_train_large_prosodylab(large_prosodylab_format_directory,
large_dataset_dictionary,
prosodylab_output_directory,
prosodylab_output_model_path, temp_dir,
basic_train_config, skip_large):
if skip_large:
pytest.skip('Large testsets disabled')
args = DummyArgs()
args.num_jobs = 2
args.clean = True
args.corpus_directory = large_prosodylab_format_directory
args.dictionary_path = large_dataset_dictionary
args.output_directory = prosodylab_output_directory
args.output_model_path = prosodylab_output_model_path
args.temp_directory = temp_dir
args.config_path = basic_train_config
train_and_align_corpus(args)
# assert_export_exist(large_prosodylab_format_directory, prosodylab_output_directory)
assert (os.path.exists(args.output_model_path))
train_and_align_corpus(args)
