77from trainer .io import get_user_data_dir
88
99from tests import get_tests_data_path , run_cli
10+ from TTS .api import TTS
1011from TTS .tts .utils .languages import LanguageManager
1112from TTS .tts .utils .speakers import SpeakerManager
1213from TTS .utils .manage import ModelManager
@@ -29,55 +30,61 @@ def run_around_tests(tmp_path):
2930 shutil .rmtree (tmp_path )
3031
3132
32- def run_models (tmp_path , offset = 0 , step = 1 ):
33- """Check if all the models are downloadable and tts models run correctly."""
34- print (" > Run synthesizer with all the models." )
33+ @pytest .fixture
34+ def manager (tmp_path ):
35+ """Set up model manager."""
36+ return ModelManager (output_prefix = tmp_path , progress_bar = False )
37+
38+
39+ # To split tests into different CI jobs
40+ num_partitions = int (os .getenv ("NUM_PARTITIONS" , "1" ))
41+ partition = int (os .getenv ("TEST_PARTITION" , "0" ))
42+ model_names = [name for name in TTS .list_models () if name not in MODELS_WITH_SEP_TESTS ]
43+ model_names = [name for i , name in enumerate (model_names ) if i % num_partitions == partition ]
44+
45+
46+ @pytest .mark .parametrize ("model_name" , model_names )
47+ def test_models (tmp_path , model_name , manager ):
48+ print (f"\n > Run - { model_name } )
3549 output_path = tmp_path / "output.wav"
36- manager = ModelManager (output_prefix = tmp_path , progress_bar = False )
37- model_names = [name for name in manager .list_models () if name not in MODELS_WITH_SEP_TESTS ]
38- print ("Model names:" , model_names )
39- for model_name in model_names [offset ::step ]:
40- print (f"\n > Run - { model_name } )
41- model_path , _ , _ = manager .download_model (model_name )
42- if "tts_models" in model_name :
43- local_download_dir = model_path .parent
44- # download and run the model
45- speaker_files = list (local_download_dir .glob ("speaker*" ))
46- language_files = list (local_download_dir .glob ("language*" ))
47- speaker_arg = ""
48- language_arg = ""
49- if len (speaker_files ) > 0 :
50- # multi-speaker model
51- if "speaker_ids" in speaker_files [0 ].stem :
52- speaker_manager = SpeakerManager (speaker_id_file_path = speaker_files [0 ])
53- elif "speakers" in speaker_files [0 ].stem :
54- speaker_manager = SpeakerManager (d_vectors_file_path = speaker_files [0 ])
55- speakers = list (speaker_manager .name_to_id .keys ())
56- if len (speakers ) > 1 :
57- speaker_arg = f'--speaker_idx "{ speakers [0 ]}
58- if len (language_files ) > 0 and "language_ids" in language_files [0 ].stem :
59- # multi-lingual model
60- language_manager = LanguageManager (language_ids_file_path = language_files [0 ])
61- languages = language_manager .language_names
62- if len (languages ) > 1 :
63- language_arg = f'--language_idx "{ languages [0 ]}
64- run_cli (
65- f'tts --model_name { model_name }
66- f'--out_path "{ output_path } { speaker_arg } { language_arg }
67- )
68- elif "voice_conversion_models" in model_name :
69- speaker_wav = os .path .join (get_tests_data_path (), "ljspeech" , "wavs" , "LJ001-0001.wav" )
70- reference_wav = os .path .join (get_tests_data_path (), "ljspeech" , "wavs" , "LJ001-0032.wav" )
71- run_cli (
72- f"tts --model_name { model_name }
73- f'--out_path "{ output_path } { speaker_wav } { reference_wav }
74- )
75- else :
76- # only download the model
77- manager .download_model (model_name )
78- # remove downloaded models
79- shutil .rmtree (get_user_data_dir ("tts" ))
80- print (f" | > OK: { model_name } )
50+ model_path , _ , _ = manager .download_model (model_name )
51+ if "tts_models" in model_name :
52+ local_download_dir = model_path .parent
53+ # download and run the model
54+ speaker_files = list (local_download_dir .glob ("speaker*" ))
55+ language_files = list (local_download_dir .glob ("language*" ))
56+ speaker_arg = ""
57+ language_arg = ""
58+ if len (speaker_files ) > 0 :
59+ # multi-speaker model
60+ if "speaker_ids" in speaker_files [0 ].stem :
61+ speaker_manager = SpeakerManager (speaker_id_file_path = speaker_files [0 ])
62+ elif "speakers" in speaker_files [0 ].stem :
63+ speaker_manager = SpeakerManager (d_vectors_file_path = speaker_files [0 ])
64+ speakers = list (speaker_manager .name_to_id .keys ())
65+ if len (speakers ) > 1 :
66+ speaker_arg = f'--speaker_idx "{ speakers [0 ]}
67+ if len (language_files ) > 0 and "language_ids" in language_files [0 ].stem :
68+ # multi-lingual model
69+ language_manager = LanguageManager (language_ids_file_path = language_files [0 ])
70+ languages = language_manager .language_names
71+ if len (languages ) > 1 :
72+ language_arg = f'--language_idx "{ languages [0 ]}
73+ run_cli (
74+ f'tts --model_name { model_name }
75+ f'--out_path "{ output_path } { speaker_arg } { language_arg }
76+ )
77+ elif "voice_conversion_models" in model_name :
78+ speaker_wav = os .path .join (get_tests_data_path (), "ljspeech" , "wavs" , "LJ001-0001.wav" )
79+ reference_wav = os .path .join (get_tests_data_path (), "ljspeech" , "wavs" , "LJ001-0032.wav" )
80+ run_cli (
81+ f"tts --model_name { model_name }
82+ f'--out_path "{ output_path } { speaker_wav } { reference_wav }
83+ )
84+ else :
85+ # only download the model
86+ manager .download_model (model_name )
87+ print (f" | > OK: { model_name } )
8188
8289
8390@pytest .mark .skipif (GITHUB_ACTIONS , reason = "Model too big for CI" )
@@ -263,20 +270,3 @@ def test_voice_conversion(tmp_path):
263270 f"tts --model_name { model_name }
264271 f" --out_path { output_path } { speaker_wav } { reference_wav } { language_id }
265272 )
266-
267-
268- """
269- These are used to split tests into different actions on Github.
270- """
271-
272-
273- def test_models_offset_0_step_3 (tmp_path ):
274- run_models (tmp_path , offset = 0 , step = 3 )
275-
276-
277- def test_models_offset_1_step_3 (tmp_path ):
278- run_models (tmp_path , offset = 1 , step = 3 )
279-
280-
281- def test_models_offset_2_step_3 (tmp_path ):
282- run_models (tmp_path , offset = 2 , step = 3 )
0 commit comments