| import os |
| import unittest |
|
|
| import torch |
|
|
| from tests import get_tests_input_path, get_tests_output_path, run_cli |
| from TTS.config import load_config |
| from TTS.tts.models import setup_model |
|
|
| torch.manual_seed(1) |
|
|
|
|
| |
| class TestExtractTTSSpectrograms(unittest.TestCase): |
| @staticmethod |
| def test_GlowTTS(): |
| |
| config_path = os.path.join(get_tests_input_path(), "test_glow_tts.json") |
| checkpoint_path = os.path.join(get_tests_output_path(), "glowtts.pth") |
| output_path = os.path.join(get_tests_output_path(), "output_extract_tts_spectrograms/") |
| |
| c = load_config(config_path) |
| |
| model = setup_model(c) |
| |
| torch.save({"model": model.state_dict()}, checkpoint_path) |
| |
| run_cli( |
| f'CUDA_VISIBLE_DEVICES="" python TTS/bin/extract_tts_spectrograms.py --config_path "{config_path}" --checkpoint_path "{checkpoint_path}" --output_path "{output_path}"' |
| ) |
| run_cli(f'rm -rf "{output_path}" "{checkpoint_path}"') |
|
|
| @staticmethod |
| def test_Tacotron2(): |
| |
| config_path = os.path.join(get_tests_input_path(), "test_tacotron2_config.json") |
| checkpoint_path = os.path.join(get_tests_output_path(), "tacotron2.pth") |
| output_path = os.path.join(get_tests_output_path(), "output_extract_tts_spectrograms/") |
| |
| c = load_config(config_path) |
| |
| model = setup_model(c) |
| |
| torch.save({"model": model.state_dict()}, checkpoint_path) |
| |
| run_cli( |
| f'CUDA_VISIBLE_DEVICES="" python TTS/bin/extract_tts_spectrograms.py --config_path "{config_path}" --checkpoint_path "{checkpoint_path}" --output_path "{output_path}"' |
| ) |
| run_cli(f'rm -rf "{output_path}" "{checkpoint_path}"') |
|
|
| @staticmethod |
| def test_Tacotron(): |
| |
| config_path = os.path.join(get_tests_input_path(), "test_tacotron_config.json") |
| checkpoint_path = os.path.join(get_tests_output_path(), "tacotron.pth") |
| output_path = os.path.join(get_tests_output_path(), "output_extract_tts_spectrograms/") |
| |
| c = load_config(config_path) |
| |
| model = setup_model(c) |
| |
| torch.save({"model": model.state_dict()}, checkpoint_path) |
| |
| run_cli( |
| f'CUDA_VISIBLE_DEVICES="" python TTS/bin/extract_tts_spectrograms.py --config_path "{config_path}" --checkpoint_path "{checkpoint_path}" --output_path "{output_path}"' |
| ) |
| run_cli(f'rm -rf "{output_path}" "{checkpoint_path}"') |
|
|