|
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}"') |
|
|