video-dubbing / TTS /tests /aux_tests /test_extract_tts_spectrograms.py
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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)
# pylint: disable=protected-access
class TestExtractTTSSpectrograms(unittest.TestCase):
@staticmethod
def test_GlowTTS():
# set paths
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/")
# load config
c = load_config(config_path)
# create model
model = setup_model(c)
# save model
torch.save({"model": model.state_dict()}, checkpoint_path)
# run test
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():
# set paths
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/")
# load config
c = load_config(config_path)
# create model
model = setup_model(c)
# save model
torch.save({"model": model.state_dict()}, checkpoint_path)
# run test
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():
# set paths
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/")
# load config
c = load_config(config_path)
# create model
model = setup_model(c)
# save model
torch.save({"model": model.state_dict()}, checkpoint_path)
# run test
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}"')