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video-dubbing
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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}"')