mirror of https://github.com/coqui-ai/TTS.git
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
import os
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import unittest
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import torch
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from tests import get_tests_input_path
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from TTS.vc.models.openvoice import OpenVoice, OpenVoiceConfig
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torch.manual_seed(1)
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use_cuda = torch.cuda.is_available()
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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c = OpenVoiceConfig()
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WAV_FILE = os.path.join(get_tests_input_path(), "example_1.wav")
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class TestOpenVoice(unittest.TestCase):
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@staticmethod
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def _create_inputs_inference():
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source_wav = torch.rand(16100)
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target_wav = torch.rand(16000)
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return source_wav, target_wav
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def test_load_audio(self):
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config = OpenVoiceConfig()
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model = OpenVoice(config).to(device)
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wav = model.load_audio(WAV_FILE)
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wav2 = model.load_audio(wav)
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assert all(torch.isclose(wav, wav2))
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def test_voice_conversion(self):
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config = OpenVoiceConfig()
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model = OpenVoice(config).to(device)
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model.eval()
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source_wav, target_wav = self._create_inputs_inference()
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output_wav = model.voice_conversion(source_wav, target_wav)
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assert (
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output_wav.shape[0] == source_wav.shape[0] - source_wav.shape[0] % config.audio.hop_length
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), f"{output_wav.shape} != {source_wav.shape}"
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