mirror of https://github.com/coqui-ai/TTS.git
update tests
parent
7eb0c60d2e
commit
a878d8fb42
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@ -1,4 +1,5 @@
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import os
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import torch
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import unittest
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import numpy as np
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@ -11,9 +12,9 @@ from TTS.utils.io import load_config
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encoder_config_path = os.path.join(get_tests_input_path(), "test_speaker_encoder_config.json")
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encoder_model_path = os.path.join(get_tests_input_path(), "dummy_speaker_encoder.pth.tar")
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sample_wav_path = os.path.join(get_tests_input_path(), "../data/ljspeech/wavs/LJ001-0001.wav")
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sample_wav_path2 = os.path.join(get_tests_input_path(), "../data/ljspeech/wavs/LJ001-0002.wav")
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x_vectors_file_path = os.path.join(get_tests_input_path(), "../data/dummy_speakers.json")
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class SpeakerManagerTest(unittest.TestCase):
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"""Test SpeakerManager for loading embedding files and computing x_vectors from waveforms"""
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@staticmethod
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@ -32,6 +33,21 @@ class SpeakerManagerTest(unittest.TestCase):
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x_vector = manager.compute_x_vector(mel.T)
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assert x_vector.shape[1] == 256
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# compute x_vector directly from an input file
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x_vector = manager.compute_x_vector_from_clip(sample_wav_path)
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x_vector2 = manager.compute_x_vector_from_clip(sample_wav_path)
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x_vector = torch.FloatTensor(x_vector)
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x_vector2 = torch.FloatTensor(x_vector2)
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assert x_vector.shape[0] == 256
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assert (x_vector - x_vector2).sum() == 0.0
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# compute x_vector from a list of wav files.
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x_vector3 = manager.compute_x_vector_from_clip([sample_wav_path, sample_wav_path2])
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x_vector3 = torch.FloatTensor(x_vector3)
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assert x_vector3.shape[0] == 256
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assert (x_vector - x_vector3).sum() != 0.0
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@staticmethod
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def test_speakers_file_processing():
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manager = SpeakerManager(x_vectors_file_path=x_vectors_file_path)
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