Medix-AI/coqui-tts
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coqui-tts
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fix unit tests

This commit is contained in:
Edresson 2021-05-26 18:14:06 -03:00
parent c90037c2e9
commit 7a9a27282a
1 changed files with 3 additions and 17 deletions
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20
tests/test_speaker_encoder.py
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@ -4,8 +4,8 @@ import torch as T
from tests import get_tests_input_path
from TTS.speaker_encoder.losses import AngleProtoLoss, GE2ELoss
from TTS.speaker_encoder.model import SpeakerEncoder
from TTS.speaker_encoder.models.lstm import LSTMSpeakerEncoder
# from TTS.speaker_encoder.models.resnet import ResNetSpeakerEncoder
file_path = get_tests_input_path()
@ -14,7 +14,7 @@ class SpeakerEncoderTests(unittest.TestCase):
def test_in_out(self):
dummy_input = T.rand(4, 20, 80) # B x T x D
dummy_hidden = [T.rand(2, 4, 128), T.rand(2, 4, 128)]
model = SpeakerEncoder(input_dim=80, proj_dim=256, lstm_dim=768, num_lstm_layers=3)
model = LSTMSpeakerEncoder(input_dim=80, proj_dim=256, lstm_dim=768, num_lstm_layers=3)
# computing d vectors
output = model.forward(dummy_input)
assert output.shape[0] == 4
@ -96,17 +96,3 @@ class AngleProtoLossTests(unittest.TestCase):
loss = AngleProtoLoss()
output = loss.forward(dummy_input)
assert output.item() < 0.005
# class LoaderTest(unittest.TestCase):
# def test_output(self):
# items = libri_tts("/home/erogol/Data/Libri-TTS/train-clean-360/")
# ap = AudioProcessor(**c['audio'])
# dataset = MyDataset(ap, items, 1.6, 64, 10)
# loader = DataLoader(dataset, batch_size=32, shuffle=False, num_workers=0, collate_fn=dataset.collate_fn)
# count = 0
# for mel, spk in loader:
# print(mel.shape)
# if count == 4:
# break
# count += 1