mirror of https://github.com/coqui-ai/TTS.git
Remove unused vars in Delightful TTS layers tests
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@ -28,7 +28,7 @@ tokenizer, config = TTSTokenizer.init_from_config(config)
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def test_acoustic_model():
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dummy_tokens = torch.rand((1, 41)).long().to(device)
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dummy_text_lens = torch.tensor([41]).to(device)
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dummy_text_lens = torch.tensor([41]).long().to(device)
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dummy_spec = torch.rand((1, 100, 207)).to(device)
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dummy_spec_lens = torch.tensor([207]).to(device)
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dummy_pitch = torch.rand((1, 1, 207)).long().to(device)
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@ -38,6 +38,7 @@ def test_acoustic_model():
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args.num_mels = 100
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acoustic_model = AcousticModel(args=args, tokenizer=tokenizer, speaker_manager=None).to(device)
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acoustic_model = acoustic_model.train()
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output = acoustic_model(
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tokens=dummy_tokens,
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@ -56,11 +57,7 @@ def test_acoustic_model():
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def test_hifi_decoder():
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dummy_input = torch.rand((1, 207, 100)).to(device)
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dummy_text_lens = torch.tensor([41]).to(device)
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dummy_spec = torch.rand((1, 100, 207)).to(device)
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dummy_spec_lens = torch.tensor([207]).to(device)
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dummy_pitch = torch.rand((1, 1, 207)).long().to(device)
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dummy_energy = torch.rand((1, 1, 207)).long().to(device)
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waveform_decoder = HifiganGenerator(
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100,
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@ -77,6 +74,7 @@ def test_hifi_decoder():
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conv_post_weight_norm=False,
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conv_post_bias=False,
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).to(device)
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waveform_decoder = waveform_decoder.train()
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vocoder_input_slices, slice_ids = rand_segments( # pylint: disable=unused-variable
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x=dummy_input.transpose(1, 2),
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