mirror of https://github.com/coqui-ai/TTS.git
47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
import numpy as np
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import torch
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from TTS.vocoder.models.parallel_wavegan_discriminator import (
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ParallelWaveganDiscriminator,
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ResidualParallelWaveganDiscriminator,
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)
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def test_pwgan_disciminator():
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model = ParallelWaveganDiscriminator(
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in_channels=1,
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out_channels=1,
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kernel_size=3,
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num_layers=10,
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conv_channels=64,
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dilation_factor=1,
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nonlinear_activation="LeakyReLU",
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nonlinear_activation_params={"negative_slope": 0.2},
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bias=True,
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)
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dummy_x = torch.rand((4, 1, 64 * 256))
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output = model(dummy_x)
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assert np.all(output.shape == (4, 1, 64 * 256))
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model.remove_weight_norm()
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def test_redisual_pwgan_disciminator():
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model = ResidualParallelWaveganDiscriminator(
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in_channels=1,
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out_channels=1,
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kernel_size=3,
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num_layers=30,
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stacks=3,
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res_channels=64,
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gate_channels=128,
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skip_channels=64,
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dropout=0.0,
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bias=True,
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nonlinear_activation="LeakyReLU",
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nonlinear_activation_params={"negative_slope": 0.2},
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)
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dummy_x = torch.rand((4, 1, 64 * 256))
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output = model(dummy_x)
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assert np.all(output.shape == (4, 1, 64 * 256))
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model.remove_weight_norm()
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