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62 lines
2.0 KiB
62 lines
2.0 KiB
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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from paddlespeech.audiotools.core.audio_signal import AudioSignal
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from paddlespeech.t2s.modules.losses import GANLoss
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from paddlespeech.t2s.modules.losses import MultiScaleSTFTLoss
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from paddlespeech.t2s.modules.losses import SISDRLoss
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def get_input():
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x = AudioSignal("https://paddlespeech.cdn.bcebos.com/PaddleAudio/en.wav",
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2_05)
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y = x * 0.01
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return x, y
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def test_multi_scale_stft_loss():
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x, y = get_input()
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loss = MultiScaleSTFTLoss()
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pd_loss = loss(x, y)
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assert np.abs(pd_loss.numpy() - 7.562150) < 1e-06
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def test_sisdr_loss():
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x, y = get_input()
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loss = SISDRLoss()
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pd_loss = loss(x, y)
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assert np.abs(pd_loss.numpy() - (-145.377640)) < 1e-06
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def test_gan_loss():
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class My_discriminator0:
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def __call__(self, x):
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return x.sum()
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class My_discriminator1:
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def __call__(self, x):
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return x * (-0.2)
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x, y = get_input()
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loss = GANLoss(My_discriminator0())
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pd_loss0, pd_loss1 = loss(x, y)
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assert np.abs(pd_loss0.numpy() - (-0.102722)) < 1e-06
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assert np.abs(pd_loss1.numpy() - (-0.001027)) < 1e-06
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loss = GANLoss(My_discriminator1())
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pd_loss0, _ = loss.generator_loss(x, y)
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assert np.abs(pd_loss0.numpy() - 1.000199) < 1e-06
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pd_loss = loss.discriminator_loss(x, y)
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assert np.abs(pd_loss.numpy() - 1.000200) < 1e-06
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