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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import random
import torch
from audiocraft.losses import (
MelSpectrogramL1Loss,
MultiScaleMelSpectrogramLoss,
MRSTFTLoss,
SISNR,
STFTLoss,
)
def test_mel_l1_loss():
N, C, T = 2, 2, random.randrange(1000, 100_000)
t1 = torch.randn(N, C, T)
t2 = torch.randn(N, C, T)
mel_l1 = MelSpectrogramL1Loss(sample_rate=22_050)
loss = mel_l1(t1, t2)
loss_same = mel_l1(t1, t1)
assert isinstance(loss, torch.Tensor)
assert isinstance(loss_same, torch.Tensor)
assert loss_same.item() == 0.0
def test_msspec_loss():
N, C, T = 2, 2, random.randrange(1000, 100_000)
t1 = torch.randn(N, C, T)
t2 = torch.randn(N, C, T)
msspec = MultiScaleMelSpectrogramLoss(sample_rate=22_050)
loss = msspec(t1, t2)
loss_same = msspec(t1, t1)
assert isinstance(loss, torch.Tensor)
assert isinstance(loss_same, torch.Tensor)
assert loss_same.item() == 0.0
def test_mrstft_loss():
N, C, T = 2, 2, random.randrange(1000, 100_000)
t1 = torch.randn(N, C, T)
t2 = torch.randn(N, C, T)
mrstft = MRSTFTLoss()
loss = mrstft(t1, t2)
assert isinstance(loss, torch.Tensor)
def test_sisnr_loss():
N, C, T = 2, 2, random.randrange(1000, 100_000)
t1 = torch.randn(N, C, T)
t2 = torch.randn(N, C, T)
sisnr = SISNR()
loss = sisnr(t1, t2)
assert isinstance(loss, torch.Tensor)
def test_stft_loss():
N, C, T = 2, 2, random.randrange(1000, 100_000)
t1 = torch.randn(N, C, T)
t2 = torch.randn(N, C, T)
mrstft = STFTLoss()
loss = mrstft(t1, t2)
assert isinstance(loss, torch.Tensor)
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