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import unittest | |
import torch | |
from training.loss import LogSTFTMagnitudeLoss | |
class TestLogSTFTMagnitudeLoss(unittest.TestCase): | |
def test_log_stft_magnitude_loss(self): | |
# Test the log STFT magnitude loss function with random input tensors | |
loss_fn = LogSTFTMagnitudeLoss() | |
x_mag = torch.randn(4, 100, 513) | |
y_mag = torch.randn(4, 100, 513) | |
loss = loss_fn(x_mag, y_mag) | |
self.assertIsInstance(loss, torch.Tensor) | |
self.assertEqual(loss.shape, torch.Size([])) | |
def test_log_stft_magnitude_loss_nonzero(self): | |
# Test the log STFT magnitude loss function with non-zero loss | |
loss_fn = LogSTFTMagnitudeLoss() | |
x_mag = torch.tensor([[1, 4, 9, 64], [1, 1, 1, 2]]) | |
y_mag = torch.tensor([[1, 8, 16, 256], [1, 1, 2, 2]]) | |
loss = loss_fn(x_mag, y_mag) | |
self.assertIsInstance(loss, torch.Tensor) | |
self.assertEqual(loss.shape, torch.Size([])) | |
expected = torch.tensor(0.4185) | |
self.assertTrue(torch.allclose(loss, expected, rtol=1e-4, atol=1e-4)) | |
if __name__ == "__main__": | |
unittest.main() | |