| import torch | |
| import unittest | |
| from model.spectrogram import Melspectrogram | |
| class TestMelspectrogram(unittest.TestCase): | |
| def test_melspectrogram(self): | |
| # Create a Melspectrogram instance with default parameters | |
| melspec = Melspectrogram() | |
| # Create a random input tensor (B, C, T) with T = 32767 samples for 2048 ms | |
| x = torch.randn(2, 1, 32767) | |
| # Compute the Melspectrogram | |
| y = melspec(x) | |
| # Check the output shape | |
| self.assertEqual(y.shape, (2, 256, 512)) | |
| # Check if the output contains NaN values | |
| self.assertFalse(torch.isnan(y).any()) | |
| # Check if the output contains infinite values | |
| self.assertFalse(torch.isinf(y).any()) | |
| if __name__ == "__main__": | |
| unittest.main() |