| import unittest | |
| import torch | |
| import numpy as np | |
| from model.ops import minmax_normalize | |
| class TestMinMaxNormalize(unittest.TestCase): | |
| def test_minmax_normalize(self): | |
| x = torch.tensor([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]]) | |
| x_norm = minmax_normalize(x) | |
| x_norm_expected = torch.tensor([[[0.0, 0.2, 0.4], [0.6, 0.8, 1.0]]]) | |
| np.testing.assert_almost_equal(x_norm.numpy(), x_norm_expected.numpy(), decimal=2) | |
| if __name__ == '__main__': | |
| unittest.main() | |