forked from catalyst-team/catalyst
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
1 changed file
with
22 additions
and
35 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,47 +1,34 @@ | ||
| import numpy as np | ||
|
|
||
| import torch | ||
|
|
||
| from catalyst.utils import metrics | ||
|
|
||
|
|
||
| def test_ndcg(): | ||
| def test_zero_ndcg(): | ||
| """ | ||
| Tests for catalyst.utils.metrics.ndcg metric. | ||
| """ | ||
| # check 0: common values | ||
| assert ( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([1, 0, 0])) == 1.0 | ||
| ) | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 1, 0])), 0.63093 | ||
| ) | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 0, 1])), 0.5 | ||
| ) | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([1, 0, 1])), 0.91972 | ||
| ) | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([1, 0, 1]), k=2), | ||
| 0.61315, | ||
| ) | ||
| ndcg_at1, ndcg_at3, ndcg_at7 = metrics.ndcg( | ||
| torch.tensor([6, 5, 4, 3, 2, 1, 0]), | ||
| torch.tensor([0, 0, 0, 0, 0, 0, 1]), | ||
| topk=(1, 3, 7), | ||
| ) | ||
| assert torch.isclose(ndcg_at1, torch.tensor(0.0)) | ||
| assert torch.isclose(ndcg_at3, torch.tensor(0.0)) | ||
| assert torch.isclose(ndcg_at7, torch.tensor(3.0)) | ||
|
|
||
| # check 1: ordering invariance | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 0, 1])), | ||
| metrics.ndcg(torch.tensor([0, 1, 2]), torch.tensor([1, 0, 0])), | ||
| ) | ||
| assert np.allclose( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 0, 1])), | ||
| metrics.ndcg(torch.tensor([2, 0, 1]), torch.tensor([0, 1, 0])), | ||
| ) | ||
|
|
||
| # check2: zero ndcg | ||
| assert ( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 0, 0])) == 0.0 | ||
| def test_ndcg_ordering_invariance(): | ||
| """ | ||
| Tests for catalyst.utils.metrics.ndcg metric. | ||
| """ | ||
| [in_order] = metrics.ndcg( | ||
| torch.tensor([2, 1, 0]), torch.tensor([1, 0, 0]), topk=(1,) | ||
| ) | ||
| [first_last] = metrics.ndcg( | ||
| torch.tensor([0, 1, 2]), torch.tensor([0, 0, 1]), topk=(1,) | ||
| ) | ||
| assert ( | ||
| metrics.ndcg(torch.tensor([2, 1, 0]), torch.tensor([0, 0, 1]), k=2) | ||
| == 0.0 | ||
| [first_middle] = metrics.ndcg( | ||
| torch.tensor([1, 2, 0]), torch.tensor([0, 1, 0]), topk=(1,) | ||
| ) | ||
| assert torch.isclose(in_order, first_last) | ||
| assert torch.isclose(first_last, first_middle) |