mirror of
https://github.com/open-mmlab/mmselfsup.git
synced 2025-06-03 14:59:38 +08:00
aa1e65cee3
* fix a bug of showing kmeans losses * fix a bug of showing kmeans losses * isort * fix typo (#180) * add unit test * remove gpu restrict * restore gpu restrict * bypass gpu by mock * mock bypass * mock bypass * mock bypass * mock bypass * apply flake8 * apply flask8 * typo * Upgrade isort (#184) * Fix isort config * Trigger commit hook * Trigger commit hook * Upgrade isort in ci and remove seed-isort-config * Update test requirement * Add unit test for build_dataset * Fix test data * Fix typo * Use deepclustering dataset as test dataset config * fix a bug of showing kmeans losses * fix a bug of showing kmeans losses * isort * add unit test * remove gpu restrict * restore gpu restrict * bypass gpu by mock * mock bypass * mock bypass * mock bypass * mock bypass * apply flake8 * apply flask8 * typo * apply isort * remove session scope func Co-authored-by: Uno Wu <st9007a@gmail.com>
45 lines
1.2 KiB
Python
45 lines
1.2 KiB
Python
from unittest.mock import patch
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import numpy as np
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import pytest
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from mmselfsup.utils.clustering import PIC, Kmeans
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@pytest.fixture
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def mock_faiss_in_clutering():
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with patch('mmselfsup.utils.clustering.faiss') as faiss:
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yield faiss
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@pytest.fixture
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def mock_faiss(mock_faiss_in_clutering):
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mock_PCAmatrix = mock_faiss_in_clutering.PCAMatrix.return_value
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mock_GpuIndexFlatL2 = mock_faiss_in_clutering.GpuIndexFlatL2.return_value
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mock_PCAmatrix.apply_py.return_value = np.random.rand(10, 8)
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mock_GpuIndexFlatL2.search.return_value = (
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np.random.rand(1000, 6),
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np.random.rand(1000, 6),
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)
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@pytest.mark.parametrize('verbose', [True, False])
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def test_kmeans(mock_faiss, verbose):
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fake_input = np.random.rand(10, 8).astype(np.float32)
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pca_dim = 2
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kmeans = Kmeans(2, pca_dim)
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loss = kmeans.cluster(fake_input, verbose=verbose)
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assert loss is not None
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with pytest.raises(AssertionError):
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loss = kmeans.cluster(np.random.rand(10, 8), verbose=verbose)
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def test_pic(mock_faiss):
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fake_input = np.random.rand(1000, 16).astype(np.float32)
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pic = PIC(pca_dim=8)
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res = pic.cluster(fake_input)
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assert res == 0
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