mirror of
https://github.com/deepset-ai/haystack.git
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bogdankostic
ea5e10f9e6
* Raise warning if dataclasses are modified in-place * Add tests * Add release note * Fix release note formatting * fix release note formatting * Update copyright year in dataclasses.py * Update warnings in dataclasses to use Warning instead of DeprecationWarning for in-place mutations * Remove decorator from Protocol * Refactor dunder access in dataclasses to comply with ruff guidelines * Update warnings in dataclasses to consistently use Warning for in-place mutations * Update warning messahe and release note
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# SPDX-FileCopyrightText: 2022-present deepset GmbH <[email protected]>
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#
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# SPDX-License-Identifier: Apache-2.0
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import warnings
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import pytest
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from haystack.dataclasses.sparse_embedding import SparseEmbedding
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class TestSparseEmbedding:
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def test_init(self):
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se = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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assert se.indices == [0, 2, 4]
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assert se.values == [0.1, 0.2, 0.3]
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def test_init_with_wrong_parameters(self):
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with pytest.raises(ValueError):
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SparseEmbedding(indices=[0, 2], values=[0.1, 0.2, 0.3, 0.4])
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def test_to_dict(self):
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se = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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assert se.to_dict() == {"indices": [0, 2, 4], "values": [0.1, 0.2, 0.3]}
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def test_from_dict(self):
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se = SparseEmbedding.from_dict({"indices": [0, 2, 4], "values": [0.1, 0.2, 0.3]})
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assert se.indices == [0, 2, 4]
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assert se.values == [0.1, 0.2, 0.3]
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def test_eq(self):
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se1 = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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se2 = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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assert se1 == se2
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se3 = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.4])
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assert se1 != se3
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def test_no_warning_on_init(self):
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with warnings.catch_warnings():
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warnings.simplefilter("error", Warning)
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SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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def test_warn_on_inplace_mutation(self):
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se = SparseEmbedding(indices=[0, 2, 4], values=[0.1, 0.2, 0.3])
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with pytest.warns(Warning, match="dataclasses.replace"):
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se.indices = [1, 3, 5]
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