96 lines
3.0 KiB
Python
96 lines
3.0 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""test cosine_similarity"""
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import pytest
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import numpy as np
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from sklearn.metrics import pairwise
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from mindspore.nn.metrics import CosineSimilarity
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def test_cosine_similarity():
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"""test_cosine_similarity"""
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test_data = np.array([[5, 8, 3, 2], [5, 8, 3, 2], [4, 2, 3, 4]])
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metric = CosineSimilarity()
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metric.clear()
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metric.update(test_data)
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square_matrix = metric.eval()
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assert np.allclose(square_matrix, np.array([[0, 1, 0.78229315], [1, 0, 0.78229315], [0.78229315, 0.78229315, 0]]))
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def test_cosine_similarity_compare():
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"""test_cosine_similarity_compare"""
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test_data = np.array([[5, 8, 3, 2], [5, 8, 3, 2], [4, 2, 3, 4]])
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metric = CosineSimilarity(similarity='cosine', reduction='none', zero_diagonal=False)
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metric.clear()
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metric.update(test_data)
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ms_square_matrix = metric.eval()
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def sklearn_cosine_similarity(test_data, similarity, reduction):
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"""sklearn_cosine_similarity"""
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metric_func = {'cosine': pairwise.cosine_similarity,
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'dot': pairwise.linear_kernel}[similarity]
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square_matrix = metric_func(test_data, test_data)
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if reduction == 'mean':
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return square_matrix.mean(axis=-1)
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if reduction == 'sum':
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return square_matrix.sum(axis=-1)
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return square_matrix
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sk_square_matrix = sklearn_cosine_similarity(test_data, similarity='cosine', reduction='none')
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assert np.allclose(sk_square_matrix, ms_square_matrix)
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def test_cosine_similarity_init1():
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"""test_cosine_similarity_init1"""
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with pytest.raises(ValueError):
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CosineSimilarity(similarity="4")
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def test_cosine_similarity_init2():
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"""test_cosine_similarity_init2"""
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with pytest.raises(TypeError):
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CosineSimilarity(similarity=4)
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def test_cosine_similarity_init3():
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"""test_cosine_similarity_init3"""
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with pytest.raises(TypeError):
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CosineSimilarity(reduction=2)
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def test_cosine_similarity_init4():
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"""test_cosine_similarity_init4"""
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with pytest.raises(ValueError):
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CosineSimilarity(reduction="1")
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def test_cosine_similarity_init5():
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"""test_cosine_similarity_init5"""
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with pytest.raises(TypeError):
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CosineSimilarity(zero_diagonal=3)
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def test_cosine_similarity_runtime():
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"""test_cosine_similarity_runtime"""
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metric = CosineSimilarity()
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metric.clear()
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with pytest.raises(RuntimeError):
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metric.eval()
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