wehub-resource-sync
74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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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import random
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import unittest
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import numpy as np
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from paddlenlp.metrics import MRR
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from tests.common_test import CommonTest
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class TestMRR(CommonTest):
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def setUp(self):
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self.distance = "cosine"
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self.mrr = MRR(distance=self.distance)
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self.label_num = 10
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self.label_shape = (20,)
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self.embedding_shape = (20, 128)
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def get_random_case(self):
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labels = np.random.randint(0, self.label_num, size=self.label_shape).astype("int64")
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embeddings = np.random.uniform(0.1, 1.0, self.embedding_shape).astype("float64")
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all_distance = ["cityblock", "cosine", "euclidean", "l1", "l2", "manhattan"]
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distance = random.choice(all_distance)
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return labels, embeddings, distance, all_distance
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def get_true_mrr_case(self):
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labels = np.array([1, 2, 1]).astype("int64")
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embeddings = np.array(
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[
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# cosine similarity: 1,2 => 0.991; 1,3=>0.851; 2,3=>0.912
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[1.0, 2.0, 3.0],
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[1.0, 2.0, 4.0],
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[1.0, 100.0, 1000.0],
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]
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)
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distance = "cosine"
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true_mrr = (1.0 / 2 + 0 + 1.0 / 2) / 3
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return labels, embeddings, distance, true_mrr
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def test_reset_distance(self):
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_, _, distance, _ = self.get_random_case()
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self.mrr.reset_distance(distance)
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self.check_output_equal(self.mrr.distance, distance)
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def test_compute_matrix_mrr(self):
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step = 100
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for i in range(step):
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labels, embeddings, distance, _ = self.get_random_case()
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self.mrr.reset_distance(distance)
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self.mrr.compute_matrix_mrr(labels, embeddings)
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def test_compute_true_mrr(self):
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labels, embeddings, distance, true_mrr = self.get_true_mrr_case()
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self.mrr.reset_distance(distance)
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mrr = self.mrr.compute_matrix_mrr(labels, embeddings)
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self.check_output_equal(mrr, true_mrr)
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if __name__ == "__main__":
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unittest.main()
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