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1# Copyright 2020 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15"""test topk"""
16import math
17import numpy as np
18import pytest
19
20from mindspore import Tensor
21from mindspore.nn.metrics import TopKCategoricalAccuracy, Top1CategoricalAccuracy, Top5CategoricalAccuracy
22
23
24def test_type_topk():
25    with pytest.raises(TypeError):
26        TopKCategoricalAccuracy(2.1)
27
28
29def test_value_topk():
30    with pytest.raises(ValueError):
31        TopKCategoricalAccuracy(-1)
32
33
34def test_input_topk():
35    x = Tensor(np.array([[0.2, 0.5, 0.3, 0.6, 0.2],
36                         [0.3, 0.1, 0.5, 0.1, 0.],
37                         [0.9, 0.6, 0.2, 0.01, 0.3]]))
38    topk = TopKCategoricalAccuracy(3)
39    topk.clear()
40    with pytest.raises(ValueError):
41        topk.update(x)
42
43
44def test_topk():
45    """test_topk"""
46    x = Tensor(np.array([[0.2, 0.5, 0.3, 0.6, 0.2],
47                         [0.1, 0.35, 0.5, 0.2, 0.],
48                         [0.9, 0.6, 0.2, 0.01, 0.3]]))
49    y = Tensor(np.array([2, 0, 1]))
50    y2 = Tensor(np.array([[0, 0, 1, 0, 0],
51                          [1, 0, 0, 0, 0],
52                          [0, 1, 0, 0, 0]]))
53    topk = TopKCategoricalAccuracy(3)
54    topk.clear()
55    topk.update(x, y)
56    result = topk.eval()
57    result2 = topk(x, y2)
58    assert math.isclose(result, 2 / 3)
59    assert math.isclose(result2, 2 / 3)
60
61
62def test_zero_topk():
63    topk = TopKCategoricalAccuracy(3)
64    topk.clear()
65    with pytest.raises(RuntimeError):
66        topk.eval()
67
68
69def test_top1():
70    """test_top1"""
71    x = Tensor(np.array([[0.2, 0.5, 0.2, 0.1, 0.],
72                         [0.1, 0.35, 0.25, 0.2, 0.1],
73                         [0.9, 0.1, 0, 0., 0]]))
74    y = Tensor(np.array([2, 0, 0]))
75    y2 = Tensor(np.array([[0, 0, 1, 0, 0],
76                          [1, 0, 0, 0, 0],
77                          [1, 0, 0, 0, 0]]))
78    topk = Top1CategoricalAccuracy()
79    topk.clear()
80    topk.update(x, y)
81    result = topk.eval()
82    result2 = topk(x, y2)
83    assert math.isclose(result, 1 / 3)
84    assert math.isclose(result2, 1 / 3)
85
86
87def test_top5():
88    """test_top5"""
89    x = Tensor(np.array([[0.15, 0.4, 0.1, 0.05, 0., 0.2, 0.1],
90                         [0.1, 0.35, 0.25, 0.2, 0.1, 0., 0.],
91                         [0., 0.5, 0.2, 0.1, 0.1, 0.1, 0.]]))
92    y = Tensor(np.array([2, 0, 0]))
93    y2 = Tensor(np.array([[0, 0, 1, 0, 0],
94                          [1, 0, 0, 0, 0],
95                          [1, 0, 0, 0, 0]]))
96    topk = Top5CategoricalAccuracy()
97    topk.clear()
98    topk.update(x, y)
99    result = topk.eval()
100    result2 = topk(x, y2)
101    assert math.isclose(result, 2 / 3)
102    assert math.isclose(result2, 2 / 3)
103