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1# Copyright 2020-2021 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
16import numpy as np
17import pytest
18
19import mindspore.context as context
20import mindspore.nn as nn
21from mindspore import Tensor
22from mindspore.ops import operations as P
23
24context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
25
26
27class OpNetWrapper(nn.Cell):
28    def __init__(self, op):
29        super(OpNetWrapper, self).__init__()
30        self.op = op
31
32    def construct(self, *inputs):
33        return self.op(*inputs)
34
35
36@pytest.mark.level0
37@pytest.mark.platform_x86_cpu
38@pytest.mark.env_onecard
39def test_logicaland():
40    op = P.LogicalAnd()
41    op_wrapper = OpNetWrapper(op)
42
43    input_x = Tensor(np.array([True, False, False]))
44    input_y = Tensor(np.array([True, True, False]))
45    outputs = op_wrapper(input_x, input_y)
46
47    assert np.allclose(outputs.asnumpy(), (True, False, False))
48
49
50@pytest.mark.level0
51@pytest.mark.platform_x86_cpu
52@pytest.mark.env_onecard
53def test_logicalor():
54    op = P.LogicalOr()
55    op_wrapper = OpNetWrapper(op)
56
57    input_x = Tensor(np.array([True, False, False]))
58    input_y = Tensor(np.array([True, True, False]))
59    outputs = op_wrapper(input_x, input_y)
60
61    assert np.allclose(outputs.asnumpy(), (True, True, False))
62
63
64@pytest.mark.level0
65@pytest.mark.platform_x86_cpu
66@pytest.mark.env_onecard
67def test_logicalnot():
68    op = P.LogicalNot()
69    op_wrapper = OpNetWrapper(op)
70
71    input_x = Tensor(np.array([True, False, False]))
72    outputs = op_wrapper(input_x)
73
74    assert np.allclose(outputs.asnumpy(), (False, True, True))
75
76
77if __name__ == '__main__':
78    test_logicaland()
79    test_logicalor()
80    test_logicalnot()
81