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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
16import numpy as np
17import pytest
18
19import mindspore.context as context
20from mindspore.common.tensor import Tensor
21from mindspore.nn import Cell
22from mindspore.ops import operations as P
23
24
25class NetAnd(Cell):
26    def __init__(self):
27        super(NetAnd, self).__init__()
28        self.logicaland = P.LogicalAnd()
29
30    def construct(self, input_x, input_y):
31        return self.logicaland(input_x, input_y)
32
33
34class NetOr(Cell):
35    def __init__(self):
36        super(NetOr, self).__init__()
37        self.logicalor = P.LogicalOr()
38
39    def construct(self, input_x, input_y):
40        return self.logicalor(input_x, input_y)
41
42
43class NetNot(Cell):
44    def __init__(self):
45        super(NetNot, self).__init__()
46        self.logicalnot = P.LogicalNot()
47
48    def construct(self, input_x):
49        return self.logicalnot(input_x)
50
51
52x = np.array([True, False, False]).astype(np.bool)
53y = np.array([False]).astype(np.bool)
54
55
56@pytest.mark.level0
57@pytest.mark.platform_x86_gpu_training
58@pytest.mark.env_onecard
59def test_logicaland():
60    context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
61    logicaland = NetAnd()
62    output = logicaland(Tensor(x), Tensor(y))
63    assert np.all(output.asnumpy() == np.logical_and(x, y))
64
65    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
66    logicaland = NetAnd()
67    output = logicaland(Tensor(x), Tensor(y))
68    assert np.all(output.asnumpy() == np.logical_and(x, y))
69
70
71@pytest.mark.level0
72@pytest.mark.platform_x86_gpu_training
73@pytest.mark.env_onecard
74def test_logicalor():
75    context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
76    logicalor = NetOr()
77    output = logicalor(Tensor(x), Tensor(y))
78    assert np.all(output.asnumpy() == np.logical_or(x, y))
79
80    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
81    logicalor = NetOr()
82    output = logicalor(Tensor(x), Tensor(y))
83    assert np.all(output.asnumpy() == np.logical_or(x, y))
84
85
86@pytest.mark.level0
87@pytest.mark.platform_x86_gpu_training
88@pytest.mark.env_onecard
89def test_logicalnot():
90    context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
91    logicalnot = NetNot()
92    output = logicalnot(Tensor(x))
93    assert np.all(output.asnumpy() == np.logical_not(x))
94
95    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
96    logicalnot = NetNot()
97    output = logicalnot(Tensor(x))
98    assert np.all(output.asnumpy() == np.logical_not(x))
99