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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
20import mindspore.nn as nn
21from mindspore import Tensor
22from mindspore.common.initializer import initializer
23from mindspore.common.parameter import Parameter
24from mindspore.ops import operations as P
25
26context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
27
28
29class NetEqualBool(nn.Cell):
30    def __init__(self):
31        super(NetEqualBool, self).__init__()
32        self.equal = P.Equal()
33        x = Tensor(np.array([True, True, False]).astype(np.bool))
34        y = Tensor(np.array([True, False, True]).astype(np.bool))
35        self.x = Parameter(initializer(x, x.shape), name="x")
36        self.y = Parameter(initializer(y, y.shape), name="y")
37
38    def construct(self):
39        return self.equal(self.x, self.y)
40
41
42@pytest.mark.level0
43@pytest.mark.platform_x86_cpu
44@pytest.mark.env_onecard
45def test_equal_bool():
46    Equal = NetEqualBool()
47    output = Equal()
48    print("================================")
49    expect = np.array([True, False, False]).astype(np.bool)
50    print(output)
51    assert (output.asnumpy() == expect).all()
52
53
54class NetEqualInt(nn.Cell):
55    def __init__(self):
56        super(NetEqualInt, self).__init__()
57        self.equal = P.Equal()
58        x = Tensor(np.array([1, 20, 5]).astype(np.int32))
59        y = Tensor(np.array([2, 20, 5]).astype(np.int32))
60        self.x = Parameter(initializer(x, x.shape), name="x")
61        self.y = Parameter(initializer(y, y.shape), name="y")
62
63    def construct(self):
64        return self.equal(self.x, self.y)
65
66
67@pytest.mark.level0
68@pytest.mark.platform_x86_cpu
69@pytest.mark.env_onecard
70def test_equal_int():
71    Equal = NetEqualInt()
72    output = Equal()
73    print("================================")
74    expect = np.array([False, True, True]).astype(np.bool)
75    print(output)
76    assert (output.asnumpy() == expect).all()
77
78
79class NetEqualFloat(nn.Cell):
80    def __init__(self):
81        super(NetEqualFloat, self).__init__()
82        self.equal = P.Equal()
83        x = Tensor(np.array([1.2, 10.4, 5.5]).astype(np.float32))
84        y = Tensor(np.array([1.2, 10.3, 5.4]).astype(np.float32))
85        self.x = Parameter(initializer(x, x.shape), name="x")
86        self.y = Parameter(initializer(y, y.shape), name="y")
87
88    def construct(self):
89        return self.equal(self.x, self.y)
90
91
92@pytest.mark.level0
93@pytest.mark.platform_x86_cpu
94@pytest.mark.env_onecard
95def test_equal_float():
96    Equal = NetEqualFloat()
97    output = Equal()
98    print("================================")
99    expect = np.array([True, False, False]).astype(np.bool)
100    print(output)
101    assert (output.asnumpy() == expect).all()
102