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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.ops import operations as P
23
24
25class Net(nn.Cell):
26    def __init__(self):
27        super(Net, self).__init__()
28        self.select = P.Select()
29
30    def construct(self, cond_op, input_x, input_y):
31        return self.select(cond_op, input_x, input_y)
32
33
34context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
35
36
37@pytest.mark.level0
38@pytest.mark.platform_x86_cpu
39@pytest.mark.env_onecard
40def test_select_float32():
41    cond = np.array([[True, False], [True, False]]).astype(np.bool)
42    x = np.array([[1.2, 1], [1, 0]]).astype(np.float32)
43    y = np.array([[1, 2], [3, 4.0]]).astype(np.float32)
44    select = Net()
45    output = select(Tensor(cond), Tensor(x), Tensor(y))
46    print(output.asnumpy())
47    expect = [[1.2, 2], [1, 4.0]]
48    error = np.ones(shape=[2, 2]) * 1.0e-6
49    diff = output.asnumpy() - expect
50    assert np.all(diff < error)
51    assert np.all(-diff < error)
52
53
54@pytest.mark.level0
55@pytest.mark.platform_x86_cpu
56@pytest.mark.env_onecard
57def test_select_float16():
58    cond = np.array([[True, False], [True, False]]).astype(np.bool)
59    x = np.array([[1.2, 1], [1, 0]]).astype(np.float16)
60    y = np.array([[1, 2], [3, 4.0]]).astype(np.float16)
61    select = Net()
62    output = select(Tensor(cond), Tensor(x), Tensor(y))
63    print(output.asnumpy())
64    expect = [[1.2, 2], [1, 4.0]]
65    error = np.ones(shape=[2, 2]) * 1.0e-3
66    diff = output.asnumpy() - expect
67    assert np.all(diff < error)
68    assert np.all(-diff < error)
69
70
71@pytest.mark.level0
72@pytest.mark.platform_x86_cpu
73@pytest.mark.env_onecard
74def test_select_int32():
75    cond = np.array([[True, False], [True, False]]).astype(np.bool)
76    x = np.array([[12, 1], [1, 0]]).astype(np.int32)
77    y = np.array([[1, 2], [3, 4]]).astype(np.int32)
78    select = Net()
79    output = select(Tensor(cond), Tensor(x), Tensor(y))
80    print(output.asnumpy())
81    expect = [[12, 2], [1, 4]]
82    error = np.ones(shape=[2, 2]) * 1.0e-6
83    diff = output.asnumpy() - expect
84    assert np.all(diff < error)
85    assert np.all(-diff < error)
86