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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# ============================================================================
15import numpy as np
16import pytest
17import mindspore.context as context
18import mindspore.nn as nn
19from mindspore import Tensor
20import mindspore.common.dtype as mstype
21from mindspore.ops import operations as P
22
23context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
24
25
26class Net(nn.Cell):
27    def __init__(self):
28        super(Net, self).__init__()
29        self.unique = P.Unique().add_prim_attr("primitive_target", "CPU")
30
31    def construct(self, x):
32        x, y = self.unique(x)
33        return (x, y)
34
35
36class UniqueSquare(nn.Cell):
37    def __init__(self):
38        super(UniqueSquare, self).__init__()
39        self.unique = P.Unique().add_prim_attr("primitive_target", "CPU")
40        self.square = P.Square()
41
42    def construct(self, x):
43        x, _ = self.unique(x)
44        return self.square(x)
45
46
47@pytest.mark.level0
48@pytest.mark.platform_arm_ascend_training
49@pytest.mark.platform_x86_ascend_training
50@pytest.mark.env_onecard
51def test_unique_ascend():
52    x = Tensor(np.array([1, 1, 2, 2, 3, 3]), mstype.int32)
53    unique = Net()
54    output = unique(x)
55    expect1 = np.array([1, 2, 3])
56    expect2 = np.array([0, 0, 1, 1, 2, 2])
57    assert (output[0].asnumpy() == expect1).all()
58    assert (output[1].asnumpy() == expect2).all()
59
60
61@pytest.mark.level0
62@pytest.mark.platform_arm_ascend_training
63@pytest.mark.platform_x86_ascend_training
64@pytest.mark.env_onecard
65def test_unique_square():
66    x = Tensor(np.array([1, 1, 2, 2, 3, 3]), mstype.int32)
67    net = UniqueSquare()
68    output = net(x)
69    expect1 = np.array([1, 4, 9])
70    assert (output.asnumpy() == expect1).all()
71