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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.ops = P.Pow()
29
30    def construct(self, x, y):
31        return self.ops(x, y)
32
33
34@pytest.mark.level0
35@pytest.mark.platform_x86_cpu
36@pytest.mark.env_onecard
37def test_net():
38    x0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
39    y0_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
40    x1_np = np.random.randint(1, 5, (2, 3, 4, 4)).astype(np.float32)
41    y1_np = np.array(3).astype(np.float32)
42
43    x0 = Tensor(x0_np)
44    y0 = Tensor(y0_np)
45    x1 = Tensor(x1_np)
46    y1 = Tensor(y1_np)
47
48    context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
49    net = Net()
50    out = net(x0, y0).asnumpy()
51    expect = np.power(x0_np, y0_np)
52    assert np.all(out == expect)
53    assert out.shape == expect.shape
54
55    out = net(x1, y1).asnumpy()
56    expect = np.power(x1_np, y1_np)
57    assert np.all(out == expect)
58    assert out.shape == expect.shape
59