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1# Copyright 2020-2021 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
18import mindspore.context as context
19from mindspore import Tensor
20from mindspore.nn import Cell
21import mindspore.ops.operations as P
22from mindspore.ops.operations import _grad_ops as G
23
24
25class Net(Cell):
26    def __init__(self):
27        super(Net, self).__init__()
28        self.add = P.Add()
29        self.sub = P.Sub()
30        self.mul = P.Mul()
31        self.sqrt_grad = G.SqrtGrad()
32
33    def construct(self, x, y, z):
34        sub_res = self.sub(x, y)
35        mul_res = self.mul(sub_res, x)
36        sqrt_grad_res = self.sqrt_grad(mul_res, z)
37        square_res = P.Square()(sqrt_grad_res)
38        add_res = self.add(sqrt_grad_res, square_res)
39        add1_res = self.add(add_res, add_res)
40        return self.add(add1_res, add1_res)
41
42
43def get_output(i0, i1, i2, enable_graph_kernel=False):
44    context.set_context(enable_graph_kernel=enable_graph_kernel)
45    net = Net()
46    output = net(i0, i1, i2)
47    return output
48
49
50def test_basic():
51    i0 = Tensor(np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32))
52    i1 = Tensor(np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32))
53    i2 = Tensor(np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32))
54
55    expect = get_output(i0, i1, i2, False)
56    output = get_output(i0, i1, i2, True)
57
58    expect_np = expect.asnumpy().copy()
59    output_np = output.asnumpy().copy()
60
61    assert np.allclose(expect_np, output_np, 1.e-4, 1.e-7)
62
63
64@pytest.mark.level0
65@pytest.mark.platform_x86_gpu_training
66@pytest.mark.env_onecard
67def test_basic_gpu():
68    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
69    test_basic()
70
71
72@pytest.mark.level0
73@pytest.mark.platform_arm_ascend_training
74@pytest.mark.platform_x86_ascend_training
75@pytest.mark.env_onecard
76def test_basic_ascend():
77    context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
78    test_basic()
79