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1# Copyright 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
19import mindspore.nn as nn
20from mindspore import Tensor
21from mindspore.ops import operations as P
22
23
24class ReduceMax(nn.Cell):
25    def __init__(self, keep_dims):
26        super(ReduceMax, self).__init__()
27        self.reduce_max = P.ReduceMax(keep_dims)
28
29    def construct(self, x, axis):
30        return self.reduce_max(x, axis)
31
32
33def get_output(x, axis, keep_dims, enable_graph_kernel=False):
34    context.set_context(enable_graph_kernel=enable_graph_kernel)
35    net = ReduceMax(keep_dims)
36    output = net(x, axis)
37    return output
38
39
40def test_reduce_max():
41    x0 = Tensor(np.random.normal(0, 1, [2, 3, 4, 4]).astype(np.float32))
42    axis0 = 3
43    keep_dims0 = True
44    expect = get_output(x0, axis0, keep_dims0, False)
45    output = get_output(x0, axis0, keep_dims0, True)
46    assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
47
48    x1 = Tensor(np.random.normal(0, 1, [2, 3, 4, 4]).astype(np.float32))
49    axis1 = 3
50    keep_dims1 = False
51    expect = get_output(x1, axis1, keep_dims1, False)
52    output = get_output(x1, axis1, keep_dims1, True)
53    assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
54
55    x2 = Tensor(np.random.normal(0, 1, [2, 3, 1, 4]).astype(np.float32))
56    axis2 = 2
57    keep_dims2 = True
58    expect = get_output(x2, axis2, keep_dims2, False)
59    output = get_output(x2, axis2, keep_dims2, True)
60    assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
61
62
63@pytest.mark.level0
64@pytest.mark.platform_x86_gpu_training
65@pytest.mark.env_onecard
66def test_reduce_max_gpu():
67    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
68    test_reduce_max()
69