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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"""
16test pooling api
17"""
18import numpy as np
19import pytest
20
21import mindspore.nn as nn
22from mindspore import Tensor
23
24
25def test_avgpool2d():
26    """ test_avgpool2d """
27    kernel_size = 3
28    stride = 2
29    avg_pool = nn.AvgPool2d(kernel_size, stride)
30    assert avg_pool.kernel_size == 3
31    assert avg_pool.stride == 2
32    input_data = Tensor(np.random.randint(0, 255, [1, 3, 6, 6]) * 0.1)
33    output = avg_pool(input_data)
34    output_np = output.asnumpy()
35    assert isinstance(output_np[0][0][0][0], (np.float32, np.float64))
36
37
38def test_avgpool2d_error_input():
39    """ test_avgpool2d_error_input """
40    kernel_size = 5
41    stride = 2.3
42    with pytest.raises(TypeError):
43        nn.AvgPool2d(kernel_size, stride)
44
45
46def test_maxpool2d():
47    """ test_maxpool2d """
48    kernel_size = 3
49    stride = 3
50
51    max_pool = nn.MaxPool2d(kernel_size, stride, pad_mode='SAME')
52    assert max_pool.kernel_size == 3
53    assert max_pool.stride == 3
54    input_data = Tensor(np.random.randint(0, 255, [1, 3, 6, 6]) * 0.1)
55    output = max_pool(input_data)
56    output_np = output.asnumpy()
57    assert isinstance(output_np[0][0][0][0], (np.float32, np.float64))
58