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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- """
- test pooling api
- """
- import numpy as np
- import pytest
-
- import mindspore.nn as nn
- from mindspore import Tensor
-
- def test_avgpool2d():
- """ test_avgpool2d """
- kernel_size = 3
- stride = 2
- avg_pool = nn.AvgPool2d(kernel_size, stride)
- assert avg_pool.kernel_size == 3
- assert avg_pool.stride == 2
- input_data = Tensor(np.random.randint(0, 255, [1, 3, 6, 6])*0.1)
- output = avg_pool(input_data)
- output_np = output.asnumpy()
- assert isinstance(output_np[0][0][0][0], (np.float32, np.float64))
-
-
- def test_avgpool2d_error_input():
- """ test_avgpool2d_error_input """
- kernel_size = 5
- stride = 2.3
- with pytest.raises(TypeError):
- nn.AvgPool2d(kernel_size, stride)
-
-
-
-
-
- def test_maxpool2d():
- """ test_maxpool2d """
- kernel_size = 3
- stride = 3
-
- max_pool = nn.MaxPool2d(kernel_size, stride, pad_mode='SAME')
- assert max_pool.kernel_size == 3
- assert max_pool.stride == 3
- input_data = Tensor(np.random.randint(0, 255, [1, 3, 6, 6])*0.1)
- output = max_pool(input_data)
- output_np = output.asnumpy()
- assert isinstance(output_np[0][0][0][0], (np.float32, np.float64))
-
-
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