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