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95 lines
2.9 KiB
95 lines
2.9 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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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_avgpool_k2s1pv():
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x = np.arange(1 * 1 * 6 * 6).reshape((1, 1, 6, 6)).astype(np.float32)
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net = nn.AvgPool2d(kernel_size=2, stride=1, pad_mode='valid')
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out = net(Tensor(x))
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print(out)
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expect_result = np.array(
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[[[[3.5, 4.5, 5.5, 6.5, 7.5],
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[9.5, 10.5, 11.5, 12.5, 13.5],
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[15.5, 16.5, 17.5, 18.5, 19.5],
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[21.5, 22.5, 23.5, 24.5, 25.5],
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[27.5, 28.5, 29.5, 30.5, 31.5]]]]
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)
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assert np.allclose(out.asnumpy(), expect_result)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_avgpool_k2s2pv():
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x = np.arange(1 * 1 * 6 * 6).reshape((1, 1, 6, 6)).astype(np.float32)
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net = nn.AvgPool2d(kernel_size=2, stride=2, pad_mode='valid')
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out = net(Tensor(x))
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print(out)
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expect_result = np.array(
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[[[[3.5, 5.5, 7.5],
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[15.5, 17.5, 19.5],
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[27.5, 29.5, 31.5]]]]
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)
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assert np.allclose(out.asnumpy(), expect_result)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_avgpool_k3s2pv():
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x = np.arange(1 * 1 * 6 * 6).reshape((1, 1, 6, 6)).astype(np.float32)
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net = nn.AvgPool2d(kernel_size=3, stride=2, pad_mode='valid')
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out = net(Tensor(x))
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print(out)
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expect_result = np.array(
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[[[[7., 9.],
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[19., 21.]]]]
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)
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assert np.allclose(out.asnumpy(), expect_result)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_avgpool_k3s2ps():
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x = np.arange(1 * 1 * 6 * 6).reshape((1, 1, 6, 6)).astype(np.float32)
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net = nn.AvgPool2d(kernel_size=3, stride=2, pad_mode='same')
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out = net(Tensor(x))
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print(out)
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expect_result = np.array(
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[[[[7., 9., 10.5],
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[19., 21., 22.5],
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[28., 30., 31.5]]]]
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)
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assert np.allclose(out.asnumpy(), expect_result)
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if __name__ == '__main__':
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test_avgpool_k2s1pv()
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test_avgpool_k2s2pv()
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test_avgpool_k3s2pv()
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test_avgpool_k3s2ps()
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