forked from mindspore-Ecosystem/mindspore
91 lines
2.6 KiB
Python
91 lines
2.6 KiB
Python
# Copyright 2019 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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class Net_Pool(nn.Cell):
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def __init__(self):
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super(Net_Pool, self).__init__()
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self.maxpool_fun = nn.MaxPool2d(kernel_size=2, stride=2, pad_mode="VALID")
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def construct(self, x):
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return self.maxpool_fun(x)
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class Net_Pool2(nn.Cell):
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def __init__(self):
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super(Net_Pool2, self).__init__()
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self.maxpool_fun2 = nn.MaxPool2d(kernel_size=3, stride=2, pad_mode="SAME")
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def construct(self, x):
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return self.maxpool_fun2(x)
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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_maxpool2d():
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x = Tensor(np.array([[[
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[0, 1, 2, 3, -4, -5],
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[6, 7, 8, 9, -10, -11],
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[12, 13, 14, -15, -16, -17],
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[18, 19, 20, 21, 22, 23],
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[24, 25, 26, 27, 28, 29],
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[30, 31, 32, 33, 34, 35]
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]]]).astype(np.float32))
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maxpool2d = Net_Pool()
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maxpool2d2 = Net_Pool2()
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output2 = maxpool2d2(x)
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output = maxpool2d(x)
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expect_result = (np.array([[[
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[7, 9, -4],
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[19, 21, 23],
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[31, 33, 35]
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]]]))
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expect_result2 = (np.array([[[
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[14, 14, -4],
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[26, 28, 29],
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[32, 34, 35]
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]]]))
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print(output.asnumpy())
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assert (output.asnumpy() == expect_result).all()
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print(output2.asnumpy())
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assert (output2.asnumpy() == expect_result2).all()
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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_maxpool():
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x = Tensor(np.array([[[
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[0, 1, 2, 3, -4, -5],
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[6, 7, 8, 9, -10, -11],
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[12, 13, 14, -15, -16, -17],
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[18, 19, 20, 21, 22, 23],
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[24, 25, 26, 27, 28, 29],
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[30, 31, 32, 33, 34, 35]
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]]]).astype(np.int16))
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maxpool2d = Net_Pool()
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with pytest.raises(Exception):
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maxpool2d(x)
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