forked from mindspore-Ecosystem/mindspore
61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
# Copyright 2022 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 as ms
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import mindspore.nn as nn
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import mindspore.ops as ops
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class Net(nn.Cell):
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def construct(self, x):
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out = ops.lp_pool2d(x, norm_type=1, kernel_size=3, stride=1)
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return out
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.platform_arm_cpu
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
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def test_lppool2d_normal(mode):
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"""
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Feature: LPPool2d
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Description: Verify the result of LPPool2d
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Expectation: success
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"""
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ms.set_context(mode=mode)
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net = Net()
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x = ms.Tensor(np.arange(2 * 3 * 4 * 5).reshape((2, 3, 4, 5)), dtype=ms.float32)
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out = net(x)
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expect_out = np.array([[[[54., 63., 72.],
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[99., 108., 117.]],
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[[234., 243., 252.],
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[279., 288., 297.]],
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[[414., 423., 432.],
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[459., 468., 477.]]],
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[[[594., 603., 612.],
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[639., 648., 657.]],
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[[774., 783., 792.],
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[819., 828., 837.]],
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[[954., 963., 972.],
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[999., 1008., 1017.]]]])
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assert np.allclose(out.asnumpy(), expect_out)
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