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# 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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from mindspore.common import dtype as mstype
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class Slice(nn.Cell):
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def __init__(self):
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super(Slice, self).__init__()
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self.slice = P.Slice()
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def construct(self, x):
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return self.slice(x, (0, 1, 0), (2, 1, 3))
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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_slice():
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x = Tensor(
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np.array([[[1, -1, 1], [2, -2, 2]], [[3, -3, 3], [4, -4, 4]], [[5, -5, 5], [6, -6, 6]]]), mstype.float32)
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expect = [[[2., -2., 2.]],
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[[4., -4., 4.]]]
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slice_op = Slice()
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output = slice_op(x)
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print("output:\n", output)
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assert (output.asnumpy() == expect).all()
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if __name__ == '__main__':
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test_slice()
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