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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.common import dtype as mstype
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
-
- class Slice(nn.Cell):
- def __init__(self):
- super(Slice, self).__init__()
- self.slice = P.Slice()
-
- def construct(self, x):
- return self.slice(x, (0, 1, 0), (2, 1, 3))
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_cpu
- @pytest.mark.env_onecard
- def test_slice():
- x = Tensor(
- np.array([[[1, -1, 1], [2, -2, 2]], [[3, -3, 3], [4, -4, 4]], [[5, -5, 5], [6, -6, 6]]]), mstype.float32)
- expect = [[[2., -2., 2.]],
- [[4., -4., 4.]]]
-
- slice_op = Slice()
- output = slice_op(x)
- print("output:\n", output)
- assert (output.asnumpy() == expect).all()
-
-
- if __name__ == '__main__':
- test_slice()
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