text: # 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 mindspore.context as context
  import mindspore.nn as nn
  from mindspore import Tensor
  from mindspore.ops import operations as P
  
  context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
  
  
  class Net(nn.Cell):
      def __init__(self, begin, end, strides):
          super(Net, self).__init__()
          self.strided_slice = P.StridedSlice()
          self.begin = begin
          self.end = end
          self.strides = strides
  
      def construct(self, input):
          return self.strided_slice(input, self.begin, self.end, self.strides)
  
  
  input_x = np.array([[[0, 1, 2], [3, 4, 5]],
                      [[6, 7, 8], [9, 10, 11]],
                      [[12, 13, 14], [15, 16, 17]]
                     ]).astype(np.float32)
  begin = (1, 0, 0)
  end = (2, 2, 3)
  strides = (1, 1, 2)
  
  
  def test_net():
      net = Net(begin, end, strides)
      tinput = Tensor(input_x)
      output = net(tinput)
      print(output.asnumpy())
      assert np.all([[[6, 8], [9, 11]]] == output.asnumpy())
  