text: """
  Copyright 2020 The OneFlow Authors. All rights reserved.
  
  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.
  """
  from collections import OrderedDict
  
  import oneflow as flow
  import numpy as np
  import oneflow.typing as oft
  import test_global_storage
  from test_util import GenArgDict
  
  
  def _test_logical_slice(
      test_case, var_shape, slice_tuples, split_axis, device_tag, flow_dtype, device_num
  ):
      flow.clear_default_session()
      if device_tag == "gpu":
          flow.config.gpu_device_num(device_num)
  
      @flow.global_function()
      def slice_fn():
          with flow.scope.placement(device_tag, "0:0-{}".format(device_num - 1)):
              var = flow.get_variable(
                  name="var",
                  shape=var_shape,
                  dtype=flow_dtype,
                  initializer=flow.random_uniform_initializer(-10, 10, dtype=flow_dtype),
                  distribute=flow.distribute.split(split_axis),
              )
              flow.watch(var, test_global_storage.Setter("var"))
              ret = flow.experimental.logical_slice(var, slice_tuples)
              return ret
  
      checkpoint = flow.train.CheckPoint()
      checkpoint.init()
  
      of_res = slice_fn().get().numpy()
  
      var_np = test_global_storage.Get("var")
      slice_objs = []
      for s in slice_tuples:
          slice_objs.append(slice(s[0], s[1], s[2]))
      test_case.assertTrue(np.array_equal(of_res, var_np[tuple(slice_objs)]))
  
  
  class TestLogicalSlice(flow.unittest.TestCase):
      @flow.unittest.skip_unless_1n2d()
      def test_logical_slice_4dim_2d(test_case):
          var_shape = (30, 40, 20, 15)
          slice_tuples = [(10, 20, 3), (1, 30, 4), (3, 16, 2), (5, 11, 1)]
          arg_dict = OrderedDict()
          arg_dict["split_axis"] = list(range(4))
          arg_dict["device_tag"] = ["cpu", "gpu"]
          arg_dict["flow_dtype"] = [flow.float, flow.int8]
          arg_dict["device_num"] = [2]
          for arg in GenArgDict(arg_dict):
              _test_logical_slice(test_case, var_shape, slice_tuples, **arg)
  
      @flow.unittest.skip_unless_1n4d()
      def test_logical_slice_negative_start_stop_4dim_4d(test_case):
          var_shape = (30, 40, 20, 15)
          slice_tuples = [(10, None, 3), (1, -10, 4), (-15, -5, 2), (5, 11, 1)]
          arg_dict = OrderedDict()
          arg_dict["split_axis"] = list(range(4))
          arg_dict["device_tag"] = ["cpu", "gpu"]
          arg_dict["flow_dtype"] = [flow.float]
          arg_dict["device_num"] = [4]
          for arg in GenArgDict(arg_dict):
              _test_logical_slice(test_case, var_shape, slice_tuples, **arg)
  
      @flow.unittest.skip_unless_1n4d()
      def test_logical_slice_2dim_3d(test_case):
          var_shape = (30, 40)
          slice_tuples = [(10, 20, 3), (1, 30, 4)]
          arg_dict = OrderedDict()
          arg_dict["split_axis"] = list(range(2))
          arg_dict["device_tag"] = ["cpu", "gpu"]
          arg_dict["flow_dtype"] = [flow.float]
          arg_dict["device_num"] = [3]
          for arg in GenArgDict(arg_dict):
              _test_logical_slice(test_case, var_shape, slice_tuples, **arg)
  