text: # Copyright 2019-2021 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
  from akg.utils import kernel_exec as utils
  from tests.common.tensorio import compare_tensor
  from akg.ops.math.ascend import AssignSub
  from tests.common.gen_random import random_gaussian
  
  def assign_sub_run(shape, dtype, attrs):
      if 'tuning' in attrs.keys():
          t = attrs.get("tuning", False)
          kernel_name = attrs.get("kernel_name", False)
          mod = utils.op_build_test(AssignSub, [shape, shape], [dtype, dtype], kernel_name=kernel_name, attrs=attrs,
                                    tuning=t)
          if t:
              expect, input1, input2, output = gen_data(dtype, shape)
              return mod, expect, (input1, input2, output)
          else:
              return mod
      else:
          mod = utils.op_build_test(AssignSub, [shape, shape], [dtype, dtype], kernel_name='assign_sub', attrs=attrs)
          expect, input1, input2, output = gen_data(dtype, shape)
          output = utils.mod_launch(mod, (input1, input2, output), expect=expect)
  
          return input1, output, expect, compare_tensor(output, expect, rtol=5e-03, equal_nan=True)
  
  
  def gen_data(dtype, shape):
      """ Generate data for testing the op """
      input1 = random_gaussian(shape, miu=1, sigma=0.1).astype(dtype)
      input2 = random_gaussian(shape, miu=1, sigma=0.1).astype(dtype)
      expect = np.subtract(input1, input2)
      output = np.full(shape, np.nan, dtype)
      return expect, input1, input2, output
  