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.
  
  """operator dsl function: notequal"""
  import akg.tvm
  import akg.topi
  from akg.utils.dsl_create import produce_shapes
  from akg.utils import validation_check as vc_util
  
  
  @vc_util.check_input_type(akg.tvm.tensor.Tensor, akg.tvm.tensor.Tensor)
  def notequal(input1, input2):
      """
      check whether input1 notequals to input2.
  
      Args:
          input1 (tvm.tensor.Tensor): Tensor.
          input2 (tvm.tensor.Tensor): Tensor.
  
      Returns:
          tvm.tensor.Tensor. If input1 notequal to input2 return True, else return False.
      """
      shape1 = [x.value for x in input1.shape]
      shape2 = [x.value for x in input2.shape]
      vc_util.check_shape(shape1)
      vc_util.check_shape(shape2)
  
      shape1, shape2, shape = produce_shapes(shape1, shape2)
  
      vc_util.elemwise_dtype_check(input1.dtype, input2.dtype)
      dtype = input1.dtype
  
      # get notequal compute
      t_value = akg.tvm.compute(shape, lambda *indice: akg.tvm.const(1, dtype), "T")
      f_value = akg.tvm.compute(shape, lambda *indice: akg.tvm.const(0, dtype), "F")
  
      input1_bro = akg.topi.broadcast_to(input1, shape)
      input2_bro = akg.topi.broadcast_to(input2, shape)
      c_out = akg.tvm.compute(shape, lambda *indice: akg.tvm.expr.Select(input1_bro[indice] != input2_bro[indice],
                                                                           t_value[indice], f_value[indice]), name="C")
      res = akg.tvm.compute(shape, lambda *indice: c_out(*indice).astype("bool"), name="res")
  
      return res
  