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.
  # ============================================================================
  from mindspore import Tensor
  from mindspore.ops import operations as P
  from mindspore.ops.operations import _grad_ops as G
  import mindspore.nn as nn
  from mindspore.common.api import ms_function
  import numpy as np
  import mindspore.context as context
  from mindspore.common.initializer import initializer
  from mindspore.common.parameter import Parameter
  context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
  class Net(nn.Cell):
      def __init__(self):
          super(Net, self).__init__()
          self.bias_add_grad = G.BiasAddGrad()
  
      @ms_function
      def construct(self, dout):
          return self.bias_add_grad(dout)
  
  def test_net():
      dout = np.random.rand(1, 1001).astype(np.float32)
      bias_add_grad = Net()
      output = bias_add_grad(Tensor(dout))
      print(output.asnumpy())
  