text: # Copyright 2021 Sony Corporation.
  # Copyright 2021 Sony Group Corporation.
  #
  # 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.
  
  #
  # *WARNING*
  # THIS FILE IS AUTO-GENERATED BY CODE GENERATOR.
  # 1. IMPLEMENT BACKWARD WRT INPUTS OF THE CORRESPONDING FUNCTION
  # 2. IMPLEMENT BACKWARD_FUNCTION_CLASS IF NECESSARY (see e.g., affine.py)
  # 3. UPDATE THE MAPPING IF NECESSARY (see function_backward_functions.py.tmpl)
  
  
  import nnabla.functions as F
  
  
  def cumsum_backward(inputs, axis=None, exclusive=False, reverse=False):
      """
      Args:
        inputs (list of nn.Variable): Incomming grads/inputs to/of the forward function.
        kwargs (dict of arguments): Dictionary of the corresponding function arguments.
  
      Return:
        list of Variable: Return the gradients wrt inputs of the corresponding function.
      """
      dy = inputs[0]
      dx = F.cumsum(dy, axis=axis, exclusive=exclusive, reverse=not reverse)
      return dx
  