old_contents: #   Copyright (c) 2018 PaddlePaddle 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 layer_function_generator import generate_layer_fn
  
  __activations__ = [
      'sigmoid',
      'logsigmoid',
      'exp',
      'relu',
      'tanh',
      'tanh_shrink',
      'softshrink',
      'sqrt',
      'abs',
      'ceil',
      'floor',
      'round',
      'reciprocal',
      'log',
      'square',
      'softplus',
      'softsign',
      'brelu',
      'leaky_relu',
      'soft_relu',
      'elu',
      'relu6',
      'pow',
      'stanh',
      'hard_shrink',
      'thresholded_relu',
      'hard_sigmoid',
      'swish',
  ]
  
  __all__ = [
      'mean', 'mul', 'reshape', 'scale', 'sigmoid_cross_entropy_with_logits',
      'elementwise_add', 'elementwise_div', 'elementwise_sub', 'elementwise_mul',
      'elementwise_max', 'elementwise_min', 'elementwise_pow', 'clip',
      'clip_by_norm', 'softmax', 'sequence_softmax', 'logical_and', 'logical_or',
      'logical_xor', 'logical_not', 'uniform_random',
      'uniform_random_batch_size_like', 'gaussian_random',
      'gaussian_random_batch_size_like', 'cumsum', 'scatter'
  ] + __activations__
  
  for _OP in set(__all__):
      globals()[_OP] = generate_layer_fn(_OP)
  
new_contents: #   Copyright (c) 2018 PaddlePaddle 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 layer_function_generator import generate_layer_fn
  
  __activations__ = [
      'sigmoid',
      'logsigmoid',
      'exp',
      'relu',
      'tanh',
      'tanh_shrink',
      'softshrink',
      'sqrt',
      'abs',
      'ceil',
      'floor',
      'round',
      'reciprocal',
      'log',
      'square',
      'softplus',
      'softsign',
      'brelu',
      'leaky_relu',
      'soft_relu',
      'elu',
      'relu6',
      'pow',
      'stanh',
      'hard_shrink',
      'thresholded_relu',
      'hard_sigmoid',
      'swish',
  ]
  
  __all__ = [
      'mean', 'mul', 'reshape', 'scale', 'sigmoid_cross_entropy_with_logits',
      'elementwise_add', 'elementwise_div', 'elementwise_sub', 'elementwise_mul',
      'elementwise_max', 'elementwise_min', 'elementwise_pow', 'clip',
      'clip_by_norm', 'softmax', 'sequence_softmax', 'logical_and', 'logical_or',
      'logical_xor', 'logical_not', 'uniform_random',
      'uniform_random_batch_size_like', 'gaussian_random',
      'gaussian_random_batch_size_like', 'cumsum', 'scatter', 'sum'
  ] + __activations__
  
  for _OP in set(__all__):
      globals()[_OP] = generate_layer_fn(_OP)
  
subject: Add python API for sum op.