old_contents: # Copyright (c) 2016 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.
  import os
  import optimizer
  import layer
  import activation
  import parameters
  import trainer
  import event
  import data_type
  import topology
  import data_feeder
  import networks
  import evaluator
  from . import dataset
  from . import reader
  from . import plot
  import attr
  import pooling
  import inference
  import networks
  import py_paddle.swig_paddle as api
  import minibatch
  import plot
  
  __all__ = [
      'optimizer', 'layer', 'activation', 'parameters', 'init', 'trainer',
      'event', 'data_type', 'attr', 'pooling', 'data_feeder', 'dataset', 'reader',
      'topology', 'networks', 'infer', 'plot', 'evaluator'
  ]
  
  
  def init(**kwargs):
      args = []
      # NOTE: append arguments if they are in ENV
      for ek, ev in os.environ.iteritems():
          if ek.startswith("PADDLE_"):
              args.append('--%s=%s' % (ek.replace("PADDLE_", "").lower(), str(ev)))
  
      # NOTE: overwrite arguments from ENV if it is in kwargs
      for key in kwargs.keys():
          args.append('--%s=%s' % (key, str(kwargs[key])))
  
      api.initPaddle(*args)
  
  
  infer = inference.infer
  batch = minibatch.batch
  
new_contents: # Copyright (c) 2016 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.
  import os
  import optimizer
  import layer
  import activation
  import parameters
  import trainer
  import event
  import data_type
  import topology
  import data_feeder
  import networks
  import evaluator
  from . import dataset
  from . import reader
  from . import plot
  import attr
  import pooling
  import inference
  import networks
  import py_paddle.swig_paddle as api
  import minibatch
  import plot
  
  __all__ = [
      'optimizer', 'layer', 'activation', 'parameters', 'init', 'trainer',
      'event', 'data_type', 'attr', 'pooling', 'data_feeder', 'dataset', 'reader',
      'topology', 'networks', 'infer', 'plot', 'evaluator'
  ]
  
  
  def init(**kwargs):
      args = []
      # NOTE: append arguments if they are in ENV
      for ek, ev in os.environ.iteritems():
          if ek.startswith("PADDLE_"):
              args.append('--%s=%s' % (ek.replace("PADDLE_", "").lower(),
                                       str(ev)))
  
      # NOTE: overwrite arguments from ENV if it is in kwargs
      for key in kwargs.keys():
          args.append('--%s=%s' % (key, str(kwargs[key])))
  
      api.initPaddle(*args)
  
  
  infer = inference.infer
  batch = minibatch.batch
  
subject: update for pre-commit