old_contents: """Configuration Addon."""
  #  Copyright 2015-present Scikit Flow 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 __future__ import division, print_function, absolute_import
  
  import tensorflow as tf
  
  class ConfigAddon(object):
      """This class specifies the specific configurations for a session.
  
      Parameters:
          num_cores: Number of cores to be used. (default: 4)
          verbose: Controls the verbosity, possible values:
                   0: the algorithm and debug information is muted.
                   1: trainer prints the progress.
                   2: log device placement is printed.
          gpu_memory_fraction: Fraction of GPU memory used by the process on
              each GPU uniformly on the same machine.
     """
  
      def __init__(self, num_cores=4, verbose=1, gpu_memory_fraction=1):
          gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_memory_fraction)
          self.config = tf.ConfigProto(log_device_placement=(verbose > 1),
                                       inter_op_parallelism_threads=num_cores,
                                       intra_op_parallelism_threads=num_cores,
                                       gpu_options=gpu_options)
      
new_contents: """Configuration Addon."""
  #  Copyright 2015-present Scikit Flow 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 __future__ import division, print_function, absolute_import
  
  import tensorflow as tf
  
  class ConfigAddon(object):
      """This class specifies the specific configurations for a session.
  
      Parameters:
          num_cores: Number of cores to be used. (default: 4)
          verbose: Controls the verbosity, possible values:
                   0: the algorithm and debug information is muted.
                   1: trainer prints the progress.
                   2: log device placement is printed.
          gpu_memory_fraction: Fraction of GPU memory used by the process on
              each GPU uniformly on the same machine.
     """
  
      def __init__(self, num_cores=4, verbose=1, gpu_memory_fraction=0.95):
          gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_memory_fraction)
          self.config = tf.ConfigProto(log_device_placement=(verbose > 1),
                                       inter_op_parallelism_threads=num_cores,
                                       intra_op_parallelism_threads=num_cores,
                                       gpu_options=gpu_options)
      
  
subject: Fix #134: change default gpu allocation from 1.0 to 0.95