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configure.py
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configure.py
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# Copyright 2015 The TensorFlow 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.
# #############################################################################
# This is an implementaion of Convolutional Neural Netwroks for 3D volumes.
# The code is a modification of the code provided in TensorFlow tutorials for
# CIFAR-10 dataset.
# For help, please refer to the 'readme' file
# The code is modifed by: Mohamed ElMikaty
# Last update: 14 Dec 16
################################################################################
""" This module contains configurations for the dataset, training and evaluation
procedures.
"""
cfg = {'batch_size' : 128, # number of examples in a batch
'height' : 32, # height of the 3D volume
'width' : 32, # width of the 3D volume
'depth' : 32, # depth of the 3D volume
'nChan' : 1, # number of colour channels
'nClass' : 10, # number of classes
'nTrain' : 47892, # number of training examples
'nEval' : 10896, # number of evaluation examples
'nBatchBin' : 6, # number of binary files for training data
'data_dir' : 'x', # please specify full path
'train_ckpt_dir' : 'x', # please specify full path
'eval_ckpt_dir' : 'x', # please specify full path
'MOVING_AVERAGE_DECAY' : 0.9999, # The decay to use for the moving average.
'NUM_EPOCHS_PER_DECAY' : 350.0, # Epochs after which learning rate decays.
'LEARNING_RATE_DECAY_FACTOR' : 0.1, # Learning rate decay factor.
'INITIAL_LEARNING_RATE' : 0.1, # Initial learning rate.
'max_steps' : 2000,
'eval_interval_secs' : 60 * 5
}