config.py

# Copyright 2017 The BEGAN-tensorflow Authors(Taehoon Kim). 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.
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# http://www.apache.org/licenses/LICENSE-2.0
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# 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.
# ==============================================================================
# MIT License
#
# Modifications copyright (c) 2018 Image & Vision Computing Lab, Institute of Information Science, Academia Sinica
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
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# ==============================================================================
import argparse

def str2bool(v):
    return v.lower() in ('true', '1')

arg_lists = []
parser = argparse.ArgumentParser()

def add_argument_group(name):
    arg = parser.add_argument_group(name)
    arg_lists.append(arg)
    return arg

# Network
net_arg = add_argument_group('Network')
net_arg.add_argument('--input_scale_size', type=int, default=64,
                     help='input image will be resized with the given value as width and height')
net_arg.add_argument('--z_dim', type=int, default=128)

# Data
data_arg = add_argument_group('Data')
data_arg.add_argument('--dataset', type=str, default='marine')
data_arg.add_argument('--split', type=str, default='train')
data_arg.add_argument('--batch_size', type=int, default=16)


# Training / test parameters
train_arg = add_argument_group('Training')
train_arg.add_argument('--is_train', type=str2bool, default=True)
train_arg.add_argument('--max_step', type=int, default=500000)
train_arg.add_argument('--lr_update_step', type=int, default=200000)
train_arg.add_argument('--lr_lower_boundary', type=float, default=0.000001)
train_arg.add_argument('--z_lr', type=float, default=0.0008)
train_arg.add_argument('--g_lr', type=float, default=0.00008)
train_arg.add_argument('--beta1', type=float, default=0.5)
train_arg.add_argument('--beta2', type=float, default=0.999)


# Misc
misc_arg = add_argument_group('Misc')
misc_arg.add_argument('--load_path', type=str, default='')
misc_arg.add_argument('--log_step', type=int, default=100)
misc_arg.add_argument('--log_dir', type=str, default='logs')
misc_arg.add_argument('--data_dir', type=str, default='data')
misc_arg.add_argument('--random_seed', type=int, default=123)
misc_arg.add_argument('--p_data_dir', type=str, default='./data/string_data/training_p')
misc_arg.add_argument('--n_data_dir', type=str, default='./data/string_data/n_patches')

def get_config():
    config, unparsed = parser.parse_known_args()
    data_format = 'NCHW'
    setattr(config, 'data_format', data_format)
    return config, unparsed