mindspore/model_zoo/research/cv/IPT/src/args.py

"""args"""
# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 argparse

parser = argparse.ArgumentParser(description='EDSR and MDSR')

parser.add_argument('--debug', action='store_true',
                    help='Enables debug mode')
parser.add_argument('--template', default='.',
                    help='You can set various templates in option.py')

# Hardware specifications
parser.add_argument('--seed', type=int, default=1,
                    help='random seed')

# Data specifications
parser.add_argument('--dir_data', type=str, default='/cache/data/',
                    help='dataset directory')
parser.add_argument('--dir_demo', type=str, default='../test',
                    help='demo image directory')
parser.add_argument('--data_train', type=str, default='DIV2K',
                    help='train dataset name')
parser.add_argument('--data_test', type=str, default='DIV2K',
                    help='test dataset name')
parser.add_argument('--data_range', type=str, default='1-800/801-810',
                    help='train/test data range')
parser.add_argument('--ext', type=str, default='sep',
                    help='dataset file extension')
parser.add_argument('--scale', type=str, default='4',
                    help='super resolution scale')
parser.add_argument('--patch_size', type=int, default=48,
                    help='output patch size')
parser.add_argument('--rgb_range', type=int, default=255,
                    help='maximum value of RGB')
parser.add_argument('--n_colors', type=int, default=3,
                    help='number of color channels to use')
parser.add_argument('--chop', action='store_true',
                    help='enable memory-efficient forward')
parser.add_argument('--no_augment', action='store_true',
                    help='do not use data augmentation')

# Model specifications
parser.add_argument('--model', default='EDSR',
                    help='model name')
parser.add_argument('--act', type=str, default='relu',
                    help='activation function')
parser.add_argument('--pre_train', type=str, default='',
                    help='pre-trained model directory')
parser.add_argument('--extend', type=str, default='.',
                    help='pre-trained model directory')
parser.add_argument('--n_resblocks', type=int, default=16,
                    help='number of residual blocks')
parser.add_argument('--n_feats', type=int, default=64,
                    help='number of feature maps')
parser.add_argument('--res_scale', type=float, default=1,
                    help='residual scaling')
parser.add_argument('--shift_mean', default=True,
                    help='subtract pixel mean from the input')
parser.add_argument('--dilation', action='store_true',
                    help='use dilated convolution')
parser.add_argument('--precision', type=str, default='single',
                    choices=('single', 'half'),
                    help='FP precision for test (single | half)')

# Option for Residual dense network (RDN)
parser.add_argument('--G0', type=int, default=64,
                    help='default number of filters. (Use in RDN)')
parser.add_argument('--RDNkSize', type=int, default=3,
                    help='default kernel size. (Use in RDN)')
parser.add_argument('--RDNconfig', type=str, default='B',
                    help='parameters config of RDN. (Use in RDN)')

# Option for Residual channel attention network (RCAN)
parser.add_argument('--n_resgroups', type=int, default=10,
                    help='number of residual groups')
parser.add_argument('--reduction', type=int, default=16,
                    help='number of feature maps reduction')

# Training specifications
parser.add_argument('--reset', action='store_true',
                    help='reset the training')
parser.add_argument('--test_every', type=int, default=1000,
                    help='do test per every N batches')
parser.add_argument('--epochs', type=int, default=300,
                    help='number of epochs to train')
parser.add_argument('--batch_size', type=int, default=16,
                    help='input batch size for training')
parser.add_argument('--test_batch_size', type=int, default=1,
                    help='input batch size for training')
parser.add_argument('--split_batch', type=int, default=1,
                    help='split the batch into smaller chunks')
parser.add_argument('--self_ensemble', action='store_true',
                    help='use self-ensemble method for test')
parser.add_argument('--test_only', action='store_true',
                    help='set this option to test the model')
parser.add_argument('--gan_k', type=int, default=1,
                    help='k value for adversarial loss')

# Optimization specifications
parser.add_argument('--lr', type=float, default=1e-4,
                    help='learning rate')
parser.add_argument('--decay', type=str, default='200',
                    help='learning rate decay type')
parser.add_argument('--gamma', type=float, default=0.5,
                    help='learning rate decay factor for step decay')
parser.add_argument('--optimizer', default='ADAM',
                    choices=('SGD', 'ADAM', 'RMSprop'),
                    help='optimizer to use (SGD | ADAM | RMSprop)')
parser.add_argument('--momentum', type=float, default=0.9,
                    help='SGD momentum')
parser.add_argument('--betas', type=tuple, default=(0.9, 0.999),
                    help='ADAM beta')
parser.add_argument('--epsilon', type=float, default=1e-8,
                    help='ADAM epsilon for numerical stability')
parser.add_argument('--weight_decay', type=float, default=0,
                    help='weight decay')
parser.add_argument('--gclip', type=float, default=0,
                    help='gradient clipping threshold (0 = no clipping)')

# Loss specifications
parser.add_argument('--con_loss', action='store_true')
parser.add_argument('--loss', type=str, default='1*L1',
                    help='loss function configuration')
parser.add_argument('--skip_threshold', type=float, default='1e8',
                    help='skipping batch that has large error')

# Log specifications
parser.add_argument('--save', type=str, default='/cache/results/edsr_baseline_x2/',
                    help='file name to save')
parser.add_argument('--load', type=str, default='',
                    help='file name to load')
parser.add_argument('--resume', type=int, default=0,
                    help='resume from specific checkpoint')
parser.add_argument('--save_models', action='store_true',
                    help='save all intermediate models')
parser.add_argument('--print_every', type=int, default=100,
                    help='how many batches to wait before logging training status')
parser.add_argument('--save_results', action='store_true',
                    help='save output results')
parser.add_argument('--save_gt', action='store_true',
                    help='save low-resolution and high-resolution images together')

parser.add_argument('--scalelr', type=int, default=0)

# cloud
parser.add_argument('--moxfile', type=int, default=1)
parser.add_argument('--imagenet', type=int, default=0)
parser.add_argument('--data_url', type=str, help='path to dataset')
parser.add_argument('--train_url', type=str, help='train_dir')
parser.add_argument('--pretrain', type=str, default='')
parser.add_argument('--pth_path', type=str, default='')
parser.add_argument('--load_query', type=int, default=0)

# transformer
parser.add_argument('--patch_dim', type=int, default=3)
parser.add_argument('--num_heads', type=int, default=12)
parser.add_argument('--num_layers', type=int, default=4)
parser.add_argument('--dropout_rate', type=float, default=0)
parser.add_argument('--no_norm', action='store_true')
parser.add_argument('--post_norm', action='store_true')
parser.add_argument('--no_mlp', action='store_true')
parser.add_argument('--test', action='store_true')
parser.add_argument('--chop_new', action='store_true')
parser.add_argument('--pos_every', action='store_true')
parser.add_argument('--no_pos', action='store_true')
parser.add_argument('--num_queries', type=int, default=6)
parser.add_argument('--reweight', action='store_true')

# denoise
parser.add_argument('--denoise', action='store_true')
parser.add_argument('--sigma', type=float, default=25)

# derain
parser.add_argument('--derain', action='store_true')
parser.add_argument('--finetune', action='store_true')
parser.add_argument('--derain_test', type=int, default=10)

# alltask
parser.add_argument('--alltask', action='store_true')
parser.add_argument('--task_id', type=int, default=0)

# dehaze
parser.add_argument('--dehaze', action='store_true')
parser.add_argument('--dehaze_test', type=int, default=100)
parser.add_argument('--indoor', action='store_true')
parser.add_argument('--outdoor', action='store_true')
parser.add_argument('--nochange', action='store_true')

# deblur
parser.add_argument('--deblur', action='store_true')
parser.add_argument('--deblur_test', type=int, default=1000)

# distribute
parser.add_argument('--init_method', type=str,
                    default=None, help='master address')
parser.add_argument('--rank', type=int, default=0,
                    help='Index of current task')
parser.add_argument('--group_size', type=int, default=0,
                    help='Index of current task')
parser.add_argument('--world_size', type=int, default=1,
                    help='Total number of tasks')
parser.add_argument('--gpu', default=None, type=int,
                    help='GPU id to use.')
parser.add_argument('--dist-url', default='', type=str,
                    help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='nccl', type=str,
                    help='distributed backend')
parser.add_argument('-j', '--workers', default=4, type=int, metavar='N',
                    help='number of data loading workers (default: 4)')
parser.add_argument('--distribute', action='store_true')

args, unparsed = parser.parse_known_args()

args.scale = [int(x) for x in args.scale.split("+")]
args.data_train = args.data_train.split('+')
args.data_test = args.data_test.split('+')

if args.epochs == 0:
    args.epochs = 1e8

for arg in vars(args):
    if vars(args)[arg] == 'True':
        vars(args)[arg] = True
    elif vars(args)[arg] == 'False':
        vars(args)[arg] = False