GoodWin/Deep-Multi-scale

1import argparse2import os3from util import util4import torch5import models6import data7 8 9class BaseOptions():10    def __init__(self):11        self.initialized = False12 13    def initialize(self, parser):14        15        parser.add_argument('--batchSize', type=int, default=2, help='input batch size')16        parser.add_argument('--ngf', type=int, default=64, help='# of gen filters in first conv layer')17        parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')18        parser.add_argument('--name', type=str, default='facefh_dictionary', help='name of the experiment. It decides where to store samples and models')19        parser.add_argument('--model', type=str, default='faceDict', help='chooses which model to use. cycle_gan, pix2pix, test')20        parser.add_argument('--which_direction', type=str, default='BtoA', help='AtoB or BtoA')21        parser.add_argument('--nThreads', default=8, type=int, help='# threads for loading data')22        parser.add_argument('--checkpoints_dir', type=str, default='./checkpoints', help='models are saved here')23        parser.add_argument('--norm', type=str, default='instance', help='instance normalization or batch normalization')24        parser.add_argument('--serial_batches', action='store_true', help='if true, takes images in order to make batches, otherwise takes them randomly')25        parser.add_argument('--resize_or_crop', type=str, default='degradation', help='scaling and cropping of images at load time [resize_and_crop|crop|scale_width|scale_width_and_crop]')26        parser.add_argument('--init_type', type=str, default='kaiming', help='network initialization [normal|xavier|kaiming|orthogonal]')27        parser.add_argument('--init_gain', type=float, default=0.02, help='scaling factor for normal, xavier and orthogonal.')28        parser.add_argument('--verbose', action='store_true', help='if specified, print more debugging information')29        parser.add_argument('--suffix', default='', type=str, help='customized suffix: opt.name = opt.name + suffix: e.g., {model}_{which_model_netG}_size{loadSize}')30        self.initialized = True31        return parser32 33    def gather_options(self):34        # initialize parser with basic options35        if not self.initialized:36            parser = argparse.ArgumentParser(37                formatter_class=argparse.ArgumentDefaultsHelpFormatter)38            parser = self.initialize(parser)39 40        # get the basic options41        42        opt, _ = parser.parse_known_args()43        # modify model-related parser options44        model_name = opt.model45        model_option_setter = models.get_option_setter(model_name)46        parser = model_option_setter(parser, self.isTrain)47 48        opt, _ = parser.parse_known_args()  # parse again with the new defaults49 50        # modify dataset-related parser options51        dataset_name = opt.dataset_mode52 53        dataset_option_setter = data.get_option_setter(dataset_name)54        parser = dataset_option_setter(parser, self.isTrain)55 56        self.parser = parser57 58        return parser.parse_args()59 60    def print_options(self, opt):61        message = ''62        message += '----------------- Options ---------------\n'63        for k, v in sorted(vars(opt).items()):64            comment = ''65            default = self.parser.get_default(k)66            if v != default:67                comment = '\t[default: %s]' % str(default)68            message += '{:>25}: {:<30}{}\n'.format(str(k), str(v), comment)69        message += '----------------- End -------------------'70        print(message)71 72        # save to the disk73        expr_dir = os.path.join(opt.checkpoints_dir, opt.name)74        util.mkdirs(expr_dir)75        file_name = os.path.join(expr_dir, 'opt.txt')76        with open(file_name, 'wt') as opt_file:77            opt_file.write(message)78            opt_file.write('\n')79 80    def parse(self):81 82        opt = self.gather_options()83        opt.isTrain = self.isTrain   # train or test84 85        # process opt.suffix86        if opt.suffix:87            suffix = ('_' + opt.suffix.format(**vars(opt))) if opt.suffix != '' else ''88            opt.name = opt.name + suffix89 90        # self.print_options(opt)91 92        # set gpu ids93        str_ids = opt.gpu_ids.split(',')94        opt.gpu_ids = []95        for str_id in str_ids:96            id = int(str_id)97            if id >= 0:98                opt.gpu_ids.append(id)99        if len(opt.gpu_ids) > 0:100            torch.cuda.set_device(opt.gpu_ids[0])101 102        self.opt = opt103        return self.opt104