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Running
on
Zero
Running
on
Zero
| import spaces | |
| import argparse | |
| import os | |
| from util import util | |
| import torch | |
| import models | |
| import data | |
| class BaseOptions(): | |
| def __init__(self): | |
| self.initialized = False | |
| def initialize(self, parser): | |
| """Initialize options used during both training and test time.""" | |
| # Basic options | |
| parser.add_argument('--dataroot', required=False, help='path to images (should have subfolders trainA, trainB, valA, valB, etc)') | |
| parser.add_argument('--batch_size', type=int, default=2, help='input batch size') | |
| parser.add_argument('--load_size', type=int, default=512, help='scale images to this size') # Modified default | |
| parser.add_argument('--crop_size', type=int, default=1024, help='then crop to this size') # Modified default | |
| parser.add_argument('--input_nc', type=int, default=1, help='# of input image channels') # Modified default | |
| parser.add_argument('--output_nc', type=int, default=3, help='# of output image channels') # Modified default | |
| parser.add_argument('--nz', type=int, default=64, help='#latent vector') # Modified default | |
| parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0 0,1,2, 0,2, -1 for CPU mode') | |
| parser.add_argument('--name', type=str, default='color2manga_cycle_ganstft', help='name of the experiment') # Modified default | |
| parser.add_argument('--preprocess', type=str, default='none', help='not implemented') # Modified default | |
| parser.add_argument('--dataset_mode', type=str, default='aligned', help='aligned,single') | |
| parser.add_argument('--model', type=str, default='cycle_ganstft', help='chooses which model to use') | |
| parser.add_argument('--direction', type=str, default='BtoA', help='AtoB or BtoA') # Modified default | |
| parser.add_argument('--epoch', type=str, default='latest', help='which epoch to load? set to latest to use latest cached model') | |
| parser.add_argument('--num_threads', default=4, type=int, help='# threads for loading data') | |
| parser.add_argument('--local_rank', default=0, type=int, help='# threads for loading data') | |
| parser.add_argument('--checkpoints_dir', type=str, default=self.model_global_path+'/ScreenStyle/color2manga/', help='models are saved here') # Modified default | |
| parser.add_argument('--serial_batches', action='store_true', help='if true, takes images in order to make batches, otherwise takes them randomly') | |
| parser.add_argument('--use_dropout', action='store_true', help='use dropout for the generator') | |
| parser.add_argument('--max_dataset_size', type=int, default=float("inf"), help='Maximum number of samples allowed per dataset.') | |
| parser.add_argument('--no_flip', action='store_false', help='if specified, do not flip the images for data argumentation') # Modified default | |
| # Model parameters | |
| parser.add_argument('--level', type=int, default=0, help='level to train') | |
| parser.add_argument('--num_Ds', type=int, default=2, help='number of Discriminators') | |
| parser.add_argument('--netD', type=str, default='basic_256_multi', help='selects model to use for netD') | |
| parser.add_argument('--netD2', type=str, default='basic_256_multi', help='selects model to use for netD2') | |
| parser.add_argument('--netG', type=str, default='unet_256', help='selects model to use for netG') | |
| parser.add_argument('--netC', type=str, default='unet_128', help='selects model to use for netC') | |
| parser.add_argument('--netE', type=str, default='conv_256', help='selects model to use for netE') | |
| parser.add_argument('--nef', type=int, default=48, help='# of encoder filters in the first conv layer') # Modified default | |
| parser.add_argument('--ngf', type=int, default=48, help='# of gen filters in the last conv layer') # Modified default | |
| parser.add_argument('--ndf', type=int, default=32, help='# of discrim filters in the first conv layer') # Modified default | |
| parser.add_argument('--norm', type=str, default='layer', help='instance normalization or batch normalization') | |
| parser.add_argument('--upsample', type=str, default='bilinear', help='basic | bilinear') # Modified default | |
| parser.add_argument('--nl', type=str, default='prelu', help='non-linearity activation: relu | lrelu | elu') | |
| parser.add_argument('--no_encode', action='store_true', help='if specified, print more debugging information') | |
| parser.add_argument('--color2screen', action='store_true', help='continue training: load the latest model including RGB model') # Modified default | |
| # Extra parameters | |
| parser.add_argument('--where_add', type=str, default='all', help='input|all|middle; where to add z in the network G') | |
| parser.add_argument('--conditional_D', action='store_true', help='if use conditional GAN for D') | |
| parser.add_argument('--init_type', type=str, default='kaiming', help='network initialization [normal | xavier | kaiming | orthogonal]') | |
| parser.add_argument('--init_gain', type=float, default=0.02, help='scaling factor for normal, xavier and orthogonal.') | |
| parser.add_argument('--center_crop', action='store_true', help='if apply for center cropping for the test') # Modified default | |
| parser.add_argument('--verbose', action='store_true', help='if specified, print more debugging information') | |
| parser.add_argument('--suffix', default='', type=str, help='customized suffix: opt.name = opt.name + suffix: e.g., {model}_{netG}_size{load_size}') | |
| parser.add_argument('--display_winsize', type=int, default=256, help='display window size') | |
| # Special tasks | |
| self.initialized = True | |
| return parser | |
| def gather_options(self): | |
| """Initialize our parser with basic options (only once).""" | |
| if not self.initialized: | |
| parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) | |
| parser = self.initialize(parser) | |
| # Get the basic options | |
| opt, _ = parser.parse_known_args() | |
| # Modify model-related parser options | |
| model_name = opt.model | |
| model_option_setter = models.get_option_setter(model_name) | |
| parser = model_option_setter(parser, self.isTrain) | |
| opt, _ = parser.parse_known_args() # Parse again with new defaults | |
| # Modify dataset-related parser options | |
| dataset_name = opt.dataset_mode | |
| dataset_option_setter = data.get_option_setter(dataset_name) | |
| parser = dataset_option_setter(parser, self.isTrain) | |
| # Save and return the parser | |
| self.parser = parser | |
| return parser.parse_args() | |
| def print_options(self, opt): | |
| """Print and save options.""" | |
| message = '' | |
| message += '----------------- Options ---------------\n' | |
| for k, v in sorted(vars(opt).items()): | |
| comment = '' | |
| default = self.parser.get_default(k) | |
| if v != default: | |
| comment = '\t[default: %s]' % str(default) | |
| message += '{:>25}: {:<30}{}\n'.format(str(k), str(v), comment) | |
| message += '----------------- End -------------------' | |
| print(message) | |
| # Save to the disk | |
| expr_dir = os.path.join(opt.checkpoints_dir, opt.name) | |
| if not os.path.exists(expr_dir): | |
| try: | |
| util.mkdirs(expr_dir) | |
| except: | |
| pass | |
| file_name = os.path.join(expr_dir, 'opt.txt') | |
| with open(file_name, 'wt') as opt_file: | |
| opt_file.write(message) | |
| opt_file.write('\n') | |
| def parse(self, model_global_path): | |
| """Parse options, create checkpoints directory suffix, and set up gpu device.""" | |
| self.model_global_path = model_global_path | |
| opt = self.gather_options() | |
| opt.isTrain = self.isTrain # train or test | |
| # Process opt.suffix | |
| if opt.suffix: | |
| suffix = ('_' + opt.suffix.format(**vars(opt))) if opt.suffix != '' else '' | |
| opt.name = opt.name + suffix | |
| self.print_options(opt) | |
| # Set gpu ids | |
| str_ids = opt.gpu_ids.split(',') | |
| opt.gpu_ids = [] | |
| for str_id in str_ids: | |
| id = int(str_id) | |
| if id >= 0: | |
| opt.gpu_ids.append(id) | |
| if len(opt.gpu_ids) > 0: | |
| torch.cuda.set_device(opt.gpu_ids[0]) | |
| self.opt = opt | |
| return self.opt |