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| """ | |
| This file runs the main training/val loop | |
| """ | |
| import os | |
| import json | |
| import math | |
| import sys | |
| import pprint | |
| import torch | |
| from argparse import Namespace | |
| sys.path.append(".") | |
| sys.path.append("..") | |
| from options.train_options import TrainOptions | |
| from training.coach import Coach | |
| def main(): | |
| opts = TrainOptions().parse() | |
| previous_train_ckpt = None | |
| if opts.resume_training_from_ckpt: | |
| opts, previous_train_ckpt = load_train_checkpoint(opts) | |
| else: | |
| setup_progressive_steps(opts) | |
| create_initial_experiment_dir(opts) | |
| coach = Coach(opts, previous_train_ckpt) | |
| coach.train() | |
| def load_train_checkpoint(opts): | |
| train_ckpt_path = opts.resume_training_from_ckpt | |
| previous_train_ckpt = torch.load(opts.resume_training_from_ckpt, map_location='cpu') | |
| new_opts_dict = vars(opts) | |
| opts = previous_train_ckpt['opts'] | |
| opts['resume_training_from_ckpt'] = train_ckpt_path | |
| update_new_configs(opts, new_opts_dict) | |
| pprint.pprint(opts) | |
| opts = Namespace(**opts) | |
| if opts.sub_exp_dir is not None: | |
| sub_exp_dir = opts.sub_exp_dir | |
| opts.exp_dir = os.path.join(opts.exp_dir, sub_exp_dir) | |
| create_initial_experiment_dir(opts) | |
| return opts, previous_train_ckpt | |
| def setup_progressive_steps(opts): | |
| log_size = int(math.log(opts.stylegan_size, 2)) | |
| num_style_layers = 2*log_size - 2 | |
| num_deltas = num_style_layers - 1 | |
| if opts.progressive_start is not None: # If progressive delta training | |
| opts.progressive_steps = [0] | |
| next_progressive_step = opts.progressive_start | |
| for i in range(num_deltas): | |
| opts.progressive_steps.append(next_progressive_step) | |
| next_progressive_step += opts.progressive_step_every | |
| assert opts.progressive_steps is None or is_valid_progressive_steps(opts, num_style_layers), \ | |
| "Invalid progressive training input" | |
| def is_valid_progressive_steps(opts, num_style_layers): | |
| return len(opts.progressive_steps) == num_style_layers and opts.progressive_steps[0] == 0 | |
| def create_initial_experiment_dir(opts): | |
| if os.path.exists(opts.exp_dir): | |
| raise Exception('Oops... {} already exists'.format(opts.exp_dir)) | |
| os.makedirs(opts.exp_dir) | |
| opts_dict = vars(opts) | |
| pprint.pprint(opts_dict) | |
| with open(os.path.join(opts.exp_dir, 'opt.json'), 'w') as f: | |
| json.dump(opts_dict, f, indent=4, sort_keys=True) | |
| def update_new_configs(ckpt_opts, new_opts): | |
| for k, v in new_opts.items(): | |
| if k not in ckpt_opts: | |
| ckpt_opts[k] = v | |
| if new_opts['update_param_list']: | |
| for param in new_opts['update_param_list']: | |
| ckpt_opts[param] = new_opts[param] | |
| if __name__ == '__main__': | |
| main() | |