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main.py
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main.py
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import argparse
import traceback
import time
import shutil
import logging
import yaml
import sys
import os
import torch
import numpy as np
import torch.utils.tensorboard as tb
import copy
from runners import *
import os
def parse_args_and_config():
parser = argparse.ArgumentParser(description=globals()['__doc__'])
parser.add_argument('--config', type=str, required=True, help='Path to the config file')
parser.add_argument('--seed', type=int, default=1234, help='Random seed')
parser.add_argument('--exp', type=str, default='exp', help='Path for saving running related data.')
parser.add_argument('--doc', type=str, required=True, help='A string for documentation purpose. '
'Will be the name of the log folder.')
parser.add_argument('--comment', type=str, default='', help='A string for experiment comment')
parser.add_argument('--verbose', type=str, default='info', help='Verbose level: info | debug | warning | critical')
parser.add_argument('--test', action='store_true', help='Whether to test the model')
parser.add_argument('--sample', action='store_true', help='Whether to produce samples from the model')
parser.add_argument('--fast_fid', action='store_true', help='Whether to do fast fid test')
parser.add_argument('--resume_training', action='store_true', help='Whether to resume training')
parser.add_argument('-i', '--image_folder', type=str, default='images', help="The folder name of samples")
parser.add_argument('--ni', action='store_true', help="No interaction. Suitable for Slurm Job launcher")
args = parser.parse_args()
args.log_path = os.path.join(args.exp, 'logs', args.doc)
# parse config file
with open(os.path.join('configs', args.config), 'r') as f:
config = yaml.load(f)
new_config = dict2namespace(config)
tb_path = os.path.join(args.exp, 'tensorboard', args.doc)
if not args.test and not args.sample and not args.fast_fid:
if not args.resume_training:
if os.path.exists(args.log_path):
overwrite = False
if args.ni:
overwrite = True
else:
response = input("Folder already exists. Overwrite? (Y/N)")
if response.upper() == 'Y':
overwrite = True
if overwrite:
shutil.rmtree(args.log_path)
shutil.rmtree(tb_path)
os.makedirs(args.log_path)
if os.path.exists(tb_path):
shutil.rmtree(tb_path)
else:
print("Folder exists. Program halted.")
sys.exit(0)
else:
os.makedirs(args.log_path)
with open(os.path.join(args.log_path, 'config.yml'), 'w') as f:
yaml.dump(new_config, f, default_flow_style=False)
new_config.tb_logger = tb.SummaryWriter(log_dir=tb_path)
# setup logger
level = getattr(logging, args.verbose.upper(), None)
if not isinstance(level, int):
raise ValueError('level {} not supported'.format(args.verbose))
handler1 = logging.StreamHandler()
handler2 = logging.FileHandler(os.path.join(args.log_path, 'stdout.txt'))
formatter = logging.Formatter('%(levelname)s - %(filename)s - %(asctime)s - %(message)s')
handler1.setFormatter(formatter)
handler2.setFormatter(formatter)
logger = logging.getLogger()
logger.addHandler(handler1)
logger.addHandler(handler2)
logger.setLevel(level)
else:
level = getattr(logging, args.verbose.upper(), None)
if not isinstance(level, int):
raise ValueError('level {} not supported'.format(args.verbose))
handler1 = logging.StreamHandler()
formatter = logging.Formatter('%(levelname)s - %(filename)s - %(asctime)s - %(message)s')
handler1.setFormatter(formatter)
logger = logging.getLogger()
logger.addHandler(handler1)
logger.setLevel(level)
if args.sample:
os.makedirs(os.path.join(args.exp, 'image_samples'), exist_ok=True)
args.image_folder = os.path.join(args.exp, 'image_samples', args.image_folder)
if not os.path.exists(args.image_folder):
os.makedirs(args.image_folder)
else:
overwrite = False
if args.ni:
overwrite = True
else:
response = input("Image folder already exists. Overwrite? (Y/N)")
if response.upper() == 'Y':
overwrite = True
if overwrite:
shutil.rmtree(args.image_folder)
os.makedirs(args.image_folder)
else:
print("Output image folder exists. Program halted.")
sys.exit(0)
elif args.fast_fid:
os.makedirs(os.path.join(args.exp, 'fid_samples'), exist_ok=True)
args.image_folder = os.path.join(args.exp, 'fid_samples', args.image_folder)
if not os.path.exists(args.image_folder):
os.makedirs(args.image_folder)
else:
overwrite = False
if args.ni:
overwrite = False
else:
response = input("Image folder already exists. \n "
"Type Y to delete and start from an empty folder?\n"
"Type N to overwrite existing folders (Y/N)")
if response.upper() == 'Y':
overwrite = True
if overwrite:
shutil.rmtree(args.image_folder)
os.makedirs(args.image_folder)
# add device
device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
logging.info("Using device: {}".format(device))
new_config.device = device
# set random seed
torch.manual_seed(args.seed)
np.random.seed(args.seed)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(args.seed)
torch.backends.cudnn.benchmark = True
return args, new_config
def dict2namespace(config):
namespace = argparse.Namespace()
for key, value in config.items():
if isinstance(value, dict):
new_value = dict2namespace(value)
else:
new_value = value
setattr(namespace, key, new_value)
return namespace
def main():
args, config = parse_args_and_config()
logging.info("Writing log file to {}".format(args.log_path))
logging.info("Exp instance id = {}".format(os.getpid()))
logging.info("Exp comment = {}".format(args.comment))
logging.info("Config =")
print(">" * 80)
config_dict = copy.copy(vars(config))
if not args.test and not args.sample and not args.fast_fid:
del config_dict['tb_logger']
print(yaml.dump(config_dict, default_flow_style=False))
print("<" * 80)
try:
runner = NCSNRunner(args, config)
if args.test:
runner.test()
elif args.sample:
runner.sample()
elif args.fast_fid:
runner.fast_fid()
else:
runner.train()
except:
logging.error(traceback.format_exc())
return 0
if __name__ == '__main__':
sys.exit(main())