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import os
import sys
import shutil
import pprint
from pathlib import Path
from datetime import datetime
import yaml
import torch
from easydict import EasyDict as edict
from .log import logger, add_logging
from .distributed import synchronize, get_world_size
def init_experiment(args, model_name):
model_path = Path(args.model_path)
ftree = get_model_family_tree(model_path, model_name=model_name)
if ftree is None:
print('Models can only be located in the "models" directory in the root of the repository')
sys.exit(1)
cfg = load_config(model_path)
update_config(cfg, args)
cfg.distributed = args.distributed
cfg.local_rank = args.local_rank
if cfg.distributed:
torch.distributed.init_process_group(backend='nccl', init_method='env://')
if args.workers > 0:
torch.multiprocessing.set_start_method('forkserver', force=True)
experiments_path = Path(cfg.EXPS_PATH)
exp_parent_path = experiments_path / '/'.join(ftree)
exp_parent_path.mkdir(parents=True, exist_ok=True)
if cfg.resume_exp:
exp_path = find_resume_exp(exp_parent_path, cfg.resume_exp)
else:
last_exp_indx = find_last_exp_indx(exp_parent_path)
exp_name = f'{last_exp_indx:03d}'
if cfg.exp_name:
exp_name += '_' + cfg.exp_name
exp_path = exp_parent_path / exp_name
synchronize()
if cfg.local_rank == 0:
exp_path.mkdir(parents=True)
cfg.EXP_PATH = exp_path
cfg.CHECKPOINTS_PATH = exp_path / 'checkpoints'
cfg.VIS_PATH = exp_path / 'vis'
cfg.LOGS_PATH = exp_path / 'logs'
if cfg.local_rank == 0:
cfg.LOGS_PATH.mkdir(exist_ok=True)
cfg.CHECKPOINTS_PATH.mkdir(exist_ok=True)
cfg.VIS_PATH.mkdir(exist_ok=True)
dst_script_path = exp_path / (model_path.stem + datetime.strftime(datetime.today(), '_%Y-%m-%d-%H-%M-%S.py'))
if args.temp_model_path:
shutil.copy(args.temp_model_path, dst_script_path)
os.remove(args.temp_model_path)
else:
shutil.copy(model_path, dst_script_path)
synchronize()
if cfg.gpus != '':
gpu_ids = [int(id) for id in cfg.gpus.split(',')]
else:
gpu_ids = list(range(max(cfg.ngpus, get_world_size())))
cfg.gpus = ','.join([str(id) for id in gpu_ids])
cfg.gpu_ids = gpu_ids
cfg.ngpus = len(gpu_ids)
cfg.multi_gpu = cfg.ngpus > 1
if cfg.distributed:
cfg.device = torch.device('cuda')
cfg.gpu_ids = [cfg.gpu_ids[cfg.local_rank]]
torch.cuda.set_device(cfg.gpu_ids[0])
else:
if cfg.multi_gpu:
os.environ['CUDA_VISIBLE_DEVICES'] = cfg.gpus
ngpus = torch.cuda.device_count()
assert ngpus >= cfg.ngpus
cfg.device = torch.device(f'cuda:{cfg.gpu_ids[0]}')
if cfg.local_rank == 0:
add_logging(cfg.LOGS_PATH, prefix='train_')
logger.info(f'Number of GPUs: {cfg.ngpus}')
if cfg.distributed:
logger.info(f'Multi-Process Multi-GPU Distributed Training')
logger.info('Run experiment with config:')
logger.info(pprint.pformat(cfg, indent=4))
return cfg
def get_model_family_tree(model_path, terminate_name='models', model_name=None):
if model_name is None:
model_name = model_path.stem
family_tree = [model_name]
for x in model_path.parents:
if x.stem == terminate_name:
break
family_tree.append(x.stem)
else:
return None
return family_tree[::-1]
def find_last_exp_indx(exp_parent_path):
indx = 0
for x in exp_parent_path.iterdir():
if not x.is_dir():
continue
exp_name = x.stem
if exp_name[:3].isnumeric():
indx = max(indx, int(exp_name[:3]) + 1)
return indx
def find_resume_exp(exp_parent_path, exp_pattern):
candidates = sorted(exp_parent_path.glob(f'{exp_pattern}*'))
if len(candidates) == 0:
print(f'No experiments could be found that satisfies the pattern = "*{exp_pattern}"')
sys.exit(1)
elif len(candidates) > 1:
print('More than one experiment found:')
for x in candidates:
print(x)
sys.exit(1)
else:
exp_path = candidates[0]
print(f'Continue with experiment "{exp_path}"')
return exp_path
def update_config(cfg, args):
for param_name, value in vars(args).items():
if param_name.lower() in cfg or param_name.upper() in cfg:
continue
cfg[param_name] = value
def load_config(model_path):
model_name = model_path.stem
config_path = model_path.parent / (model_name + '.yml')
if config_path.exists():
cfg = load_config_file(config_path)
else:
cfg = dict()
cwd = Path.cwd()
config_parent = config_path.parent.absolute()
while len(config_parent.parents) > 0:
config_path = config_parent / 'config.yml'
if config_path.exists():
local_config = load_config_file(config_path, model_name=model_name)
cfg.update({k: v for k, v in local_config.items() if k not in cfg})
if config_parent.absolute() == cwd:
break
config_parent = config_parent.parent
return edict(cfg)
def load_config_file(config_path, model_name=None, return_edict=False):
with open(config_path, 'r') as f:
cfg = yaml.safe_load(f)
if 'SUBCONFIGS' in cfg:
if model_name is not None and model_name in cfg['SUBCONFIGS']:
cfg.update(cfg['SUBCONFIGS'][model_name])
del cfg['SUBCONFIGS']
return edict(cfg) if return_edict else cfg
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