def run(_):
cfgs = lz.load_cfg('./cfgs/single_ohnm.py')
procs = []
for args in cfgs.cfgs:
if args.loss != 'trivid':
print(f'skip {args.loss} {args.logs_dir}')
continue
if args.log_at is None:
args.log_at = np.concatenate([
range(0, 640, 31),
range(args.epochs - 8, args.epochs, 1)
])
args.logs_dir = lz.work_path + 'reid/work/' + args.logs_dir
if osp.exists(args.logs_dir) and osp.exists(args.logs_dir + '/checkpoint.64.pth'):
print(os.listdir(args.logs_dir))
continue
if not args.gpu_fix:
args.gpu = lz.get_dev(n=len(args.gpu),
ok=args.gpu_range,
mem_thresh=[0.09, 0.09], sleep=32.3)
lz.logging.info(f'use gpu {args.gpu}')
# args.batch_size = 16
# args.gpu = (3, )
# args.epochs = 1
# args.logs_dir+='.bak'
if isinstance(args.gpu, int):
args.gpu = [args.gpu]
if not args.evaluate and not args.vis:
assert args.logs_dir != args.resume
lz.mkdir_p(args.logs_dir, delete=True)
lz.pickle_dump(args, args.logs_dir + '/conf.pkl')
if cfgs.no_proc:
main(args)
else:
proc = mp.Process(target=main, args=(args,))
proc.start()
lz.logging.info('next')
time.sleep(random.randint(39, 90))
if not cfgs.parallel:
proc.join()
else:
procs.append(proc)
if cfgs.parallel:
for proc in procs:
proc.join()
def run(_):
cfgs = lz.load_cfg('./cfgs/single_ohnm.py')
procs = []
for args in cfgs.cfgs:
if args.loss != 'tcx':
print(f'skip {args.loss} {args.logs_dir}')
continue
# args.log_at = np.concatenate([
# args.log_at,
# range(args.epochs - 8, args.epochs, 1)
# ])
args.logs_dir = 'work/' + args.logs_dir
if not args.gpu_fix:
args.gpu = lz.get_dev(n=len(args.gpu),
ok=args.gpu_range,
mem=[0.12, 0.07],
sleep=32.3)
lz.logging.info(f'use gpu {args.gpu}')
# args.batch_size = 16
# args.gpu = (3, )
# args.epochs = 1
# args.logs_dir+='.bak'
if isinstance(args.gpu, int):
args.gpu = [args.gpu]
if not args.evaluate:
assert args.logs_dir != args.resume
lz.mkdir_p(args.logs_dir, delete=True)
lz.pickle_dump(args, args.logs_dir + '/conf.pkl')
# main(args)
proc = mp.Process(target=main, args=(args, ))
proc.start()
lz.logging.info('next')
time.sleep(random.randint(39, 90))
procs.append(proc)
for proc in procs:
proc.join()
import lz
from lz import *
from torch.nn import CrossEntropyLoss
from tools.vat import VATLoss
from torchvision import transforms as trans
# todo label smooth
dist = False
num_devs = 3
if dist:
num_devs = 1
else:
pass
# lz.init_dev(3)
lz.init_dev(lz.get_dev(num_devs))
conf = edict()
conf.num_workers = 4 # ndevs * 3
conf.num_devs = num_devs
conf.no_eval = False
conf.start_eval = False
conf.loss = 'arcface' # adacos softmax arcface arcfaceneg arcface2 cosface
conf.writer = None
conf.local_rank = None
conf.num_clss = None
conf.dop = None # top_imp
conf.id2range_dop = None # sub_imp
conf.explored = None
from easydict import EasyDict as edict
from pathlib import Path
import torch
import lz
from torch.nn import CrossEntropyLoss
from torchvision import transforms as trans
lz.init_dev(lz.get_dev(n=1))
# lz.init_dev((0, 1))
def get_config(training=True):
conf = edict()
dbg = lz.dbg
if dbg:
# conf.num_steps_per_epoch = 38049
conf.num_steps_per_epoch = 3
# conf.no_eval = False
conf.no_eval = True
else:
conf.num_steps_per_epoch = 38049
# conf.num_steps_per_epoch = 3
conf.no_eval = False
# conf.no_eval = True
conf.loss = 'softmax' # softmax arcface
conf.fgg = '' # g gg ''
conf.fgg_wei = 0 # 1
conf.start_eval = False
conf.data_path = Path('/data2/share/')
# path = paths[0]
if not osp.exists(path + '/conf.pkl'):
continue
args = pickle_load(path + '/conf.pkl')
if args.logs_dir != path:
print('not same', args.logs_dir)
args.logs_dir = path + '/eval'
args.gpu_range = range(4)
if osp.exists(args.logs_dir + '/res.json'): continue
if 'mkt' not in args.logs_dir: continue
continue
args.dataset_val = args.dataset
args.eval_conf = 'market1501'
args.gpu = lz.get_dev(n=len(args.gpu),
ok=range(4),
mem=[0.12, 0.05],
sleep=32.3)
args.evaluate = True
args.resume = path + '/model_best.pth'
if not osp.exists(args.resume):
logging.info(args.logs_dir, 'shoule delete')
# rm(args.logs_dir)
continue
# res = cmain(args) # will not release mem
proc = mp.Process(target=main, args=(args, ))
proc.start()
proc.join()
# print(res)
