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update ImageNet training

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This commit is contained in:
Xuanyi Dong
2019-04-04 20:29:41 +08:00
parent 666c105f51
commit 4121d1719f
8 changed files with 64 additions and 30 deletions
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6
exps-cnn/train_base.py
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@@ -42,7 +42,7 @@ else : print('Find CUDA_VISIBLE_DEVICES={:
assert torch.cuda.is_available(), 'torch.cuda is not available'
if args.manualSeed is None:
if args.manualSeed is None or args.manualSeed < 0:
args.manualSeed = random.randint(1, 10000)
random.seed(args.manualSeed)
cudnn.benchmark = True
@@ -54,10 +54,10 @@ torch.cuda.manual_seed_all(args.manualSeed)
def main():
# Init logger
args.save_path = os.path.join(args.save_path, 'seed-{:}'.format(args.manualSeed))
#args.save_path = os.path.join(args.save_path, 'seed-{:}'.format(args.manualSeed))
if not os.path.isdir(args.save_path):
os.makedirs(args.save_path)
log = open(os.path.join(args.save_path, 'log-seed-{:}.txt'.format(args.manualSeed)), 'w')
log = open(os.path.join(args.save_path, 'seed-{:}-log.txt'.format(args.manualSeed)), 'w')
print_log('Save Path : {:}'.format(args.save_path), log)
state = {k: v for k, v in args._get_kwargs()}
print_log(state, log)