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add logic for resuming and getting hyp for resume run

pull/104/head
Alex Stoken 2020-06-16 16:30:12 -05:00
parent 25e51bcec7
commit a448c3bcd7
1 changed files with 20 additions and 8 deletions
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28
train.py
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@ -63,7 +63,7 @@ def train(hyp):
os.makedirs(wdir, exist_ok=True)
last = wdir + 'last.pt'
best = wdir + 'best.pt'
results_file = 'results.txt'
results_file = wdir + 'results.txt'
epochs = opt.epochs # 300
batch_size = opt.batch_size # 64
@ -360,7 +360,7 @@ def train(hyp):
if len(n):
n = '_' + n if not n.isnumeric() else n
fresults, flast, fbest = 'results%s.txt' % n, wdir + 'last%s.pt' % n, wdir + 'best%s.pt' % n
for f1, f2 in zip([wdir + 'last.pt', wdir + 'best.pt', 'results.txt'], [flast, fbest, fresults]):
for f1, f2 in zip([wdir + 'last.pt', wdir + 'best.pt', wdir + 'results.txt'], [flast, fbest, fresults]):
if os.path.exists(f1):
os.rename(f1, f2) # rename
ispt = f2.endswith('.pt') # is *.pt
@ -382,10 +382,10 @@ if __name__ == '__main__':
parser.add_argument('--batch-size', type=int, default=16)
parser.add_argument('--cfg', type=str, default='models/yolov5s.yaml', help='*.cfg path')
parser.add_argument('--data', type=str, default='data/coco128.yaml', help='*.data path')
parser.add_argument('--img-size', nargs='+', type=int, default=[640, 640], help='train,test sizes')
parser.add_argument('--img-size', nargs='+', type=int, default=[640, 640], help='train,test sizes. Assumes square imgs.')
parser.add_argument('--rect', action='store_true', help='rectangular training')
parser.add_argument('--resume', action='store_true', help='resume training from last.pt')
parser.add_argument('--resume_from_run', type=str, default='', 'resume training from last.pt in this dir')
parser.add_argument('--resume-from-run', type=str, default='', help='resume training from last.pt in this dir')
parser.add_argument('--nosave', action='store_true', help='only save final checkpoint')
parser.add_argument('--notest', action='store_true', help='only test final epoch')
parser.add_argument('--evolve', action='store_true', help='evolve hyperparameters')
@ -397,18 +397,30 @@ if __name__ == '__main__':
parser.add_argument('--adam', action='store_true', help='use adam optimizer')
parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%')
parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
parser.add_argument('--hyp', type=str, default='', help ='path to hyp yaml file')
parser.add_argument('--hyp', type=str, default='', help ='path to hyp yaml file. Not needed with --resume.')
opt = parser.parse_args()
if opt.resume and not opt.resume_from_run:
# logic to resume from latest run if either --resume or --resume-from-run is selected
# Note if neither --resume or --resume-from-run, last is set to empty string
if opt.resume_from_run:
opt.resume = True
last = opt.resume_from_run
elif opt.resume and not opt.resume_from_run:
last = get_latest_run()
print(f'WARNING: No run provided to resume from. Resuming from most recent run found at {last}')
else:
last = opt.resume_from_run
last = ''
# if resuming, check for hyp file
if last:
last_hyp = last.replace('last.pt', 'hyp.yaml')
if os.path.exists(last_hyp):
opt.hyp = last_hyp
opt.weights = last if opt.resume else opt.weights
opt.cfg = check_file(opt.cfg) # check file
opt.data = check_file(opt.data) # check file
opt.hyp = check_file(opt.hyp) #check file
opt.hyp = check_file(opt.hyp) if opt.hyp else '' #check file
print(opt)
opt.img_size.extend([opt.img_size[-1]] * (2 - len(opt.img_size))) # extend to 2 sizes (train, test)
device = torch_utils.select_device(opt.device, apex=mixed_precision, batch_size=opt.batch_size)