* Update train.py Fix the bug of always the same W&B ID and continue overwrite with the old logging. BUG report https://github.com/ultralytics/yolov5/issues/1851 * Fix the bug of duplicate W&B ID fix the bug of https://github.com/ultralytics/yolov5/issues/1851 If we had trained on yolov5s.pt, the program will generate a new unique W&B ID. If we hadn't, the program will keep the old code, we can still use --resume aug. * Update general.py * revert train.py changes Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>5.0
@@ -361,8 +361,8 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non | |||
def strip_optimizer(f='weights/best.pt', s=''): # from utils.general import *; strip_optimizer() | |||
# Strip optimizer from 'f' to finalize training, optionally save as 's' | |||
x = torch.load(f, map_location=torch.device('cpu')) | |||
x['optimizer'] = None | |||
x['training_results'] = None | |||
for key in 'optimizer', 'training_results', 'wandb_id': | |||
x[key] = None | |||
x['epoch'] = -1 | |||
x['model'].half() # to FP16 | |||
for p in x['model'].parameters(): |