Fix batch-size on resume for multi-gpu (ultralytics#1942)

train.py

@@ -477,7 +477,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
         apriori = opt.global_rank, opt.local_rank
         with open(Path(ckpt).parent.parent / 'opt.yaml') as f:
             opt = argparse.Namespace(**yaml.load(f, Loader=yaml.FullLoader))  # replace
-        opt.cfg, opt.weights, opt.resume, opt.global_rank, opt.local_rank = '', ckpt, True, *apriori  # reinstate
+        opt.cfg, opt.weights, opt.resume, opt.batch_size, opt.global_rank, opt.local_rank = '', ckpt, True, opt.total_batch_size, *apriori  # reinstate
         logger.info('Resuming training from %s' % ckpt)
     else:
         # opt.hyp = opt.hyp or ('hyp.finetune.yaml' if opt.weights else 'hyp.scratch.yaml')