DDP WORLD_SIZE-safe dataloader workers (#5631)

* WORLD_SIZE-safe workers

* Update with DDP comment

train.py

@@ -266,7 +266,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
     stopper = EarlyStopping(patience=opt.patience)
     compute_loss = ComputeLoss(model)  # init loss class
     LOGGER.info(f'Image sizes {imgsz} train, {imgsz} val\n'
-                f'Using {train_loader.num_workers} dataloader workers\n'
+                f'Using {train_loader.num_workers * WORLD_SIZE} dataloader workers\n'
                 f"Logging results to {colorstr('bold', save_dir)}\n"
                 f'Starting training for {epochs} epochs...')
     for epoch in range(start_epoch, epochs):  # epoch ------------------------------------------------------------------
@@ -460,7 +460,7 @@ def parse_opt(known=False):
     parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class')
     parser.add_argument('--adam', action='store_true', help='use torch.optim.Adam() optimizer')
     parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode')
-    parser.add_argument('--workers', type=int, default=8, help='maximum number of dataloader workers')
+    parser.add_argument('--workers', type=int, default=8, help='max dataloader workers (per RANK in DDP mode)')
     parser.add_argument('--project', default=ROOT / 'runs/train', help='save to project/name')
     parser.add_argument('--name', default='exp', help='save to project/name')
     parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')