DDP WORLD_SIZE-safe dataloader workers (#5631)

* WORLD_SIZE-safe workers

* Update with DDP comment

utils/datasets.py

@@ -34,6 +34,7 @@ from utils.torch_utils import torch_distributed_zero_first
 HELP_URL = 'https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data'
 IMG_FORMATS = ['bmp', 'jpg', 'jpeg', 'png', 'tif', 'tiff', 'dng', 'webp', 'mpo']  # acceptable image suffixes
 VID_FORMATS = ['mov', 'avi', 'mp4', 'mpg', 'mpeg', 'm4v', 'wmv', 'mkv']  # acceptable video suffixes
+WORLD_SIZE = int(os.getenv('WORLD_SIZE', 1))  # DPP
 NUM_THREADS = min(8, os.cpu_count())  # number of multiprocessing threads
 
 # Get orientation exif tag
@@ -107,7 +108,7 @@ def create_dataloader(path, imgsz, batch_size, stride, single_cls=False, hyp=Non
                                       prefix=prefix)
 
     batch_size = min(batch_size, len(dataset))
-    nw = min([os.cpu_count(), batch_size if batch_size > 1 else 0, workers])  # number of workers
+    nw = min([os.cpu_count() // WORLD_SIZE, batch_size if batch_size > 1 else 0, workers])  # number of workers
     sampler = torch.utils.data.distributed.DistributedSampler(dataset) if rank != -1 else None
     loader = torch.utils.data.DataLoader if image_weights else InfiniteDataLoader
     # Use torch.utils.data.DataLoader() if dataset.properties will update during training else InfiniteDataLoader()