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Validate with 2x `--workers` (#6658)

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Glenn Jocher 2022-02-16 14:44:44 +01:00 committed by GitHub
parent ee6c70ae43
commit 6769021901
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2 changed files with 2 additions and 2 deletions
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2
train.py
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@ -232,7 +232,7 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
if RANK in [-1, 0]: if RANK in [-1, 0]:
val_loader = create_dataloader(val_path, imgsz, batch_size // WORLD_SIZE * 2, gs, single_cls, val_loader = create_dataloader(val_path, imgsz, batch_size // WORLD_SIZE * 2, gs, single_cls,
hyp=hyp, cache=None if noval else opt.cache, rect=True, rank=-1, hyp=hyp, cache=None if noval else opt.cache, rect=True, rank=-1,
workers=workers, pad=0.5, workers=workers * 2, pad=0.5,
prefix=colorstr('val: '))[0] prefix=colorstr('val: '))[0]
if not resume: if not resume:

2
utils/datasets.py
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@ -110,7 +110,7 @@ def create_dataloader(path, imgsz, batch_size, stride, single_cls=False, hyp=Non
batch_size = min(batch_size, len(dataset)) batch_size = min(batch_size, len(dataset))
nd = torch.cuda.device_count() # number of CUDA devices nd = torch.cuda.device_count() # number of CUDA devices
nw = min([os.cpu_count() // max(nd, 1), batch_size if batch_size > 1 else 0, workers]) # number of workers nw = min([2 * os.cpu_count() // max(nd, 1), batch_size if batch_size > 1 else 0, workers]) # number of workers
sampler = None if rank == -1 else distributed.DistributedSampler(dataset, shuffle=shuffle) sampler = None if rank == -1 else distributed.DistributedSampler(dataset, shuffle=shuffle)
loader = DataLoader if image_weights else InfiniteDataLoader # only DataLoader allows for attribute updates loader = DataLoader if image_weights else InfiniteDataLoader # only DataLoader allows for attribute updates
return loader(dataset, return loader(dataset,