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Add `--cache val` (#6663) 

New `--cache val` argument will cache validation set only into RAM. Should help multi-GPU training speeds without consuming as much RAM as full `--cache ram`.
pull/6669/head
Glenn Jocher 2022-02-17 00:47:42 +01:00 committed by GitHub
parent 1ff43702a8
commit 7b80545e8e
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1 changed files with 5 additions and 4 deletions
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train.py
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@ -221,8 +221,9 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
# Trainloader
train_loader, dataset = create_dataloader(train_path, imgsz, batch_size // WORLD_SIZE, gs, single_cls,
hyp=hyp, augment=True, cache=opt.cache, rect=opt.rect, rank=LOCAL_RANK,
workers=workers, image_weights=opt.image_weights, quad=opt.quad,
hyp=hyp, augment=True, cache=None if opt.cache == 'val' else opt.cache,
rect=opt.rect, rank=LOCAL_RANK, workers=workers,
image_weights=opt.image_weights, quad=opt.quad,
prefix=colorstr('train: '), shuffle=True)
mlc = int(np.concatenate(dataset.labels, 0)[:, 0].max()) # max label class
nb = len(train_loader) # number of batches
@ -231,8 +232,8 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
# Process 0
if RANK in [-1, 0]:
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,
workers=workers * 2, pad=0.5,
hyp=hyp, cache=None if noval else opt.cache,
rect=True, rank=-1, workers=workers * 2, pad=0.5,
prefix=colorstr('val: '))[0]
if not resume: