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TAL min_memory argument, precommit, Docker fixes (#836)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Jaap van de Loosdrecht <jaap@vdlmv.nl>
This commit is contained in:
Glenn Jocher
2023-02-07 02:37:13 +04:00
committed by GitHub
parent 64f247d692
commit 3633d4c06b
6 changed files with 75 additions and 30 deletions
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13
ultralytics/yolo/v8/detect/train.py
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@ -33,14 +33,15 @@ class DetectionTrainer(BaseTrainer):
augment=mode == "train",
cache=self.args.cache,
pad=0 if mode == "train" else 0.5,
rect=self.args.rect or mode=="val",
rect=self.args.rect or mode == "val",
rank=rank,
workers=self.args.workers,
close_mosaic=self.args.close_mosaic != 0,
prefix=colorstr(f'{mode}: '),
shuffle=mode == "train",
seed=self.args.seed)[0] if self.args.v5loader else \
build_dataloader(self.args, batch_size, img_path=dataset_path, stride=gs, rank=rank, mode=mode, rect=mode=="val")[0]
build_dataloader(self.args, batch_size, img_path=dataset_path, stride=gs, rank=rank, mode=mode,
rect=mode == "val")[0]
def preprocess_batch(self, batch):
batch["img"] = batch["img"].to(self.device, non_blocking=True).float() / 255
@ -121,7 +122,13 @@ class Loss:
self.device = device
self.use_dfl = m.reg_max > 1
self.assigner = TaskAlignedAssigner(topk=10, num_classes=self.nc, alpha=0.5, beta=6.0)
roll_out_thr = h.min_memory if h.min_memory > 1 else 64 if h.min_memory else 0 # 64 is default
self.assigner = TaskAlignedAssigner(topk=10,
num_classes=self.nc,
alpha=0.5,
beta=6.0,
roll_out_thr=roll_out_thr)
self.bbox_loss = BboxLoss(m.reg_max - 1, use_dfl=self.use_dfl).to(device)
self.proj = torch.arange(m.reg_max, dtype=torch.float, device=device)