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Apply learning rate scaling to min_lr #64

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Apply learning rate scaling to min_lr #64

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6 changes: 4 additions & 2 deletions main_dino.py
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Original file line number Diff line number Diff line change
Expand Up @@ -227,9 +227,11 @@ def train_dino(args):
fp16_scaler = torch.cuda.amp.GradScaler()

# ============ init schedulers ... ============
# linear scaling rule
lr_scale = (args.batch_size_per_gpu * utils.get_world_size()) / 256.
lr_schedule = utils.cosine_scheduler(
args.lr * (args.batch_size_per_gpu * utils.get_world_size()) / 256., # linear scaling rule
args.min_lr,
args.lr * lr_scale,
args.min_lr * lr_scale,
args.epochs, len(data_loader),
warmup_epochs=args.warmup_epochs,
)
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