42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
import sys
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from pathlib import Path
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import wandb
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FILE = Path(__file__).resolve()
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ROOT = FILE.parents[3] # YOLOv5 root directory
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if str(ROOT) not in sys.path:
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sys.path.append(str(ROOT)) # add ROOT to PATH
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from train import parse_opt, train
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from utils.callbacks import Callbacks
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from utils.general import increment_path
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from utils.torch_utils import select_device
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def sweep():
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wandb.init()
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# Get hyp dict from sweep agent. Copy because train() modifies parameters which confused wandb.
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hyp_dict = vars(wandb.config).get("_items").copy()
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# Workaround: get necessary opt args
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opt = parse_opt(known=True)
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opt.batch_size = hyp_dict.get("batch_size")
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opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok or opt.evolve))
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opt.epochs = hyp_dict.get("epochs")
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opt.nosave = True
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opt.data = hyp_dict.get("data")
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opt.weights = str(opt.weights)
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opt.cfg = str(opt.cfg)
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opt.data = str(opt.data)
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opt.hyp = str(opt.hyp)
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opt.project = str(opt.project)
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device = select_device(opt.device, batch_size=opt.batch_size)
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# train
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train(hyp_dict, opt, device, callbacks=Callbacks())
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if __name__ == "__main__":
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sweep()
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