updates
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train.py
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train.py
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@ -27,7 +27,6 @@ from utils.adabound import *
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# 0.161 0.327 0.190 0.193 7.82 1.153 4.062 0.1845 24.28 3.05 20.93 2.842 0.2759 0.001357 -4 0.916 0.000572 # hd 0.438 mAP @ epoch 100
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# Training hyperparameters f
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hyp = {'giou': 1.2, # giou loss gain
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'xy': 4.062, # xy loss gain
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@ -318,7 +317,8 @@ def train(cfg,
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# Report time
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print('%g epochs completed in %.3f hours.' % (epoch - start_epoch + 1, (time.time() - t0) / 3600))
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del model, optimizer
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del model, optimizer, loss, dataset, dataloader, scaled_loss, scheduler
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torch.cuda.empty_cache()
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return results
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