updates
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train.py
5
train.py
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@ -235,9 +235,10 @@ def train(cfg,
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# SGD burn-in
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# SGD burn-in
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if epoch == 0 and i <= n_burnin:
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if epoch == 0 and i <= n_burnin:
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lr = hyp['lr0'] * (i / n_burnin) ** 4
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g = (i / n_burnin) ** 4 # gain
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for x in optimizer.param_groups:
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for x in optimizer.param_groups:
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x['lr'] = lr
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x['lr'] = hyp['lr0'] * g
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x['weight_decay'] = hyp['weight_decay'] * g
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# Run model
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# Run model
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pred = model(imgs)
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pred = model(imgs)
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