updates
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11
train.py
11
train.py
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@ -238,15 +238,10 @@ def train():
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targets = targets.to(device)
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targets = targets.to(device)
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# Hyperparameter burn-in
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# Hyperparameter burn-in
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# n_burn = nb - 1 # min(nb // 5 + 1, 1000) # number of burn-in batches
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# n_burn = 100 # number of burn-in batches
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# if ni <= n_burn:
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# if ni < n_burn:
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# for m in model.named_modules():
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# if m[0].endswith('BatchNorm2d'):
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# m[1].momentum = 1 - i / n_burn * 0.99 # BatchNorm2d momentum falls from 1 - 0.01
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# g = (i / n_burn) ** 4 # gain rises from 0 - 1
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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'] = hyp['lr0'] * g
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# x['lr'] = x['initial_lr'] * (ni / n_burn) ** 4 # gain rises from 0 - 1
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# x['weight_decay'] = hyp['weight_decay'] * g
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# Plot images with bounding boxes
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# Plot images with bounding boxes
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if ni < 1:
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if ni < 1:
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