updates
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train.py
4
train.py
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@ -211,13 +211,13 @@ def train():
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torch_utils.model_info(model, report='summary') # 'full' or 'summary'
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print('Using %g dataloader workers' % nw)
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print('Starting training for %g epochs...' % epochs)
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for epoch in range(start_epoch, epochs): # epoch ------------------------------
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for epoch in range(start_epoch, epochs): # epoch ------------------------------------------------------------------
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model.train()
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# Prebias
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if prebias:
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if epoch < 3: # prebias
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ps = 0.1, 0.9 # prebias settings (lr=0.1, momentum=0.9)
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ps = np.interp(epoch, [0, 3], [0.1, hyp['lr0']]), 0.0 # prebias settings (lr=0.1, momentum=0.0)
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else: # normal training
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ps = hyp['lr0'], hyp['momentum'] # normal training settings
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print_model_biases(model)
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