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@ -73,6 +73,14 @@ def train(hyp, opt, device, tb_writer=None):
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else:
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else:
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model = Model(opt.cfg, ch=3, nc=nc).to(device) # create
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model = Model(opt.cfg, ch=3, nc=nc).to(device) # create
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# Freeze
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freeze = ['', ] # parameter names to freeze (full or partial)
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if any(freeze):
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for k, v in model.named_parameters():
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if any(x in k for x in freeze):
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print('freezing %s' % k)
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v.requires_grad = False
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# Optimizer
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# Optimizer
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nbs = 64 # nominal batch size
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nbs = 64 # nominal batch size
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accumulate = max(round(nbs / total_batch_size), 1) # accumulate loss before optimizing
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accumulate = max(round(nbs / total_batch_size), 1) # accumulate loss before optimizing
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