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@@ -165,7 +165,7 @@ class YoloTrainer(object):
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metric_logger = MetricLogger(delimiter=" ")
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metric_logger.add_meter('lr', SmoothedValue(window_size=1, fmt='{value:.6f}'))
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metric_logger.add_meter('size', SmoothedValue(window_size=1, fmt='{value:d}'))
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- metric_logger.add_meter('gnorm', SmoothedValue(window_size=1, fmt='{value:1f}'))
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+ metric_logger.add_meter('gnorm', SmoothedValue(window_size=1, fmt='{value:.1f}'))
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header = 'Epoch: [{} / {}]'.format(self.epoch, self.cfg.max_epoch)
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epoch_size = len(self.train_loader)
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print_freq = 10
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@@ -214,7 +214,7 @@ class YoloTrainer(object):
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# Backward
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self.scaler.scale(losses).backward()
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- gnorm = 0.0
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+ gnorm = get_total_grad_norm(model.parameters())
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# Optimize
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if (iter_i + 1) % self.grad_accumulate == 0:
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