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@ -400,6 +400,7 @@ def train(hyp, opt, device, data_list,id,callbacks): # hyp is path/to/hyp.yaml
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# Backward
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# Backward
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scaler.scale(loss).backward()
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scaler.scale(loss).backward()
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report_cellback(epoch, epochs, float(loss))
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# Optimize - https://pytorch.org/docs/master/notes/amp_examples.html
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# Optimize - https://pytorch.org/docs/master/notes/amp_examples.html
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if ni - last_opt_step >= accumulate:
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if ni - last_opt_step >= accumulate:
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@ -484,7 +485,7 @@ def train(hyp, opt, device, data_list,id,callbacks): # hyp is path/to/hyp.yaml
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# break # must break all DDP ranks
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# break # must break all DDP ranks
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######实时传输训练精度参数#############
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######实时传输训练精度参数#############
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#gain_train_report(int(epoch + 1), float(results[0]), pro, version, epochs)
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#gain_train_report(int(epoch + 1), float(results[0]), pro, version, epochs)
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report_cellback(epoch, epochs, float(results[0]))
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# report_cellback(epoch, epochs, float(results[0]))
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# end epoch ----------------------------------------------------------------------------------------------------
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# end epoch ----------------------------------------------------------------------------------------------------
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########训练数量和保存模型###########
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########训练数量和保存模型###########
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#save_train_report_result(pro, train_num, best)
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#save_train_report_result(pro, train_num, best)
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