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您好!感谢您开源代码,这对我有很大帮助!
但是我对您train_brats.py中如下的代码有些疑惑:
train_brats.py
for epoch_num in tqdm(range(max_epoch), ncols=70): time1 = time.time() for i_batch, (sampled_batch, sample_stats) in enumerate(trainloader): ........ ## ================ Evaluate ================ logging.info(f'Epoch {epoch_num} Evaluation:') # print() t1_MSE_all, t1_PSNR_all, t1_SSIM_all = [], [], [] t2_MSE_all, t2_PSNR_all, t2_SSIM_all = [], [], [] t1_MSE_krecon, t1_PSNR_krecon, t1_SSIM_krecon = [], [], [] t2_MSE_krecon, t2_PSNR_krecon, t2_SSIM_krecon = [], [], [] for (sampled_batch, sample_stats) in testloader: ........
请问为什么要在训练代码中使用测试集选择best model呢?可能我的理解有误,但是我同样没有在训练代码中发现验证集?
再次感谢您的精彩工作,谢谢。
The text was updated successfully, but these errors were encountered:
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您好!感谢您开源代码,这对我有很大帮助!
但是我对您
train_brats.py
中如下的代码有些疑惑:请问为什么要在训练代码中使用测试集选择best model呢?可能我的理解有误,但是我同样没有在训练代码中发现验证集?
再次感谢您的精彩工作,谢谢。
The text was updated successfully, but these errors were encountered: