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python robust_dividemix.py --gpu 0 --r 02  --dataset 'cifar100' --log 'robdm_bad' --noise-file '../eval_badlabels/noise/badlabels_cifar100_r0.2.json' --warmup 20 --lam 1 --tol 0.01 --max-iter 500 --noise-mode 'bad' &

load noise labels from ../eval_badlabels/noise/badlabels_cifar100_r0.1.json ..
===> epoch: 20, lambda: 1.0.
gmm.means:  [[0.52740902]
 [0.42178395]]
gmm.means:  [[0.40338232]
 [0.5466281 ]]
gmm0.means:  [[0.42655838]
 [0.43710862]]
gmm0.converged:  True
gmm0.n_iter_ 127
gmm0.means:  [[0.46136058]
 [0.44749019]]
gmm0.converged:  True
gmm0.n_iter_ 162
Train Net1
load noise labels from ../eval_badlabels/noise/badlabels_cifar100_r0.1.json ..
labeled data has a size of 1645
num of clean data is 1135 (69.00%)
load noise labels from ../eval_badlabels/noise/badlabels_cifar100_r0.1.json ..
unlabeled data has a size of 48355
num of clean data is 43865 (90.71%)
756
0it [00:00, ?it/s]
Traceback (most recent call last):
  File "robust_dividemix.py", line 77, in train
    inputs_u, inputs_u2 = unlabeled_train_iter.next()
AttributeError: '_MultiProcessingDataLoaderIter' object has no attribute 'next'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "robust_dividemix.py", line 374, in <module>
    train(epoch, net1, net2, optimizer1, labeled_trainloader, unlabeled_trainloader)  # train net1
  File "robust_dividemix.py", line 80, in train
    inputs_u, inputs_u2 = unlabeled_train_iter.next()                 
AttributeError: '_MultiProcessingDataLoaderIter' object has no attribute 'next'