(mulann) C:\Users\user\Desktop\MuLANN-master>python pysrc/mnist_exp.py --data_folder C:\Users\user\Desktop\MuLANN-master\data --result_folder C:\Users\user\Desktop\MuLANN-master\result
Random seed: 42
C:\Users\user\Desktop\MuLANN-master\pysrc\data\loader_getter.py:36: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
labels = torch.tensor(dataset.targets)
SmallNet(
(feature_extractor): SmallFeatureExtractor(
(conv1): Conv2d(3, 32, kernel_size=(5, 5), stride=(1, 1))
(maxpool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(conv2): Conv2d(32, 48, kernel_size=(5, 5), stride=(1, 1))
)
(label_predictor): SmallLabelPredictor(
(fc1): Linear(in_features=1200, out_features=100, bias=True)
(fc2): Linear(in_features=100, out_features=100, bias=True)
(fc3): Linear(in_features=100, out_features=10, bias=True)
)
)
Params(dataset='DIGITS', inputsize=32, nchannelsin=3, nclasses=10, cell_line='Cells', image_div=4, num_patch_per_im=10, model='small', gpu_id=0, device=device(type='cpu'), seed=42, fold=None, num_workers=2, testingBatch=320, result_folder='C:\\Users\\user\\Desktop\\MuLANN-master\\result', data_folder='C:\\Users\\user\\Desktop\\MuLANN-master\\data', batchsize=64, num_epochs=8, plotinterval=1, statinterval=1, train_setting=0, indiv_lr=False, eta0=0.001, momentum=0.9, lambda_schedule_gamma=10, gamma=0.001, beta=0.75, weight_decay=0, lr_decay=False, shuffling_iter=5, source='mnist', target='mnistm', domain_method='None', domain_lambda=0, info_zeta=None, proba=0.5, common_class_percentage=100, num_common_labelled_classes=7, target_unlabelled_presence=True, fully_transductive=True, target_supervision_level=50, iterative_labeling='entropy', unknown_perc=0.7)
training non-office task
Traceback (most recent call last):
File "pysrc/mnist_exp.py", line 41, in <module>
launch_training(options=options, model_class=SmallNet, data_getter=DigitsGetLoader)
File "C:\Users\user\Desktop\MuLANN-master\pysrc\main.py", line 68, in launch_training
train(model, options, source, target, SummaryWriter())
File "C:\Users\user\Desktop\MuLANN-master\pysrc\train.py", line 93, in train
source_class_loss, target_class_loss, source_dom_loss, target_dom_loss, global_step = train_epoch(
File "C:\Users\user\Desktop\MuLANN-master\pysrc\train.py", line 81, in train_epoch
logger.add_scalar('target_class_loss', tgt_class_loss.item(), total_step)
AttributeError: 'NoneType' object has no attribute 'item'
Hello dear author,
I am trying to run mnist_exp.py and I face the
AttributeError: 'NoneType' object has no attribute 'item'error. I don't know what to do next. Could you please help me out through it?Best regards.