Traceback (most recent call last):


 "scoring.py", line 96, in <module>

clf.fit(X_train, y_train)


 "/usr/local/lib/python2.7/dist-packages/sklearn/multiclass.py", line 205, in fit

Y = self.label_binarizer_.fit_transform(y)


 "/usr/local/lib/python2.7/dist-packages/sklearn/base.py", line 494, in fit_transform

return self.fit(X, **fit_params).transform(X)


 "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py", line 296, in fit

self.y_type_ = type_of_target(y)


 "/usr/local/lib/python2.7/dist-packages/sklearn/utils/multiclass.py", line 250, in type_of_target

raise ValueError('You appear to be using a legacy multi-label data'
ValueError: You appear to be using a legacy multi-label data representation. Sequence of sequences are no longer supported; use a binary array or sparse matrix instead.

`Traceback (most recent call last):


 "main.py", line 33, in <module>

main()


 "main.py", line 22, in main

loader = data.Data(args)


 "/home/liangjc/Desktop/EDSR-PyTorch/src/data/__init__.py", line 31, in __init__

num_workers=args.n_threads,


 "/home/liangjc/anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 213, in __init__

sampler = RandomSampler(dataset)


 "/home/liangjc/anaconda3/lib/python3.6/site-packages/torch/utils/data/sampler.py", line 94, in __init__

"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
