/home/ubuntu/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.
FutureWarning)
Traceback (most recent call last):
File "graphsage_sampling_unsup.py", line 336, in <module>
run(args, device, data)
File "graphsage_sampling_unsup.py", line 288, in run
eval_acc, test_acc = evaluate(model, g, g.ndata['features'], labels, train_nid, val_nid, test_nid, args.batch_size, device)
File "graphsage_sampling_unsup.py", line 216, in evaluate
return compute_acc(pred, labels, train_nids, val_nids, test_nids)
File "graphsage_sampling_unsup.py", line 193, in compute_acc
lr.fit(emb[train_nids], labels[train_nids])
File "/home/ubuntu/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/sklearn/linear_model/logistic.py", line 1294, in fit
len(self.classes_))
File "/home/ubuntu/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/sklearn/linear_model/logistic.py", line 473, in _check_multi_class
"a multinomial backend." % solver)
ValueError: Solver liblinear does not support a multinomial backend.
🐛 Bug
To Reproduce
Steps to reproduce the behavior:
Expected behavior
No error when I change https://github.com/dmlc/dgl/blob/master/examples/pytorch/graphsage/train_sampling_unsupervised.py#L192 to
Environment
conda
,pip
, source): condaAdditional context