RuntimeError: expand(torch.LongTensor{[50, 1]}, size=[50]): the number of sizes provided (1) must be greater or equal to the number of dimensions in the tensor (2) about lm-lstm-crf

[SeekPoint]

how to fix it

[ahmadshabbir2468]

? How to fix

Namespace(batch_size=10, caseless=True, char_dim=30, char_hidden=300, char_layers=1, checkpoint='./checkpoint/ner_', clip_grad=5.0, co_train=True, dev_file='./data/ner/testa.txt', drop_out=0.2, emb_file='./embedding/glove.6B.100d.txt', epoch=200, eva_matrix='fa', fine_tune=False, gpu=0, high_way=True, highway_layers=1, lambda0=1, least_iters=20, load_check_point='', load_opt=False, lr=0.015, lr_decay=0.05, mini_count=5, momentum=0.9, patience=15, rand_embedding=False, shrink_embedding=False, small_crf=True, start_epoch=0, test_file='./data/ner/testb.txt', train_file='./data/ner/train.txt', unk='unk', update='sgd', word_dim=100, word_hidden=300, word_layers=1)

loading corpus
constructing coding table
feature size: '171'
loading embedding
embedding size: '400002'
constructing dataset
building model

-------> /usr/local/lib/python3.6/dist-packages/torch/nn/modules/rnn.py:54: UserWarning: dropout option adds dropout after all but last recurrent layer, so non-zero dropout expects num_layers greater than 1, but got dropout=0.2 and num_layers=1
"num_layers={}".format(dropout, num_layers))
device: 0
Traceback (most recent call last):
File "train_wc.py", line 162, in
ner_model.cuda()
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 265, in cuda
return self._apply(lambda t: t.cuda(device))
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 193, in _apply
module._apply(fn)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/rnn.py", line 127, in _apply
self.flatten_parameters()
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/rnn.py", line 123, in flatten_parameters
self.batch_first, bool(self.bidirectional))
RuntimeError: cuDNN error: CUDNN_STATUS_EXECUTION_FAILED

[zakarianamikaz]

same error can u show me how you did plz

[vasilikivmo]

@weixiao12345678 you have closed this issue. Can you please explain how you solved it? Thank you!