GPU error when run sample code

[vachelch]

When I run the sample code,
python examples/sample.py --train_path $TRAIN_PATH --dev_path $DEV_PATH

GPU errors appear as below, It seems data don't satisfy a gpu tensor, I failed to solve it. Has anyone meet the error, too?

---

/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py:52: UserWarning: size_average and reduce args will be deprecated, please use reduction='elementwise_mean' instead.
warnings.warn(warning.format(ret))
2018-11-20 23:33:48,774 root INFO Namespace(dev_path='data/toy_reverse/dev/data.txt', expt_dir='./experiment', load_checkpoint=None, log_level='info', resume=False, train_path='data/toy_reverse/train/data.txt')
/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py:52: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
warnings.warn(warning.format(ret))
/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/rnn.py:38: 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))
2018-11-20 23:33:51,817 seq2seq.trainer.supervised_trainer INFO Optimizer: Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
eps: 1e-08
lr: 0.001
weight_decay: 0
), Scheduler: None
Traceback (most recent call last):
File "examples/sample.py", line 129, in
resume=opt.resume)
File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 186, in train
teacher_forcing_ratio=teacher_forcing_ratio)
File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 103, in _train_epoches
loss = self._train_batch(input_variables, input_lengths.tolist(), target_variables, model, teacher_forcing_ratio)
File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 55, in _train_batch
teacher_forcing_ratio=teacher_forcing_ratio)
File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/models/seq2seq.py", line 48, in forward
encoder_outputs, encoder_hidden = self.encoder(input_variable, input_lengths)
File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/models/EncoderRNN.py", line 68, in forward
embedded = self.embedding(input_var)
File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/sparse.py", line 110, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py", line 1110, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected object of type torch.cuda.LongTensor but found type torch.LongTensor for argument #3 'index'

[pskrunner14]

@soHardToPickName please see #169.

[KevinMatrix]

@soHardToPickName please see #169.

your issue is not helpfule, I solve this by
change
"device = None if torch.cuda.is_available() else -1"
to
"device = torch.device("cuda" if torch.cuda.is_available() else "cpu")"
in seq2seq/trainer/supervised_trainer.py:75

use this way also in seq2seq/evaluator/evaluator.py:38

[vachelch]

@soHardToPickName please see #169.

your issue is not helpfule, I solve this by
change
"device = None if torch.cuda.is_available() else -1"
to
"device = torch.device("cuda" if torch.cuda.is_available() else "cpu")"
in seq2seq/trainer/supervised_trainer.py:75

use this way also in seq2seq/evaluator/evaluator.py:38

Thanks very much for your answer! this is just the solution, and sorry for reply late~

[Huijun-Cui]

good !