dtype mismatch in beam_search.py

[keyakkie]

Sorry for the rudimentary question.
For predicting queries, I run the following code as instructed in README.md:

python ./OpenNMT-py/translate.py \
  -gpu 0 \
  -model ${DATA_DIR}/doc2query_step_10000.pt \
  -src ${DATA_DIR}/opennmt_format/src-collection.txt \
  -output ${DATA_DIR}/opennmt_format/pred-collection_beam5.txt \
  -batch_size 32 \
  -beam_size 5 \
  --n_best 5 \
  -replace_unk \
  -report_time

Then, I got an error as follows:

Traceback (most recent call last):
  File "/home/work/doc2query/./OpenNMT-py/translate.py", line 46, in <module>
    main(opt)
  File "/home/work/doc2query/./OpenNMT-py/translate.py", line 25, in main
    translator.translate(
  File "/home/work/doc2query/OpenNMT-py/onmt/translate/translator.py", line 314, in translate
    batch_data = self.translate_batch(
  File "/home/work/doc2query/OpenNMT-py/onmt/translate/translator.py", line 498, in translate_batch
    return self._translate_batch(
  File "/home/work/doc2query/OpenNMT-py/onmt/translate/translator.py", line 650, in _translate_batch
    beam.advance(log_probs, attn)
  File "/home/work/doc2query/OpenNMT-py/onmt/translate/beam_search.py", line 155, in advance
    torch.div(self.topk_ids, vocab_size, out=self._batch_index)
RuntimeError: result type Float can't be cast to the desired output type Long

ref:

self._batch_index = torch.empty([batch_size, beam_size],
  dtype=torch.long, device=mb_device)

It seems dtype of self._batch_index is torch.float , but it causes another error.

Does anyone know how to fix it?
Thanks in advance!