guillaumekln on master
Updating the intel-mkl URL. (#5… (compare)
guillaumekln on master
Add CTranslate2 Change project cards title (compare)
-update_vocab merge
. If the vocabulary is merged, I guess I should also merge the BPE models to use when translating, right?
THCudaCheck FAIL file=/tmp/luarocks_cunn-scm-1-1394/cunn/lib/THCUNN/generic/SoftMax.cu line=72 error=48 : no kernel image is available for execution on the device
/torch/install/bin/luajit: /torch/install/share/lua/5.1/nn/THNN.lua:110: cuda runtime error (48) : no kernel image is available for execution on the device at /tmp/luarocks_cunn-scm-1-1394/cunn/lib/THCUNN/generic/SoftMax.cu:72
after [07/06/18 11:09:23 INFO] Preparing memory optimization...
? I run training on a Tesla V100 having 4 GPU cores and can't work around this issue. I run training using th ./train.lua ... -gpuid 1 2 3 4
.
CUDA_VISIBLE_DEVICES=0,1,2,3 th ./train.lua ... gpuid 1 2 3 4
, but for the life of me, it still says there is no nccl though I installed it from NVIDIA site, both Ubuntu 16.04 normal and S agonstic versions (for CUDA 9.0, though I have CUDA 9.1 installed - but there is no NCCL 9.1 :().
<unk> tag replace
work in that case.-phrase_table
that can be used for this: for any <unk>
token in the target, the corresponding source token is looked up in the table to find a translation. Other approaches include splitting names on characters and let the model learn the translation or, more commonly, replacing entities with placeholder tokens and have a separate processing software to replace these placeholders.
Otherwise, this requires an external pre- and post- processing.