【发布时间】:2020-01-02 14:47:50
【问题描述】:
我正在尝试调用 Laia - HRW 的深度学习工具包:https://github.com/jpuigcerver/Laia
这是我的代码:
INPUT_DIR=`pwd`/RecognitionHand/dir_input
OUTPUT_DIR=`pwd`/RecognitionHand/dir_output
CHAR_TRANSCRIBE_FILE=char.txt
WORD_TRANSCRIBE_FILE=word.txt
rm $INPUT_DIR/filelist/filenames.lst
ls -d -1 $INPUT_DIR/images/* > $INPUT_DIR/filelist/filenames.lst
COMMAND="decode --batch_size 20 --log_level info --symbols_table \
$INPUT_DIR/symbtable/symbs.txt \
$INPUT_DIR/model/model_htr.t7 \
$INPUT_DIR/filelist/filenames.lst> $OUTPUT_DIR/$CHAR_TRANSCRIBE_FILE";
# local volumes mapped to the docker volumes
OPTS=( -u $(id -u):$(id -g) );
[ -d "/home" ] && OPTS+=( -v /home:/home );
[ -d "/mnt" ] && OPTS+=( -v /mnt:/mnt );
[ -d "/media" ] && OPTS+=( -v /media:/media );
[ -d "/tmp" ] && OPTS+=( -v /tmp:/tmp );
# call the GPU docker for transcribing
docker run --rm -t "${OPTS[@]}" laia:active \
bash -c "cd $(pwd) && PATH=\" .:$PATH:\$PATH\" laia-$COMMAND";
最后一个 docker 命令指的是 nvidia-docker,我收到了这个奇怪的错误:
THCudaCheck FAIL file=/tmp/luarocks_cutorch-scm-1-918/cutorch/lib/THC/THCGeneral.c line=66 error=35
: CUDA driver version is insufficient for CUDA runtime version
[2020-01-02 14:43:45 WARN] /opt/torch/share/lua/5.1/laia/util/base.lua:39: Optional lua module "cutorch" was not found!
[2020-01-02 14:43:45 WARN] /opt/torch/share/lua/5.1/laia/util/base.lua:39: Optional lua module "cunn" was not found!
[2020-01-02 14:43:45 WARN] /opt/torch/share/lua/5.1/laia/util/base.lua:39: Optional lua module "laia.util.cudnn" was not found!
[2020-01-02 14:43:45 WARN] /opt/torch/share/lua/5.1/laia/util/base.lua:39: Optional lua module "laia.ImageDistorter" was not found!
/opt/torch/bin/luajit: /opt/torch/lib/luarocks/rocks/laia/scm-1/bin/laia-decode:16: attempt to call field 'registerOptions' (a nil value)
stack traceback:
/opt/torch/lib/luarocks/rocks/laia/scm-1/bin/laia-decode:16: in main chunk
[C]: at 0x00405d50
为什么会这样?请问有人在运行 nvidia-docker 时遇到过类似的错误吗?
【问题讨论】:
-
“CUDA 驱动程序版本不足以支持 CUDA 运行时版本”是一个非常常见的错误,通常与为您尝试使用的 CUDA 版本安装的驱动程序太旧有关。如果你搜索那个确切的错误,你会发现很多关于如何解决它的信息
标签: cuda nvidia-docker