mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
702ec03ad8
* add hotword for deploy_tools * Support wfst decoder and contextual biasing (#1039) * Support wfst decoder and contextual biasing * Turn on fstbin compilation --------- Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com> * mv funasr/runtime runtime * Fix crash caused by OOV in hotwords list * funasr infer * funasr infer * funasr infer * funasr infer * funasr infer * fix some bugs about fst hotword; support wfst for websocket server and clients; mv runtime out of funasr; modify relative docs * del onnxruntime/include/gflags * update tensor.h * update run_server.sh * update deploy tools * update deploy tools * update websocket-server * update funasr-wss-server * Remove self loop propagation * Update websocket_protocol_zh.md * Update websocket_protocol_zh.md * update hotword protocol * author zhaomingwork: change hotwords for h5 and java * update hotword protocol * catch exception for json_fst_hws * update hotword on message * update onnx benchmark for ngram&hotword * update docs * update funasr-wss-serve * add NONE for LM_DIR * update docs * update run_server.sh * add whats-new * modify whats-new * update whats-new * update whats-new * Support decoder option for beam searching * update benchmark_onnx_cpp * Support decoder option for websocket * fix bug of CompileHotwordEmbedding * update html client * update docs --------- Co-authored-by: gongbo.gb <35997837+aibulamusi@users.noreply.github.com> Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com> Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
71 lines
2.2 KiB
Bash
71 lines
2.2 KiB
Bash
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nj=32
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stage=0
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scp="/nfs/haoneng.lhn/funasr_data/aishell-1/data/test/wav.scp"
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export_root="/nfs/zhifu.gzf/export"
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split_scps_tool=split_scp.pl
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rtf_tool=test_rtf.py
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#:<<!
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model_name="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
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backend="onnx" # "torch"
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quantize='true' # 'False'
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tag=${model_name}/${backend}_quantize_${quantize}
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!
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logs_outputs_dir=${export_root}/logs/${tag}/split$nj
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mkdir -p ${logs_outputs_dir}
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echo ${logs_outputs_dir}
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if [ ${stage} -le 0 ];then
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python -m funasr.export.export_model --model-name ${model_name} --export-dir ${export_root} --type ${backend} --quantize ${quantize} --audio_in ${scp}
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fi
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if [ ${stage} -le 1 ];then
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model_dir=${export_root}/${model_name}
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split_scps=""
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for JOB in $(seq ${nj}); do
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split_scps="$split_scps $logs_outputs_dir/wav.$JOB.scp"
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done
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perl ${split_scps_tool} $scp ${split_scps}
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for JOB in $(seq ${nj}); do
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{
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core_id=`expr $JOB - 1`
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taskset -c ${core_id} python ${rtf_tool} --backend ${backend} --model_dir ${model_dir} --wav_file ${logs_outputs_dir}/wav.$JOB.scp --quantize ${quantize} &> ${logs_outputs_dir}/log.$JOB.txt
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}&
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done
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wait
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rm -rf ${logs_outputs_dir}/total_time_comput.txt
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rm -rf ${logs_outputs_dir}/total_time_wav.txt
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rm -rf ${logs_outputs_dir}/total_rtf.txt
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for JOB in $(seq ${nj}); do
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{
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cat ${logs_outputs_dir}/log.$JOB.txt | grep "total_time_comput" | awk -F ' ' '{print $2}' >> ${logs_outputs_dir}/total_time_comput.txt
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cat ${logs_outputs_dir}/log.$JOB.txt | grep "total_time_wav" | awk -F ' ' '{print $2}' >> ${logs_outputs_dir}/total_time_wav.txt
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cat ${logs_outputs_dir}/log.$JOB.txt | grep "total_rtf" | awk -F ' ' '{print $2}' >> ${logs_outputs_dir}/total_rtf.txt
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}
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done
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total_time_comput=`cat ${logs_outputs_dir}/total_time_comput.txt | awk 'BEGIN {max = 0} {if ($1+0>max+0) max=$1 fi} END {print max}'`
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total_time_wav=`cat ${logs_outputs_dir}/total_time_wav.txt | awk '{sum +=$1};END {print sum}'`
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rtf=`awk 'BEGIN{printf "%.5f\n",'$total_time_comput'/'$total_time_wav'}'`
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speed=`awk 'BEGIN{printf "%.2f\n",1/'$rtf'}'`
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echo "total_time_comput_ms: $total_time_comput"
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echo "total_time_wav: $total_time_wav"
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echo "total_rtf: $rtf, speech: $speed"
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fi |