From e702cad2fb38d8458d57b8ee7639e35ef84f0967 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E8=AF=AD=E5=B8=86?= Date: Wed, 28 Feb 2024 19:36:19 +0800 Subject: [PATCH] test --- .../lcbnet/demo_nj.sh | 72 +++++++++++++++++++ .../lcbnet/demo_nj2.sh | 72 ------------------- 2 files changed, 72 insertions(+), 72 deletions(-) create mode 100644 examples/industrial_data_pretraining/lcbnet/demo_nj.sh delete mode 100644 examples/industrial_data_pretraining/lcbnet/demo_nj2.sh diff --git a/examples/industrial_data_pretraining/lcbnet/demo_nj.sh b/examples/industrial_data_pretraining/lcbnet/demo_nj.sh new file mode 100644 index 000000000..d9f42a033 --- /dev/null +++ b/examples/industrial_data_pretraining/lcbnet/demo_nj.sh @@ -0,0 +1,72 @@ +file_dir="/nfs/yufan.yf/workspace/github/FunASR/examples/industrial_data_pretraining/lcbnet/exp/speech_lcbnet_contextual_asr-en-16k-bpe-vocab5002-pytorch" +CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" +inference_device="cuda" + +if [ ${inference_device} == "cuda" ]; then + nj=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}') +else + inference_batch_size=1 + CUDA_VISIBLE_DEVICES="" + for JOB in $(seq ${nj}); do + CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"-1," + done +fi + +inference_dir="outputs/test" +_logdir="${inference_dir}/logdir" +echo "inference_dir: ${inference_dir}" + +# mkdir -p "${_logdir}" +# key_file1=${file_dir}/wav.scp +# key_file2=${file_dir}/ocr.txt +# split_scps1= +# split_scps2= +# for JOB in $(seq "${nj}"); do +# split_scps1+=" ${_logdir}/wav.${JOB}.scp" +# split_scps2+=" ${_logdir}/ocr.${JOB}.txt" +# done +# utils/split_scp.pl "${key_file1}" ${split_scps1} +# utils/split_scp.pl "${key_file2}" ${split_scps2} + +# gpuid_list_array=(${CUDA_VISIBLE_DEVICES//,/ }) +# for JOB in $(seq ${nj}); do +# { +# id=$((JOB-1)) +# gpuid=${gpuid_list_array[$id]} + +# export CUDA_VISIBLE_DEVICES=${gpuid} + +# python -m funasr.bin.inference \ +# --config-path=${file_dir} \ +# --config-name="config.yaml" \ +# ++init_param=${file_dir}/model.pb \ +# ++tokenizer_conf.token_list=${file_dir}/tokens.txt \ +# ++input=[${_logdir}/wav.${JOB}.scp,${_logdir}/ocr.${JOB}.txt] \ +# +data_type='["kaldi_ark", "text"]' \ +# ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \ +# ++output_dir="${inference_dir}/${JOB}" \ +# ++device="${inference_device}" \ +# ++ncpu=1 \ +# ++disable_log=true &> ${_logdir}/log.${JOB}.txt + +# }& +# done +# wait + + +#mkdir -p ${inference_dir}/1best_recog +for f in token; do + if [ -f "${inference_dir}/${JOB}/1best_recog/${f}" ]; then + for JOB in $(seq "${nj}"); do + cat "${inference_dir}/${JOB}/1best_recog/${f}" + done | sort -k1 >"${inference_dir}/1best_recog/${f}" + fi +done + +echo "Computing WER ..." +echo "Computing WER ..." +#python utils/postprocess_text_zh.py ${inference_dir}/1best_recog/text ${inference_dir}/1best_recog/text.proc + +#cp ${data_dir}/text ${inference_dir}/1best_recog/text.ref +#python utils/compute_wer.py ${inference_dir}/1best_recog/text.ref ${inference_dir}/1best_recog/text.proc ${inference_dir}/1best_recog/text.cer +#tail -n 3 ${inference_dir}/1best_recog/text.cer \ No newline at end of file diff --git a/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh b/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh deleted file mode 100644 index 205c28fa3..000000000 --- a/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh +++ /dev/null @@ -1,72 +0,0 @@ -file_dir="/nfs/yufan.yf/workspace/github/FunASR/examples/industrial_data_pretraining/lcbnet/exp/speech_lcbnet_contextual_asr-en-16k-bpe-vocab5002-pytorch" -CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" -inference_device="cuda" - -if [ ${inference_device} == "cuda" ]; then - nj=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}') - else - inference_batch_size=1 - CUDA_VISIBLE_DEVICES="" - for JOB in $(seq ${nj}); do - CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"-1," - done - fi - - inference_dir="outputs/test" - _logdir="${inference_dir}/logdir" - echo "inference_dir: ${inference_dir}" - - # mkdir -p "${_logdir}" - # key_file1=${file_dir}/wav.scp - # key_file2=${file_dir}/ocr.txt - # split_scps1= - # split_scps2= - # for JOB in $(seq "${nj}"); do - # split_scps1+=" ${_logdir}/wav.${JOB}.scp" - # split_scps2+=" ${_logdir}/ocr.${JOB}.txt" - # done - # utils/split_scp.pl "${key_file1}" ${split_scps1} - # utils/split_scp.pl "${key_file2}" ${split_scps2} - - # gpuid_list_array=(${CUDA_VISIBLE_DEVICES//,/ }) - # for JOB in $(seq ${nj}); do - # { - # id=$((JOB-1)) - # gpuid=${gpuid_list_array[$id]} - - # export CUDA_VISIBLE_DEVICES=${gpuid} - - # python -m funasr.bin.inference \ - # --config-path=${file_dir} \ - # --config-name="config.yaml" \ - # ++init_param=${file_dir}/model.pb \ - # ++tokenizer_conf.token_list=${file_dir}/tokens.txt \ - # ++input=[${_logdir}/wav.${JOB}.scp,${_logdir}/ocr.${JOB}.txt] \ - # +data_type='["kaldi_ark", "text"]' \ - # ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \ - # ++output_dir="${inference_dir}/${JOB}" \ - # ++device="${inference_device}" \ - # ++ncpu=1 \ - # ++disable_log=true &> ${_logdir}/log.${JOB}.txt - - # }& - # done - # wait - - - #mkdir -p ${inference_dir}/1best_recog - for f in token; do - if [ -f "${inference_dir}/${JOB}/1best_recog/${f}" ]; then - for JOB in $(seq "${nj}"); do - cat "${inference_dir}/${JOB}/1best_recog/${f}" - done | sort -k1 >"${inference_dir}/1best_recog/${f}" - fi - done - - echo "Computing WER ..." - echo "Computing WER ..." - #python utils/postprocess_text_zh.py ${inference_dir}/1best_recog/text ${inference_dir}/1best_recog/text.proc - - #cp ${data_dir}/text ${inference_dir}/1best_recog/text.ref - #python utils/compute_wer.py ${inference_dir}/1best_recog/text.ref ${inference_dir}/1best_recog/text.proc ${inference_dir}/1best_recog/text.cer - #tail -n 3 ${inference_dir}/1best_recog/text.cer