| | |
| | | |
| | | split_scps_tool=split_scp.pl |
| | | inference_tool=infer.py |
| | | proce_text_tool=proce_text.py |
| | | compute_wer_tool=compute_wer.py |
| | | |
| | | nj=32 |
| | | stage=0 |
| | | stop_stage=2 |
| | |
| | | scp="/nfs/haoneng.lhn/funasr_data/aishell-1/data/test/wav.scp" |
| | | label_text="/nfs/haoneng.lhn/funasr_data/aishell-1/data/test/text" |
| | | export_root="/nfs/zhifu.gzf/export" |
| | | split_scps_tool=split_scp.pl |
| | | inference_tool=infer.py |
| | | proce_text_tool=proce_text.py |
| | | compute_wer_tool=compute_wer.py |
| | | |
| | | |
| | | #:<<! |
| | | model_name="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
| | | backend="onnx" # "torch" |
| | | quantize='true' # 'False' |
| | | tag=${model_name}/${backend}_quantize_${quantize} |
| | | fallback_op_num_torch=20 |
| | | tag=${model_name}/${backend}_quantize_${quantize}_${fallback_op_num_torch} |
| | | ! |
| | | |
| | | output_dir=${export_root}/logs/${tag}/split$nj |
| | |
| | | |
| | | if [ $stage -le 0 ] && [ $stop_stage -ge 0 ];then |
| | | |
| | | python -m funasr.export.export_model --model-name ${model_name} --export-dir ${export_root} --type ${backend} --quantize ${quantize} --audio_in ${scp} |
| | | python -m funasr.export.export_model --model-name ${model_name} --export-dir ${export_root} --type ${backend} --quantize ${quantize} --audio_in ${scp} --fallback-num ${fallback_op_num_torch} |
| | | |
| | | fi |
| | | |
| | |
| | | for JOB in $(seq ${nj}); do |
| | | { |
| | | core_id=`expr $JOB - 1` |
| | | taskset -c ${core_id} python ${rtf_tool} --backend ${backend} --model_dir ${model_dir} --wav_file ${output_dir}/wav.$JOB.scp --quantize ${quantize} --output_dir ${output_dir}/${JOB} &> ${output_dir}/log.$JOB.txt |
| | | taskset -c ${core_id} python ${inference_tool} --backend ${backend} --model_dir ${model_dir} --wav_file ${output_dir}/wav.$JOB.scp --quantize ${quantize} --output_dir ${output_dir}/${JOB} &> ${output_dir}/log.$JOB.txt |
| | | }& |
| | | |
| | | done |
| | |
| | | for f in token text; do |
| | | if [ -f "${output_dir}/1/${f}" ]; then |
| | | for JOB in $(seq "${nj}"); do |
| | | cat "${output_dir}/${JOB}/1best_recog/${f}" |
| | | cat "${output_dir}/${JOB}/${f}" |
| | | done | sort -k1 >"${output_dir}/1best_recog/${f}" |
| | | fi |
| | | done |