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91 lines
2.2 KiB
91 lines
2.2 KiB
#!/bin/bash
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set -e
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expdir=exp
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datadir=data
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nj=32
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lmtag=
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recog_set="test-clean test-other dev-clean dev-other"
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recog_set="test-clean"
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# bpemode (unigram or bpe)
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nbpe=5000
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bpemode=unigram
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bpeprefix="data/bpe_${bpemode}_${nbpe}"
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bpemodel=${bpeprefix}.model
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if [ $# != 3 ];then
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echo "usage: ${0} config_path dict_path ckpt_path_prefix"
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exit -1
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fi
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ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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echo "using $ngpu gpus..."
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config_path=$1
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dict=$2
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ckpt_prefix=$3
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chunk_mode=false
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if [[ ${config_path} =~ ^.*chunk_.*yaml$ ]];then
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chunk_mode=true
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fi
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echo "chunk mode ${chunk_mode}"
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# download language model
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#bash local/download_lm_en.sh
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#if [ $? -ne 0 ]; then
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# exit 1
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#fi
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pids=() # initialize pids
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for dmethd in attention ctc_greedy_search ctc_prefix_beam_search attention_rescoring; do
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(
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for rtask in ${recog_set}; do
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(
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decode_dir=decode_${rtask}_${dmethd}_$(basename ${config_path%.*})_${lmtag}
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feat_recog_dir=${datadir}
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mkdir -p ${expdir}/${decode_dir}
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mkdir -p ${feat_recog_dir}
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# split data
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split_json.sh ${feat_recog_dir}/manifest.${rtask} ${nj}
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#### use CPU for decoding
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ngpu=0
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# set batchsize 0 to disable batch decoding
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batch_size=1
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${decode_cmd} JOB=1:${nj} ${expdir}/${decode_dir}/log/decode.JOB.log \
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python3 -u ${BIN_DIR}/test.py \
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--model-name u2_kaldi \
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--run-mode test \
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--nproc ${ngpu} \
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--dict-path ${dict} \
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--config ${config_path} \
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--checkpoint_path ${ckpt_prefix} \
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--result-file ${expdir}/${decode_dir}/data.JOB.json \
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--opts decoding.decoding_method ${dmethd} \
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--opts decoding.batch_size ${batch_size} \
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--opts data.test_manifest ${feat_recog_dir}/split${nj}/JOB/manifest.${rtask}
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score_sclite.sh --bpe ${nbpe} --bpemodel ${bpemodel}.model --wer true ${expdir}/${decode_dir} ${dict}
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) &
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pids+=($!) # store background pids
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done
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) &
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pids+=($!) # store background pids
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done
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i=0; for pid in "${pids[@]}"; do wait ${pid} || ((++i)); done
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[ ${i} -gt 0 ] && echo "$0: ${i} background jobs are failed." && false
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echo "Finished"
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exit 0
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