#!/usr/bin/env bash
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set -e
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set -u
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set -o pipefail
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stage=1
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stop_stage=2
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model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
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data_dir="./data/test"
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output_dir="./results"
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gpu_inference=true # whether to perform gpu decoding
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gpuid_list="0,1" # set gpus, e.g., gpuid_list="0,1"
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njob=64 # the number of jobs for CPU decoding, if gpu_inference=false, use CPU decoding, please set njob
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checkpoint_dir=
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checkpoint_name="punc.pb"
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. utils/parse_options.sh || exit 1;
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if ${gpu_inference} == "true"; then
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nj=$(echo $gpuid_list | awk -F "," '{print NF}')
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else
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nj=$njob
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gpuid_list=""
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for JOB in $(seq ${nj}); do
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gpuid_list=$gpuid_list"-1,"
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done
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fi
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mkdir -p $output_dir/split
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split_scps=""
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for JOB in $(seq ${nj}); do
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split_scps="$split_scps $output_dir/split/text.$JOB.scp"
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done
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perl utils/split_scp.pl ${data_dir}/punc.txt ${split_scps}
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if [ -n "${checkpoint_dir}" ]; then
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python utils/prepare_checkpoint.py ${model} ${checkpoint_dir} ${checkpoint_name}
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model=${checkpoint_dir}/${model}
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fi
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if [ $stage -le 1 ] && [ $stop_stage -ge 1 ];then
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echo "Decoding ..."
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gpuid_list_array=(${gpuid_list//,/ })
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for JOB in $(seq ${nj}); do
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{
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id=$((JOB-1))
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gpuid=${gpuid_list_array[$id]}
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mkdir -p ${output_dir}/output.$JOB
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python infer.py \
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--model ${model} \
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--text_in ${output_dir}/split/text.$JOB.scp \
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--output_dir ${output_dir}/output.$JOB \
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--gpuid ${gpuid}
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}&
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done
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wait
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mkdir -p ${output_dir}/final_res
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if [ -f "${output_dir}/output.1/infer.out" ]; then
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for i in $(seq "${nj}"); do
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cat "${output_dir}/output.${i}/infer.out"
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done | sort -k1 >"${output_dir}/final_res/infer.out"
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fi
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fi
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