| | |
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| | | |
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| | | # general configuration |
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| | | feats_dir="../DATA" #feature output dictionary |
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| | | exp_dir="." |
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| | | exp_dir=`pwd` |
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| | | lang=zh |
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| | | token_type=char |
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| | | stage=0 |
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| | |
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| | | log_file="${exp_dir}/exp/${model_dir}/train.log.txt.${current_time}" |
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| | | echo "log_file: ${log_file}" |
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| | | |
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| | | export CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES |
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| | | gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}') |
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| | | torchrun \ |
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| | | --nnodes 1 \ |
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| | |
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| | | if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then |
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| | | echo "stage 5: Inference" |
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| | | |
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| | | if ${inference_device} == "cuda"; then |
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| | | if [ ${inference_device} == "cuda" ]; then |
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| | | nj=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}') |
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| | | else |
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| | | inference_batch_size=1 |
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| | |
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| | | ++input="${_logdir}/keys.${JOB}.scp" \ |
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| | | ++output_dir="${inference_dir}/${JOB}" \ |
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| | | ++device="${inference_device}" \ |
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| | | ++batch_size="${inference_batch_size}" |
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| | | ++batch_size="${inference_batch_size}" &> ${_logdir}/log.${JOB}.txt |
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| | | }& |
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| | | |
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| | | done |
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