##################################### # SpeechUT ASR model # ##################################### [ $# -lt 2 ] && echo "Usage: $0 [gen-set=dev_other] [beam_size=10] [ctc_weight=0.2] [nj=32] [ngpu=8] [--normalize]" && exit 1 [ ${PWD##*/} != SpeechUT ] && echo "Error: dir not match! Switch to SpeechUT/ and run it again!" && exit 1 model_path=$1 DATA_DIR=$2 gen_set=$3 beam_size=$4 ctc_weight=$5 nj=$6 ngpu=$7 extra=$8 [ -z $extra ] && echo "Assert decoding base model! If you are decoding large model, please add '--normalize' at the end..." [ -z $gen_set ] && gen_set="dev_other" [ -z $beam_size ] && beam_size=10 [ -z $ctc_weight ] && ctc_weight=0.2 [ $ctc_weight == 0 ] && [ $beam_size != 1 ] && echo "Change beam size to 1 as no ctc-decoding used..." && beam_size=1 [ $ctc_weight != 0 ] && extra="$extra --batch-size 1" [ -z $nj ] && nj=32 [ -z $ngpu ] && ngpu=8 src_dir=${model_path%/*} cpt=${model_path##*/} cpt=${cpt%.*} CODE_ROOT=${PWD} world_size=$nj for rank in $(seq 0 $((nj - 1))); do export CUDA_VISIBLE_DEVICES=$((rank % $ngpu)) for subset in ${gen_set//,/ }; do results_path=$src_dir/decode_${cpt}/beam${beam_size}_ctc${ctc_weight}/${subset}_${world_size}_${rank} [ ! -d $results_path ] && mkdir -p $results_path python $CODE_ROOT/fairseq/fairseq_cli/generate.py $DATA_DIR \ --user-dir $CODE_ROOT/speechut \ --label-dir ${DATA_DIR} \ --labels '["ltr"]' \ --single-target \ --post-process letter \ --gen-subset ${subset} \ --max-tokens 2000000 \ \ --task joint_sc2t_pretraining \ --add-decoder-target \ --fine-tuning \ --pad-audio \ --random-crop \ \ --ctc-weight ${ctc_weight} $extra \ --beam ${beam_size} \ \ --path ${model_path} \ --results-path $results_path \ \ --scoring wer --max-len-a 0.00078125 --max-len-b 200 \ --distributed-world-size ${world_size} --distributed-rank ${rank} \ & done done wait for subset in ${gen_set//,/ }; do results_dir=$src_dir/decode_${cpt}/beam${beam_size}_ctc${ctc_weight} cat $results_dir/${subset}_${world_size}_*/generate-${subset}.txt | grep -v "^Generate" > $results_dir/generate-${subset}.all.txt done