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#####################################
# SpeechUT ASR model #
#####################################
[ $# -lt 2 ] && echo "Usage: $0 <model_path> <data_dir> [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
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