atsr

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2024-03-04 1a6d9d5cc422dcd1e6dd5b9c67047d63bc6cd667

 examples/industrial_data_pretraining/lcbnet/demo.sh

@@ -1,5 +1,5 @@
file_dir="/nfs/yufan.yf/workspace/github/FunASR/examples/industrial_data_pretraining/lcbnet/exp/speech_lcbnet_contextual_asr-en-16k-bpe-vocab5002-pytorch"
CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
file_dir="/home/yf352572/.cache/modelscope/hub/iic/LCB-NET/"
CUDA_VISIBLE_DEVICES="0,1"
inference_device="cuda"

if [ ${inference_device} == "cuda" ]; then
@@ -12,7 +12,7 @@
    done
fi

inference_dir="outputs/slidespeech_dev_beamsearch_new"
inference_dir="outputs/slidespeech_dev"
_logdir="${inference_dir}/logdir"
echo "inference_dir: ${inference_dir}"

@@ -39,11 +39,11 @@
        python -m funasr.bin.inference \
        --config-path=${file_dir} \
        --config-name="config.yaml" \
        ++init_param=${file_dir}/model.pb \
        ++init_param=${file_dir}/model.pt \
        ++tokenizer_conf.token_list=${file_dir}/tokens.txt \
        ++input=[${_logdir}/wav.${JOB}.scp,${_logdir}/ocr.${JOB}.txt] \
        +data_type='["kaldi_ark", "text"]' \
        ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \
        ++tokenizer_conf.bpemodel=${file_dir}/bpe.pt \
        ++output_dir="${inference_dir}/${JOB}" \
        ++device="${inference_device}" \
        ++ncpu=1 \