From 5f91acae0d8be4b3223bcb4732bad2796d654547 Mon Sep 17 00:00:00 2001
From: 语帆 <yf352572@alibaba-inc.com>
Date: 星期三, 28 二月 2024 19:35:32 +0800
Subject: [PATCH] test
---
/dev/null | 72 ------------------------
examples/industrial_data_pretraining/lcbnet/demo_nj2.sh | 72 ++++++++++++++++++++++++
examples/industrial_data_pretraining/lcbnet/utils | 1
3 files changed, 73 insertions(+), 72 deletions(-)
diff --git a/examples/industrial_data_pretraining/lcbnet/demo_nj.sh b/examples/industrial_data_pretraining/lcbnet/demo_nj.sh
deleted file mode 100755
index d9f42a0..0000000
--- a/examples/industrial_data_pretraining/lcbnet/demo_nj.sh
+++ /dev/null
@@ -1,72 +0,0 @@
-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"
-inference_device="cuda"
-
-if [ ${inference_device} == "cuda" ]; then
- nj=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
-else
- inference_batch_size=1
- CUDA_VISIBLE_DEVICES=""
- for JOB in $(seq ${nj}); do
- CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"-1,"
- done
-fi
-
-inference_dir="outputs/test"
-_logdir="${inference_dir}/logdir"
-echo "inference_dir: ${inference_dir}"
-
-# mkdir -p "${_logdir}"
-# key_file1=${file_dir}/wav.scp
-# key_file2=${file_dir}/ocr.txt
-# split_scps1=
-# split_scps2=
-# for JOB in $(seq "${nj}"); do
-# split_scps1+=" ${_logdir}/wav.${JOB}.scp"
-# split_scps2+=" ${_logdir}/ocr.${JOB}.txt"
-# done
-# utils/split_scp.pl "${key_file1}" ${split_scps1}
-# utils/split_scp.pl "${key_file2}" ${split_scps2}
-
-# gpuid_list_array=(${CUDA_VISIBLE_DEVICES//,/ })
-# for JOB in $(seq ${nj}); do
-# {
-# id=$((JOB-1))
-# gpuid=${gpuid_list_array[$id]}
-
-# export CUDA_VISIBLE_DEVICES=${gpuid}
-
-# python -m funasr.bin.inference \
-# --config-path=${file_dir} \
-# --config-name="config.yaml" \
-# ++init_param=${file_dir}/model.pb \
-# ++tokenizer_conf.token_list=${file_dir}/tokens.txt \
-# ++input=[${_logdir}/wav.${JOB}.scp,${_logdir}/ocr.${JOB}.txt] \
-# +data_type='["kaldi_ark", "text"]' \
-# ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \
-# ++output_dir="${inference_dir}/${JOB}" \
-# ++device="${inference_device}" \
-# ++ncpu=1 \
-# ++disable_log=true &> ${_logdir}/log.${JOB}.txt
-
-# }&
-# done
-# wait
-
-
-#mkdir -p ${inference_dir}/1best_recog
-for f in token; do
- if [ -f "${inference_dir}/${JOB}/1best_recog/${f}" ]; then
- for JOB in $(seq "${nj}"); do
- cat "${inference_dir}/${JOB}/1best_recog/${f}"
- done | sort -k1 >"${inference_dir}/1best_recog/${f}"
- fi
-done
-
-echo "Computing WER ..."
-echo "Computing WER ..."
-#python utils/postprocess_text_zh.py ${inference_dir}/1best_recog/text ${inference_dir}/1best_recog/text.proc
-
-#cp ${data_dir}/text ${inference_dir}/1best_recog/text.ref
-#python utils/compute_wer.py ${inference_dir}/1best_recog/text.ref ${inference_dir}/1best_recog/text.proc ${inference_dir}/1best_recog/text.cer
-#tail -n 3 ${inference_dir}/1best_recog/text.cer
\ No newline at end of file
diff --git a/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh b/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh
new file mode 100644
index 0000000..205c28f
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/demo_nj2.sh
@@ -0,0 +1,72 @@
+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"
+inference_device="cuda"
+
+if [ ${inference_device} == "cuda" ]; then
+ nj=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
+ else
+ inference_batch_size=1
+ CUDA_VISIBLE_DEVICES=""
+ for JOB in $(seq ${nj}); do
+ CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"-1,"
+ done
+ fi
+
+ inference_dir="outputs/test"
+ _logdir="${inference_dir}/logdir"
+ echo "inference_dir: ${inference_dir}"
+
+ # mkdir -p "${_logdir}"
+ # key_file1=${file_dir}/wav.scp
+ # key_file2=${file_dir}/ocr.txt
+ # split_scps1=
+ # split_scps2=
+ # for JOB in $(seq "${nj}"); do
+ # split_scps1+=" ${_logdir}/wav.${JOB}.scp"
+ # split_scps2+=" ${_logdir}/ocr.${JOB}.txt"
+ # done
+ # utils/split_scp.pl "${key_file1}" ${split_scps1}
+ # utils/split_scp.pl "${key_file2}" ${split_scps2}
+
+ # gpuid_list_array=(${CUDA_VISIBLE_DEVICES//,/ })
+ # for JOB in $(seq ${nj}); do
+ # {
+ # id=$((JOB-1))
+ # gpuid=${gpuid_list_array[$id]}
+
+ # export CUDA_VISIBLE_DEVICES=${gpuid}
+
+ # python -m funasr.bin.inference \
+ # --config-path=${file_dir} \
+ # --config-name="config.yaml" \
+ # ++init_param=${file_dir}/model.pb \
+ # ++tokenizer_conf.token_list=${file_dir}/tokens.txt \
+ # ++input=[${_logdir}/wav.${JOB}.scp,${_logdir}/ocr.${JOB}.txt] \
+ # +data_type='["kaldi_ark", "text"]' \
+ # ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \
+ # ++output_dir="${inference_dir}/${JOB}" \
+ # ++device="${inference_device}" \
+ # ++ncpu=1 \
+ # ++disable_log=true &> ${_logdir}/log.${JOB}.txt
+
+ # }&
+ # done
+ # wait
+
+
+ #mkdir -p ${inference_dir}/1best_recog
+ for f in token; do
+ if [ -f "${inference_dir}/${JOB}/1best_recog/${f}" ]; then
+ for JOB in $(seq "${nj}"); do
+ cat "${inference_dir}/${JOB}/1best_recog/${f}"
+ done | sort -k1 >"${inference_dir}/1best_recog/${f}"
+ fi
+ done
+
+ echo "Computing WER ..."
+ echo "Computing WER ..."
+ #python utils/postprocess_text_zh.py ${inference_dir}/1best_recog/text ${inference_dir}/1best_recog/text.proc
+
+ #cp ${data_dir}/text ${inference_dir}/1best_recog/text.ref
+ #python utils/compute_wer.py ${inference_dir}/1best_recog/text.ref ${inference_dir}/1best_recog/text.proc ${inference_dir}/1best_recog/text.cer
+ #tail -n 3 ${inference_dir}/1best_recog/text.cer
diff --git a/examples/industrial_data_pretraining/lcbnet/utils b/examples/industrial_data_pretraining/lcbnet/utils
new file mode 120000
index 0000000..be5e5a3
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/utils
@@ -0,0 +1 @@
+../../aishell/paraformer/utils
\ No newline at end of file
--
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