From 1d7ba1be1ad824135698e8000386c1fd55268ae4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E8=AF=AD=E5=B8=86?= <yf352572@alibaba-inc.com>
Date: Mon, 4 Mar 2024 13:52:21 +0800
Subject: [PATCH] atsr

---
 .gitignore                                    |  1 +
 .../lcbnet/demo2.sh                           | 71 +++++++++++++++++++
 .../lcbnet/demo2_tmp.sh                       | 71 +++++++++++++++++++
 .../lcbnet/demo_pdb.sh                        |  9 ++-
 .../lcbnet/demo_pdb2.sh                       | 15 ++++
 .../lcbnet/demo_tmp1.sh                       | 71 +++++++++++++++++++
 6 files changed, 236 insertions(+), 2 deletions(-)
 create mode 100755 examples/industrial_data_pretraining/lcbnet/demo2.sh
 create mode 100755 examples/industrial_data_pretraining/lcbnet/demo2_tmp.sh
 create mode 100755 examples/industrial_data_pretraining/lcbnet/demo_pdb2.sh
 create mode 100755 examples/industrial_data_pretraining/lcbnet/demo_tmp1.sh

diff --git a/.gitignore b/.gitignore
index bdfe70f1a..d2b4c53b9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -25,4 +25,5 @@ outputs*
 emotion2vec*
 GPT-SoVITS*
 examples/*/*/outputs
+examples/*/*/exp
 cmd_read
diff --git a/examples/industrial_data_pretraining/lcbnet/demo2.sh b/examples/industrial_data_pretraining/lcbnet/demo2.sh
new file mode 100755
index 000000000..69df6d16c
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/demo2.sh
@@ -0,0 +1,71 @@
+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"
+test_set="dev_wav"
+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/slidespeech_dev_beamsearch_wav"
+_logdir="${inference_dir}/logdir"
+echo "inference_dir: ${inference_dir}"
+
+mkdir -p "${_logdir}"
+key_file1=${file_dir}/${test_set}/wav.scp
+key_file2=${file_dir}/${test_set}/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='["sound", "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 JOB in $(seq "${nj}"); do
+   cat "${inference_dir}/${JOB}/1best_recog/token" >> "${inference_dir}/1best_recog/token"
+done  
+
+echo "Computing WER ..."
+sed -e 's/ /\t/' -e 's/ //g' -e 's/▁/ /g' -e 's/\t /\t/'  ${inference_dir}/1best_recog/token > ${inference_dir}/1best_recog/token.proc
+cp  ${file_dir}/${test_set}/text ${inference_dir}/1best_recog/token.ref
+cp  ${file_dir}/${test_set}/ocr.list ${inference_dir}/1best_recog/ocr.list
+python utils/compute_wer.py ${inference_dir}/1best_recog/token.ref ${inference_dir}/1best_recog/token.proc ${inference_dir}/1best_recog/token.cer
+tail -n 3 ${inference_dir}/1best_recog/token.cer
+
+./run_bwer_recall.sh  ${inference_dir}/1best_recog/
+tail -n 6 ${inference_dir}/1best_recog/BWER-UWER.results |head -n 5
diff --git a/examples/industrial_data_pretraining/lcbnet/demo2_tmp.sh b/examples/industrial_data_pretraining/lcbnet/demo2_tmp.sh
new file mode 100755
index 000000000..da6ad686d
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/demo2_tmp.sh
@@ -0,0 +1,71 @@
+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"
+test_set="test_wav"
+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/slidespeech_test_beamsearch_wav"
+_logdir="${inference_dir}/logdir"
+echo "inference_dir: ${inference_dir}"
+
+mkdir -p "${_logdir}"
+key_file1=${file_dir}/${test_set}/wav.scp
+key_file2=${file_dir}/${test_set}/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='["sound", "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 JOB in $(seq "${nj}"); do
+   cat "${inference_dir}/${JOB}/1best_recog/token" >> "${inference_dir}/1best_recog/token"
+done  
+
+echo "Computing WER ..."
+sed -e 's/ /\t/' -e 's/ //g' -e 's/▁/ /g' -e 's/\t /\t/'  ${inference_dir}/1best_recog/token > ${inference_dir}/1best_recog/token.proc
+cp  ${file_dir}/${test_set}/text ${inference_dir}/1best_recog/token.ref
+cp  ${file_dir}/${test_set}/ocr.list ${inference_dir}/1best_recog/ocr.list
+python utils/compute_wer.py ${inference_dir}/1best_recog/token.ref ${inference_dir}/1best_recog/token.proc ${inference_dir}/1best_recog/token.cer
+tail -n 3 ${inference_dir}/1best_recog/token.cer
+
+./run_bwer_recall.sh  ${inference_dir}/1best_recog/
+tail -n 6 ${inference_dir}/1best_recog/BWER-UWER.results |head -n 5
diff --git a/examples/industrial_data_pretraining/lcbnet/demo_pdb.sh b/examples/industrial_data_pretraining/lcbnet/demo_pdb.sh
index e435905bf..0747a8d7b 100755
--- a/examples/industrial_data_pretraining/lcbnet/demo_pdb.sh
+++ b/examples/industrial_data_pretraining/lcbnet/demo_pdb.sh
@@ -6,8 +6,13 @@ python -m funasr.bin.inference \
 --config-name="config.yaml" \
 ++init_param=${file_dir}/model.pb \
 ++tokenizer_conf.token_list=${file_dir}/tokens.txt \
-++input=[${file_dir}/dev/wav.scp,${file_dir}/dev/ocr.txt] \
-+data_type='["kaldi_ark", "text"]' \
++input=["${file_dir}/example/asr_example.wav","${file_dir}/example/ocr.txt"] \
++data_type='["sound","text"]' \
 ++tokenizer_conf.bpemodel=${file_dir}/bpe.model \
 ++output_dir="./outputs/debug" \
 ++device="cpu" \
+
+#++input=["/nfs/yufan.yf/workspace/espnet/egs2/youtube_ppt/asr/dump/raw/dev_oracle_v1_new/data/format.1/YTB+--tMoLpQI-w+00322.wav"] \
+#+data_type='["sound"]' \
+#++input=["/nfs/yufan.yf/workspace/espnet/egs2/youtube_ppt/asr/dump/raw/dev_oracle_v1_new/data/format.1/YTB+--tMoLpQI-w+00322.wav","/nfs/yufan.yf/workspace/github/FunASR/examples/industrial_data_pretraining/lcbnet/exp/speech_lcbnet_contextual_asr-en-16k-bpe-vocab5002-pytorch/example/ocr2.txt"]  \
+#+data_type='["sound","text"]' \
diff --git a/examples/industrial_data_pretraining/lcbnet/demo_pdb2.sh b/examples/industrial_data_pretraining/lcbnet/demo_pdb2.sh
new file mode 100755
index 000000000..557e9b2d8
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/demo_pdb2.sh
@@ -0,0 +1,15 @@
+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="" \
+python -m funasr.bin.inference \
+--config-path=${file_dir} \
+--config-name="config.yaml" \
+++init_param=${file_dir}/model.pb \
+++tokenizer_conf.token_list=${file_dir}/tokens.txt \
+++input=[${file_dir}/dev_wav/wav.scp,${file_dir}/dev_wav/ocr.txt] \
++data_type='["sound", "text"]' \
+++tokenizer_conf.bpemodel=${file_dir}/bpe.model \
+++output_dir="./outputs/debug" \
+++device="cpu" \
+
+#++input=[${file_dir}/dev_wav/wav.scp,${file_dir}/dev_wav/ocr.txt] \
diff --git a/examples/industrial_data_pretraining/lcbnet/demo_tmp1.sh b/examples/industrial_data_pretraining/lcbnet/demo_tmp1.sh
new file mode 100755
index 000000000..488f7d2a1
--- /dev/null
+++ b/examples/industrial_data_pretraining/lcbnet/demo_tmp1.sh
@@ -0,0 +1,71 @@
+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/slidespeech_test_beamsearch_new"
+_logdir="${inference_dir}/logdir"
+echo "inference_dir: ${inference_dir}"
+
+mkdir -p "${_logdir}"
+key_file1=${file_dir}/test/wav.scp
+key_file2=${file_dir}/test/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 JOB in $(seq "${nj}"); do
+   cat "${inference_dir}/${JOB}/1best_recog/token" >> "${inference_dir}/1best_recog/token"
+done  
+
+echo "Computing WER ..."
+sed -e 's/ /\t/' -e 's/ //g' -e 's/▁/ /g' -e 's/\t /\t/'  ${inference_dir}/1best_recog/token > ${inference_dir}/1best_recog/token.proc
+cp  ${file_dir}/test/text ${inference_dir}/1best_recog/token.ref
+cp  ${file_dir}/test/ocr.list ${inference_dir}/1best_recog/ocr.list
+python utils/compute_wer.py ${inference_dir}/1best_recog/token.ref ${inference_dir}/1best_recog/token.proc ${inference_dir}/1best_recog/token.cer
+tail -n 3 ${inference_dir}/1best_recog/token.cer
+
+./run_bwer_recall.sh  ${inference_dir}/1best_recog/
+tail -n 6 ${inference_dir}/1best_recog/BWER-UWER.results |head -n 5