large punc model modelscope pipeline

This commit is contained in:
mengzhe.cmz 2023-07-25 15:41:48 +08:00
parent 1dcdd5f8a6
commit edcd1a7292
11 changed files with 129 additions and 6 deletions

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@ -15,9 +15,9 @@ def modelscope_infer(args):
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=str, default="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch")
parser.add_argument('--model', type=str, default="damo/punc_ct-transformer_cn-en-common-vocab471067-large")
parser.add_argument('--text_in', type=str, default="./data/test/punc.txt")
parser.add_argument('--output_dir', type=str, default="./results/")
parser.add_argument('--gpuid', type=str, default="0")
args = parser.parse_args()
modelscope_infer(args)
modelscope_infer(args)

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@ -7,7 +7,7 @@ set -o pipefail
stage=1
stop_stage=2
model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
data_dir="./data/test"
data_dir="./data"
output_dir="./results"
gpu_inference=true # whether to perform gpu decoding
gpuid_list="0,1" # set gpus, e.g., gpuid_list="0,1"
@ -32,7 +32,7 @@ split_scps=""
for JOB in $(seq ${nj}); do
split_scps="$split_scps $output_dir/split/text.$JOB.scp"
done
perl utils/split_scp.pl ${data_dir}/punc.txt ${split_scps}
perl utils/split_scp.pl ${data_dir}/punc_example.txt ${split_scps}
if [ -n "${checkpoint_dir}" ]; then
python utils/prepare_checkpoint.py ${model} ${checkpoint_dir} ${checkpoint_name}

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@ -0,0 +1 @@
../TEMPLATE/README.md

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@ -0,0 +1,3 @@
1 跨境河流是养育沿岸人民的生命之源长期以来为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难甚至冒着生命危险向印方提供汛期水文资料处理紧急事件中方重视印方在跨境河流问题上的关切愿意进一步完善双方联合工作机制凡是中方能做的我们都会去做而且会做得更好我请印度朋友们放心中国在上游的任何开发利用都会经过科学规划和论证兼顾上下游的利益
2 从存储上来说仅仅是全景图片它就会是图片的四倍的容量然后全景的视频会是普通视频八倍的这个存储的容要求而三d的模型会是图片的十倍这都对我们今天运行在的云计算的平台存储的平台提出了更高的要求
3 那今天的会就到这里吧 happy new year 明年见

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@ -0,0 +1,22 @@
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
inference_pipeline = pipeline(
task=Tasks.punctuation,
model='damo/punc_ct-transformer_cn-en-common-vocab471067-large',
model_revision="v1.0.0",
output_dir="./tmp/"
)
##################text.scp###################
# inputs = "./egs_modelscope/punctuation/punc_ct-transformer_cn-en-common-vocab471067-large/data/punc_example.txt"
##################text#####################
#inputs = "我们都是木头人不会讲话不会动"
##################text file url#######################
inputs = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/punc_example.txt"
rec_result = inference_pipeline(text_in=inputs)
print(rec_result)

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@ -0,0 +1,25 @@
import os
import shutil
import argparse
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
def modelscope_infer(args):
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpuid)
inference_pipeline = pipeline(
task=Tasks.punctuation,
model=args.model,
model_revision=args.model_revision,
output_dir=args.output_dir,
)
inference_pipeline(text_in=args.text_in)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=str, default="damo/punc_ct-transformer_cn-en-common-vocab471067-large")
parser.add_argument('--text_in', type=str, default="./data/test/punc.txt")
parser.add_argument('--model_revision', type=str, default=None)
parser.add_argument('--output_dir', type=str, default="./results/")
parser.add_argument('--gpuid', type=str, default="0")
args = parser.parse_args()
modelscope_infer(args)

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@ -0,0 +1,68 @@
#!/usr/bin/env bash
set -e
set -u
set -o pipefail
stage=1
stop_stage=2
model="damo/punc_ct-transformer_cn-en-common-vocab471067-large"
model_revision="v1.0.0"
data_dir="./data"
output_dir="./results"
gpu_inference=true # whether to perform gpu decoding
gpuid_list="0,1" # set gpus, e.g., gpuid_list="0,1"
njob=64 # the number of jobs for CPU decoding, if gpu_inference=false, use CPU decoding, please set njob
checkpoint_dir=
checkpoint_name="punc.pb"
. utils/parse_options.sh || exit 1;
if ${gpu_inference} == "true"; then
nj=$(echo $gpuid_list | awk -F "," '{print NF}')
else
nj=$njob
gpuid_list=""
for JOB in $(seq ${nj}); do
gpuid_list=$gpuid_list"-1,"
done
fi
mkdir -p $output_dir/split
split_scps=""
for JOB in $(seq ${nj}); do
split_scps="$split_scps $output_dir/split/text.$JOB.scp"
done
perl utils/split_scp.pl ${data_dir}/punc_example.txt ${split_scps}
if [ -n "${checkpoint_dir}" ]; then
python utils/prepare_checkpoint.py ${model} ${checkpoint_dir} ${checkpoint_name}
model=${checkpoint_dir}/${model}
fi
if [ $stage -le 1 ] && [ $stop_stage -ge 1 ];then
echo "Decoding ..."
gpuid_list_array=(${gpuid_list//,/ })
for JOB in $(seq ${nj}); do
{
id=$((JOB-1))
gpuid=${gpuid_list_array[$id]}
mkdir -p ${output_dir}/output.$JOB
python infer.py \
--model ${model} \
--text_in ${output_dir}/split/text.$JOB.scp \
--output_dir ${output_dir}/output.$JOB \
--model_revision ${model_revision}
--gpuid ${gpuid}
}&
done
wait
mkdir -p ${output_dir}/final_res
if [ -f "${output_dir}/output.1/infer.out" ]; then
for i in $(seq "${nj}"); do
cat "${output_dir}/output.${i}/infer.out"
done | sort -k1 >"${output_dir}/final_res/infer.out"
fi
fi

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@ -0,0 +1 @@
../../../egs/aishell/transformer/utils

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@ -0,0 +1,3 @@
1 跨境河流是养育沿岸人民的生命之源长期以来为帮助下游地区防灾减灾中方技术人员在上游地区极为恶劣的自然条件下克服巨大困难甚至冒着生命危险向印方提供汛期水文资料处理紧急事件中方重视印方在跨境河流问题上的关切愿意进一步完善双方联合工作机制凡是中方能做的我们都会去做而且会做得更好我请印度朋友们放心中国在上游的任何开发利用都会经过科学规划和论证兼顾上下游的利益
2 从存储上来说仅仅是全景图片它就会是图片的四倍的容量然后全景的视频会是普通视频八倍的这个存储的容要求而三d的模型会是图片的十倍这都对我们今天运行在的云计算的平台存储的平台提出了更高的要求
3 那今天的会就到这里吧 happy new year 明年见

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@ -0,0 +1 @@
../../../egs/aishell/transformer/utils

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@ -11,7 +11,7 @@ from typing import Union
import numpy as np
import scipy.signal
import soundfile
import jieba
from funasr.text.build_tokenizer import build_tokenizer
from funasr.text.cleaner import TextCleaner
@ -659,7 +659,6 @@ class CodeMixTokenizerCommonPreprocessor(CommonPreprocessor):
self.split_text_name = split_text_name
self.seg_jieba = seg_jieba
if self.seg_jieba:
import jieba
jieba.load_userdict(seg_dict_file)
@classmethod