From 05f8022500ece4bd0aad838af8e36f7f0264eba4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 01 七月 2024 11:16:23 +0800
Subject: [PATCH] update
---
/dev/null | 83 -----------------------------------------
1 files changed, 0 insertions(+), 83 deletions(-)
diff --git a/examples/industrial_data_pretraining/sense_voice/demo.py b/examples/industrial_data_pretraining/sense_voice/demo.py
deleted file mode 100644
index 5303999..0000000
--- a/examples/industrial_data_pretraining/sense_voice/demo.py
+++ /dev/null
@@ -1,28 +0,0 @@
-#!/usr/bin/env python3
-# -*- encoding: utf-8 -*-
-# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
-# MIT License (https://opensource.org/licenses/MIT)
-
-from funasr import AutoModel
-
-model = AutoModel(
- model="/Users/zhifu/Downloads/modelscope_models/SenseVoiceModelscope",
- # vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch",
- # vad_kwargs={"max_single_segment_time": 30000},
-)
-
-
-input_wav = (
- "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"
-)
-
-DecodingOptions = {
- "task": ("ASR", "AED", "SER"),
- "language": "auto",
- "fp16": True,
- "gain_event": True,
- "beam_size": 5,
-}
-
-res = model.generate(input=input_wav, batch_size_s=0, DecodingOptions=DecodingOptions)
-print(res)
diff --git a/examples/industrial_data_pretraining/sense_voice/demo_ctc.py b/examples/industrial_data_pretraining/sense_voice/demo_ctc.py
deleted file mode 100644
index a8ba7f9..0000000
--- a/examples/industrial_data_pretraining/sense_voice/demo_ctc.py
+++ /dev/null
@@ -1,25 +0,0 @@
-#!/usr/bin/env python3
-# -*- encoding: utf-8 -*-
-# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
-# MIT License (https://opensource.org/licenses/MIT)
-
-import sys
-from funasr import AutoModel
-
-model_dir = "/Users/zhifu/Downloads/modelscope_models/SenseVoiceCTC"
-input_file = (
- "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"
-)
-
-model = AutoModel(
- model=model_dir,
-)
-
-res = model.generate(
- input=input_file,
- cache={},
- language="auto",
- text_norm="woitn",
-)
-
-print(res)
diff --git a/examples/industrial_data_pretraining/sense_voice/demo_fsmn.py b/examples/industrial_data_pretraining/sense_voice/demo_fsmn.py
deleted file mode 100644
index ce4bdf8..0000000
--- a/examples/industrial_data_pretraining/sense_voice/demo_fsmn.py
+++ /dev/null
@@ -1,28 +0,0 @@
-#!/usr/bin/env python3
-# -*- encoding: utf-8 -*-
-# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
-# MIT License (https://opensource.org/licenses/MIT)
-
-from funasr import AutoModel
-
-model = AutoModel(
- model="/Users/zhifu/Downloads/modelscope_models/SenseVoiceModelscopeFSMN",
- vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch",
- vad_kwargs={"max_single_segment_time": 30000},
-)
-
-
-input_wav = (
- "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"
-)
-
-DecodingOptions = {
- "task": ("ASR", "AED", "SER"),
- "language": "auto",
- "fp16": True,
- "gain_event": True,
- "beam_size": 5,
-}
-
-res = model.generate(input=input_wav, batch_size_s=0, DecodingOptions=DecodingOptions, beam_size=5)
-print(res)
diff --git a/examples/industrial_data_pretraining/sense_voice/finetune.sh b/examples/industrial_data_pretraining/sense_voice/finetune.sh
deleted file mode 100644
index ce19eb3..0000000
--- a/examples/industrial_data_pretraining/sense_voice/finetune.sh
+++ /dev/null
@@ -1,83 +0,0 @@
-# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
-# MIT License (https://opensource.org/licenses/MIT)
-
-workspace=`pwd`
-
-# which gpu to train or finetune
-export CUDA_VISIBLE_DEVICES="0"
-gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
-
-# model_name from model_hub, or model_dir in local path
-
-## option 1, download model automatically
-model_name_or_model_dir="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
-model_name_or_model_dir="/Users/zhifu/Downloads/modelscope_models/SenseVoiceModelscope"
-## option 2, download model by git
-#local_path_root=${workspace}/modelscope_models
-#mkdir -p ${local_path_root}/${model_name_or_model_dir}
-#git clone https://www.modelscope.cn/${model_name_or_model_dir}.git ${local_path_root}/${model_name_or_model_dir}
-#model_name_or_model_dir=${local_path_root}/${model_name_or_model_dir}
-
-
-# data dir, which contains: train.json, val.json
-data_dir="../../../data/list"
-
-train_data="${data_dir}/train.jsonl"
-val_data="${data_dir}/val.jsonl"
-
-# generate train.jsonl and val.jsonl from wav.scp and text.txt
-scp2jsonl \
-++scp_file_list='["../../../data/list/train_wav.scp", "../../../data/list/train_text.txt"]' \
-++data_type_list='["source", "target"]' \
-++jsonl_file_out="${train_data}"
-
-scp2jsonl \
-++scp_file_list='["../../../data/list/val_wav.scp", "../../../data/list/val_text.txt"]' \
-++data_type_list='["source", "target"]' \
-++jsonl_file_out="${val_data}"
-
-
-# exp output dir
-output_dir="./outputs"
-log_file="${output_dir}/log.txt"
-
-
-mkdir -p ${output_dir}
-echo "log_file: ${log_file}"
-
-deepspeed_config=${workspace}/../../ds_stage1.json
-
-DISTRIBUTED_ARGS="
- --nnodes ${WORLD_SIZE:-1} \
- --nproc_per_node $gpu_num \
- --node_rank ${RANK:-0} \
- --master_addr ${MASTER_ADDR:-127.0.0.1} \
- --master_port ${MASTER_PORT:-26669}
-"
-
-echo $DISTRIBUTED_ARGS
-
-torchrun $DISTRIBUTED_ARGS \
-../../../funasr/bin/train_ds.py \
-++model="${model_name_or_model_dir}" \
-++train_data_set_list="${train_data}" \
-++valid_data_set_list="${val_data}" \
-++dataset="SenseVoiceDataset" \
-++dataset_conf.IndexDSJsonl="IndexDSJsonl" \
-++dataset_conf.data_split_num=1 \
-++dataset_conf.batch_sampler="BatchSampler" \
-++dataset_conf.batch_size=6000 \
-++dataset_conf.sort_size=1024 \
-++dataset_conf.batch_type="token" \
-++dataset_conf.num_workers=4 \
-++train_conf.max_epoch=50 \
-++train_conf.log_interval=1 \
-++train_conf.resume=true \
-++train_conf.validate_interval=2000 \
-++train_conf.save_checkpoint_interval=2000 \
-++train_conf.keep_nbest_models=20 \
-++train_conf.avg_nbest_model=10 \
-++train_conf.use_deepspeed=false \
-++train_conf.deepspeed_config=${deepspeed_config} \
-++optim_conf.lr=0.0002 \
-++output_dir="${output_dir}" #&> ${log_file}
\ No newline at end of file
--
Gitblit v1.9.1