From e9241112654ea55ed55d02617d52fa93b5f6d8f9 Mon Sep 17 00:00:00 2001
From: 雾聪 <wucong.lyb@alibaba-inc.com>
Date: 星期三, 28 六月 2023 10:38:02 +0800
Subject: [PATCH] add ct-transformer-online
---
funasr/runtime/onnxruntime/src/ct-transformer-online.cpp | 283 +++++++++++++++++++++++++++++++++++++++++++++++
funasr/runtime/onnxruntime/src/ct-transformer-online.h | 37 ++++++
2 files changed, 320 insertions(+), 0 deletions(-)
diff --git a/funasr/runtime/onnxruntime/src/ct-transformer-online.cpp b/funasr/runtime/onnxruntime/src/ct-transformer-online.cpp
new file mode 100644
index 0000000..191cda8
--- /dev/null
+++ b/funasr/runtime/onnxruntime/src/ct-transformer-online.cpp
@@ -0,0 +1,283 @@
+/**
+ * Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+ * MIT License (https://opensource.org/licenses/MIT)
+*/
+
+#include "precomp.h"
+
+namespace funasr {
+CTTransformerOnline::CTTransformerOnline()
+:env_(ORT_LOGGING_LEVEL_ERROR, ""),session_options{}
+{
+}
+
+void CTTransformerOnline::InitPunc(const std::string &punc_model, const std::string &punc_config, int thread_num){
+ session_options.SetIntraOpNumThreads(thread_num);
+ session_options.SetGraphOptimizationLevel(ORT_ENABLE_ALL);
+ session_options.DisableCpuMemArena();
+
+ try{
+ m_session = std::make_unique<Ort::Session>(env_, punc_model.c_str(), session_options);
+ LOG(INFO) << "Successfully load model from " << punc_model;
+ }
+ catch (std::exception const &e) {
+ LOG(ERROR) << "Error when load punc onnx model: " << e.what();
+ exit(0);
+ }
+ // read inputnames outputnames
+ string strName;
+ GetInputName(m_session.get(), strName);
+ m_strInputNames.push_back(strName.c_str());
+ GetInputName(m_session.get(), strName, 1);
+ m_strInputNames.push_back(strName);
+ GetInputName(m_session.get(), strName, 2);
+ m_strInputNames.push_back(strName);
+ GetInputName(m_session.get(), strName, 3);
+ m_strInputNames.push_back(strName);
+
+ GetOutputName(m_session.get(), strName);
+ m_strOutputNames.push_back(strName);
+
+ for (auto& item : m_strInputNames)
+ m_szInputNames.push_back(item.c_str());
+ for (auto& item : m_strOutputNames)
+ m_szOutputNames.push_back(item.c_str());
+
+ m_tokenizer.OpenYaml(punc_config.c_str());
+}
+
+CTTransformerOnline::~CTTransformerOnline()
+{
+}
+
+string CTTransformerOnline::AddPunc(const char* sz_input, vector<string> &arr_cache)
+{
+ string strResult;
+ vector<string> strOut;
+ vector<int> InputData;
+ string strText; //full_text
+ strText = accumulate(arr_cache.begin(), arr_cache.end(), strText);
+ strText += sz_input; // full_text = precache + text
+ m_tokenizer.Tokenize(strText.c_str(), strOut, InputData);
+
+ int nTotalBatch = ceil((float)InputData.size() / TOKEN_LEN);
+ int nCurBatch = -1;
+ int nSentEnd = -1, nLastCommaIndex = -1;
+ vector<int32_t> RemainIDs; //
+ vector<string> RemainStr; //
+ vector<int> new_mini_sentence_punc; // sentence_punc_list = []
+ vector<string> sentenceOut; // sentenceOut
+ vector<string> sentence_punc_list,sentence_words_list,sentence_punc_list_out; // sentence_words_list = []
+
+ int nSkipNum = 0;
+ int nDiff = 0;
+ for (size_t i = 0; i < InputData.size(); i += TOKEN_LEN)
+ {
+ nDiff = (i + TOKEN_LEN) < InputData.size() ? (0) : (i + TOKEN_LEN - InputData.size());
+ vector<int32_t> InputIDs(InputData.begin() + i, InputData.begin() + i + TOKEN_LEN - nDiff);
+ vector<string> InputStr(strOut.begin() + i, strOut.begin() + i + TOKEN_LEN - nDiff);
+ InputIDs.insert(InputIDs.begin(), RemainIDs.begin(), RemainIDs.end()); // RemainIDs+InputIDs;
+ InputStr.insert(InputStr.begin(), RemainStr.begin(), RemainStr.end()); // RemainStr+InputStr;
+
+ auto Punction = Infer(InputIDs, arr_cache.size());
+ nCurBatch = i / TOKEN_LEN;
+ if (nCurBatch < nTotalBatch - 1) // not the last minisetence
+ {
+ nSentEnd = -1;
+ nLastCommaIndex = -1;
+ for (int nIndex = Punction.size() - 2; nIndex > 0; nIndex--)
+ {
+ if (m_tokenizer.Id2Punc(Punction[nIndex]) == m_tokenizer.Id2Punc(PERIOD_INDEX) || m_tokenizer.Id2Punc(Punction[nIndex]) == m_tokenizer.Id2Punc(QUESTION_INDEX))
+ {
+ nSentEnd = nIndex;
+ break;
+ }
+ if (nLastCommaIndex < 0 && m_tokenizer.Id2Punc(Punction[nIndex]) == m_tokenizer.Id2Punc(COMMA_INDEX))
+ {
+ nLastCommaIndex = nIndex;
+ }
+ }
+ if (nSentEnd < 0 && InputStr.size() > CACHE_POP_TRIGGER_LIMIT && nLastCommaIndex > 0)
+ {
+ nSentEnd = nLastCommaIndex;
+ Punction[nSentEnd] = PERIOD_INDEX;
+ }
+ RemainStr.assign(InputStr.begin() + nSentEnd + 1, InputStr.end());
+ RemainIDs.assign(InputIDs.begin() + nSentEnd + 1, InputIDs.end());
+ InputStr.assign(InputStr.begin(), InputStr.begin() + nSentEnd + 1); // minit_sentence
+ Punction.assign(Punction.begin(), Punction.begin() + nSentEnd + 1);
+ }
+
+ for (auto& item : Punction)
+ {
+ sentence_punc_list.push_back(m_tokenizer.Id2Punc(item));
+ }
+
+ sentence_words_list.insert(sentence_words_list.end(), InputStr.begin(), InputStr.end());
+
+ new_mini_sentence_punc.insert(new_mini_sentence_punc.end(), Punction.begin(), Punction.end());
+ }
+ vector<string> WordWithPunc;
+ for (int i = 0; i < sentence_words_list.size(); i++) // for i in range(0, len(sentence_words_list)):
+ {
+ if (i > 0 && !(sentence_words_list[i][0] & 0x80) && (i + 1) < sentence_words_list.size() && !(sentence_words_list[i + 1][0] & 0x80))
+ {
+ sentence_words_list[i] = sentence_words_list[i] + " ";
+ }
+ if (nSkipNum < arr_cache.size()) // if skip_num < len(cache):
+ nSkipNum++;
+ else
+ WordWithPunc.push_back(sentence_words_list[i]);
+
+ if (nSkipNum >= arr_cache.size())
+ {
+ sentence_punc_list_out.push_back(sentence_punc_list[i]);
+ if (sentence_punc_list[i] != NOTPUNC)
+ {
+ WordWithPunc.push_back(sentence_punc_list[i]);
+ }
+ }
+ }
+
+ sentenceOut.insert(sentenceOut.end(), WordWithPunc.begin(), WordWithPunc.end()); //
+ nSentEnd = -1;
+ for (int i = sentence_punc_list.size() - 2; i > 0; i--)
+ {
+ if (new_mini_sentence_punc[i] == PERIOD_INDEX || new_mini_sentence_punc[i] == QUESTION_INDEX)
+ {
+ nSentEnd = i;
+ break;
+ }
+ }
+ arr_cache.assign(sentence_words_list.begin() + nSentEnd + 1, sentence_words_list.end());
+
+ if (sentenceOut.size() > 0 && m_tokenizer.IsPunc(sentenceOut[sentenceOut.size() - 1]))
+ {
+ sentenceOut.assign(sentenceOut.begin(), sentenceOut.end() - 1);
+ sentence_punc_list_out[sentence_punc_list_out.size() - 1] = m_tokenizer.Id2Punc(NOTPUNC_INDEX);
+ }
+ return accumulate(sentenceOut.begin(), sentenceOut.end(), string(""));
+}
+
+vector<int> CTTransformerOnline::Infer(vector<int32_t> input_data, int nCacheSize)
+{
+ Ort::MemoryInfo m_memoryInfo = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
+ vector<int> punction;
+ std::array<int64_t, 2> input_shape_{ 1, (int64_t)input_data.size()};
+ Ort::Value onnx_input = Ort::Value::CreateTensor(
+ m_memoryInfo,
+ input_data.data(),
+ input_data.size() * sizeof(int32_t),
+ input_shape_.data(),
+ input_shape_.size(), ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32);
+
+ std::array<int32_t,1> text_lengths{ (int32_t)input_data.size() };
+ std::array<int64_t,1> text_lengths_dim{ 1 };
+ Ort::Value onnx_text_lengths = Ort::Value::CreateTensor<int32_t>(
+ m_memoryInfo,
+ text_lengths.data(),
+ text_lengths.size(),
+ text_lengths_dim.data(),
+ text_lengths_dim.size()); //, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32);
+
+ //vad_mask
+ vector<float> arVadMask,arSubMask;
+ int nTextLength = input_data.size();
+
+ VadMask(nTextLength, nCacheSize, arVadMask);
+ Triangle(nTextLength, arSubMask);
+ std::array<int64_t, 4> VadMask_Dim{ 1,1, nTextLength ,nTextLength };
+ Ort::Value onnx_vad_mask = Ort::Value::CreateTensor<float>(
+ m_memoryInfo,
+ arVadMask.data(),
+ arVadMask.size(), // * sizeof(float),
+ VadMask_Dim.data(),
+ VadMask_Dim.size()); // , ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);
+ //sub_masks
+
+ std::array<int64_t, 4> SubMask_Dim{ 1,1, nTextLength ,nTextLength };
+ Ort::Value onnx_sub_mask = Ort::Value::CreateTensor<float>(
+ m_memoryInfo,
+ arSubMask.data(),
+ arSubMask.size() ,
+ SubMask_Dim.data(),
+ SubMask_Dim.size()); // , ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);
+
+ std::vector<Ort::Value> input_onnx;
+ input_onnx.emplace_back(std::move(onnx_input));
+ input_onnx.emplace_back(std::move(onnx_text_lengths));
+ input_onnx.emplace_back(std::move(onnx_vad_mask));
+ input_onnx.emplace_back(std::move(onnx_sub_mask));
+
+ try {
+ auto outputTensor = m_session->Run(Ort::RunOptions{nullptr}, m_szInputNames.data(), input_onnx.data(), m_szInputNames.size(), m_szOutputNames.data(), m_szOutputNames.size());
+ std::vector<int64_t> outputShape = outputTensor[0].GetTensorTypeAndShapeInfo().GetShape();
+
+ int64_t outputCount = std::accumulate(outputShape.begin(), outputShape.end(), 1, std::multiplies<int64_t>());
+ float * floatData = outputTensor[0].GetTensorMutableData<float>();
+
+ for (int i = 0; i < outputCount; i += CANDIDATE_NUM)
+ {
+ int index = Argmax(floatData + i, floatData + i + CANDIDATE_NUM-1);
+ punction.push_back(index);
+ }
+ }
+ catch (std::exception const &e)
+ {
+ LOG(ERROR) << "Error when run punc onnx forword: " << (e.what());
+ exit(0);
+ }
+ return punction;
+}
+
+void CTTransformerOnline::VadMask(int nSize, int vad_pos, vector<float>& Result)
+{
+ Result.resize(0);
+ Result.assign(nSize * nSize, 1);
+ if (vad_pos <= 0 || vad_pos >= nSize)
+ {
+ return;
+ }
+ for (int i = 0; i < vad_pos-1; i++)
+ {
+ for (int j = vad_pos; j < nSize; j++)
+ {
+ Result[i * nSize + j] = 0.0f;
+ }
+ }
+}
+
+void CTTransformerOnline::Triangle(int text_length, vector<float>& Result)
+{
+ Result.resize(0);
+ Result.assign(text_length * text_length,1); // generate a zeros: text_length x text_length
+
+ for (int i = 0; i < text_length; i++) // rows
+ {
+ for (int j = i+1; j<text_length; j++) //cols
+ {
+ Result[i * text_length + j] = 0.0f;
+ }
+
+ }
+ //Transport(Result, text_length, text_length);
+}
+
+void CTTransformerOnline::Transport(vector<float>& In,int nRows, int nCols)
+{
+ vector<float> Out;
+ Out.resize(nRows * nCols);
+ int i = 0;
+ for (int j = 0; j < nCols; j++) {
+ for (; i < nRows * nCols; i++) {
+ Out[i] = In[j + nCols * (i % nRows)];
+ if ((i + 1) % nRows == 0) {
+ i++;
+ break;
+ }
+ }
+ }
+ In = Out;
+}
+
+} // namespace funasr
diff --git a/funasr/runtime/onnxruntime/src/ct-transformer-online.h b/funasr/runtime/onnxruntime/src/ct-transformer-online.h
new file mode 100644
index 0000000..5db183a
--- /dev/null
+++ b/funasr/runtime/onnxruntime/src/ct-transformer-online.h
@@ -0,0 +1,37 @@
+/**
+ * Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+ * MIT License (https://opensource.org/licenses/MIT)
+*/
+
+#pragma once
+
+namespace funasr {
+class CTTransformerOnline : public PuncModel {
+/**
+ * Author: Speech Lab of DAMO Academy, Alibaba Group
+ * CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection
+ * https://arxiv.org/pdf/2003.01309.pdf
+*/
+
+private:
+
+ CTokenizer m_tokenizer;
+ vector<string> m_strInputNames, m_strOutputNames;
+ vector<const char*> m_szInputNames;
+ vector<const char*> m_szOutputNames;
+
+ std::shared_ptr<Ort::Session> m_session;
+ Ort::Env env_;
+ Ort::SessionOptions session_options;
+public:
+
+ CTTransformerOnline();
+ void InitPunc(const std::string &punc_model, const std::string &punc_config, int thread_num);
+ ~CTTransformerOnline();
+ vector<int> Infer(vector<int32_t> input_data, int nCacheSize);
+ string AddPunc(const char* sz_input, vector<string> &arr_cache);
+ void Transport(vector<float>& In, int nRows, int nCols);
+ void VadMask(int size, int vad_pos,vector<float>& Result);
+ void Triangle(int text_length, vector<float>& Result);
+};
+} // namespace funasr
\ No newline at end of file
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