Datasets:
shibing624
/
source_code

Dataset card Data Studio Files Community
2
text
stringlengths
0
2.2M
p.setElementHandlerStringRef(StartDescriptionElementStringRef<std::string>, EndDescriptionElementStringRef);
p.setXmlDeclHandler(DeclHandler);
p.setCDataHandler(StartCData,EndCData);
p.setCharacterDataHandler(CharacterHandler);
p.setUserData(&userdata);
if (!p.Parse((unsigned char*)data, size))
{
delete mXML;
return 0;
}
if(userdata.mNodeHierarchy.size())
mXML->setRoot(userdata.mNodeHierarchy[0]);
userdata.mNodeHierarchy.clear();
return (XML*)mXML;
}
XMLBase* XMLReaderFile::ProtectedReadFileStringRef(const SP<CoreRawBuffer> buffer, char* encoding)
{
MinimalXML p;
MyUserData userdata;
userdata.mReader = this;
mXML = new XMLStringRef(buffer);
p.setElementHandlerStringRef(StartDescriptionElementStringRef<std::string_view>, EndDescriptionElementStringRef);
p.setXmlDeclHandler(DeclHandler);
p.setCDataHandler(StartCData, EndCDataStringRef<std::string_view>);
p.setCharacterDataHandler(CharacterHandlerStringRef<std::string_view>);
p.setUserData(&userdata);
u64 size = buffer->length();
char* Buff = (char*)buffer->buffer();
if (!p.Parse((unsigned char*)Buff, size))
{
delete mXML;
return 0;
}
if (userdata.mNodeHierarchy.size())
mXML->setRoot(userdata.mNodeHierarchy[0]);
userdata.mNodeHierarchy.clear();
return (XMLStringRef*)mXML;
}
XMLBase* XMLReaderFile::ProtectedReadFile( FileHandle * file )
{
u64 size;
auto rawbuffer = ModuleFileManager::LoadFileAsCharString(file,size,1);
if(rawbuffer)
{
XMLBase* result=0;
result = ProtectedReadFile(rawbuffer.get());
return result;
}
return 0;
}
/*
* Copyright (c) Facebook, Inc. and its affiliates.
*
* This source code is licensed under the MIT-style license found in the
* LICENSE file in the root directory of this source tree.
*/
/**
* Performs voice-activity detection with a CTC model.
* For each input sample in the dataset, outputs the following:
* - Chunk level probabilities of non-speech based on the probability of a
* blank label assigned as per the acoustic model trained with CTC. These are
* assigned for each chunk of output. For stride 1 model, these will be each
* frame (10 ms), but for a model with stride 8, these will be (80 ms)
* intervals (output in .vad file for each sample)
* - The perplexity of the predicted sequence based on a specified input
* language model (first output in .sts file for each sample)
* - The percentage of the audio containing speech based on the passed
* --vad_threshold flag (second output in .sts file for each sample)
* - The most likely token-level transcription of given audio based on the
* acoustic model output only (output in .tsc file for each sample).
* - Frame wise token emissions based on the most-likely token emitted for each
* chunk, (output in .fwt file for each sample).
*/
#include <stdlib.h>
#include <cmath>
#include <fstream>
#include <iomanip>
#include <string>