MLECO-1868: Code static analyzer warnings fixes
Signed-off-by: alexander <alexander.efremov@arm.com>
Change-Id: Ie423e9cad3fabec6ab077ded7236813fe4933dea
diff --git a/source/use_case/asr/include/AsrClassifier.hpp b/source/use_case/asr/include/AsrClassifier.hpp
index 1a63814..2c97a39 100644
--- a/source/use_case/asr/include/AsrClassifier.hpp
+++ b/source/use_case/asr/include/AsrClassifier.hpp
@@ -51,9 +51,9 @@
* @return true if successful, false otherwise.
**/
template<typename T>
- bool _GetTopResults(TfLiteTensor* tensor,
- std::vector<ClassificationResult>& vecResults,
- const std::vector <std::string>& labels, double scale, double zeroPoint);
+ bool GetTopResults(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels, double scale, double zeroPoint);
};
} /* namespace app */
diff --git a/source/use_case/asr/include/Wav2LetterMfcc.hpp b/source/use_case/asr/include/Wav2LetterMfcc.hpp
index 3cb43b9..b5a21d3 100644
--- a/source/use_case/asr/include/Wav2LetterMfcc.hpp
+++ b/source/use_case/asr/include/Wav2LetterMfcc.hpp
@@ -60,8 +60,8 @@
bool ApplyMelFilterBank(
std::vector<float>& fftVec,
std::vector<std::vector<float>>& melFilterBank,
- std::vector<int32_t>& filterBankFilterFirst,
- std::vector<int32_t>& filterBankFilterLast,
+ std::vector<uint32_t>& filterBankFilterFirst,
+ std::vector<uint32_t>& filterBankFilterLast,
std::vector<float>& melEnergies) override;
/**
diff --git a/source/use_case/asr/include/Wav2LetterModel.hpp b/source/use_case/asr/include/Wav2LetterModel.hpp
index b801e10..4c62578 100644
--- a/source/use_case/asr/include/Wav2LetterModel.hpp
+++ b/source/use_case/asr/include/Wav2LetterModel.hpp
@@ -49,10 +49,10 @@
private:
/* Maximum number of individual operations that can be enlisted. */
- static constexpr int _ms_maxOpCnt = 5;
+ static constexpr int ms_maxOpCnt = 5;
/* A mutable op resolver instance. */
- tflite::MicroMutableOpResolver<_ms_maxOpCnt> _m_opResolver;
+ tflite::MicroMutableOpResolver<ms_maxOpCnt> _m_opResolver;
};
} /* namespace app */
diff --git a/source/use_case/asr/include/Wav2LetterPostprocess.hpp b/source/use_case/asr/include/Wav2LetterPostprocess.hpp
index 69567a3..e16d35b 100644
--- a/source/use_case/asr/include/Wav2LetterPostprocess.hpp
+++ b/source/use_case/asr/include/Wav2LetterPostprocess.hpp
@@ -72,33 +72,33 @@
* initialised.
* @return true if valid, false otherwise.
*/
- bool _IsInputValid(TfLiteTensor* tensor,
- uint32_t axisIdx) const;
+ bool IsInputValid(TfLiteTensor* tensor,
+ const uint32_t axisIdx) const;
/**
* @brief Gets the tensor data element size in bytes based
* on the tensor type.
* @return Size in bytes, 0 if not supported.
*/
- uint32_t _GetTensorElementSize(TfLiteTensor* tensor);
+ static uint32_t GetTensorElementSize(TfLiteTensor* tensor);
/**
* @brief Erases sections from the data assuming row-wise
* arrangement along the context axis.
* @return true if successful, false otherwise.
*/
- bool _EraseSectionsRowWise(uint8_t* ptrData,
- uint32_t strideSzBytes,
- bool lastIteration);
+ bool EraseSectionsRowWise(uint8_t* ptrData,
+ const uint32_t strideSzBytes,
+ const bool lastIteration);
/**
* @brief Erases sections from the data assuming col-wise
* arrangement along the context axis.
* @return true if successful, false otherwise.
*/
- bool _EraseSectionsColWise(uint8_t* ptrData,
- uint32_t strideSzBytes,
- bool lastIteration);
+ static bool EraseSectionsColWise(const uint8_t* ptrData,
+ const uint32_t strideSzBytes,
+ const bool lastIteration);
};
} /* namespace asr */
diff --git a/source/use_case/asr/include/Wav2LetterPreprocess.hpp b/source/use_case/asr/include/Wav2LetterPreprocess.hpp
index 8a4e0b7..10512b9 100644
--- a/source/use_case/asr/include/Wav2LetterPreprocess.hpp
+++ b/source/use_case/asr/include/Wav2LetterPreprocess.hpp
@@ -74,16 +74,16 @@
* @param[out] delta2 Result of the second diff computation.
* @return true if successful, false otherwise.
*/
- static bool _ComputeDeltas(Array2d<float>& mfcc,
- Array2d<float>& delta1,
- Array2d<float>& delta2);
+ static bool ComputeDeltas(Array2d<float>& mfcc,
+ Array2d<float>& delta1,
+ Array2d<float>& delta2);
/**
* @brief Given a 2D vector of floats, computes the mean.
* @param[in] vec Vctor of vector of floats.
* @return Mean value.
*/
- static float _GetMean(Array2d<float>& vec);
+ static float GetMean(Array2d<float>& vec);
/**
* @brief Given a 2D vector of floats, computes the stddev.
@@ -91,20 +91,20 @@
* @param[in] mean Mean value of the vector passed in.
* @return stddev value.
*/
- static float _GetStdDev(Array2d<float>& vec,
- float mean);
+ static float GetStdDev(Array2d<float>& vec,
+ const float mean);
/**
* @brief Given a 2D vector of floats, normalises it using
* the mean and the stddev.
* @param[in,out] vec Vector of vector of floats.
*/
- static void _NormaliseVec(Array2d<float>& vec);
+ static void NormaliseVec(Array2d<float>& vec);
/**
* @brief Normalises the MFCC and delta buffers.
*/
- void _Normalise();
+ void Normalise();
/**
* @brief Given the quantisation and data type limits, computes
@@ -116,7 +116,7 @@
* @param[in] maxVal Numerical limit - maximum.
* @return Floating point quantised value.
*/
- static float _GetQuantElem(
+ static float GetQuantElem(
float elem,
float quantScale,
int quantOffset,
@@ -137,7 +137,7 @@
* @param[in] quantOffset Quantisation offset.
*/
template <typename T>
- bool _Quantise(
+ bool Quantise(
T * outputBuf,
const uint32_t outputBufSz,
const float quantScale,
@@ -161,15 +161,15 @@
/* Need to transpose while copying and concatenating the tensor. */
for (uint32_t j = 0; j < this->_m_numFeatVectors; ++j) {
for (uint32_t i = 0; i < this->_m_numMfccFeats; ++i) {
- *outputBufMfcc++ = static_cast<T>(Preprocess::_GetQuantElem(
- this->_m_mfccBuf(i, j), quantScale,
- quantOffset, minVal, maxVal));
- *outputBufD1++ = static_cast<T>(Preprocess::_GetQuantElem(
- this->_m_delta1Buf(i, j), quantScale,
- quantOffset, minVal, maxVal));
- *outputBufD2++ = static_cast<T>(Preprocess::_GetQuantElem(
- this->_m_delta2Buf(i, j), quantScale,
- quantOffset, minVal, maxVal));
+ *outputBufMfcc++ = static_cast<T>(Preprocess::GetQuantElem(
+ this->_m_mfccBuf(i, j), quantScale,
+ quantOffset, minVal, maxVal));
+ *outputBufD1++ = static_cast<T>(Preprocess::GetQuantElem(
+ this->_m_delta1Buf(i, j), quantScale,
+ quantOffset, minVal, maxVal));
+ *outputBufD2++ = static_cast<T>(Preprocess::GetQuantElem(
+ this->_m_delta2Buf(i, j), quantScale,
+ quantOffset, minVal, maxVal));
}
outputBufMfcc += ptrIncr;
outputBufD1 += ptrIncr;
diff --git a/source/use_case/asr/src/AsrClassifier.cc b/source/use_case/asr/src/AsrClassifier.cc
index 7377d30..df26a7f 100644
--- a/source/use_case/asr/src/AsrClassifier.cc
+++ b/source/use_case/asr/src/AsrClassifier.cc
@@ -21,13 +21,18 @@
#include "Wav2LetterModel.hpp"
template<typename T>
-bool arm::app::AsrClassifier::_GetTopResults(TfLiteTensor* tensor,
- std::vector<ClassificationResult>& vecResults,
- const std::vector <std::string>& labels, double scale, double zeroPoint)
+bool arm::app::AsrClassifier::GetTopResults(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels, double scale, double zeroPoint)
{
const uint32_t nElems = tensor->dims->data[arm::app::Wav2LetterModel::ms_outputRowsIdx];
const uint32_t nLetters = tensor->dims->data[arm::app::Wav2LetterModel::ms_outputColsIdx];
+ if (nLetters != labels.size()) {
+ printf("Output size doesn't match the labels' size\n");
+ return false;
+ }
+
/* NOTE: tensor's size verification against labels should be
* checked by the calling/public function. */
if (nLetters < 1) {
@@ -58,12 +63,12 @@
return true;
}
-template bool arm::app::AsrClassifier::_GetTopResults<uint8_t>(TfLiteTensor* tensor,
- std::vector<ClassificationResult>& vecResults,
- const std::vector <std::string>& labels, double scale, double zeroPoint);
-template bool arm::app::AsrClassifier::_GetTopResults<int8_t>(TfLiteTensor* tensor,
- std::vector<ClassificationResult>& vecResults,
- const std::vector <std::string>& labels, double scale, double zeroPoint);
+template bool arm::app::AsrClassifier::GetTopResults<uint8_t>(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels, double scale, double zeroPoint);
+template bool arm::app::AsrClassifier::GetTopResults<int8_t>(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels, double scale, double zeroPoint);
bool arm::app::AsrClassifier::GetClassificationResults(
TfLiteTensor* outputTensor,
@@ -104,16 +109,16 @@
switch (outputTensor->type) {
case kTfLiteUInt8:
- resultState = this->_GetTopResults<uint8_t>(
- outputTensor, vecResults,
- labels, quantParams.scale,
- quantParams.offset);
+ resultState = this->GetTopResults<uint8_t>(
+ outputTensor, vecResults,
+ labels, quantParams.scale,
+ quantParams.offset);
break;
case kTfLiteInt8:
- resultState = this->_GetTopResults<int8_t>(
- outputTensor, vecResults,
- labels, quantParams.scale,
- quantParams.offset);
+ resultState = this->GetTopResults<int8_t>(
+ outputTensor, vecResults,
+ labels, quantParams.scale,
+ quantParams.offset);
break;
default:
printf_err("Tensor type %s not supported by classifier\n",
diff --git a/source/use_case/asr/src/UseCaseHandler.cc b/source/use_case/asr/src/UseCaseHandler.cc
index 5d3157a..efaefc2 100644
--- a/source/use_case/asr/src/UseCaseHandler.cc
+++ b/source/use_case/asr/src/UseCaseHandler.cc
@@ -35,7 +35,7 @@
* @brief Helper function to increment current audio clip index.
* @param[in,out] ctx Pointer to the application context object.
**/
- static void _IncrementAppCtxClipIdx(ApplicationContext& ctx);
+ static void IncrementAppCtxClipIdx(ApplicationContext& ctx);
/**
* @brief Helper function to set the audio clip index.
@@ -43,7 +43,7 @@
* @param[in] idx Value to be set.
* @return true if index is set, false otherwise.
**/
- static bool _SetAppCtxClipIdx(ApplicationContext& ctx, uint32_t idx);
+ static bool SetAppCtxClipIdx(ApplicationContext& ctx, uint32_t idx);
/**
* @brief Presents inference results using the data presentation
@@ -54,7 +54,7 @@
* otherwise, this can be passed in as 0.
* @return true if successful, false otherwise.
**/
- static bool _PresentInferenceResult(
+ static bool PresentInferenceResult(
hal_platform& platform,
const std::vector<arm::app::asr::AsrResult>& results);
@@ -71,7 +71,7 @@
/* If the request has a valid size, set the audio index. */
if (clipIndex < NUMBER_OF_FILES) {
- if (!_SetAppCtxClipIdx(ctx, clipIndex)) {
+ if (!SetAppCtxClipIdx(ctx, clipIndex)) {
return false;
}
}
@@ -207,20 +207,20 @@
ctx.Set<std::vector<arm::app::asr::AsrResult>>("results", results);
- if (!_PresentInferenceResult(platform, results)) {
+ if (!PresentInferenceResult(platform, results)) {
return false;
}
profiler.PrintProfilingResult();
- _IncrementAppCtxClipIdx(ctx);
+ IncrementAppCtxClipIdx(ctx);
} while (runAll && ctx.Get<uint32_t>("clipIndex") != startClipIdx);
return true;
}
- static void _IncrementAppCtxClipIdx(ApplicationContext& ctx)
+ static void IncrementAppCtxClipIdx(ApplicationContext& ctx)
{
auto curAudioIdx = ctx.Get<uint32_t>("clipIndex");
@@ -232,7 +232,7 @@
ctx.Set<uint32_t>("clipIndex", curAudioIdx);
}
- static bool _SetAppCtxClipIdx(ApplicationContext& ctx, const uint32_t idx)
+ static bool SetAppCtxClipIdx(ApplicationContext& ctx, uint32_t idx)
{
if (idx >= NUMBER_OF_FILES) {
printf_err("Invalid idx %u (expected less than %u)\n",
@@ -244,8 +244,8 @@
return true;
}
- static bool _PresentInferenceResult(hal_platform& platform,
- const std::vector<arm::app::asr::AsrResult>& results)
+ static bool PresentInferenceResult(hal_platform& platform,
+ const std::vector<arm::app::asr::AsrResult>& results)
{
constexpr uint32_t dataPsnTxtStartX1 = 20;
constexpr uint32_t dataPsnTxtStartY1 = 60;
diff --git a/source/use_case/asr/src/Wav2LetterMfcc.cc b/source/use_case/asr/src/Wav2LetterMfcc.cc
index 92c91bc..0eb152a 100644
--- a/source/use_case/asr/src/Wav2LetterMfcc.cc
+++ b/source/use_case/asr/src/Wav2LetterMfcc.cc
@@ -27,8 +27,8 @@
bool Wav2LetterMFCC::ApplyMelFilterBank(
std::vector<float>& fftVec,
std::vector<std::vector<float>>& melFilterBank,
- std::vector<int32_t>& filterBankFilterFirst,
- std::vector<int32_t>& filterBankFilterLast,
+ std::vector<uint32_t>& filterBankFilterFirst,
+ std::vector<uint32_t>& filterBankFilterLast,
std::vector<float>& melEnergies)
{
const size_t numBanks = melEnergies.size();
@@ -41,11 +41,14 @@
for (size_t bin = 0; bin < numBanks; ++bin) {
auto filterBankIter = melFilterBank[bin].begin();
- float melEnergy = 1e-10; /* Avoid log of zero at later stages, same value used in librosa. */
- const int32_t firstIndex = filterBankFilterFirst[bin];
- const int32_t lastIndex = filterBankFilterLast[bin];
+ auto end = melFilterBank[bin].end();
+ /* Avoid log of zero at later stages, same value used in librosa.
+ * The number was used during our default wav2letter model training. */
+ float melEnergy = 1e-10;
+ const uint32_t firstIndex = filterBankFilterFirst[bin];
+ const uint32_t lastIndex = std::min<uint32_t>(filterBankFilterLast[bin], fftVec.size() - 1);
- for (int32_t i = firstIndex; i <= lastIndex; ++i) {
+ for (uint32_t i = firstIndex; i <= lastIndex && filterBankIter != end; ++i) {
melEnergy += (*filterBankIter++ * fftVec[i]);
}
@@ -73,7 +76,7 @@
/* Scale the log values and get the max. */
for (auto iterM = melEnergies.begin(), iterL = vecLogEnergies.begin();
- iterM != melEnergies.end(); ++iterM, ++iterL) {
+ iterM != melEnergies.end() && iterL != vecLogEnergies.end(); ++iterM, ++iterL) {
*iterM = *iterL * multiplier;
@@ -86,8 +89,8 @@
/* Clamp the mel energies. */
constexpr float maxDb = 80.0;
const float clampLevelLowdB = maxMelEnergy - maxDb;
- for (auto iter = melEnergies.begin(); iter != melEnergies.end(); ++iter) {
- *iter = std::max(*iter, clampLevelLowdB);
+ for (float& melEnergy : melEnergies) {
+ melEnergy = std::max(melEnergy, clampLevelLowdB);
}
}
diff --git a/source/use_case/asr/src/Wav2LetterPostprocess.cc b/source/use_case/asr/src/Wav2LetterPostprocess.cc
index 60ee51e..9157a6f 100644
--- a/source/use_case/asr/src/Wav2LetterPostprocess.cc
+++ b/source/use_case/asr/src/Wav2LetterPostprocess.cc
@@ -39,13 +39,13 @@
const bool lastIteration)
{
/* Basic checks. */
- if (!this->_IsInputValid(tensor, axisIdx)) {
+ if (!this->IsInputValid(tensor, axisIdx)) {
return false;
}
/* Irrespective of tensor type, we use unsigned "byte" */
uint8_t* ptrData = tflite::GetTensorData<uint8_t>(tensor);
- const uint32_t elemSz = this->_GetTensorElementSize(tensor);
+ const uint32_t elemSz = this->GetTensorElementSize(tensor);
/* Other sanity checks. */
if (0 == elemSz) {
@@ -59,13 +59,15 @@
/* Which axis do we need to process? */
switch (axisIdx) {
case arm::app::Wav2LetterModel::ms_outputRowsIdx:
- return this->_EraseSectionsRowWise(ptrData,
- elemSz * tensor->dims->data[arm::app::Wav2LetterModel::ms_outputColsIdx],
- lastIteration);
+ return this->EraseSectionsRowWise(ptrData,
+ elemSz *
+ tensor->dims->data[arm::app::Wav2LetterModel::ms_outputColsIdx],
+ lastIteration);
case arm::app::Wav2LetterModel::ms_outputColsIdx:
- return this->_EraseSectionsColWise(ptrData,
- elemSz * tensor->dims->data[arm::app::Wav2LetterModel::ms_outputRowsIdx],
- lastIteration);
+ return this->EraseSectionsColWise(ptrData,
+ elemSz *
+ tensor->dims->data[arm::app::Wav2LetterModel::ms_outputRowsIdx],
+ lastIteration);
default:
printf_err("Unsupported axis index: %u\n", axisIdx);
}
@@ -73,8 +75,8 @@
return false;
}
- bool Postprocess::_IsInputValid(TfLiteTensor* tensor,
- const uint32_t axisIdx) const
+ bool Postprocess::IsInputValid(TfLiteTensor* tensor,
+ const uint32_t axisIdx) const
{
if (nullptr == tensor) {
return false;
@@ -96,17 +98,15 @@
return true;
}
- uint32_t Postprocess::_GetTensorElementSize(TfLiteTensor* tensor)
+ uint32_t Postprocess::GetTensorElementSize(TfLiteTensor* tensor)
{
switch(tensor->type) {
case kTfLiteUInt8:
- return 1;
case kTfLiteInt8:
return 1;
case kTfLiteInt16:
return 2;
case kTfLiteInt32:
- return 4;
case kTfLiteFloat32:
return 4;
default:
@@ -117,7 +117,7 @@
return 0;
}
- bool Postprocess::_EraseSectionsRowWise(
+ bool Postprocess::EraseSectionsRowWise(
uint8_t* ptrData,
const uint32_t strideSzBytes,
const bool lastIteration)
@@ -154,8 +154,8 @@
return true;
}
- bool Postprocess::_EraseSectionsColWise(
- uint8_t* ptrData,
+ bool Postprocess::EraseSectionsColWise(
+ const uint8_t* ptrData,
const uint32_t strideSzBytes,
const bool lastIteration)
{
diff --git a/source/use_case/asr/src/Wav2LetterPreprocess.cc b/source/use_case/asr/src/Wav2LetterPreprocess.cc
index e46cca3..d65ea75 100644
--- a/source/use_case/asr/src/Wav2LetterPreprocess.cc
+++ b/source/use_case/asr/src/Wav2LetterPreprocess.cc
@@ -88,12 +88,12 @@
}
/* Compute first and second order deltas from MFCCs. */
- this->_ComputeDeltas(this->_m_mfccBuf,
- this->_m_delta1Buf,
- this->_m_delta2Buf);
+ Preprocess::ComputeDeltas(this->_m_mfccBuf,
+ this->_m_delta1Buf,
+ this->_m_delta2Buf);
/* Normalise. */
- this->_Normalise();
+ this->Normalise();
/* Quantise. */
QuantParams quantParams = GetTensorQuantParams(tensor);
@@ -105,11 +105,11 @@
switch(tensor->type) {
case kTfLiteUInt8:
- return this->_Quantise<uint8_t>(
+ return this->Quantise<uint8_t>(
tflite::GetTensorData<uint8_t>(tensor), tensor->bytes,
quantParams.scale, quantParams.offset);
case kTfLiteInt8:
- return this->_Quantise<int8_t>(
+ return this->Quantise<int8_t>(
tflite::GetTensorData<int8_t>(tensor), tensor->bytes,
quantParams.scale, quantParams.offset);
default:
@@ -120,9 +120,9 @@
return false;
}
- bool Preprocess::_ComputeDeltas(Array2d<float>& mfcc,
- Array2d<float>& delta1,
- Array2d<float>& delta2)
+ bool Preprocess::ComputeDeltas(Array2d<float>& mfcc,
+ Array2d<float>& delta1,
+ Array2d<float>& delta2)
{
const std::vector <float> delta1Coeffs =
{6.66666667e-02, 5.00000000e-02, 3.33333333e-02,
@@ -175,20 +175,20 @@
return true;
}
- float Preprocess::_GetMean(Array2d<float>& vec)
+ float Preprocess::GetMean(Array2d<float>& vec)
{
return math::MathUtils::MeanF32(vec.begin(), vec.totalSize());
}
- float Preprocess::_GetStdDev(Array2d<float>& vec, const float mean)
+ float Preprocess::GetStdDev(Array2d<float>& vec, const float mean)
{
return math::MathUtils::StdDevF32(vec.begin(), vec.totalSize(), mean);
}
- void Preprocess::_NormaliseVec(Array2d<float>& vec)
+ void Preprocess::NormaliseVec(Array2d<float>& vec)
{
- auto mean = Preprocess::_GetMean(vec);
- auto stddev = Preprocess::_GetStdDev(vec, mean);
+ auto mean = Preprocess::GetMean(vec);
+ auto stddev = Preprocess::GetStdDev(vec, mean);
debug("Mean: %f, Stddev: %f\n", mean, stddev);
if (stddev == 0) {
@@ -204,14 +204,14 @@
}
}
- void Preprocess::_Normalise()
+ void Preprocess::Normalise()
{
- Preprocess::_NormaliseVec(this->_m_mfccBuf);
- Preprocess::_NormaliseVec(this->_m_delta1Buf);
- Preprocess::_NormaliseVec(this->_m_delta2Buf);
+ Preprocess::NormaliseVec(this->_m_mfccBuf);
+ Preprocess::NormaliseVec(this->_m_delta1Buf);
+ Preprocess::NormaliseVec(this->_m_delta2Buf);
}
- float Preprocess::_GetQuantElem(
+ float Preprocess::GetQuantElem(
const float elem,
const float quantScale,
const int quantOffset,