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-rw-r--r--source/use_case/asr/src/AsrClassifier.cc196
1 files changed, 102 insertions, 94 deletions
diff --git a/source/use_case/asr/src/AsrClassifier.cc b/source/use_case/asr/src/AsrClassifier.cc
index 84e66b7..4ba8c7b 100644
--- a/source/use_case/asr/src/AsrClassifier.cc
+++ b/source/use_case/asr/src/AsrClassifier.cc
@@ -20,117 +20,125 @@
#include "TensorFlowLiteMicro.hpp"
#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)
-{
- 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;
- }
+namespace arm {
+namespace app {
+
+ template<typename T>
+ bool 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[Wav2LetterModel::ms_outputRowsIdx];
+ const uint32_t nLetters = tensor->dims->data[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) {
- return false;
- }
+ /* NOTE: tensor's size verification against labels should be
+ * checked by the calling/public function. */
+ if (nLetters < 1) {
+ return false;
+ }
- /* Final results' container. */
- vecResults = std::vector<ClassificationResult>(nElems);
+ /* Final results' container. */
+ vecResults = std::vector<ClassificationResult>(nElems);
- T* tensorData = tflite::GetTensorData<T>(tensor);
+ T* tensorData = tflite::GetTensorData<T>(tensor);
- /* Get the top 1 results. */
- for (uint32_t i = 0, row = 0; i < nElems; ++i, row+=nLetters) {
- std::pair<T, uint32_t> top_1 = std::make_pair(tensorData[row + 0], 0);
+ /* Get the top 1 results. */
+ for (uint32_t i = 0, row = 0; i < nElems; ++i, row+=nLetters) {
+ std::pair<T, uint32_t> top_1 = std::make_pair(tensorData[row + 0], 0);
- for (uint32_t j = 1; j < nLetters; ++j) {
- if (top_1.first < tensorData[row + j]) {
- top_1.first = tensorData[row + j];
- top_1.second = j;
+ for (uint32_t j = 1; j < nLetters; ++j) {
+ if (top_1.first < tensorData[row + j]) {
+ top_1.first = tensorData[row + j];
+ top_1.second = j;
+ }
}
+
+ double score = static_cast<int> (top_1.first);
+ vecResults[i].m_normalisedVal = scale * (score - zeroPoint);
+ vecResults[i].m_label = labels[top_1.second];
+ vecResults[i].m_labelIdx = top_1.second;
}
- double score = static_cast<int> (top_1.first);
- vecResults[i].m_normalisedVal = scale * (score - zeroPoint);
- vecResults[i].m_label = labels[top_1.second];
- vecResults[i].m_labelIdx = top_1.second;
+ return true;
}
-
- 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);
-
-bool arm::app::AsrClassifier::GetClassificationResults(
+ template bool AsrClassifier::GetTopResults<uint8_t>(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels,
+ double scale, double zeroPoint);
+ template bool AsrClassifier::GetTopResults<int8_t>(TfLiteTensor* tensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels,
+ double scale, double zeroPoint);
+
+ bool AsrClassifier::GetClassificationResults(
TfLiteTensor* outputTensor,
std::vector<ClassificationResult>& vecResults,
const std::vector <std::string>& labels, uint32_t topNCount, bool use_softmax)
-{
- UNUSED(use_softmax);
- vecResults.clear();
+ {
+ UNUSED(use_softmax);
+ vecResults.clear();
- constexpr int minTensorDims = static_cast<int>(
- (arm::app::Wav2LetterModel::ms_outputRowsIdx > arm::app::Wav2LetterModel::ms_outputColsIdx)?
- arm::app::Wav2LetterModel::ms_outputRowsIdx : arm::app::Wav2LetterModel::ms_outputColsIdx);
+ constexpr int minTensorDims = static_cast<int>(
+ (Wav2LetterModel::ms_outputRowsIdx > Wav2LetterModel::ms_outputColsIdx)?
+ Wav2LetterModel::ms_outputRowsIdx : Wav2LetterModel::ms_outputColsIdx);
- constexpr uint32_t outColsIdx = arm::app::Wav2LetterModel::ms_outputColsIdx;
+ constexpr uint32_t outColsIdx = Wav2LetterModel::ms_outputColsIdx;
- /* Sanity checks. */
- if (outputTensor == nullptr) {
- printf_err("Output vector is null pointer.\n");
- return false;
- } else if (outputTensor->dims->size < minTensorDims) {
- printf_err("Output tensor expected to be %dD\n", minTensorDims);
- return false;
- } else if (static_cast<uint32_t>(outputTensor->dims->data[outColsIdx]) < topNCount) {
- printf_err("Output vectors are smaller than %" PRIu32 "\n", topNCount);
- return false;
- } else if (static_cast<uint32_t>(outputTensor->dims->data[outColsIdx]) != labels.size()) {
- printf("Output size doesn't match the labels' size\n");
- return false;
- }
+ /* Sanity checks. */
+ if (outputTensor == nullptr) {
+ printf_err("Output vector is null pointer.\n");
+ return false;
+ } else if (outputTensor->dims->size < minTensorDims) {
+ printf_err("Output tensor expected to be %dD\n", minTensorDims);
+ return false;
+ } else if (static_cast<uint32_t>(outputTensor->dims->data[outColsIdx]) < topNCount) {
+ printf_err("Output vectors are smaller than %" PRIu32 "\n", topNCount);
+ return false;
+ } else if (static_cast<uint32_t>(outputTensor->dims->data[outColsIdx]) != labels.size()) {
+ printf("Output size doesn't match the labels' size\n");
+ return false;
+ }
- if (topNCount != 1) {
- warn("TopNCount value ignored in this implementation\n");
- }
+ if (topNCount != 1) {
+ warn("TopNCount value ignored in this implementation\n");
+ }
- /* To return the floating point values, we need quantization parameters. */
- QuantParams quantParams = GetTensorQuantParams(outputTensor);
-
- bool resultState;
-
- switch (outputTensor->type) {
- case kTfLiteUInt8:
- 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);
- break;
- default:
- printf_err("Tensor type %s not supported by classifier\n",
- TfLiteTypeGetName(outputTensor->type));
+ /* To return the floating point values, we need quantization parameters. */
+ QuantParams quantParams = GetTensorQuantParams(outputTensor);
+
+ bool resultState;
+
+ switch (outputTensor->type) {
+ case kTfLiteUInt8:
+ 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);
+ break;
+ default:
+ printf_err("Tensor type %s not supported by classifier\n",
+ TfLiteTypeGetName(outputTensor->type));
+ return false;
+ }
+
+ if (!resultState) {
+ printf_err("Failed to get sorted set\n");
return false;
- }
+ }
- if (!resultState) {
- printf_err("Failed to get sorted set\n");
- return false;
- }
+ return true;
+ }
- return true;
-} \ No newline at end of file
+} /* namespace app */
+} /* namespace arm */ \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-30 16:30:49 +0000