Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/source/use_case/asr/src/AsrClassifier.cc b/source/use_case/asr/src/AsrClassifier.cc
new file mode 100644
index 0000000..7377d30
--- /dev/null
+++ b/source/use_case/asr/src/AsrClassifier.cc
@@ -0,0 +1,130 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "AsrClassifier.hpp"
+
+#include "hal.h"
+#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];
+
+ /* 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);
+
+ 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);
+
+ 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;
+ }
+
+ 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(
+ TfLiteTensor* outputTensor,
+ std::vector<ClassificationResult>& vecResults,
+ const std::vector <std::string>& labels, uint32_t topNCount)
+{
+ 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 uint32_t outColsIdx = arm::app::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 %u\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");
+ }
+
+ /* 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;
+ }
+
+ return true;
+}
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