Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/source/use_case/asr/src/Wav2LetterPostprocess.cc b/source/use_case/asr/src/Wav2LetterPostprocess.cc
new file mode 100644
index 0000000..60ee51e
--- /dev/null
+++ b/source/use_case/asr/src/Wav2LetterPostprocess.cc
@@ -0,0 +1,172 @@
+/*
+ * 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 "Wav2LetterPostprocess.hpp"
+
+#include "Wav2LetterModel.hpp"
+
+
+namespace arm {
+namespace app {
+namespace audio {
+namespace asr {
+
+ Postprocess::Postprocess(const uint32_t contextLen,
+ const uint32_t innerLen,
+ const uint32_t blankTokenIdx)
+ : _m_contextLen(contextLen),
+ _m_innerLen(innerLen),
+ _m_totalLen(2 * this->_m_contextLen + this->_m_innerLen),
+ _m_countIterations(0),
+ _m_blankTokenIdx(blankTokenIdx)
+ {}
+
+ bool Postprocess::Invoke(TfLiteTensor* tensor,
+ const uint32_t axisIdx,
+ const bool lastIteration)
+ {
+ /* Basic checks. */
+ 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);
+
+ /* Other sanity checks. */
+ if (0 == elemSz) {
+ printf_err("Tensor type not supported for post processing\n");
+ return false;
+ } else if (elemSz * this->_m_totalLen > tensor->bytes) {
+ printf_err("Insufficient number of tensor bytes\n");
+ return false;
+ }
+
+ /* 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);
+ case arm::app::Wav2LetterModel::ms_outputColsIdx:
+ return this->_EraseSectionsColWise(ptrData,
+ elemSz * tensor->dims->data[arm::app::Wav2LetterModel::ms_outputRowsIdx],
+ lastIteration);
+ default:
+ printf_err("Unsupported axis index: %u\n", axisIdx);
+ }
+
+ return false;
+ }
+
+ bool Postprocess::_IsInputValid(TfLiteTensor* tensor,
+ const uint32_t axisIdx) const
+ {
+ if (nullptr == tensor) {
+ return false;
+ }
+
+ if (static_cast<int>(axisIdx) >= tensor->dims->size) {
+ printf_err("Invalid axis index: %u; Max: %d\n",
+ axisIdx, tensor->dims->size);
+ return false;
+ }
+
+ if (static_cast<int>(this->_m_totalLen) !=
+ tensor->dims->data[axisIdx]) {
+ printf_err("Unexpected tensor dimension for axis %d, \n",
+ tensor->dims->data[axisIdx]);
+ return false;
+ }
+
+ return true;
+ }
+
+ 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:
+ printf_err("Unsupported tensor type %s\n",
+ TfLiteTypeGetName(tensor->type));
+ }
+
+ return 0;
+ }
+
+ bool Postprocess::_EraseSectionsRowWise(
+ uint8_t* ptrData,
+ const uint32_t strideSzBytes,
+ const bool lastIteration)
+ {
+ /* In this case, the "zero-ing" is quite simple as the region
+ * to be zeroed sits in contiguous memory (row-major). */
+ const uint32_t eraseLen = strideSzBytes * this->_m_contextLen;
+
+ /* Erase left context? */
+ if (this->_m_countIterations > 0) {
+ /* Set output of each classification window to the blank token. */
+ std::memset(ptrData, 0, eraseLen);
+ for (size_t windowIdx = 0; windowIdx < this->_m_contextLen; windowIdx++) {
+ ptrData[windowIdx*strideSzBytes + this->_m_blankTokenIdx] = 1;
+ }
+ }
+
+ /* Erase right context? */
+ if (false == lastIteration) {
+ uint8_t * rightCtxPtr = ptrData + (strideSzBytes * (this->_m_contextLen + this->_m_innerLen));
+ /* Set output of each classification window to the blank token. */
+ std::memset(rightCtxPtr, 0, eraseLen);
+ for (size_t windowIdx = 0; windowIdx < this->_m_contextLen; windowIdx++) {
+ rightCtxPtr[windowIdx*strideSzBytes + this->_m_blankTokenIdx] = 1;
+ }
+ }
+
+ if (lastIteration) {
+ this->_m_countIterations = 0;
+ } else {
+ ++this->_m_countIterations;
+ }
+
+ return true;
+ }
+
+ bool Postprocess::_EraseSectionsColWise(
+ uint8_t* ptrData,
+ const uint32_t strideSzBytes,
+ const bool lastIteration)
+ {
+ /* Not implemented. */
+ UNUSED(ptrData);
+ UNUSED(strideSzBytes);
+ UNUSED(lastIteration);
+ return false;
+ }
+
+} /* namespace asr */
+} /* namespace audio */
+} /* namespace app */
+} /* namespace arm */
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