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author | alexander <alexander.efremov@arm.com> | 2021-03-26 21:42:19 +0000 |
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committer | Kshitij Sisodia <kshitij.sisodia@arm.com> | 2021-03-29 16:29:55 +0100 |
commit | 3c79893217bc632c9b0efa815091bef3c779490c (patch) | |
tree | ad06b444557eb8124652b45621d736fa1b92f65d /source/use_case/kws_asr/src/Wav2LetterPostprocess.cc | |
parent | 6ad6d55715928de72979b04194da1bdf04a4c51b (diff) | |
download | ml-embedded-evaluation-kit-3c79893217bc632c9b0efa815091bef3c779490c.tar.gz |
Opensource ML embedded evaluation kit21.03
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
Diffstat (limited to 'source/use_case/kws_asr/src/Wav2LetterPostprocess.cc')
-rw-r--r-- | source/use_case/kws_asr/src/Wav2LetterPostprocess.cc | 155 |
1 files changed, 155 insertions, 0 deletions
diff --git a/source/use_case/kws_asr/src/Wav2LetterPostprocess.cc b/source/use_case/kws_asr/src/Wav2LetterPostprocess.cc new file mode 100644 index 0000000..b173968 --- /dev/null +++ b/source/use_case/kws_asr/src/Wav2LetterPostprocess.cc @@ -0,0 +1,155 @@ +/* + * 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); + 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; + } + +} /* namespace asr */ +} /* namespace audio */ +} /* namespace app */ +} /* namespace arm */
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