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* SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <>
* 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
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* See the License for the specific language governing permissions and
* limitations under the License.
#include "TensorFlowLiteMicro.hpp" /* TensorFlow headers. */
#include "BaseProcessing.hpp"
#include "Model.hpp"
#include "AsrClassifier.hpp"
#include "AsrResult.hpp"
#include "log_macros.h"
namespace arm {
namespace app {
* @brief Helper class to manage tensor post-processing for "wav2letter"
* output.
class AsrPostProcess : public BasePostProcess {
bool m_lastIteration = false; /* Flag to set if processing the last set of data for a clip. */
* @brief Constructor
* @param[in] outputTensor Pointer to the TFLite Micro output Tensor.
* @param[in] classifier Object used to get top N results from classification.
* @param[in] labels Vector of string labels to identify each output of the model.
* @param[in/out] result Vector of classification results to store decoded outputs.
* @param[in] outputContextLen Left/right context length for output tensor.
* @param[in] blankTokenIdx Index in the labels that the "Blank token" takes.
* @param[in] reductionAxis The axis that the logits of each time step is on.
AsrPostProcess(TfLiteTensor* outputTensor, AsrClassifier& classifier,
const std::vector<std::string>& labels, asr::ResultVec& result,
uint32_t outputContextLen,
uint32_t blankTokenIdx, uint32_t reductionAxis);
* @brief Should perform post-processing of the result of inference then
* populate ASR result data for any later use.
* @return true if successful, false otherwise.
bool DoPostProcess() override;
/** @brief Gets the output inner length for post-processing. */
static uint32_t GetOutputInnerLen(const TfLiteTensor*, uint32_t outputCtxLen);
/** @brief Gets the output context length (left/right) for post-processing. */
static uint32_t GetOutputContextLen(const Model& model, uint32_t inputCtxLen);
/** @brief Gets the number of feature vectors to be computed. */
static uint32_t GetNumFeatureVectors(const Model& model);
AsrClassifier& m_classifier; /* ASR Classifier object. */
TfLiteTensor* m_outputTensor; /* Model output tensor. */
const std::vector<std::string>& m_labels; /* ASR Labels. */
asr::ResultVec & m_results; /* Results vector for a single inference. */
uint32_t m_outputContextLen; /* lengths of left/right contexts for output. */
uint32_t m_outputInnerLen; /* Length of output inner context. */
uint32_t m_totalLen; /* Total length of the required axis. */
uint32_t m_countIterations; /* Current number of iterations. */
uint32_t m_blankTokenIdx; /* Index of the labels blank token. */
uint32_t m_reductionAxisIdx; /* Axis containing output logits for a single step. */
* @brief Checks if the tensor and axis index are valid
* inputs to the object - based on how it has been initialised.
* @return true if valid, false otherwise.
bool IsInputValid(TfLiteTensor* tensor,
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.
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);
} /* namespace app */
} /* namespace arm */