MLECO-3183: Refactoring application sources
Platform agnostic application sources are moved into application
api module with their own independent CMake projects.
Changes for MLECO-3080 also included - they create CMake projects
individial API's (again, platform agnostic) that dependent on the
common logic. The API for KWS_API "joint" API has been removed and
now the use case relies on individual KWS, and ASR API libraries.
Change-Id: I1f7748dc767abb3904634a04e0991b74ac7b756d
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>
diff --git a/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp b/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp
new file mode 100644
index 0000000..02738bc
--- /dev/null
+++ b/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp
@@ -0,0 +1,109 @@
+/*
+ * Copyright (c) 2021-2022 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.
+ */
+#ifndef ASR_WAV2LETTER_POSTPROCESS_HPP
+#define ASR_WAV2LETTER_POSTPROCESS_HPP
+
+#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 {
+ public:
+ 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);
+
+ private:
+ 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 */
+
+#endif /* ASR_WAV2LETTER_POSTPROCESS_HPP */
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