From 56ee6207c1524ddc4c444c6e48e05eb34105985a Mon Sep 17 00:00:00 2001 From: Isabella Gottardi Date: Wed, 12 May 2021 08:27:15 +0100 Subject: MLECO-1858: Documentation update * Removing `_` in front of private functions and member Signed-off-by: Isabella Gottardi Change-Id: I5a5d652f9647ebb16d2d2bd16ab980e73f7be3cf --- source/application/tensorflow-lite-micro/Model.cc | 102 +++++++++++----------- 1 file changed, 51 insertions(+), 51 deletions(-) (limited to 'source/application/tensorflow-lite-micro/Model.cc') diff --git a/source/application/tensorflow-lite-micro/Model.cc b/source/application/tensorflow-lite-micro/Model.cc index 4a7f0a4..e9c6cd3 100644 --- a/source/application/tensorflow-lite-micro/Model.cc +++ b/source/application/tensorflow-lite-micro/Model.cc @@ -24,8 +24,8 @@ /* Initialise the model */ arm::app::Model::~Model() { - if (this->_m_pInterpreter) { - delete this->_m_pInterpreter; + if (this->m_pInterpreter) { + delete this->m_pInterpreter; } /** @@ -34,10 +34,10 @@ arm::app::Model::~Model() } arm::app::Model::Model() : - _m_inited (false), - _m_type(kTfLiteNoType) + m_inited (false), + m_type(kTfLiteNoType) { - this->_m_pErrorReporter = &this->_m_uErrorReporter; + this->m_pErrorReporter = &this->m_uErrorReporter; } bool arm::app::Model::Init(tflite::MicroAllocator* allocator) @@ -47,13 +47,13 @@ bool arm::app::Model::Init(tflite::MicroAllocator* allocator) * copying or parsing, it's a very lightweight operation. */ const uint8_t* model_addr = ModelPointer(); debug("loading model from @ 0x%p\n", model_addr); - this->_m_pModel = ::tflite::GetModel(model_addr); + this->m_pModel = ::tflite::GetModel(model_addr); - if (this->_m_pModel->version() != TFLITE_SCHEMA_VERSION) { - this->_m_pErrorReporter->Report( + if (this->m_pModel->version() != TFLITE_SCHEMA_VERSION) { + this->m_pErrorReporter->Report( "[ERROR] model's schema version %d is not equal " "to supported version %d.", - this->_m_pModel->version(), TFLITE_SCHEMA_VERSION); + this->m_pModel->version(), TFLITE_SCHEMA_VERSION); return false; } @@ -69,80 +69,80 @@ bool arm::app::Model::Init(tflite::MicroAllocator* allocator) this->EnlistOperations(); /* Create allocator instance, if it doesn't exist */ - this->_m_pAllocator = allocator; - if (!this->_m_pAllocator) { + this->m_pAllocator = allocator; + if (!this->m_pAllocator) { /* Create an allocator instance */ info("Creating allocator using tensor arena in %s\n", ACTIVATION_BUF_SECTION_NAME); - this->_m_pAllocator = tflite::MicroAllocator::Create( + this->m_pAllocator = tflite::MicroAllocator::Create( this->GetTensorArena(), this->GetActivationBufferSize(), - this->_m_pErrorReporter); + this->m_pErrorReporter); - if (!this->_m_pAllocator) { + if (!this->m_pAllocator) { printf_err("Failed to create allocator\n"); return false; } - debug("Created new allocator @ 0x%p\n", this->_m_pAllocator); + debug("Created new allocator @ 0x%p\n", this->m_pAllocator); } else { - debug("Using existing allocator @ 0x%p\n", this->_m_pAllocator); + debug("Using existing allocator @ 0x%p\n", this->m_pAllocator); } - this->_m_pInterpreter = new ::tflite::MicroInterpreter( - this->_m_pModel, this->GetOpResolver(), - this->_m_pAllocator, this->_m_pErrorReporter); + this->m_pInterpreter = new ::tflite::MicroInterpreter( + this->m_pModel, this->GetOpResolver(), + this->m_pAllocator, this->m_pErrorReporter); - if (!this->_m_pInterpreter) { + if (!this->m_pInterpreter) { printf_err("Failed to allocate interpreter\n"); return false; } /* Allocate memory from the tensor_arena for the model's tensors. */ info("Allocating tensors\n"); - TfLiteStatus allocate_status = this->_m_pInterpreter->AllocateTensors(); + TfLiteStatus allocate_status = this->m_pInterpreter->AllocateTensors(); if (allocate_status != kTfLiteOk) { - this->_m_pErrorReporter->Report("[ERROR] allocateTensors() failed"); + this->m_pErrorReporter->Report("[ERROR] allocateTensors() failed"); printf_err("tensor allocation failed!\n"); - delete this->_m_pInterpreter; + delete this->m_pInterpreter; return false; } /* Get information about the memory area to use for the model's input. */ - this->_m_input.resize(this->GetNumInputs()); + this->m_input.resize(this->GetNumInputs()); for (size_t inIndex = 0; inIndex < this->GetNumInputs(); inIndex++) - this->_m_input[inIndex] = this->_m_pInterpreter->input(inIndex); + this->m_input[inIndex] = this->m_pInterpreter->input(inIndex); - this->_m_output.resize(this->GetNumOutputs()); + this->m_output.resize(this->GetNumOutputs()); for (size_t outIndex = 0; outIndex < this->GetNumOutputs(); outIndex++) - this->_m_output[outIndex] = this->_m_pInterpreter->output(outIndex); + this->m_output[outIndex] = this->m_pInterpreter->output(outIndex); - if (this->_m_input.empty() || this->_m_output.empty()) { + if (this->m_input.empty() || this->m_output.empty()) { printf_err("failed to get tensors\n"); return false; } else { - this->_m_type = this->_m_input[0]->type; /* Input 0 should be the main input */ + this->m_type = this->m_input[0]->type; /* Input 0 should be the main input */ /* Clear the input & output tensors */ for (size_t inIndex = 0; inIndex < this->GetNumInputs(); inIndex++) { - std::memset(this->_m_input[inIndex]->data.data, 0, this->_m_input[inIndex]->bytes); + std::memset(this->m_input[inIndex]->data.data, 0, this->m_input[inIndex]->bytes); } for (size_t outIndex = 0; outIndex < this->GetNumOutputs(); outIndex++) { - std::memset(this->_m_output[outIndex]->data.data, 0, this->_m_output[outIndex]->bytes); + std::memset(this->m_output[outIndex]->data.data, 0, this->m_output[outIndex]->bytes); } this->LogInterpreterInfo(); } - this->_m_inited = true; + this->m_inited = true; return true; } tflite::MicroAllocator* arm::app::Model::GetAllocator() { if (this->IsInited()) { - return this->_m_pAllocator; + return this->m_pAllocator; } return nullptr; } @@ -178,31 +178,31 @@ void arm::app::Model::LogTensorInfo(TfLiteTensor* tensor) void arm::app::Model::LogInterpreterInfo() { - if (!this->_m_pInterpreter) { + if (!this->m_pInterpreter) { printf_err("Invalid interpreter\n"); return; } info("Model INPUT tensors: \n"); - for (auto input : this->_m_input) { + for (auto input : this->m_input) { this->LogTensorInfo(input); } info("Model OUTPUT tensors: \n"); - for (auto output : this->_m_output) { + for (auto output : this->m_output) { this->LogTensorInfo(output); } info("Activation buffer (a.k.a tensor arena) size used: %zu\n", - this->_m_pInterpreter->arena_used_bytes()); + this->m_pInterpreter->arena_used_bytes()); - const size_t nOperators = this->_m_pInterpreter->operators_size(); + const size_t nOperators = this->m_pInterpreter->operators_size(); info("Number of operators: %zu\n", nOperators); /* For each operator, display registration information */ for (size_t i = 0 ; i < nOperators; ++i) { const tflite::NodeAndRegistration nodeReg = - this->_m_pInterpreter->node_and_registration(i); + this->m_pInterpreter->node_and_registration(i); const TfLiteRegistration* reg = nodeReg.registration; std::string opName{""}; @@ -220,7 +220,7 @@ void arm::app::Model::LogInterpreterInfo() bool arm::app::Model::IsInited() const { - return this->_m_inited; + return this->m_inited; } bool arm::app::Model::IsDataSigned() const @@ -231,8 +231,8 @@ bool arm::app::Model::IsDataSigned() const bool arm::app::Model::RunInference() { bool inference_state = false; - if (this->_m_pModel && this->_m_pInterpreter) { - if (kTfLiteOk != this->_m_pInterpreter->Invoke()) { + if (this->m_pModel && this->m_pInterpreter) { + if (kTfLiteOk != this->m_pInterpreter->Invoke()) { printf_err("Invoke failed.\n"); } else { inference_state = true; @@ -246,7 +246,7 @@ bool arm::app::Model::RunInference() TfLiteTensor* arm::app::Model::GetInputTensor(size_t index) const { if (index < this->GetNumInputs()) { - return this->_m_input.at(index); + return this->m_input.at(index); } return nullptr; } @@ -254,23 +254,23 @@ TfLiteTensor* arm::app::Model::GetInputTensor(size_t index) const TfLiteTensor* arm::app::Model::GetOutputTensor(size_t index) const { if (index < this->GetNumOutputs()) { - return this->_m_output.at(index); + return this->m_output.at(index); } return nullptr; } size_t arm::app::Model::GetNumInputs() const { - if (this->_m_pModel && this->_m_pInterpreter) { - return this->_m_pInterpreter->inputs_size(); + if (this->m_pModel && this->m_pInterpreter) { + return this->m_pInterpreter->inputs_size(); } return 0; } size_t arm::app::Model::GetNumOutputs() const { - if (this->_m_pModel && this->_m_pInterpreter) { - return this->_m_pInterpreter->outputs_size(); + if (this->m_pModel && this->m_pInterpreter) { + return this->m_pInterpreter->outputs_size(); } return 0; } @@ -278,13 +278,13 @@ size_t arm::app::Model::GetNumOutputs() const TfLiteType arm::app::Model::GetType() const { - return this->_m_type; + return this->m_type; } TfLiteIntArray* arm::app::Model::GetInputShape(size_t index) const { if (index < this->GetNumInputs()) { - return this->_m_input.at(index)->dims; + return this->m_input.at(index)->dims; } return nullptr; } @@ -292,7 +292,7 @@ TfLiteIntArray* arm::app::Model::GetInputShape(size_t index) const TfLiteIntArray* arm::app::Model::GetOutputShape(size_t index) const { if (index < this->GetNumOutputs()) { - return this->_m_output.at(index)->dims; + return this->m_output.at(index)->dims; } return nullptr; } -- cgit v1.2.1