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Diffstat (limited to 'delegate/src/ElementwiseBinary.hpp')
| -rw-r--r-- | delegate/src/ElementwiseBinary.hpp | 401 |
1 files changed, 0 insertions, 401 deletions
diff --git a/delegate/src/ElementwiseBinary.hpp b/delegate/src/ElementwiseBinary.hpp deleted file mode 100644 index fa9021b5c1..0000000000 --- a/delegate/src/ElementwiseBinary.hpp +++ /dev/null @@ -1,401 +0,0 @@ -// -// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#pragma once - -#include "DelegateUtils.hpp" -#include "MultiLayerFacade.hpp" -#include "SharedFunctions.hpp" - -#include <tensorflow/lite/builtin_ops.h> -#include <tensorflow/lite/c/builtin_op_data.h> -#include <tensorflow/lite/c/common.h> -#include <tensorflow/lite/minimal_logging.h> -#include "tensorflow/lite/delegates/utils.h" - -namespace armnnDelegate -{ - -TfLiteStatus ValidateAddOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - std::vector<armnn::TensorInfo> infos { inputInfo1, inputInfo2, outputInfo }; - FORWARD_LAYER_SUPPORT_FUNC("ADD", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputInfo, - armnn::BinaryOperation::Add); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - - -TfLiteStatus ValidateDivOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - FORWARD_LAYER_SUPPORT_FUNC("DIV", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputTensorInfo, - armnn::BinaryOperation::Div); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - -TfLiteStatus ValidateFloorDivOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - // need first to validate that the div operator is supported - // then that the floor operator is supported - TfLiteStatus status = ValidateDivOperator(delegateData, tfLiteContext, inputInfo1, inputInfo2, outputInfo); - if (status != kTfLiteOk) - { - return status; - } - // if the inputs and output of the div are all Signed32 we don't need to add the floor operator afterward. - if (AreAllSigned32(inputInfo1, inputInfo2, outputInfo)) - { - return status; - } - // in case broadcasting is being done from one of the inputs to the div - // choose the full sized input tensor to pass to the floor validation routine - armnn::TensorInfo floorInputInfo = inputInfo1; - if (inputInfo1.GetNumDimensions() < inputInfo2.GetNumDimensions()) - { - floorInputInfo = inputInfo2; - } - status = ValidateFloorOperator(delegateData, tfLiteContext, floorInputInfo, outputInfo); - return status; -} - -TfLiteStatus ValidateMaximumOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - FORWARD_LAYER_SUPPORT_FUNC("MAXIMUM", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputTensorInfo, - armnn::BinaryOperation::Maximum); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - -TfLiteStatus ValidateMinimumOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - FORWARD_LAYER_SUPPORT_FUNC("MINIMUM", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputTensorInfo, - armnn::BinaryOperation::Minimum); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - -TfLiteStatus ValidateMulOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - FORWARD_LAYER_SUPPORT_FUNC("MUL", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputTensorInfo, - armnn::BinaryOperation::Mul); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - -TfLiteStatus ValidateSubOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - const armnn::TensorInfo& inputInfo1, - const armnn::TensorInfo& inputInfo2, - const armnn::TensorInfo& outputInfo) -{ - bool isSupported = false; - auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) - { - FORWARD_LAYER_SUPPORT_FUNC("SUB", - tfLiteContext, - IsElementwiseBinarySupported, - delegateData.m_Backends, - isSupported, - armnn::BackendId(), - inputInfo1, - inputInfo2, - outputTensorInfo, - armnn::BinaryOperation::Sub); - }; - - validateFunc(outputInfo, isSupported); - return isSupported ? kTfLiteOk : kTfLiteError; -} - -std::pair<armnn::IConnectableLayer*, armnn::IConnectableLayer*> AddFloorDivLayer( - DelegateData& delegateData, - const armnn::TensorInfo& outputTensorInfo) -{ - armnn::IConnectableLayer* divisionLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Div); - // if the output of the div is Signed32 the Floor layer is not required - if (armnn::DataType::Signed32 == outputTensorInfo.GetDataType()) - { - return std::make_pair(divisionLayer, divisionLayer); - } - armnn::IOutputSlot& outputSlot = divisionLayer->GetOutputSlot(0); - outputSlot.SetTensorInfo(outputTensorInfo); - armnn::IConnectableLayer* floorLayer = delegateData.m_Network->AddFloorLayer(); - outputSlot.Connect(floorLayer->GetInputSlot(0)); - return std::make_pair(divisionLayer, floorLayer); -} - -TfLiteStatus VisitElementwiseBinaryOperator(DelegateData& delegateData, - TfLiteContext* tfLiteContext, - TfLiteNode* tfLiteNode, - int nodeIndex, - int32_t elementwiseBinaryOperatorCode) -{ - TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); - TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); - - const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; - const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]]; - if (IsDynamicTensor(tfLiteInputTensor0)) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", - elementwiseBinaryOperatorCode, nodeIndex); - return kTfLiteError; - } - - const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]]; - if (IsDynamicTensor(tfLiteInputTensor1)) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", - elementwiseBinaryOperatorCode, nodeIndex); - return kTfLiteError; - } - - const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; - if (IsDynamicTensor(tfLiteOutputTensor)) - { - TF_LITE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", - elementwiseBinaryOperatorCode, nodeIndex); - return kTfLiteError; - } - - armnn::TensorInfo inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0); - armnn::TensorInfo inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1); - - const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); - - // Check if we need to expand the dims of the input tensor infos. - // This is required for a few of the backends. - if(inputTensorInfo0.GetNumDimensions() != inputTensorInfo1.GetNumDimensions()) - { - ExpandTensorRankToEqual(inputTensorInfo0, inputTensorInfo1); - } - - auto* tfLiteNodeParameters = reinterpret_cast<TfLiteAddParams*>(tfLiteNode->builtin_data); - TfLiteFusedActivation activationType = kTfLiteActNone; - if (tfLiteNodeParameters) - { - activationType = tfLiteNodeParameters->activation; - TfLiteStatus activationStatus = ValidateFusedActivationOperator(delegateData, tfLiteContext, outputTensorInfo, - outputTensorInfo, activationType); - if(activationStatus != kTfLiteOk) - { - return kTfLiteError; - } - } - - if (!delegateData.m_Network) - { - switch(elementwiseBinaryOperatorCode) - { - case kTfLiteBuiltinAdd: - return ValidateAddOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinDiv: - return ValidateDivOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinFloorDiv: - return ValidateFloorDivOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinMaximum: - return ValidateMaximumOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinMinimum: - return ValidateMinimumOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinMul: - return ValidateMulOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - case kTfLiteBuiltinSub: - return ValidateSubOperator(delegateData, - tfLiteContext, - inputTensorInfo0, - inputTensorInfo1, - outputTensorInfo); - default: - return kTfLiteError; - } - } - - armnn::IConnectableLayer* elementwiseBinaryLayer = nullptr; - MultiLayerFacade multiLayer; - switch(elementwiseBinaryOperatorCode) - { - case kTfLiteBuiltinAdd: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Add); - break; - case kTfLiteBuiltinDiv: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Div); - break; - case kTfLiteBuiltinFloorDiv: - { - auto layers = AddFloorDivLayer(delegateData, outputTensorInfo); - multiLayer.AssignValues(layers.first, layers.second); - elementwiseBinaryLayer = &multiLayer; - } - break; - case kTfLiteBuiltinMaximum: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Maximum); - break; - case kTfLiteBuiltinMinimum: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Minimum); - break; - case kTfLiteBuiltinMul: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Mul); - break; - case kTfLiteBuiltinSub: - elementwiseBinaryLayer = delegateData.m_Network->AddElementwiseBinaryLayer( - armnn::BinaryOperation::Sub); - break; - default: - return kTfLiteError; - } - ARMNN_ASSERT(elementwiseBinaryLayer != nullptr); - armnn::IOutputSlot& outputSlot = elementwiseBinaryLayer->GetOutputSlot(0); - outputSlot.SetTensorInfo(outputTensorInfo); - - auto inputsTensorsProcess = ProcessInputs(elementwiseBinaryLayer, - delegateData, - tfLiteContext, - tfLiteNode); - if (inputsTensorsProcess == kTfLiteError) - { - return inputsTensorsProcess; - } - - if(Connect(elementwiseBinaryLayer, tfLiteNode, delegateData) != kTfLiteOk) - { - return kTfLiteError; - } - - if (!tfLiteNodeParameters) - { - // No Activation - return kTfLiteOk; - } - // Check and Create Activation - return FusedActivation(tfLiteContext, tfLiteNode, activationType, elementwiseBinaryLayer, 0, delegateData); -} - -} // namespace armnnDelegate |