| // |
| // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include <OpaqueDelegateUtils.hpp> |
| |
| namespace armnnOpaqueDelegate |
| { |
| |
| std::string GetLayerName(armnn::ActivationFunction activationFunction) |
| { |
| std::string layerName = "ACTIVATION"; |
| switch (activationFunction) |
| { |
| case armnn::ActivationFunction::Abs: |
| layerName += " ABS"; |
| break; |
| case armnn::ActivationFunction::BoundedReLu: |
| layerName += " BOUNDED_RELU"; |
| break; |
| case armnn::ActivationFunction::Elu: |
| layerName += " ELU"; |
| break; |
| case armnn::ActivationFunction::HardSwish: |
| layerName += " HARD_SWISH"; |
| break; |
| case armnn::ActivationFunction::LeakyReLu: |
| layerName += " LEAKY_RELU"; |
| break; |
| case armnn::ActivationFunction::Linear: |
| layerName += " LINEAR"; |
| break; |
| case armnn::ActivationFunction::ReLu: |
| layerName += " RELU"; |
| break; |
| case armnn::ActivationFunction::Sigmoid: |
| layerName += " SIGMOID"; |
| break; |
| case armnn::ActivationFunction::SoftReLu: |
| layerName += " SOFT_RELU"; |
| break; |
| case armnn::ActivationFunction::Square: |
| layerName += " SQUARE"; |
| break; |
| case armnn::ActivationFunction::Sqrt: |
| layerName += " SQRT"; |
| break; |
| case armnn::ActivationFunction::TanH: |
| layerName += " TANH"; |
| break; |
| default: |
| layerName += " UNKNOWN"; |
| } |
| return layerName; |
| } |
| |
| TfLiteStatus ValidateActivationOperator(DelegateData& delegateData, |
| TfLiteOpaqueContext* tfLiteContext, |
| const armnn::TensorInfo& inputInfo, |
| const armnn::TensorInfo& outputInfo, |
| armnn::ActivationDescriptor& activationDesc) |
| { |
| bool isSupported = false; |
| auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported, std::string layerName) |
| { |
| FORWARD_LAYER_OPAQUE_SUPPORT_FUNC(layerName.c_str(), |
| tfLiteContext, |
| IsActivationSupported, |
| delegateData.m_Backends, |
| isSupported, |
| armnn::BackendId(), |
| inputInfo, |
| outputInfo, |
| activationDesc); |
| }; |
| |
| validateFunc(outputInfo, isSupported, GetLayerName(activationDesc.m_Function)); |
| return isSupported ? kTfLiteOk : kTfLiteError; |
| } |
| |
| TfLiteStatus VisitActivationOperator(DelegateData& delegateData, |
| TfLiteOpaqueContext* tfLiteContext, |
| TfLiteOpaqueNode* tfLiteNode, |
| int nodeIndex, |
| int32_t operatorCode) |
| { |
| TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
| |
| // Gather input indices and use to get input tensor. |
| int numInputs = 0; |
| const int* inputTensors; |
| if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| // Gather output indices and use to get output tensors. |
| int numOutputs = 0; |
| const int* outputTensors; |
| if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk) |
| { |
| TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( |
| tfLiteContext, |
| "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ", |
| nodeIndex); |
| return kTfLiteError; |
| } |
| |
| const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); |
| if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) |
| { |
| return kTfLiteError; |
| } |
| |
| const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); |
| const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); |
| |
| armnn::ActivationDescriptor activationDesc; |
| switch(operatorCode) |
| { |
| case kTfLiteBuiltinRelu: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::ReLu; |
| break; |
| } |
| case kTfLiteBuiltinRelu6: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::BoundedReLu; |
| activationDesc.m_A = 6.0f; |
| break; |
| } |
| case kTfLiteBuiltinLogistic: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::Sigmoid; |
| break; |
| } |
| case kTfLiteBuiltinTanh: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::TanH; |
| activationDesc.m_A = 1.0f; |
| activationDesc.m_B = 1.0f; |
| break; |
| } |
| case kTfLiteBuiltinElu: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::Elu; |
| activationDesc.m_A = 1.0f; |
| break; |
| } |
| case kTfLiteBuiltinHardSwish: |
| { |
| activationDesc.m_Function = armnn::ActivationFunction::HardSwish; |
| break; |
| } |
| default: |
| { |
| return kTfLiteError; |
| } |
| } |
| if (!delegateData.m_Network) |
| { |
| return ValidateActivationOperator(delegateData, |
| tfLiteContext, |
| inputTensorInfo, |
| outputTensorInfo, |
| activationDesc); |
| } |
| armnn::IConnectableLayer* activationLayer = delegateData.m_Network->AddActivationLayer(activationDesc); |
| ARMNN_ASSERT(activationLayer != nullptr); |
| |
| armnn::IOutputSlot& outputSlot = activationLayer->GetOutputSlot(0); |
| outputSlot.SetTensorInfo(outputTensorInfo); |
| |
| // try to connect the Constant Inputs if there are any |
| if(ProcessInputs(activationLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) |
| { |
| return kTfLiteError; |
| } |
| |
| // Connect |
| return Connect(activationLayer, tfLiteContext, tfLiteNode, delegateData); |
| } |
| |
| } // namespace armnnDelegate |