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author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-14 12:10:28 +0000 |
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committer | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-28 11:41:55 +0100 |
commit | ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9 (patch) | |
tree | a5b8e1ad68a2437f007338f0b6195ca5ed2bddc3 /delegate/classic/src/Activation.hpp | |
parent | 9cb3466b677a1048b8abb24661e92c4c83fdda04 (diff) | |
download | armnn-ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9.tar.gz |
IVGCVSW-7555 Restructure Delegate
* New folders created:
* common is for common code where TfLite API is not used
* classic is for existing delegate implementations
* opaque is for new opaque delegate implementation,
* tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed
Diffstat (limited to 'delegate/classic/src/Activation.hpp')
-rw-r--r-- | delegate/classic/src/Activation.hpp | 133 |
1 files changed, 133 insertions, 0 deletions
diff --git a/delegate/classic/src/Activation.hpp b/delegate/classic/src/Activation.hpp new file mode 100644 index 0000000000..b86d89b4e5 --- /dev/null +++ b/delegate/classic/src/Activation.hpp @@ -0,0 +1,133 @@ +// +// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <DelegateUtils.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> + +namespace armnnDelegate +{ + +TfLiteStatus ValidateActivationOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + const armnn::TensorInfo& inputInfo, + const armnn::TensorInfo& outputInfo, + armnn::ActivationDescriptor& activationDesc) +{ + bool isSupported = false; + auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC("ACTIVATION", + tfLiteContext, + IsActivationSupported, + delegateData.m_Backends, + isSupported, + armnn::BackendId(), + inputInfo, + outputInfo, + activationDesc); + }; + + validateFunc(outputInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; +} + +TfLiteStatus VisitActivationOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + TfLiteNode* tfLiteNode, + int nodeIndex, + int32_t operatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(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, tfLiteNode, delegateData); +} + +} // namespace armnnDelegate |