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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/Transpose.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/Transpose.hpp')
-rw-r--r-- | delegate/classic/src/Transpose.hpp | 110 |
1 files changed, 110 insertions, 0 deletions
diff --git a/delegate/classic/src/Transpose.hpp b/delegate/classic/src/Transpose.hpp new file mode 100644 index 0000000000..41178d0b59 --- /dev/null +++ b/delegate/classic/src/Transpose.hpp @@ -0,0 +1,110 @@ +// +// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <armnn/utility/IgnoreUnused.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/kernels/internal/tensor_ctypes.h> + +namespace armnnDelegate +{ + +TfLiteStatus VisitTransposeOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + TfLiteNode* tfLiteNode, + int nodeIndex, + int32_t tfliteTransposeOperatorCode) +{ + 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: ", + tfliteTransposeOperatorCode, 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: ", + tfliteTransposeOperatorCode, 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: ", + tfliteTransposeOperatorCode, nodeIndex); + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); + + auto* permTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteInputTensor1); + unsigned int numEl = tfLiteInputTensor1.dims->data[0]; + + ARMNN_ASSERT( numEl <= static_cast<int>(armnn::MaxNumOfTensorDimensions)); + ARMNN_ASSERT( tfLiteInputTensor1.dims->size == 1); // ensure only single dimension to the permutation tensor + + armnn::TransposeDescriptor descriptor(armnn::PermutationVector( + reinterpret_cast<const armnn::PermutationVector::ValueType *> (permTensorDataPtr), + static_cast<armnn::PermutationVector::SizeType>(numEl))); + + bool isSupported = false; + armnn::BackendId setBackend; + auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC("TRANSPOSE", + tfLiteContext, + IsTransposeSupported, + delegateData.m_Backends, + isSupported, + setBackend, + inputTensorInfo0, + outputTensorInfo, + descriptor); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + armnn::IConnectableLayer* transposeLayer = delegateData.m_Network->AddTransposeLayer(descriptor); + transposeLayer->SetBackendId(setBackend); + ARMNN_ASSERT(transposeLayer != nullptr); + ARMNN_ASSERT(transposeLayer->GetNumInputSlots() == 1); // permutation vector given to descriptor object + + armnn::IOutputSlot& outputSlot = transposeLayer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // try to connect the Constant Inputs if there are any + if(ProcessInputs(transposeLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) + { + return kTfLiteError; + } + + return Connect(transposeLayer, tfLiteNode, delegateData); +} +} // namespace armnnDelegate |