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Diffstat (limited to 'delegate/classic/src/Pad.hpp')
| -rw-r--r-- | delegate/classic/src/Pad.hpp | 179 |
1 files changed, 179 insertions, 0 deletions
diff --git a/delegate/classic/src/Pad.hpp b/delegate/classic/src/Pad.hpp new file mode 100644 index 0000000000..440a3d023c --- /dev/null +++ b/delegate/classic/src/Pad.hpp @@ -0,0 +1,179 @@ +// +// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#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 VisitPadOperator(DelegateData& delegateData, + TfLiteContext* tfLiteContext, + TfLiteNode* tfLiteNode, + int nodeIndex, + int32_t tfLitePadOperatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + switch(tfLitePadOperatorCode) + { + case kTfLiteBuiltinMirrorPad: + case kTfLiteBuiltinPad: + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + break; + case kTfLiteBuiltinPadv2: + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex)); + break; + default: + return kTfLiteError; + } + + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; + const TfLiteTensor& tfLitepaddingTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; + + if (IsDynamicTensor(tfLiteInputTensor)) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, 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: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); + const armnn::TensorInfo& paddingTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true); + + // Get the padding data from the input tensor + auto* paddingData = tflite::GetTensorData<int32_t>(&tfLitepaddingTensor); + + size_t step = 2; + armnn::PadDescriptor descriptor; + for (unsigned int i = 0; i < paddingTensorInfo.GetNumElements() / step; ++i) + { + descriptor.m_PadList.emplace_back(paddingData[i * step], paddingData[i * step + 1]); + } + + if (tfLitePadOperatorCode == kTfLiteBuiltinPad && inputTensorInfo.IsQuantized()) + { + descriptor.m_PadValue = inputTensorInfo.GetQuantizationOffset(); + } + else if (tfLitePadOperatorCode == kTfLiteBuiltinPadv2) + { + const TfLiteTensor& tfLitepaddingValue = tfLiteTensors[tfLiteNode->inputs->data[2]]; + armnn::TensorInfo paddingValueTensorInfo = GetTensorInfoForTfLiteTensor(tfLitepaddingValue); + if (paddingValueTensorInfo.GetNumElements() != 1) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Multiple padding value are not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + // Get the padding value from the input tensor + switch (tfLitepaddingValue.type) + { + case kTfLiteFloat32: + descriptor.m_PadValue = tflite::GetTensorData<float>(&tfLitepaddingValue)[0]; + break; + case kTfLiteUInt8: + descriptor.m_PadValue = tflite::GetTensorData<uint8>(&tfLitepaddingValue)[0]; + break; + case kTfLiteInt8: + descriptor.m_PadValue = tflite::GetTensorData<int8>(&tfLitepaddingValue)[0]; + break; + default: + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Padding value datatype is not supported in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + return kTfLiteError; + } + } + else if (tfLitePadOperatorCode == kTfLiteBuiltinMirrorPad) + { + TfLiteMirrorPaddingParams* options = reinterpret_cast<TfLiteMirrorPaddingParams*>(tfLiteNode->builtin_data); + + + if (options->mode == TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingReflect) + { + descriptor.m_PaddingMode = armnn::PaddingMode::Reflect; + } + else if (options->mode == TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingSymmetric) + { + descriptor.m_PaddingMode = armnn::PaddingMode::Symmetric; + } + else + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: PaddingMode must be either REFLECT or SYMMETRIC in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + } + + // If padding mode is Reflect then both paddings must be no greater than inputShape(i) - 1. + // If padding mode is Symmetric then both paddings must be no greater than inputShape(i). + auto inputShape = inputTensorInfo.GetShape(); + auto padList = descriptor.m_PadList; + + const unsigned int isReflect = + static_cast<unsigned int>(descriptor.m_PaddingMode == armnn::PaddingMode::Reflect); + for(unsigned int i = 0; i < padList.size(); ++i) + { + if(padList.at(i).first > (inputShape[i] - isReflect) || + padList.at(i).second > (inputShape[i] - isReflect)) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: Padding values must be less (Reflect) or " + "equal (Symmetric) to the dimension size in operator #%d node #%d: ", + tfLitePadOperatorCode, nodeIndex); + } + } + } + + armnn::BackendId setBackend; + if (!delegateData.m_Network) + { + bool isSupported = false; + FORWARD_LAYER_SUPPORT_FUNC("PAD", + tfLiteContext, + IsPadSupported, + delegateData.m_Backends, + isSupported, + setBackend, + inputTensorInfo, + outputTensorInfo, + descriptor); + + return isSupported ? kTfLiteOk : kTfLiteError; + } + + armnn::IConnectableLayer* padLayer = delegateData.m_Network->AddPadLayer(descriptor); + padLayer->SetBackendId(setBackend); + ARMNN_ASSERT(padLayer != nullptr); + + armnn::IOutputSlot& outputSlot = padLayer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + return Connect(padLayer, tfLiteNode, delegateData); +} + +} // namespace armnnDelegate |