From 92ce35cda7c5e97eff05d6f37dc86990386309bb Mon Sep 17 00:00:00 2001 From: Tianle Cheng Date: Tue, 25 Jul 2023 16:41:00 +0100 Subject: IVGCVSW-7886 Add TILE to delegate and opaque delegate * Adding support for Tile in classic and opaque delegates * CMake files updated * Tests added Signed-off-by: Tianle Cheng Change-Id: I9b52cea3480eb71961cbccb1a346805f73b5661a --- delegate/opaque/CMakeLists.txt | 1 + delegate/opaque/src/Tile.hpp | 188 +++++++++++++++++++++++++++++++++ delegate/opaque/src/armnn_delegate.cpp | 15 ++- 3 files changed, 200 insertions(+), 4 deletions(-) create mode 100644 delegate/opaque/src/Tile.hpp (limited to 'delegate/opaque') diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt index 787046d80c..c05bccf8c9 100644 --- a/delegate/opaque/CMakeLists.txt +++ b/delegate/opaque/CMakeLists.txt @@ -41,6 +41,7 @@ list(APPEND armnnOpaqueDelegateObject_sources src/SpaceDepth.hpp src/Split.hpp src/StridedSlice.hpp + src/Tile.hpp src/Transpose.hpp src/UnidirectionalSequenceLstm.hpp src/Unpack.hpp) diff --git a/delegate/opaque/src/Tile.hpp b/delegate/opaque/src/Tile.hpp new file mode 100644 index 0000000000..17cbdee7eb --- /dev/null +++ b/delegate/opaque/src/Tile.hpp @@ -0,0 +1,188 @@ +// +// Copyright © 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include + +namespace armnnOpaqueDelegate +{ +TfLiteStatus ValidateTileOperator(DelegateData& delegateData, + TfLiteOpaqueContext *tfLiteContext, + const armnn::TensorInfo& inputInfo, + const armnn::TensorInfo& outputInfo, + const armnn::TileDescriptor& descriptor) +{ + bool isSupported = false; + FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("TILE", + tfLiteContext, + IsTileSupported, + delegateData.m_Backends, + isSupported, + armnn::BackendId(), + inputInfo, + outputInfo, + descriptor); + return isSupported ? kTfLiteOk : kTfLiteError; +} + +TfLiteStatus VisitTileOperator(DelegateData& delegateData, + TfLiteOpaqueContext* tfLiteContext, + TfLiteOpaqueNode* tfLiteNode, + int nodeIndex, + int32_t tileOperatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + // Gather input tensors + auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode); + 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; + } + + // Gather 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; + } + + // The input contains the data that should be tiled + const TfLiteOpaqueTensor* tfLiteInputTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); + if (IsDynamicTensor(tfLiteInputTensor)) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + + // The multiples tensor contains the number of copies for each axis + const TfLiteOpaqueTensor* tfLiteMultiplesTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);; + if (IsDynamicTensor(tfLiteMultiplesTensor)) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + + // The output tensor + const TfLiteOpaqueTensor* tfLiteOutputTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]); + if (IsDynamicTensor(tfLiteOutputTensor)) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); + const armnn::TensorInfo& multiplesTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteMultiplesTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); + + // Multiples length must be the same as the number of dimension in input tensor + if (multiplesTensorInfo.GetNumElements() != inputTensorInfo.GetNumDimensions()) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate:", + "The Multiples length must be the same as the number of dimension in input tensor", + "Operator: #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + + // Get the Multiples data: In armnn, the values of the multiples input tensor is saved in the operator descriptor + // We have to read it from the input tensor and write it the descriptor + auto* multiplesTensorDataPtr = static_cast(TfLiteOpaqueTensorData(tfLiteMultiplesTensor)); + auto multiplesTensorNum = TfLiteOpaqueTensorDim(tfLiteMultiplesTensor, 0); + std::vector multiplesIntData(multiplesTensorDataPtr, multiplesTensorDataPtr + multiplesTensorNum); + + // The multiples must be positive + for (auto multiple : multiplesIntData) + { + if (multiple < 0) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: The Multiples must be positive values", + "Operator: #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + } + + // The original input from TFLite is int32, and we have to make it as uint32 for our descriptor + std::vector multiplesUintData; + std::transform(multiplesIntData.begin(), + multiplesIntData.end(), + std::back_inserter(multiplesUintData), + [] (const int value) + { + return static_cast(value); + }); + + armnn::TileDescriptor tileDescriptor; + tileDescriptor.m_Multiples = multiplesUintData; + + // Check output dimensions + if (inputTensorInfo.GetNumDimensions() != outputTensorInfo.GetNumDimensions()) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Input tensor dimension and output tensor dimension differ", + "Operator: #%d node #%d: ", + tileOperatorCode, nodeIndex); + return kTfLiteError; + } + + // No network pointer indicates that only support for this operator should be checked + if (!delegateData.m_Network) + { + return ValidateTileOperator(delegateData, + tfLiteContext, + inputTensorInfo, + outputTensorInfo, + tileDescriptor); + } + + std::string layerName("Tile"); + armnn::IConnectableLayer* layer = delegateData.m_Network->AddTileLayer(tileDescriptor, layerName.c_str()); + + if (layer == nullptr) + { + return kTfLiteError; + } + + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk) + { + return kTfLiteError; + } + + return Connect(layer, tfLiteContext, tfLiteNode, delegateData); +} + +} // namespace armnnOpaqueDelegate \ No newline at end of file diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp index 510352eae9..49fa30d8f0 100644 --- a/delegate/opaque/src/armnn_delegate.cpp +++ b/delegate/opaque/src/armnn_delegate.cpp @@ -38,6 +38,7 @@ #include "Softmax.hpp" #include "SpaceDepth.hpp" #include "Split.hpp" +#include "Tile.hpp" #include "Transpose.hpp" #include "UnidirectionalSequenceLstm.hpp" #include "Unpack.hpp" @@ -1138,12 +1139,18 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData, tfLiteNode, nodeIndex, kTfLiteBuiltinTanh); + case kTfLiteBuiltinTile: + return VisitTileOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinTile); case kTfLiteBuiltinTranspose: return VisitTransposeOperator(delegateData, - tfLiteContext, - tfLiteNode, - nodeIndex, - kTfLiteBuiltinTranspose); + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinTranspose); case kTfLiteBuiltinTransposeConv: return VisitConvolutionOperator(delegateData, tfLiteContext, -- cgit v1.2.1