From 083586da02165341b252d7c3ffd4381a1fe30414 Mon Sep 17 00:00:00 2001 From: John Mcloughlin Date: Fri, 28 Apr 2023 18:36:52 +0100 Subject: IVGCVSW-7606 IVGCVSW-7607 Add Resize and Reduce to Opaque Delegate * Added 2 opaque delegate operators and associated test cases * Removed IsDynamicTensor check from BatchMatMul as covered by IsValid. Signed-off-by: John Mcloughlin Change-Id: If7c58cb23ae5c5b8a9451dddfd7b6dfcbf248d4c --- delegate/CMakeLists.txt | 4 + delegate/opaque/CMakeLists.txt | 2 + delegate/opaque/src/BatchMatMul.hpp | 9 -- delegate/opaque/src/Reduce.hpp | 163 ++++++++++++++++++++++++ delegate/opaque/src/Resize.hpp | 218 +++++++++++++++++++++++++++++++++ delegate/opaque/src/armnn_delegate.cpp | 36 ++++++ 6 files changed, 423 insertions(+), 9 deletions(-) diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt index acd1255b0f..4f190c0601 100644 --- a/delegate/CMakeLists.txt +++ b/delegate/CMakeLists.txt @@ -302,6 +302,10 @@ if(BUILD_UNIT_TESTS) test/Pooling3dTestHelper.hpp test/PreluTest.cpp test/PreluTestHelper.hpp + test/ReduceTest.cpp + test/ReduceTestHelper.hpp + test/ResizeTest.cpp + test/ResizeTestHelper.hpp test/RoundTest.cpp test/RoundTestHelper.hpp test/QuantizationTest.cpp diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt index ac205ee959..897263d63e 100644 --- a/delegate/opaque/CMakeLists.txt +++ b/delegate/opaque/CMakeLists.txt @@ -28,6 +28,8 @@ list(APPEND armnnOpaqueDelegateObject_sources src/Pack.hpp src/Prelu.hpp src/Redefine.hpp + src/Reduce.hpp + src/Resize.hpp src/Round.hpp src/Shape.hpp src/SharedFunctions.cpp diff --git a/delegate/opaque/src/BatchMatMul.hpp b/delegate/opaque/src/BatchMatMul.hpp index 5da6e5ac6a..5261fbd6c4 100644 --- a/delegate/opaque/src/BatchMatMul.hpp +++ b/delegate/opaque/src/BatchMatMul.hpp @@ -44,15 +44,6 @@ TfLiteStatus VisitBatchMatMulOperator(DelegateData& delegateData, return kTfLiteError; } - if (IsDynamicTensor(kTfLiteLHSInputTensor) || IsDynamicTensor(kTfLiteRHSInputTensor)) - { - TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( - tfLiteContext, - "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", - operatorCode, nodeIndex); - return kTfLiteError; - } - // Gather output indices and use to get output tensors. int numOutputs = 0; const int* outputTensors; diff --git a/delegate/opaque/src/Reduce.hpp b/delegate/opaque/src/Reduce.hpp index e16969768e..afea7aafb0 100644 --- a/delegate/opaque/src/Reduce.hpp +++ b/delegate/opaque/src/Reduce.hpp @@ -2,3 +2,166 @@ // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // +#pragma once + +#include + +namespace armnnOpaqueDelegate +{ + +TfLiteStatus VisitReduceOperator(DelegateData& delegateData, + TfLiteOpaqueContext* tfLiteContext, + TfLiteOpaqueNode* tfLiteNode, + int nodeIndex, + int32_t reduceOperatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + // Gather input indices and use to get input tensor. + 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; + } + + const TfLiteOpaqueTensor* tfLiteInputTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]); + if (!IsValid(tfLiteContext, tfLiteInputTensor, reduceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const TfLiteOpaqueTensor* tfLiteAxisTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]); + if (!IsValid(tfLiteContext, tfLiteAxisTensor, reduceOperatorCode, 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, reduceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); + + // Get const axis value from model and set it to descriptor. + const armnn::TensorInfo& axisTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteAxisTensor); + auto* axisTensorData = static_cast(TfLiteOpaqueTensorData(tfLiteAxisTensor)); + + std::vector axis; + // Add axis data to vector to be converter to unsigned int and assigned to descriptor axis. + if (axisTensorData != nullptr) + { + for (unsigned int i = 0; i < axisTensorInfo.GetNumElements(); ++i) + { + axis.emplace_back(axisTensorData[i]); + } + } + else + { + for (unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); ++i) + { + axis.push_back(i); + } + } + + // Convert the axis to unsigned int and remove duplicates. + unsigned int rank = inputTensorInfo.GetNumDimensions(); + std::set uniqueAxis; + std::transform(axis.begin(), + axis.end(), + std::inserter(uniqueAxis, uniqueAxis.begin()), + [rank](int i)->unsigned int{ return (i + rank) % rank; }); + + armnn::ReduceDescriptor desc; + desc.m_vAxis.assign(uniqueAxis.begin(), uniqueAxis.end()); + + auto* reducerParameters = reinterpret_cast(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); + desc.m_KeepDims = reducerParameters->keep_dims; + if (reduceOperatorCode == kTfLiteBuiltinReduceMax) + { + desc.m_ReduceOperation = armnn::ReduceOperation::Max; + } + else if (reduceOperatorCode == kTfLiteBuiltinReduceMin) + { + desc.m_ReduceOperation = armnn::ReduceOperation::Min; + } + else if (reduceOperatorCode == kTfLiteBuiltinSum) + { + desc.m_ReduceOperation = armnn::ReduceOperation::Sum; + } + else if (reduceOperatorCode == kTfLiteBuiltinReduceProd) + { + desc.m_ReduceOperation = armnn::ReduceOperation::Prod; + } + else + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Unsupported Reduction Operator #%d node #%d: ", + reduceOperatorCode, nodeIndex); + return kTfLiteError; + } + + bool isSupported = false; + armnn::BackendId setBackend; + auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) + { + FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("REDUCE", + tfLiteContext, + IsReduceSupported, + delegateData.m_Backends, + isSupported, + setBackend, + inputTensorInfo, + outInfo, + desc); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + // Add an Reduce layer + armnn::IConnectableLayer* layer = delegateData.m_Network->AddReduceLayer(desc); + layer->SetBackendId(setBackend); + ARMNN_ASSERT(layer != nullptr); + + armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // try to connect the Constant Inputs if there are any + if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) + { + return kTfLiteError; + } + + // Connect + return Connect(layer, tfLiteContext, tfLiteNode, delegateData); +} + +} // namespace armnnOpaqueDelegate diff --git a/delegate/opaque/src/Resize.hpp b/delegate/opaque/src/Resize.hpp index e16969768e..509ae62524 100644 --- a/delegate/opaque/src/Resize.hpp +++ b/delegate/opaque/src/Resize.hpp @@ -2,3 +2,221 @@ // Copyright © 2023 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // + +#pragma once + +#include + +namespace armnnOpaqueDelegate +{ + +TfLiteStatus ValidateResizeOperator(DelegateData& delegateData, + TfLiteOpaqueContext* tfLiteContext, + const armnn::TensorInfo& inputInfo, + const armnn::TensorInfo& outputInfo, + const armnn::ResizeDescriptor& descriptor) +{ + bool isSupported = false; + FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("RESIZE", + tfLiteContext, + IsResizeSupported, + delegateData.m_Backends, + isSupported, + armnn::BackendId(), + inputInfo, + outputInfo, + descriptor); + + return isSupported ? kTfLiteOk : kTfLiteError; +} + +TfLiteStatus VisitResizeOperator(DelegateData& delegateData, + TfLiteOpaqueContext* tfLiteContext, + TfLiteOpaqueNode* tfLiteNode, + int nodeIndex, + int32_t resizeOperatorCode) +{ + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); + + // Gather input indices and use to get input tensor. + 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; + } + + // The first input contains the data of the image that should be resized [batch, height, width, channels] + 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: ", + resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + + // The second input contains a size tensor. The size tensor contains two integer values + // that describe the new height and width of the image [new_height, new_width] + const TfLiteOpaqueTensor* tfLiteSizeTensor = + TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]); + if (IsDynamicTensor(tfLiteSizeTensor)) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ", + resizeOperatorCode, 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; + } + + // The output tensor should have the shape [batch, new_height, new_width, channels] + 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: ", + resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = + GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor); + const armnn::TensorInfo& outputTensorInfo = + GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true); + + std::string layerName("Resize"); + + // Fill descriptor + armnn::ResizeDescriptor desc; + switch (resizeOperatorCode) + { + case kTfLiteBuiltinResizeBilinear: + { + desc.m_Method = armnn::ResizeMethod::Bilinear; + + layerName += "Bilinear:" + std::to_string(nodeIndex); + + TfLiteResizeBilinearParams* bilinearOptions = + reinterpret_cast(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); + + desc.m_AlignCorners = bilinearOptions->align_corners; + desc.m_HalfPixelCenters = bilinearOptions->half_pixel_centers; + break; + } + case kTfLiteBuiltinResizeNearestNeighbor: + { + desc.m_Method = armnn::ResizeMethod::NearestNeighbor; + layerName += "NearestNeighbor:" + std::to_string(nodeIndex); + + TfLiteResizeNearestNeighborParams* nearestNeighborOptions = + reinterpret_cast(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode)); + + desc.m_AlignCorners = nearestNeighborOptions->align_corners; + desc.m_HalfPixelCenters = nearestNeighborOptions->half_pixel_centers; + break; + } + default: + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: Unknown TfLite built in operation for Resize. " + "Given operator: #%d node #%d: ", + resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + } + + // In Arm NN the values of the size input tensor [new_height, new_width] is saved in the operator + // descriptor. We have to read it from the input tensor and write it to the descriptor. + + auto* sizeTensorDataPtr = static_cast(TfLiteOpaqueTensorData(tfLiteSizeTensor)); + auto sizeTensorNumDimensions = TfLiteOpaqueTensorNumDims(tfLiteSizeTensor); + // The size tensor is only a 1D tensor -> [new_height, new width] + if (sizeTensorNumDimensions != 1) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a " + "dynamic tensor. Operator: #%d node #%d: ", + resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + + // Get number of values in the size tensor + auto sizeTensorNumValues = TfLiteOpaqueTensorDim(tfLiteSizeTensor,0); + if (sizeTensorNumValues == 0) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a " + "dynamic tensor. Operator: #%d node #%d: ", + resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + else if (sizeTensorNumValues != 2) + { + TF_LITE_OPAQUE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation requires to " + "have a dimension of 2 [new_height, new width] but a tensor with a dimension of #%d was given. " + "Operator: #%d node #%d: ", + sizeTensorNumValues, resizeOperatorCode, nodeIndex); + return kTfLiteError; + } + // get size tensor data + std::vector sizeTensorData(sizeTensorDataPtr, sizeTensorDataPtr+sizeTensorNumValues); + + desc.m_TargetHeight = static_cast (sizeTensorData[0]); + desc.m_TargetWidth = static_cast (sizeTensorData[1]); + desc.m_DataLayout = armnn::DataLayout::NHWC; + + // No network pointer indicates that only support for this operator should be checked + if (!delegateData.m_Network) + { + return ValidateResizeOperator(delegateData, + tfLiteContext, + inputTensorInfo, + outputTensorInfo, + desc); + } + + + armnn::IConnectableLayer* resizeLayer = nullptr; + resizeLayer = delegateData.m_Network->AddResizeLayer(desc, layerName.c_str()); + + armnn::IOutputSlot& outputSlot = resizeLayer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // try to connect the Constant Inputs if there are any + if(ProcessInputs(resizeLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk ) + { + return kTfLiteError; + } + + ARMNN_ASSERT(resizeLayer != nullptr); + + return Connect(resizeLayer, tfLiteContext, tfLiteNode, delegateData); +} + +} // namespace armnnOpaqueDelegate diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp index 9b1c3a1f46..936e75a034 100644 --- a/delegate/opaque/src/armnn_delegate.cpp +++ b/delegate/opaque/src/armnn_delegate.cpp @@ -966,6 +966,24 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData, tfLiteNode, nodeIndex, kTfLiteBuiltinQuantize); + case kTfLiteBuiltinReduceMax: + return VisitReduceOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinReduceMax); + case kTfLiteBuiltinReduceMin: + return VisitReduceOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinReduceMin); + case kTfLiteBuiltinReduceProd: + return VisitReduceOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinReduceProd); case kTfLiteBuiltinRelu: return VisitActivationOperator(delegateData, tfLiteContext, @@ -984,6 +1002,18 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData, tfLiteNode, nodeIndex, kTfLiteBuiltinRelu6); + case kTfLiteBuiltinResizeNearestNeighbor: + return VisitResizeOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinResizeNearestNeighbor); + case kTfLiteBuiltinResizeBilinear: + return VisitResizeOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinResizeBilinear); case kTfLiteBuiltinRsqrt: return VisitElementwiseUnaryOperator(delegateData, tfLiteContext, @@ -1035,6 +1065,12 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData, nodeIndex, kTfLiteBuiltinSqrt, armnn::UnaryOperation::Sqrt); + case kTfLiteBuiltinSum: + return VisitReduceOperator(delegateData, + tfLiteContext, + tfLiteNode, + nodeIndex, + kTfLiteBuiltinSum); case kTfLiteBuiltinTanh: return VisitActivationOperator(delegateData, tfLiteContext, -- cgit v1.2.1