From 2ffddda9d9f890a041bcdcc80948d2de1e627832 Mon Sep 17 00:00:00 2001 From: Jan Eilers Date: Wed, 3 Feb 2021 09:14:30 +0000 Subject: IVGCVSW-5386 TfLiteDelegate: Add Strided Slice operator Signed-off-by: Jan Eilers Change-Id: Icd87b1c54e1a5de84893882da30840a9097f6d84 --- delegate/CMakeLists.txt | 2 + delegate/src/Slice.hpp | 125 ++++++++++++++++- delegate/src/test/SliceTest.cpp | 243 ++++++++++++++++++++++++++++++++++ delegate/src/test/SliceTestHelper.hpp | 241 +++++++++++++++++++++++++++++++++ 4 files changed, 605 insertions(+), 6 deletions(-) create mode 100644 delegate/src/test/SliceTest.cpp create mode 100644 delegate/src/test/SliceTestHelper.hpp diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt index f792821d1c..7de168fa97 100644 --- a/delegate/CMakeLists.txt +++ b/delegate/CMakeLists.txt @@ -157,6 +157,8 @@ if(BUILD_UNIT_TESTS) src/test/SoftmaxTestHelper.hpp src/test/SpaceDepthTest.cpp src/test/SpaceDepthTestHelper.hpp + src/test/SliceTest.cpp + src/test/SliceTestHelper.hpp src/test/SplitTest.cpp src/test/SplitTestHelper.hpp src/test/TestUtils.hpp diff --git a/delegate/src/Slice.hpp b/delegate/src/Slice.hpp index 0311abf41c..a237034bb6 100644 --- a/delegate/src/Slice.hpp +++ b/delegate/src/Slice.hpp @@ -21,13 +21,126 @@ TfLiteStatus VisitSliceOperator(DelegateData& delegateData, int nodeIndex, int32_t sliceOperatorCode) { - armnn::IgnoreUnused(delegateData, - tfLiteContext, - tfLiteNode, - nodeIndex, - sliceOperatorCode); + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex)); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); - return kTfLiteError; + // Read inputs [input, begin, end, strides] + int numInputs = tfLiteNode->inputs->size; + std::vector tfLiteInputs; + tfLiteInputs.reserve(numInputs); + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + for (int i = 0; i < numInputs; i++) + { + const TfLiteTensor* inputTensor = &tfLiteTensors[tfLiteNode->inputs->data[i]]; + tfLiteInputs.push_back(inputTensor); + if (!IsValid(tfLiteContext, *inputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + } + + // We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs + int inputRank = tfLiteInputs[0]->dims->size; + auto ReadInt32Input = [&](int inputIndex, std::vector& outputData) -> TfLiteStatus + { + if (tfLiteInputs[inputIndex]->type != kTfLiteInt32) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be of type int32. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int rank = tfLiteInputs[inputIndex]->dims->size; + if (rank != 1) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " + "be a 1D-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + int numValues = tfLiteInputs[inputIndex]->dims->data[0]; + if (numValues != inputRank) + { + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: The number of values in the Begin-, End- and Stride-Tensors of the " + "StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ", + sliceOperatorCode, nodeIndex); + return kTfLiteError; + } + // return tensor data + auto* tensorDataPtr = tflite::GetTensorData(tfLiteInputs[inputIndex]); + outputData.assign(tensorDataPtr, tensorDataPtr+numValues); + return kTfLiteOk; + }; + + std::vector beginData; + if (ReadInt32Input(1, beginData) != kTfLiteOk) + return kTfLiteError; + std::vector endData; + if (ReadInt32Input(2, endData) != kTfLiteOk) + return kTfLiteError; + std::vector strideData; + if (ReadInt32Input(3, strideData) != kTfLiteOk) + return kTfLiteError; + + // parse built in options + auto* stridedSliceParams = reinterpret_cast(tfLiteNode->builtin_data); + + // Write all data to the descriptor + armnn::StridedSliceDescriptor descriptor; + descriptor.m_Begin = std::move(beginData); + descriptor.m_End = std::move(endData); + descriptor.m_Stride = std::move(strideData); + descriptor.m_BeginMask = stridedSliceParams->begin_mask; + descriptor.m_EllipsisMask = stridedSliceParams->ellipsis_mask; + descriptor.m_EndMask = stridedSliceParams->end_mask; + descriptor.m_NewAxisMask = stridedSliceParams->new_axis_mask; + descriptor.m_ShrinkAxisMask = stridedSliceParams->shrink_axis_mask; + descriptor.m_DataLayout = armnn::DataLayout::NHWC; + + // Validate output + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, sliceOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(*tfLiteInputs[0]); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); + + bool isSupported = false; + auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC(__func__, + tfLiteContext, + IsStridedSliceSupported, + delegateData.m_Backends, + isSupported, + inputTensorInfo, + outInfo, + descriptor); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + // Add a StridedSlice layer + armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor); + ARMNN_ASSERT(layer != nullptr); + + armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + // Connect + return Connect(layer, tfLiteNode, delegateData); } } // namespace armnnDelegate diff --git a/delegate/src/test/SliceTest.cpp b/delegate/src/test/SliceTest.cpp new file mode 100644 index 0000000000..bd0584936e --- /dev/null +++ b/delegate/src/test/SliceTest.cpp @@ -0,0 +1,243 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "SliceTestHelper.hpp" + +#include + +#include +#include + +#include + +namespace armnnDelegate +{ + +void StridedSlice4DTest(std::vector& backends) +{ + std::vector inputShape { 3, 2, 3, 1 }; + std::vector outputShape { 1, 2, 3, 1 }; + std::vector beginShape { 4 }; + std::vector endShape { 4 }; + std::vector strideShape { 4 }; + + std::vector beginData { 1, 0, 0, 0 }; + std::vector endData { 2, 2, 3, 1 }; + std::vector strideData { 1, 1, 1, 1 }; + std::vector inputData { 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f }; + std::vector outputData { 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f }; + + StridedSliceTestImpl( + backends, + inputData, + outputData, + beginData, + endData, + strideData, + inputShape, + beginShape, + endShape, + strideShape, + outputShape + ); +} + +void StridedSlice4DReverseTest(std::vector& backends) +{ + std::vector inputShape { 3, 2, 3, 1 }; + std::vector outputShape { 1, 2, 3, 1 }; + std::vector beginShape { 4 }; + std::vector endShape { 4 }; + std::vector strideShape { 4 }; + + std::vector beginData { 1, -1, 0, 0 }; + std::vector endData { 2, -3, 3, 1 }; + std::vector strideData { 1, -1, 1, 1 }; + std::vector inputData { 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f }; + std::vector outputData { 4.0f, 4.0f, 4.0f, 3.0f, 3.0f, 3.0f }; + + StridedSliceTestImpl( + backends, + inputData, + outputData, + beginData, + endData, + strideData, + inputShape, + beginShape, + endShape, + strideShape, + outputShape + ); +} + +void StridedSliceSimpleStrideTest(std::vector& backends) +{ + std::vector inputShape { 3, 2, 3, 1 }; + std::vector outputShape { 2, 1, 2, 1 }; + std::vector beginShape { 4 }; + std::vector endShape { 4 }; + std::vector strideShape { 4 }; + + std::vector beginData { 0, 0, 0, 0 }; + std::vector endData { 3, 2, 3, 1 }; + std::vector strideData { 2, 2, 2, 1 }; + std::vector inputData { 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f }; + std::vector outputData { 1.0f, 1.0f, + 5.0f, 5.0f }; + + StridedSliceTestImpl( + backends, + inputData, + outputData, + beginData, + endData, + strideData, + inputShape, + beginShape, + endShape, + strideShape, + outputShape + ); +} + +void StridedSliceSimpleRangeMaskTest(std::vector& backends) +{ + std::vector inputShape { 3, 2, 3, 1 }; + std::vector outputShape { 3, 2, 3, 1 }; + std::vector beginShape { 4 }; + std::vector endShape { 4 }; + std::vector strideShape { 4 }; + + std::vector beginData { 1, 1, 1, 1 }; + std::vector endData { 1, 1, 1, 1 }; + std::vector strideData { 1, 1, 1, 1 }; + + int beginMask = -1; + int endMask = -1; + + std::vector inputData { 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f }; + std::vector outputData { 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f }; + + StridedSliceTestImpl( + backends, + inputData, + outputData, + beginData, + endData, + strideData, + inputShape, + beginShape, + endShape, + strideShape, + outputShape, + beginMask, + endMask + ); +} + + +TEST_SUITE("StridedSlice_CpuRefTests") +{ + +TEST_CASE ("StridedSlice_4D_CpuRef_Test") +{ + std::vector backends = {armnn::Compute::CpuRef}; + StridedSlice4DTest(backends); +} + +TEST_CASE ("StridedSlice_4D_Reverse_CpuRef_Test") +{ + std::vector backends = {armnn::Compute::CpuRef}; + StridedSlice4DReverseTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleStride_CpuRef_Test") +{ + std::vector backends = {armnn::Compute::CpuRef}; + StridedSliceSimpleStrideTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleRange_CpuRef_Test") +{ + std::vector backends = {armnn::Compute::CpuRef}; + StridedSliceSimpleRangeMaskTest(backends); +} + +} // StridedSlice_CpuRefTests TestSuite + + + +TEST_SUITE("StridedSlice_CpuAccTests") +{ + +TEST_CASE ("StridedSlice_4D_CpuAcc_Test") +{ + std::vector backends = {armnn::Compute::CpuAcc}; + StridedSlice4DTest(backends); +} + +TEST_CASE ("StridedSlice_4D_Reverse_CpuAcc_Test") +{ + std::vector backends = {armnn::Compute::CpuAcc}; + StridedSlice4DReverseTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleStride_CpuAcc_Test") +{ + std::vector backends = {armnn::Compute::CpuAcc}; + StridedSliceSimpleStrideTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleRange_CpuAcc_Test") +{ + std::vector backends = {armnn::Compute::CpuAcc}; + StridedSliceSimpleRangeMaskTest(backends); +} + +} // StridedSlice_CpuAccTests TestSuite + + + +TEST_SUITE("StridedSlice_GpuAccTests") +{ + +TEST_CASE ("StridedSlice_4D_GpuAcc_Test") +{ + std::vector backends = {armnn::Compute::GpuAcc}; + StridedSlice4DTest(backends); +} + +TEST_CASE ("StridedSlice_4D_Reverse_GpuAcc_Test") +{ + std::vector backends = {armnn::Compute::GpuAcc}; + StridedSlice4DReverseTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleStride_GpuAcc_Test") +{ + std::vector backends = {armnn::Compute::GpuAcc}; + StridedSliceSimpleStrideTest(backends); +} + +TEST_CASE ("StridedSlice_SimpleRange_GpuAcc_Test") +{ + std::vector backends = {armnn::Compute::GpuAcc}; + StridedSliceSimpleRangeMaskTest(backends); +} + +} // StridedSlice_GpuAccTests TestSuite + +} // namespace armnnDelegate \ No newline at end of file diff --git a/delegate/src/test/SliceTestHelper.hpp b/delegate/src/test/SliceTestHelper.hpp new file mode 100644 index 0000000000..abaa807aed --- /dev/null +++ b/delegate/src/test/SliceTestHelper.hpp @@ -0,0 +1,241 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TestUtils.hpp" + +#include +#include + +#include +#include +#include +#include +#include +#include + +#include + +#include + +namespace +{ + +struct StridedSliceParams +{ + StridedSliceParams(std::vector& inputTensorShape, + std::vector& beginTensorData, + std::vector& endTensorData, + std::vector& strideTensorData, + std::vector& outputTensorShape, + armnn::StridedSliceDescriptor& descriptor) + : m_InputTensorShape(inputTensorShape), + m_BeginTensorData(beginTensorData), + m_EndTensorData(endTensorData), + m_StrideTensorData(strideTensorData), + m_OutputTensorShape(outputTensorShape), + m_Descriptor (descriptor) {} + + std::vector m_InputTensorShape; + std::vector m_BeginTensorData; + std::vector m_EndTensorData; + std::vector m_StrideTensorData; + std::vector m_OutputTensorShape; + armnn::StridedSliceDescriptor m_Descriptor; +}; + +std::vector CreateSliceTfLiteModel(tflite::TensorType tensorType, + const std::vector& inputTensorShape, + const std::vector& beginTensorData, + const std::vector& endTensorData, + const std::vector& strideTensorData, + const std::vector& beginTensorShape, + const std::vector& endTensorShape, + const std::vector& strideTensorShape, + const std::vector& outputTensorShape, + const int32_t beginMask, + const int32_t endMask, + const int32_t ellipsisMask, + const int32_t newAxisMask, + const int32_t ShrinkAxisMask, + const armnn::DataLayout& dataLayout) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::array, 4> buffers; + buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); + buffers[1] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast(beginTensorData.data()), + sizeof(int32_t) * beginTensorData.size())); + buffers[2] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast(endTensorData.data()), + sizeof(int32_t) * endTensorData.size())); + buffers[3] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast(strideTensorData.data()), + sizeof(int32_t) * strideTensorData.size())); + + std::array, 5> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(inputTensorShape.data(), + inputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("input")); + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(beginTensorShape.data(), + beginTensorShape.size()), + ::tflite::TensorType_INT32, + 1, + flatBufferBuilder.CreateString("begin_tensor")); + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(endTensorShape.data(), + endTensorShape.size()), + ::tflite::TensorType_INT32, + 2, + flatBufferBuilder.CreateString("end_tensor")); + tensors[3] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(strideTensorShape.data(), + strideTensorShape.size()), + ::tflite::TensorType_INT32, + 3, + flatBufferBuilder.CreateString("stride_tensor")); + tensors[4] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output")); + + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_StridedSliceOptions; + flatbuffers::Offset operatorBuiltinOptions = CreateStridedSliceOptions(flatBufferBuilder, + beginMask, + endMask, + ellipsisMask, + newAxisMask, + ShrinkAxisMask).Union(); + + const std::vector operatorInputs{ 0, 1, 2, 3 }; + const std::vector operatorOutputs{ 4 }; + flatbuffers::Offset sliceOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + const std::vector subgraphInputs{ 0, 1, 2, 3 }; + const std::vector subgraphOutputs{ 4 }; + flatbuffers::Offset subgraph = + CreateSubGraph(flatBufferBuilder, + flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), + flatBufferBuilder.CreateVector(subgraphInputs.data(), subgraphInputs.size()), + flatBufferBuilder.CreateVector(subgraphOutputs.data(), subgraphOutputs.size()), + flatBufferBuilder.CreateVector(&sliceOperator, 1)); + + flatbuffers::Offset modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: StridedSlice Operator Model"); + flatbuffers::Offset operatorCode = CreateOperatorCode(flatBufferBuilder, + BuiltinOperator_STRIDED_SLICE); + + flatbuffers::Offset flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&operatorCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); + + flatBufferBuilder.Finish(flatbufferModel); + + return std::vector(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); +} + +template +void StridedSliceTestImpl(std::vector& backends, + std::vector& inputValues, + std::vector& expectedOutputValues, + std::vector& beginTensorData, + std::vector& endTensorData, + std::vector& strideTensorData, + std::vector& inputTensorShape, + std::vector& beginTensorShape, + std::vector& endTensorShape, + std::vector& strideTensorShape, + std::vector& outputTensorShape, + const int32_t beginMask = 0, + const int32_t endMask = 0, + const int32_t ellipsisMask = 0, + const int32_t newAxisMask = 0, + const int32_t ShrinkAxisMask = 0, + const armnn::DataLayout& dataLayout = armnn::DataLayout::NHWC) +{ + using namespace tflite; + std::vector modelBuffer = CreateSliceTfLiteModel( + ::tflite::TensorType_FLOAT32, + inputTensorShape, + beginTensorData, + endTensorData, + strideTensorData, + beginTensorShape, + endTensorShape, + strideTensorShape, + outputTensorShape, + beginMask, + endMask, + ellipsisMask, + newAxisMask, + ShrinkAxisMask, + dataLayout); + + auto tfLiteModel = GetModel(modelBuffer.data()); + + // Create TfLite Interpreters + std::unique_ptr armnnDelegate; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&armnnDelegate) == kTfLiteOk); + CHECK(armnnDelegate != nullptr); + CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk); + + std::unique_ptr tfLiteDelegate; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&tfLiteDelegate) == kTfLiteOk); + CHECK(tfLiteDelegate != nullptr); + CHECK(tfLiteDelegate->AllocateTensors() == kTfLiteOk); + + // Create the ArmNN Delegate + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); + + // Modify armnnDelegateInterpreter to use armnnDelegate + CHECK(armnnDelegate->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); + + // Set input data + armnnDelegate::FillInput(tfLiteDelegate, 0, inputValues); + armnnDelegate::FillInput(armnnDelegate, 0, inputValues); + + // Run EnqueWorkload + CHECK(tfLiteDelegate->Invoke() == kTfLiteOk); + CHECK(armnnDelegate->Invoke() == kTfLiteOk); + + // Compare output data + armnnDelegate::CompareOutputData(tfLiteDelegate, + armnnDelegate, + outputTensorShape, + expectedOutputValues); + + tfLiteDelegate.reset(nullptr); + armnnDelegate.reset(nullptr); +} // End of StridedSlice Test + +} // anonymous namespace \ No newline at end of file -- cgit v1.2.1