diff options
Diffstat (limited to 'delegate')
-rw-r--r-- | delegate/CMakeLists.txt | 2 | ||||
-rw-r--r-- | delegate/src/Fill.hpp | 98 | ||||
-rw-r--r-- | delegate/src/test/FillTest.cpp | 221 | ||||
-rw-r--r-- | delegate/src/test/FillTestHelper.hpp | 160 | ||||
-rw-r--r-- | delegate/src/test/TestUtils.cpp | 9 | ||||
-rw-r--r-- | delegate/src/test/TestUtils.hpp | 3 |
6 files changed, 486 insertions, 7 deletions
diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt index 981fc9f0bf..5dbe83e014 100644 --- a/delegate/CMakeLists.txt +++ b/delegate/CMakeLists.txt @@ -131,6 +131,8 @@ if(BUILD_UNIT_TESTS) src/test/ElementwiseBinaryTestHelper.hpp src/test/ElementwiseUnaryTest.cpp src/test/ElementwiseUnaryTestHelper.hpp + src/test/FillTest.cpp + src/test/FillTestHelper.hpp src/test/FullyConnectedTest.cpp src/test/FullyConnectedTestHelper.hpp src/test/GatherTest.cpp diff --git a/delegate/src/Fill.hpp b/delegate/src/Fill.hpp index 99c3c625c2..c9fd159b3e 100644 --- a/delegate/src/Fill.hpp +++ b/delegate/src/Fill.hpp @@ -19,15 +19,99 @@ TfLiteStatus VisitFillOperator(DelegateData& delegateData, TfLiteContext* tfLiteContext, TfLiteNode* tfLiteNode, int nodeIndex, - int32_t operatorCode) + int32_t tfLiteFillOperatorCode) { - armnn::IgnoreUnused(delegateData, - tfLiteContext, - tfLiteNode, - nodeIndex, - operatorCode); + TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); - return kTfLiteError; + switch(tfLiteFillOperatorCode) + { + case kTfLiteBuiltinFill: + TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex)); + break; + default: + return kTfLiteError; + } + + const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; + const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteInputTensor, tfLiteFillOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const TfLiteTensor& tfLiteFillTensor = tfLiteTensors[tfLiteNode->inputs->data[1]]; + if (!IsValid(tfLiteContext, tfLiteFillTensor, tfLiteFillOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; + if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteFillOperatorCode, nodeIndex)) + { + return kTfLiteError; + } + + armnn::TensorInfo inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor); + const armnn::TensorInfo& fillTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteFillTensor); + const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); + + armnn::FillDescriptor descriptor; + switch (tfLiteFillTensor.type) + { + case kTfLiteFloat32: + descriptor.m_Value = tflite::GetTensorData<float>(&tfLiteFillTensor)[0]; + break; + case kTfLiteInt32: + descriptor.m_Value = tflite::GetTensorData<int32_t>(&tfLiteFillTensor)[0]; + break; + default: + TF_LITE_MAYBE_KERNEL_LOG( + tfLiteContext, + "TfLiteArmnnDelegate: FILL value data type is not supported in operator #%d node #%d: ", + tfLiteFillOperatorCode, nodeIndex); + return kTfLiteError; + } + + bool isSupported = false; + auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) + { + FORWARD_LAYER_SUPPORT_FUNC(__func__, + tfLiteContext, + IsFillSupported, + delegateData.m_Backends, + isSupported, + inputTensorInfo, + outInfo, + descriptor); + }; + + if (!delegateData.m_Network) + { + validateFunc(outputTensorInfo, isSupported); + return isSupported ? kTfLiteOk : kTfLiteError; + } + + armnn::IConnectableLayer* layer = delegateData.m_Network->AddFillLayer(descriptor); + ARMNN_ASSERT(layer != nullptr); + + armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); + outputSlot.SetTensorInfo(outputTensorInfo); + + if(tflite::IsConstantTensor(&tfLiteInputTensor)) + { + auto status = ConnectConstant(layer, + inputTensorInfo, + tfLiteContext, + tfLiteInputTensor, + delegateData, + tfLiteNode->inputs->data[0]); + if (status == kTfLiteError) + { + return status; + } + } + + return Connect(layer, tfLiteNode, delegateData); } } // namespace armnnDelegate diff --git a/delegate/src/test/FillTest.cpp b/delegate/src/test/FillTest.cpp new file mode 100644 index 0000000000..50f7f53d56 --- /dev/null +++ b/delegate/src/test/FillTest.cpp @@ -0,0 +1,221 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "FillTestHelper.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/schema/schema_generated.h> + +#include <doctest/doctest.h> + +namespace armnnDelegate +{ + +void Fill2dTest(std::vector<armnn::BackendId>& backends, + tflite::BuiltinOperator fillOperatorCode = tflite::BuiltinOperator_FILL, + float fill = 2.0f ) +{ + std::vector<int32_t> inputShape { 2 }; + std::vector<int32_t> tensorShape { 2, 2 }; + std::vector<float> expectedOutputValues = { fill, fill, + fill, fill }; + + FillTest<float>(fillOperatorCode, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + tensorShape, + expectedOutputValues, + fill); +} + +void Fill3dTest(std::vector<armnn::BackendId>& backends, + tflite::BuiltinOperator fillOperatorCode = tflite::BuiltinOperator_FILL, + float fill = 5.0f ) +{ + std::vector<int32_t> inputShape { 3 }; + std::vector<int32_t> tensorShape { 3, 3, 3 }; + std::vector<float> expectedOutputValues = { fill, fill, fill, + fill, fill, fill, + fill, fill, fill, + + fill, fill, fill, + fill, fill, fill, + fill, fill, fill, + + fill, fill, fill, + fill, fill, fill, + fill, fill, fill }; + + FillTest<float>(fillOperatorCode, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + tensorShape, + expectedOutputValues, + fill); +} + +void Fill4dTest(std::vector<armnn::BackendId>& backends, + tflite::BuiltinOperator fillOperatorCode = tflite::BuiltinOperator_FILL, + float fill = 3.0f ) +{ + std::vector<int32_t> inputShape { 4 }; + std::vector<int32_t> tensorShape { 2, 2, 4, 4 }; + std::vector<float> expectedOutputValues = { fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill, + fill, fill, fill, fill }; + + FillTest<float>(fillOperatorCode, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + tensorShape, + expectedOutputValues, + fill); +} + +void FillInt32Test(std::vector<armnn::BackendId>& backends, + tflite::BuiltinOperator fillOperatorCode = tflite::BuiltinOperator_FILL, + int32_t fill = 2 ) +{ + std::vector<int32_t> inputShape { 2 }; + std::vector<int32_t> tensorShape { 2, 2 }; + std::vector<int32_t> expectedOutputValues = { fill, fill, + fill, fill }; + + FillTest<int32_t>(fillOperatorCode, + ::tflite::TensorType_INT32, + backends, + inputShape, + tensorShape, + expectedOutputValues, + fill); +} + +TEST_SUITE("Fill_CpuRefTests") +{ + +TEST_CASE ("Fill2d_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + Fill2dTest(backends); +} + +TEST_CASE ("Fill3d_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill3d_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill4d_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + Fill4dTest(backends); +} + +TEST_CASE ("FillInt32_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + FillInt32Test(backends); +} + +} + +TEST_SUITE("Fill_CpuAccTests") +{ + +TEST_CASE ("Fill2d_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + Fill2dTest(backends); +} + +TEST_CASE ("Fill3d_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill3d_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill4d_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + Fill4dTest(backends); +} + +TEST_CASE ("FillInt32_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + FillInt32Test(backends); +} + +} + +TEST_SUITE("Fill_GpuAccTests") +{ + +TEST_CASE ("Fill2d_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + Fill2dTest(backends); +} + +TEST_CASE ("Fill3d_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill3d_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + Fill3dTest(backends); +} + +TEST_CASE ("Fill4d_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + Fill4dTest(backends); +} + +TEST_CASE ("FillInt32_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + FillInt32Test(backends); +} + +} + +} // namespace armnnDelegate
\ No newline at end of file diff --git a/delegate/src/test/FillTestHelper.hpp b/delegate/src/test/FillTestHelper.hpp new file mode 100644 index 0000000000..e6890a2b2d --- /dev/null +++ b/delegate/src/test/FillTestHelper.hpp @@ -0,0 +1,160 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TestUtils.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/interpreter.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/model.h> +#include <tensorflow/lite/schema/schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +namespace +{ + +template <typename T> +std::vector<char> CreateFillTfLiteModel(tflite::BuiltinOperator fillOperatorCode, + tflite::TensorType tensorType, + const std::vector<int32_t>& inputShape, + const std::vector <int32_t>& tensorShape, + const std::vector<T> fillValue) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector({}))); + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(tensorShape.data()), + sizeof(int32_t) * tensorShape.size()))); + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(fillValue.data()), + sizeof(T) * fillValue.size()))); + + std::array<flatbuffers::Offset<Tensor>, 3> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(inputShape.data(), + inputShape.size()), + tflite::TensorType_INT32, + 1, + flatBufferBuilder.CreateString("dims")); + + std::vector<int32_t> fillShape = {}; + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(fillShape.data(), + fillShape.size()), + tensorType, + 2, + flatBufferBuilder.CreateString("value")); + + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), + tensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output")); + + tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_FillOptions; + flatbuffers::Offset<void> operatorBuiltinOptions = CreateFillOptions(flatBufferBuilder).Union(); + + // create operator + const std::vector<int> operatorInputs{ {0, 1} }; + const std::vector<int> operatorOutputs{ 2 }; + flatbuffers::Offset <Operator> fillOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + const std::vector<int> subgraphInputs{ {0, 1} }; + const std::vector<int> subgraphOutputs{ 2 }; + flatbuffers::Offset <SubGraph> subgraph = + CreateSubGraph(flatBufferBuilder, + flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), + flatBufferBuilder.CreateVector(&fillOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Fill Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, + fillOperatorCode); + + flatbuffers::Offset <Model> 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<char>(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); + +} + +template <typename T> +void FillTest(tflite::BuiltinOperator fillOperatorCode, + tflite::TensorType tensorType, + const std::vector<armnn::BackendId>& backends, + std::vector<int32_t >& inputShape, + std::vector<int32_t >& tensorShape, + std::vector<T>& expectedOutputValues, + T fillValue) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateFillTfLiteModel<T>(fillOperatorCode, + tensorType, + inputShape, + tensorShape, + {fillValue}); + + const Model* tfLiteModel = GetModel(modelBuffer.data()); + CHECK(tfLiteModel != nullptr); + + std::unique_ptr<Interpreter> armnnDelegateInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&armnnDelegateInterpreter) == kTfLiteOk); + CHECK(armnnDelegateInterpreter != nullptr); + CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk); + + std::unique_ptr<Interpreter> tfLiteInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&tfLiteInterpreter) == kTfLiteOk); + CHECK(tfLiteInterpreter != nullptr); + CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); + + // Create the ArmNN Delegate + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); + // Modify armnnDelegateInterpreter to use armnnDelegate + CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); + + // Run EnqueueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + + armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, armnnDelegateInterpreter, tensorShape, expectedOutputValues); +} + +} // anonymous namespace diff --git a/delegate/src/test/TestUtils.cpp b/delegate/src/test/TestUtils.cpp index 1bc5786112..bbe89904eb 100644 --- a/delegate/src/test/TestUtils.cpp +++ b/delegate/src/test/TestUtils.cpp @@ -52,6 +52,15 @@ void CompareData(int16_t tensor1[], int16_t tensor2[], size_t tensorSize) } } +void CompareData(int32_t tensor1[], int32_t tensor2[], size_t tensorSize) +{ + int32_t tolerance = 1; + for (size_t i = 0; i < tensorSize; i++) + { + CHECK(std::max(tensor1[i], tensor2[i]) - std::min(tensor1[i], tensor2[i]) <= tolerance); + } +} + void CompareData(int8_t tensor1[], int8_t tensor2[], size_t tensorSize) { int8_t tolerance = 1; diff --git a/delegate/src/test/TestUtils.hpp b/delegate/src/test/TestUtils.hpp index d14e1edb45..8a2756f4c5 100644 --- a/delegate/src/test/TestUtils.hpp +++ b/delegate/src/test/TestUtils.hpp @@ -51,6 +51,9 @@ void CompareData(uint8_t tensor1[], uint8_t tensor2[], size_t tensorSize); /// Can be used to compare int16_t data coming from a tflite interpreter with a tolerance of 1 void CompareData(int16_t tensor1[], int16_t tensor2[], size_t tensorSize); +/// Can be used to compare int32_t data coming from a tflite interpreter with a tolerance of 1 +void CompareData(int32_t tensor1[], int32_t tensor2[], size_t tensorSize); + /// Can be used to compare Half (Float16) data with a tolerance of limit_of_float*100 void CompareData(Half tensor1[], Half tensor2[], size_t tensorSize); |