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-rw-r--r--delegate/src/test/SliceTestHelper.hpp241
1 files changed, 241 insertions, 0 deletions
diff --git a/delegate/src/test/SliceTestHelper.hpp b/delegate/src/test/SliceTestHelper.hpp
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+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "TestUtils.hpp"
+
+#include <armnn_delegate.hpp>
+#include <armnn/DescriptorsFwd.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>
+
+#include <string>
+
+namespace
+{
+
+struct StridedSliceParams
+{
+ StridedSliceParams(std::vector<int32_t>& inputTensorShape,
+ std::vector<int32_t>& beginTensorData,
+ std::vector<int32_t>& endTensorData,
+ std::vector<int32_t>& strideTensorData,
+ std::vector<int32_t>& outputTensorShape,
+ armnn::StridedSliceDescriptor& descriptor)
+ : m_InputTensorShape(inputTensorShape),
+ m_BeginTensorData(beginTensorData),
+ m_EndTensorData(endTensorData),
+ m_StrideTensorData(strideTensorData),
+ m_OutputTensorShape(outputTensorShape),
+ m_Descriptor (descriptor) {}
+
+ std::vector<int32_t> m_InputTensorShape;
+ std::vector<int32_t> m_BeginTensorData;
+ std::vector<int32_t> m_EndTensorData;
+ std::vector<int32_t> m_StrideTensorData;
+ std::vector<int32_t> m_OutputTensorShape;
+ armnn::StridedSliceDescriptor m_Descriptor;
+};
+
+std::vector<char> CreateSliceTfLiteModel(tflite::TensorType tensorType,
+ const std::vector<int32_t>& inputTensorShape,
+ const std::vector<int32_t>& beginTensorData,
+ const std::vector<int32_t>& endTensorData,
+ const std::vector<int32_t>& strideTensorData,
+ const std::vector<int32_t>& beginTensorShape,
+ const std::vector<int32_t>& endTensorShape,
+ const std::vector<int32_t>& strideTensorShape,
+ const std::vector<int32_t>& 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<flatbuffers::Offset<tflite::Buffer>, 4> buffers;
+ buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
+ buffers[1] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(beginTensorData.data()),
+ sizeof(int32_t) * beginTensorData.size()));
+ buffers[2] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(endTensorData.data()),
+ sizeof(int32_t) * endTensorData.size()));
+ buffers[3] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(strideTensorData.data()),
+ sizeof(int32_t) * strideTensorData.size()));
+
+ std::array<flatbuffers::Offset<Tensor>, 5> tensors;
+ tensors[0] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
+ inputTensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("input"));
+ tensors[1] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(beginTensorShape.data(),
+ beginTensorShape.size()),
+ ::tflite::TensorType_INT32,
+ 1,
+ flatBufferBuilder.CreateString("begin_tensor"));
+ tensors[2] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(endTensorShape.data(),
+ endTensorShape.size()),
+ ::tflite::TensorType_INT32,
+ 2,
+ flatBufferBuilder.CreateString("end_tensor"));
+ tensors[3] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(strideTensorShape.data(),
+ strideTensorShape.size()),
+ ::tflite::TensorType_INT32,
+ 3,
+ flatBufferBuilder.CreateString("stride_tensor"));
+ tensors[4] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+ outputTensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("output"));
+
+
+ // create operator
+ tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_StridedSliceOptions;
+ flatbuffers::Offset<void> operatorBuiltinOptions = CreateStridedSliceOptions(flatBufferBuilder,
+ beginMask,
+ endMask,
+ ellipsisMask,
+ newAxisMask,
+ ShrinkAxisMask).Union();
+
+ const std::vector<int> operatorInputs{ 0, 1, 2, 3 };
+ const std::vector<int> operatorOutputs{ 4 };
+ flatbuffers::Offset <Operator> sliceOperator =
+ 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, 2, 3 };
+ const std::vector<int> subgraphOutputs{ 4 };
+ 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(&sliceOperator, 1));
+
+ flatbuffers::Offset <flatbuffers::String> modelDescription =
+ flatBufferBuilder.CreateString("ArmnnDelegate: StridedSlice Operator Model");
+ flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
+ BuiltinOperator_STRIDED_SLICE);
+
+ 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 StridedSliceTestImpl(std::vector<armnn::BackendId>& backends,
+ std::vector<T>& inputValues,
+ std::vector<T>& expectedOutputValues,
+ std::vector<int32_t>& beginTensorData,
+ std::vector<int32_t>& endTensorData,
+ std::vector<int32_t>& strideTensorData,
+ std::vector<int32_t>& inputTensorShape,
+ std::vector<int32_t>& beginTensorShape,
+ std::vector<int32_t>& endTensorShape,
+ std::vector<int32_t>& strideTensorShape,
+ std::vector<int32_t>& 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<char> 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<Interpreter> armnnDelegate;
+ CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+ (&armnnDelegate) == kTfLiteOk);
+ CHECK(armnnDelegate != nullptr);
+ CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
+
+ std::unique_ptr<Interpreter> 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<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
+ 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<T>(tfLiteDelegate, 0, inputValues);
+ armnnDelegate::FillInput<T>(armnnDelegate, 0, inputValues);
+
+ // Run EnqueWorkload
+ CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
+ CHECK(armnnDelegate->Invoke() == kTfLiteOk);
+
+ // Compare output data
+ armnnDelegate::CompareOutputData<T>(tfLiteDelegate,
+ armnnDelegate,
+ outputTensorShape,
+ expectedOutputValues);
+
+ tfLiteDelegate.reset(nullptr);
+ armnnDelegate.reset(nullptr);
+} // End of StridedSlice Test
+
+} // anonymous namespace \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-18 14:44:30 +0000