IVGCVSW-7834 Add REVERSE_V2 to classic and opaque delegates

  * Adding support for ReverseV2 in the classic and opaque delegates
  * CMake files updated
  * Tests added
  * Gpu/Cpu Acc tests compiled out until functionality is written

Signed-off-by: Tracy Narine <tracy.narine@arm.com>
Change-Id: I8b41b7e71f2e28e5ea8dddbd00657900e6d7ab9a

2 files changed, 331 insertions, 0 deletions

diff --git a/delegate/test/ReverseV2Test.cpp b/delegate/test/ReverseV2Test.cpp
new file mode 100644
index 0000000000..b261474e99
--- /dev/null
+++ b/delegate/test/ReverseV2Test.cpp
@@ -0,0 +1,183 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ReverseV2TestHelper.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 <schema_generated.h>
+#include <tensorflow/lite/version.h>
+
+#include <doctest/doctest.h>
+
+namespace armnnDelegate
+{
+
+    void ReverseV2Float32Test(std::vector<armnn::BackendId>& backends)
+    {
+        // Set input data
+        std::vector<float> inputValues =
+        {
+            1.0f, 2.0f, 3.0f,
+            4.0f, 5.0f, 6.0f,
+            7.0f, 8.0f, 9.0f,
+
+            11.0f, 12.0f, 13.0f,
+            14.0f, 15.0f, 16.0f,
+            17.0f, 18.0f, 19.0f,
+
+            21.0f, 22.0f, 23.0f,
+            24.0f, 25.0f, 26.0f,
+            27.0f, 28.0f, 29.0f
+        };
+
+        // The output data
+        std::vector<float> expectedOutputValues =
+        {
+            3.0f, 2.0f, 1.0f,
+            6.0f, 5.0f, 4.0f,
+            9.0f, 8.0f, 7.0f,
+
+            13.0f, 12.0f, 11.0f,
+            16.0f, 15.0f, 14.0f,
+            19.0f, 18.0f, 17.0f,
+
+            23.0f, 22.0f, 21.0f,
+            26.0f, 25.0f, 24.0f,
+            29.0f, 28.0f, 27.0f
+        };
+
+        // The axis to reverse
+        const std::vector<int32_t> axisValues = {2};
+
+        // Shapes
+        const std::vector<int32_t> inputShape = {3, 3, 3};
+        const std::vector<int32_t> axisShapeDims = {1};
+        const std::vector<int32_t> expectedOutputShape = {3, 3, 3};
+
+        ReverseV2FP32TestImpl(tflite::BuiltinOperator_REVERSE_V2,
+                              backends,
+                              inputValues,
+                              inputShape,
+                              axisValues,
+                              axisShapeDims,
+                              expectedOutputValues,
+                              expectedOutputShape);
+    }
+
+    void ReverseV2NegativeAxisFloat32Test(std::vector<armnn::BackendId>& backends)
+    {
+        // Set input data
+        std::vector<float> inputValues =
+        {
+            1.0f, 2.0f, 3.0f,
+            4.0f, 5.0f, 6.0f,
+            7.0f, 8.0f, 9.0f,
+
+            11.0f, 12.0f, 13.0f,
+            14.0f, 15.0f, 16.0f,
+            17.0f, 18.0f, 19.0f,
+
+            21.0f, 22.0f, 23.0f,
+            24.0f, 25.0f, 26.0f,
+            27.0f, 28.0f, 29.0f
+        };
+
+        // The output data
+        std::vector<float> expectedOutputValues =
+        {
+            7.0f, 8.0f, 9.0f,
+            4.0f, 5.0f, 6.0f,
+            1.0f, 2.0f, 3.0f,
+
+            17.0f, 18.0f, 19.0f,
+            14.0f, 15.0f, 16.0f,
+            11.0f, 12.0f, 13.0f,
+
+            27.0f, 28.0f, 29.0f,
+            24.0f, 25.0f, 26.0f,
+            21.0f, 22.0f, 23.0f
+        };
+
+        // The axis to reverse
+        const std::vector<int32_t> axisValues = {-2};
+
+        // Shapes
+        const std::vector<int32_t> inputShape = {3, 3, 3};
+        const std::vector<int32_t> axisShapeDims = {1};
+        const std::vector<int32_t> expectedOutputShape = {3, 3, 3};
+
+        ReverseV2FP32TestImpl(tflite::BuiltinOperator_REVERSE_V2,
+                              backends,
+                              inputValues,
+                              inputShape,
+                              axisValues,
+                              axisShapeDims,
+                              expectedOutputValues,
+                              expectedOutputShape);
+    }
+
+#if defined(REVERSEV2_GPUACC)
+    TEST_SUITE("ReverseV2Tests_GpuAccTests")
+    {
+
+        TEST_CASE ("ReverseV2_Float32_GpuAcc_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
+            ReverseV2Float32Test(backends);
+        }
+
+        TEST_CASE ("ReverseV2_NegativeAxis_Float32_GpuAcc_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
+            ReverseV2NegativeAxisFloat32Test(backends);
+        }
+
+    } // TEST_SUITE("ReverseV2Tests_GpuAccTests")
+#endif
+
+
+#if defined(REVERSEV2_CPUACC)
+    TEST_SUITE("ReverseV2Tests_CpuAccTests")
+    {
+
+        TEST_CASE ("ReverseV2_Float32_CpuAcc_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
+            ReverseV2Float32Test(backends);
+        }
+
+        TEST_CASE ("ReverseV2_NegativeAxis_Float32_CpuAcc_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
+            ReverseV2NegativeAxisFloat32Test(backends);
+        }
+
+    } // TEST_SUITE("ReverseV2Tests_CpuAccTests")
+#endif
+
+
+    TEST_SUITE("ReverseV2Tests_CpuRefTests")
+    {
+
+        TEST_CASE ("ReverseV2_Float32_CpuRef_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+            ReverseV2Float32Test(backends);
+        }
+
+        TEST_CASE ("ReverseV2_NegativeAxis_Float32_CpuRef_Test")
+        {
+            std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+            ReverseV2NegativeAxisFloat32Test(backends);
+        }
+
+    } // TEST_SUITE("ReverseV2Tests_CpuRefTests")
+
+} // namespace armnnDelegate
diff --git a/delegate/test/ReverseV2TestHelper.hpp b/delegate/test/ReverseV2TestHelper.hpp
new file mode 100644
index 0000000000..8c4acd1a7e
--- /dev/null
+++ b/delegate/test/ReverseV2TestHelper.hpp
@@ -0,0 +1,148 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "TestUtils.hpp"
+
+#include <armnn_delegate.hpp>
+#include <DelegateTestInterpreter.hpp>
+
+#include <flatbuffers/flatbuffers.h>
+#include <tensorflow/lite/kernels/register.h>
+#include <tensorflow/lite/version.h>
+
+#include <schema_generated.h>
+
+#include <doctest/doctest.h>
+
+namespace
+{
+    std::vector<char> CreateReverseV2TfLiteModel(tflite::BuiltinOperator operatorCode,
+                                                 tflite::TensorType inputTensorType,
+                                                 const std::vector <int32_t>& inputTensorShape,
+                                                 const std::vector <int32_t>& axisTensorData,
+                                                 const std::vector <int32_t>& axisTensorShape,
+                                                 const std::vector <int32_t>& outputTensorShape)
+    {
+        using namespace tflite;
+        flatbuffers::FlatBufferBuilder flatBufferBuilder;
+
+        std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
+        buffers.push_back(CreateBuffer(flatBufferBuilder));
+        buffers.push_back(CreateBuffer(flatBufferBuilder));
+        buffers.push_back(CreateBuffer(flatBufferBuilder,
+                                       flatBufferBuilder.CreateVector(
+                                               reinterpret_cast<const uint8_t*>(axisTensorData.data()),
+                                               sizeof(int32_t) * axisTensorData.size())));
+        buffers.push_back(CreateBuffer(flatBufferBuilder));
+
+        std::array<flatbuffers::Offset<Tensor>, 3> tensors;
+        tensors[0] = CreateTensor(flatBufferBuilder,
+                                  flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
+                                                                          inputTensorShape.size()),
+                                  inputTensorType,
+                                  1,
+                                  flatBufferBuilder.CreateString("input_tensor"));
+
+        tensors[1] = CreateTensor(flatBufferBuilder,
+                                  flatBufferBuilder.CreateVector<int32_t>(axisTensorShape.data(),
+                                                                          axisTensorShape.size()),
+                                  TensorType_INT32,
+                                  2,
+                                  flatBufferBuilder.CreateString("axis_input_tensor"));
+
+        tensors[2] = CreateTensor(flatBufferBuilder,
+                                  flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+                                                                          outputTensorShape.size()),
+                                  inputTensorType,
+                                  3,
+                                  flatBufferBuilder.CreateString("output_tensor"));
+
+        // Create Operator
+        tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE;
+        flatbuffers::Offset<void> operatorBuiltinOption = 0;
+
+        const std::vector<int> operatorInputs{0, 1};
+        const std::vector<int> operatorOutputs{2};
+        flatbuffers::Offset <Operator> reverseV2Operator =
+                CreateOperator(flatBufferBuilder,
+                               0,
+                               flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+                               flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+                               operatorBuiltinOptionsType,
+                               operatorBuiltinOption);
+
+        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(&reverseV2Operator, 1));
+
+        flatbuffers::Offset <flatbuffers::String> modelDescription =
+                flatBufferBuilder.CreateString("ArmnnDelegate: ReverseV2 Operator Model");
+        flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, operatorCode);
+
+        flatbuffers::Offset <Model> flatbufferModel =
+                CreateModel(flatBufferBuilder,
+                            TFLITE_SCHEMA_VERSION,
+                            flatBufferBuilder.CreateVector(&opCode, 1),
+                            flatBufferBuilder.CreateVector(&subgraph, 1),
+                            modelDescription,
+                            flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
+
+        flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
+
+        return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
+                                 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
+    }
+
+    void ReverseV2FP32TestImpl(tflite::BuiltinOperator operatorCode,
+                               std::vector<armnn::BackendId>& backends,
+                               std::vector<float>& inputValues,
+                               std::vector<int32_t> inputShape,
+                               std::vector<int32_t> axisValues,
+                               std::vector<int32_t> axisShapeDims,
+                               std::vector<float>& expectedOutputValues,
+                               std::vector<int32_t> expectedOutputShape)
+    {
+        using namespace delegateTestInterpreter;
+
+        std::vector<char> modelBuffer = CreateReverseV2TfLiteModel(operatorCode,
+                                                                   ::tflite::TensorType_FLOAT32,
+                                                                   inputShape,
+                                                                   axisValues,
+                                                                   axisShapeDims,
+                                                                   expectedOutputShape);
+
+        // Setup interpreter with just TFLite Runtime.
+        auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+        CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+        CHECK(tfLiteInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
+        CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(axisValues, 1) == kTfLiteOk);
+        CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
+        std::vector<float>   tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0);
+        std::vector<int32_t> tfLiteOutputShape  = tfLiteInterpreter.GetOutputShape(0);
+
+        // Setup interpreter with Arm NN Delegate applied.
+        auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
+        CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
+        CHECK(armnnInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
+        CHECK(armnnInterpreter.FillInputTensor<int32_t>(axisValues, 1) == kTfLiteOk);
+        CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
+        std::vector<float>   armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0);
+        std::vector<int32_t> armnnOutputShape  = armnnInterpreter.GetOutputShape(0);
+
+        armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
+        armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
+
+        tfLiteInterpreter.Cleanup();
+        armnnInterpreter.Cleanup();
+    }
+
+} // anonymous namespace