1 files changed, 166 insertions, 0 deletions
diff --git a/delegate/src/test/SpaceDepthTestHelper.hpp b/delegate/src/test/SpaceDepthTestHelper.hpp
new file mode 100644
index 0000000000..d9a783c6a7
--- /dev/null
+++ b/delegate/src/test/SpaceDepthTestHelper.hpp
@@ -0,0 +1,166 @@
+//
+// 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
+{
+std::vector<char> CreateSpaceDepthTfLiteModel(tflite::BuiltinOperator spaceDepthOperatorCode,
+                                              tflite::TensorType tensorType,
+                                              const std::vector <int32_t>& inputTensorShape,
+                                              const std::vector <int32_t>& outputTensorShape,
+                                              int32_t blockSize)
+{
+    using namespace tflite;
+    flatbuffers::FlatBufferBuilder flatBufferBuilder;
+
+    auto quantizationParameters =
+        CreateQuantizationParameters(flatBufferBuilder,
+                                     0,
+                                     0,
+                                     flatBufferBuilder.CreateVector<float>({  1.0f }),
+                                     flatBufferBuilder.CreateVector<int64_t>({ 0 }));
+
+    std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
+    buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})));
+
+    std::array<flatbuffers::Offset<Tensor>, 2> tensors;
+    tensors[0] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
+                                                                      inputTensorShape.size()),
+                              tensorType,
+                              0,
+                              flatBufferBuilder.CreateString("input"),
+                              quantizationParameters);
+    tensors[1] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+                                                                      outputTensorShape.size()),
+                              tensorType,
+                              0,
+                              flatBufferBuilder.CreateString("output"),
+                              quantizationParameters);
+
+    const std::vector<int32_t> operatorInputs({0});
+    const std::vector<int32_t> operatorOutputs({1});
+
+    flatbuffers::Offset<Operator> spaceDepthOperator;
+    flatbuffers::Offset<flatbuffers::String> modelDescription;
+    flatbuffers::Offset<OperatorCode> operatorCode;
+
+    switch (spaceDepthOperatorCode)
+    {
+        case tflite::BuiltinOperator_SPACE_TO_DEPTH:
+            spaceDepthOperator =
+                CreateOperator(flatBufferBuilder,
+                               0,
+                               flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+                               flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+                               BuiltinOptions_SpaceToDepthOptions,
+                               CreateSpaceToDepthOptions(flatBufferBuilder, blockSize).Union());
+                modelDescription = flatBufferBuilder.CreateString("ArmnnDelegate: SPACE_TO_DEPTH Operator Model");
+                operatorCode = CreateOperatorCode(flatBufferBuilder,
+                                 tflite::BuiltinOperator_SPACE_TO_DEPTH);
+            break;
+        case tflite::BuiltinOperator_DEPTH_TO_SPACE:
+            spaceDepthOperator =
+                CreateOperator(flatBufferBuilder,
+                               0,
+                               flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+                               flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+                               BuiltinOptions_DepthToSpaceOptions,
+                               CreateDepthToSpaceOptions(flatBufferBuilder, blockSize).Union());
+                flatBufferBuilder.CreateString("ArmnnDelegate: DEPTH_TO_SPACE Operator Model");
+            operatorCode = CreateOperatorCode(flatBufferBuilder,
+                                              tflite::BuiltinOperator_DEPTH_TO_SPACE);
+            break;
+        default:
+            break;
+    }
+    const std::vector<int32_t> subgraphInputs({0});
+    const std::vector<int32_t> subgraphOutputs({1});
+    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(&spaceDepthOperator, 1));
+    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 SpaceDepthTest(tflite::BuiltinOperator spaceDepthOperatorCode,
+                    tflite::TensorType tensorType,
+                    std::vector<armnn::BackendId>& backends,
+                    std::vector<int32_t>& inputShape,
+                    std::vector<int32_t>& outputShape,
+                    std::vector<T>& inputValues,
+                    std::vector<T>& expectedOutputValues,
+                    int32_t blockSize = 2)
+{
+    using namespace tflite;
+    std::vector<char> modelBuffer = CreateSpaceDepthTfLiteModel(spaceDepthOperatorCode,
+                                                                tensorType,
+                                                                inputShape,
+                                                                outputShape,
+                                                                blockSize);
+
+    const Model* tfLiteModel = GetModel(modelBuffer.data());
+    // Create TfLite Interpreters
+    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);
+
+    // Set input data
+    armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, inputValues);
+    armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, inputValues);
+
+    // Run EnqueWorkload
+    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
+    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
+
+    // Compare output data
+    armnnDelegate::CompareOutputData(tfLiteInterpreter, armnnDelegateInterpreter, outputShape, expectedOutputValues);
+}
+
+} // anonymous namespace