IVGCVSW-6858 Add GATHERNd Support to the TfLite Delegate
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I56418875b3bb2ae45b5c69bfeaafa1a6126b8085
diff --git a/delegate/src/test/GatherNdTestHelper.hpp b/delegate/src/test/GatherNdTestHelper.hpp
new file mode 100644
index 0000000..f475584
--- /dev/null
+++ b/delegate/src/test/GatherNdTestHelper.hpp
@@ -0,0 +1,178 @@
+//
+// Copyright © 2022 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> CreateGatherNdTfLiteModel(tflite::TensorType tensorType,
+ std::vector<int32_t>& paramsShape,
+ std::vector<int32_t>& indicesShape,
+ const std::vector<int32_t>& expectedOutputShape,
+ float quantScale = 1.0f,
+ int quantOffset = 0)
+{
+ using namespace tflite;
+ flatbuffers::FlatBufferBuilder flatBufferBuilder;
+
+ std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
+ buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})));
+
+ auto quantizationParameters =
+ CreateQuantizationParameters(flatBufferBuilder,
+ 0,
+ 0,
+ flatBufferBuilder.CreateVector<float>({quantScale}),
+ flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
+
+ std::array<flatbuffers::Offset<Tensor>, 3> tensors;
+ tensors[0] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(paramsShape.data(),
+ paramsShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("params"),
+ quantizationParameters);
+ tensors[1] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(),
+ indicesShape.size()),
+ ::tflite::TensorType_INT32,
+ 0,
+ flatBufferBuilder.CreateString("indices"),
+ quantizationParameters);
+ tensors[2] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(),
+ expectedOutputShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("output"),
+ quantizationParameters);
+
+
+ // create operator
+ tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherNdOptions;
+ flatbuffers::Offset<void> operatorBuiltinOptions = CreateGatherNdOptions(flatBufferBuilder).Union();
+
+ const std::vector<int> operatorInputs{{0, 1}};
+ const std::vector<int> operatorOutputs{2};
+ flatbuffers::Offset<Operator> controlOperator =
+ 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(&controlOperator, 1));
+
+ flatbuffers::Offset<flatbuffers::String> modelDescription =
+ flatBufferBuilder.CreateString("ArmnnDelegate: GATHER_ND Operator Model");
+ flatbuffers::Offset<OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
+ BuiltinOperator_GATHER_ND);
+
+ 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 GatherNdTest(tflite::TensorType tensorType,
+ std::vector<armnn::BackendId>& backends,
+ std::vector<int32_t>& paramsShape,
+ std::vector<int32_t>& indicesShape,
+ std::vector<int32_t>& expectedOutputShape,
+ std::vector<T>& paramsValues,
+ std::vector<int32_t>& indicesValues,
+ std::vector<T>& expectedOutputValues,
+ float quantScale = 1.0f,
+ int quantOffset = 0)
+{
+ using namespace tflite;
+ std::vector<char> modelBuffer = CreateGatherNdTfLiteModel(tensorType,
+ paramsShape,
+ indicesShape,
+ expectedOutputShape,
+ quantScale,
+ quantOffset);
+ const Model* 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, paramsValues);
+ armnnDelegate::FillInput<T>(armnnDelegate, 0, paramsValues);
+ armnnDelegate::FillInput<int32_t>(tfLiteDelegate, 1, indicesValues);
+ armnnDelegate::FillInput<int32_t>(armnnDelegate, 1, indicesValues);
+
+ // Run EnqueWorkload
+ CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
+ CHECK(armnnDelegate->Invoke() == kTfLiteOk);
+
+ // Compare output data
+ armnnDelegate::CompareOutputData<T>(tfLiteDelegate,
+ armnnDelegate,
+ expectedOutputShape,
+ expectedOutputValues,
+ 0);
+
+ tfLiteDelegate.reset(nullptr);
+ armnnDelegate.reset(nullptr);
+}
+} // anonymous namespace
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