From a7a12f5c3654da554ad6197beff0f0fc54681c92 Mon Sep 17 00:00:00 2001
From: Matthew Sloyan <matthew.sloyan@arm.com>
Date: Thu, 6 May 2021 10:05:28 +0100
Subject: IVGCVSW-5969 TfLiteDelegate: Add PACK operator Support

 * Added support for PACK which is equivalent to Arm NN STACK

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I9ea134d0310eeea1caba30a8b9221712e9487c75
---
 delegate/src/test/PackTestHelper.hpp | 185 +++++++++++++++++++++++++++++++++++
 1 file changed, 185 insertions(+)
 create mode 100644 delegate/src/test/PackTestHelper.hpp

(limited to 'delegate/src/test/PackTestHelper.hpp')

diff --git a/delegate/src/test/PackTestHelper.hpp b/delegate/src/test/PackTestHelper.hpp
new file mode 100644
index 0000000000..0869228326
--- /dev/null
+++ b/delegate/src/test/PackTestHelper.hpp
@@ -0,0 +1,185 @@
+//
+// 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>
+
+#include <string>
+
+namespace
+{
+
+std::vector<char> CreatePackTfLiteModel(tflite::BuiltinOperator packOperatorCode,
+                                        tflite::TensorType tensorType,
+                                        std::vector<int32_t>& inputTensorShape,
+                                        const std::vector <int32_t>& outputTensorShape,
+                                        const int32_t inputTensorNum,
+                                        unsigned int axis = 0,
+                                        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::vector<int32_t> operatorInputs{};
+    const std::vector<int32_t> operatorOutputs{inputTensorNum};
+    std::vector<int> subgraphInputs{};
+    const std::vector<int> subgraphOutputs{inputTensorNum};
+
+    std::vector<flatbuffers::Offset<Tensor>> tensors(inputTensorNum + 1);
+    for (int i = 0; i < inputTensorNum; ++i)
+    {
+        tensors[i] = CreateTensor(flatBufferBuilder,
+                                  flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
+                                                                          inputTensorShape.size()),
+                                  tensorType,
+                                  0,
+                                  flatBufferBuilder.CreateString("input" + std::to_string(i)),
+                                  quantizationParameters);
+
+        // Add number of inputs to vector.
+        operatorInputs.push_back(i);
+        subgraphInputs.push_back(i);
+    }
+
+    // Create output tensor
+    tensors[inputTensorNum] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+                                                                      outputTensorShape.size()),
+                              tensorType,
+                              0,
+                              flatBufferBuilder.CreateString("output"),
+                              quantizationParameters);
+
+    // create operator
+    tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_PackOptions;
+    flatbuffers::Offset<void> operatorBuiltinOptions =
+            CreatePackOptions(flatBufferBuilder, inputTensorNum, axis).Union();
+
+    flatbuffers::Offset <Operator> packOperator =
+            CreateOperator(flatBufferBuilder,
+                           0,
+                           flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+                           flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+                           operatorBuiltinOptionsType,
+                           operatorBuiltinOptions);
+
+    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(&packOperator, 1));
+
+    flatbuffers::Offset <flatbuffers::String> modelDescription =
+            flatBufferBuilder.CreateString("ArmnnDelegate: Pack Operator Model");
+    flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, packOperatorCode);
+
+    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 PackTest(tflite::BuiltinOperator packOperatorCode,
+              tflite::TensorType tensorType,
+              std::vector<armnn::BackendId>& backends,
+              std::vector<int32_t>& inputShape,
+              std::vector<int32_t>& expectedOutputShape,
+              std::vector<std::vector<T>>& inputValues,
+              std::vector<T>& expectedOutputValues,
+              unsigned int axis = 0,
+              float quantScale = 1.0f,
+              int quantOffset  = 0)
+{
+    using namespace tflite;
+    std::vector<char> modelBuffer = CreatePackTfLiteModel(packOperatorCode,
+                                                          tensorType,
+                                                          inputShape,
+                                                          expectedOutputShape,
+                                                          inputValues.size(),
+                                                          axis,
+                                                          quantScale,
+                                                          quantOffset);
+
+    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 for all input tensors.
+    for (unsigned int i = 0; i < inputValues.size(); ++i)
+    {
+        // Get single input tensor and assign to interpreters.
+        auto inputTensorValues = inputValues[i];
+        armnnDelegate::FillInput<T>(tfLiteInterpreter, i, inputTensorValues);
+        armnnDelegate::FillInput<T>(armnnDelegateInterpreter, i, inputTensorValues);
+    }
+
+    // Run EnqueWorkload
+    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
+    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
+
+    // Compare output data
+    armnnDelegate::CompareOutputData<T>(tfLiteInterpreter,
+                                        armnnDelegateInterpreter,
+                                        expectedOutputShape,
+                                        expectedOutputValues);
+
+    armnnDelegateInterpreter.reset(nullptr);
+}
+
+} // anonymous namespace
\ No newline at end of file
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