From 0aef653469eebbdf88308b7fbc6bb78452d380d0 Mon Sep 17 00:00:00 2001
From: Colm Donelan <colm.donelan@arm.com>
Date: Mon, 2 Oct 2023 17:01:37 +0100
Subject: IVGCVSW-7731 Add a test executables that verify released header
 files.

Create a CMake project with executables to exercise the external
interfaces of Arm NN.

Signed-off-by: Colm Donelan <colm.donelan@arm.com>
Change-Id: I1e3a8ed726903aac5f52d78c55d2e1b1352c8362
---
 tests/InterfaceTests/OpaqueDelegateTest.cpp | 67 +++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 tests/InterfaceTests/OpaqueDelegateTest.cpp

(limited to 'tests/InterfaceTests/OpaqueDelegateTest.cpp')

diff --git a/tests/InterfaceTests/OpaqueDelegateTest.cpp b/tests/InterfaceTests/OpaqueDelegateTest.cpp
new file mode 100644
index 0000000000..240a295393
--- /dev/null
+++ b/tests/InterfaceTests/OpaqueDelegateTest.cpp
@@ -0,0 +1,67 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <armnn_delegate.hpp>
+
+#include <tensorflow/lite/c/common.h>
+#include <tensorflow/lite/core/model.h>
+#include <tensorflow/lite/interpreter.h>
+#include <tensorflow/lite/kernels/register.h>
+
+int main()
+{
+    std::unique_ptr<tflite::FlatBufferModel> model;
+    model = tflite::FlatBufferModel::BuildFromFile("./simple_conv2d_1_op.tflite");
+    if (!model)
+    {
+        std::cout << "Failed to load TfLite model from: ./simple_conv2d_1_op.tflite" << std::endl;
+        return -1;
+    }
+    std::unique_ptr<tflite::Interpreter> m_TfLiteInterpreter;
+    m_TfLiteInterpreter = std::make_unique<tflite::Interpreter>();
+    tflite::ops::builtin::BuiltinOpResolver resolver;
+    tflite::InterpreterBuilder builder(*model, resolver);
+    if (builder(&m_TfLiteInterpreter) != kTfLiteOk)
+    {
+        std::cout << "Error loading the model into the TfLiteInterpreter." << std::endl;
+        return -1;
+    }
+    // Use default settings until options have been enabled
+    flatbuffers::FlatBufferBuilder flatBufferBuilder;
+    tflite::TFLiteSettingsBuilder tfliteSettingsBuilder(flatBufferBuilder);
+    flatbuffers::Offset<tflite::TFLiteSettings> tfliteSettings = tfliteSettingsBuilder.Finish();
+    flatBufferBuilder.Finish(tfliteSettings);
+    const tflite::TFLiteSettings* settings =
+        flatbuffers::GetRoot<tflite::TFLiteSettings>(flatBufferBuilder.GetBufferPointer());
+
+    std::unique_ptr<tflite::delegates::DelegatePluginInterface> delegatePlugIn =
+        tflite::delegates::DelegatePluginRegistry::CreateByName("armnn_delegate", *settings);
+
+    // Create Armnn Opaque Delegate from Armnn Delegate Plugin
+    tflite::delegates::TfLiteDelegatePtr armnnDelegate = delegatePlugIn->Create();
+
+    // Add Delegate to the builder
+    builder.AddDelegate(armnnDelegate.get());
+    if (builder(&m_TfLiteInterpreter) != kTfLiteOk)
+    {
+        std::cout << "Unable to add the Arm NN delegate to the TfLite runtime." << std::endl;
+        return -1;
+    }
+
+    if (m_TfLiteInterpreter->AllocateTensors() != kTfLiteOk)
+    {
+        std::cout << "Failed to allocate tensors in the TfLiteInterpreter." << std::endl;
+        return -1;
+    }
+
+    // Really should populate the tensors here, but it'll work without it.
+
+    int status = m_TfLiteInterpreter->Invoke();
+    if (status != kTfLiteOk)
+    {
+        std::cout << "Inference failed." << std::endl;
+        return -1;
+    }
+}
-- 
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