1 files changed, 59 insertions, 0 deletions
diff --git a/tests/InterfaceTests/ClassicDelegateTest.cpp b/tests/InterfaceTests/ClassicDelegateTest.cpp
new file mode 100644
index 0000000000..2146c70e8c
--- /dev/null
+++ b/tests/InterfaceTests/ClassicDelegateTest.cpp
@@ -0,0 +1,59 @@
+//
+// 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/c/c_api.h>
+#include <tensorflow/lite/interpreter.h>
+#include <tensorflow/lite/kernels/register.h>
+
+#include <string>
+
+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> tfLiteInterpreter;
+    tfLiteInterpreter = std::make_unique<tflite::Interpreter>();
+    tflite::ops::builtin::BuiltinOpResolver resolver;
+    tflite::InterpreterBuilder builder(*model, resolver);
+    if (builder(&tfLiteInterpreter) != kTfLiteOk)
+    {
+        std::cout << "Error loading the model into the TfLiteInterpreter." << std::endl;
+        return -1;
+    }
+
+    // Create the Armnn Delegate
+    // Populate a DelegateOptions from the ExecuteNetworkParams.
+    armnnDelegate::DelegateOptions delegateOptions(armnn::Compute::CpuRef);
+    std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> theArmnnDelegate(
+        armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), armnnDelegate::TfLiteArmnnDelegateDelete);
+    // Register armnn_delegate to TfLiteInterpreter
+    auto result = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(theArmnnDelegate));
+    if (result != kTfLiteOk)
+    {
+        std::cout << "Could not register ArmNN TfLite Delegate to TfLiteInterpreter." << std::endl;
+        return -1;
+    }
+    if (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 = tfLiteInterpreter->Invoke();
+    if (status != kTfLiteOk)
+    {
+        std::cout << "Inference failed." << std::endl;
+        return -1;
+    }
+}