1 files changed, 28 insertions, 58 deletions

diff --git a/delegate/test/SoftmaxTestHelper.hpp b/delegate/test/SoftmaxTestHelper.hpp
index 15177b7088..ffd02abdf7 100644
--- a/delegate/test/SoftmaxTestHelper.hpp
+++ b/delegate/test/SoftmaxTestHelper.hpp
@@ -5,16 +5,18 @@
 
 #pragma once
 
+#include "TestUtils.hpp"
+
 #include <armnn_delegate.hpp>
+#include <DelegateTestInterpreter.hpp>
 #include <armnnUtils/FloatingPointComparison.hpp>
 
 #include <flatbuffers/flatbuffers.h>
-#include <tensorflow/lite/interpreter.h>
 #include <tensorflow/lite/kernels/register.h>
-#include <tensorflow/lite/model.h>
-#include <schema_generated.h>
 #include <tensorflow/lite/version.h>
 
+#include <schema_generated.h>
+
 #include <doctest/doctest.h>
 
 namespace
@@ -95,7 +97,7 @@ std::vector<char> CreateSoftmaxTfLiteModel(tflite::BuiltinOperator softmaxOperat
                     flatBufferBuilder.CreateVector(&subgraph, 1),
                     modelDescription,
                     flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
-    flatBufferBuilder.Finish(flatbufferModel);
+    flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
     return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
                              flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
 }
@@ -108,65 +110,33 @@ void SoftmaxTest(tflite::BuiltinOperator softmaxOperatorCode,
                  std::vector<float>& expectedOutputValues,
                  float beta = 0)
 {
-    using namespace tflite;
+    using namespace delegateTestInterpreter;
     std::vector<char> modelBuffer = CreateSoftmaxTfLiteModel(softmaxOperatorCode,
                                                              tensorType,
                                                              shape,
                                                              beta);
 
-    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
-    auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0];
-    auto tfLiteInterpreterInputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateInputId);
-    for (unsigned int i = 0; i < inputValues.size(); ++i)
-    {
-        tfLiteInterpreterInputData[i] = inputValues[i];
-    }
-
-    auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0];
-    auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInputId);
-    for (unsigned int i = 0; i < inputValues.size(); ++i)
-    {
-        armnnDelegateInputData[i] = inputValues[i];
-    }
-    // Run EnqueWorkload
-    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data
-    auto tfLiteInterpreterOutputId = tfLiteInterpreter->outputs()[0];
-    auto tfLiteInterpreterOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteInterpreterOutputId);
-    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
-    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId);
-
-    for (size_t i = 0; i < inputValues.size(); ++i)
-    {
-         CHECK(armnnUtils::within_percentage_tolerance(expectedOutputValues[i], armnnDelegateOutputData[i], 0.1));
-         CHECK(armnnUtils::within_percentage_tolerance(tfLiteInterpreterOutputData[i],
-                                                       armnnDelegateOutputData[i], 0.1));
-    }
+    // Setup interpreter with just TFLite Runtime.
+    auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+    CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+    CHECK(tfLiteInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
+    CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
+    std::vector<float>   tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0);
+    std::vector<int32_t> tfLiteOutputShape  = tfLiteInterpreter.GetOutputShape(0);
+
+    // Setup interpreter with Arm NN Delegate applied.
+    auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
+    CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
+    CHECK(armnnInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
+    CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
+    std::vector<float>   armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0);
+    std::vector<int32_t> armnnOutputShape  = armnnInterpreter.GetOutputShape(0);
+
+    armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
+    armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, shape);
+
+    tfLiteInterpreter.Cleanup();
+    armnnInterpreter.Cleanup();
 }