IVGCVSW-7562 Implement DelegateTestInterpreter for classic delegate

 * Updated all tests to use new DelegateTestInterpreter.
 * Fixed some unit tests where the shape was incorrect.
 * Add file identifier to FlatBuffersBuilder, as it is required for
   validation when creating the model using new API.

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I1c4f5464367b35d4528571fa94d14bfaef18fb4d

1 files changed, 26 insertions, 49 deletions

diff --git a/delegate/test/ArgMinMaxTestHelper.hpp b/delegate/test/ArgMinMaxTestHelper.hpp
index 91cf1f81e7..fd230fff94 100644
--- a/delegate/test/ArgMinMaxTestHelper.hpp
+++ b/delegate/test/ArgMinMaxTestHelper.hpp
@@ -8,14 +8,14 @@
 #include "TestUtils.hpp"
 
 #include <armnn_delegate.hpp>
+#include <DelegateTestInterpreter.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
@@ -119,7 +119,7 @@ std::vector<char> CreateArgMinMaxTfLiteModel(tflite::BuiltinOperator argMinMaxOp
                     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());
@@ -139,7 +139,7 @@ void ArgMinMaxTest(tflite::BuiltinOperator argMinMaxOperatorCode,
                    float quantScale = 1.0f,
                    int quantOffset  = 0)
 {
-    using namespace tflite;
+    using namespace delegateTestInterpreter;
     std::vector<char> modelBuffer = CreateArgMinMaxTfLiteModel<InputT, OutputT>(argMinMaxOperatorCode,
                                                                                 tensorType,
                                                                                 inputShape,
@@ -150,50 +150,27 @@ void ArgMinMaxTest(tflite::BuiltinOperator argMinMaxOperatorCode,
                                                                                 quantScale,
                                                                                 quantOffset);
 
-    const Model* tfLiteModel = GetModel(modelBuffer.data());
-    CHECK(tfLiteModel != nullptr);
-
-    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
-    armnnDelegate::FillInput<InputT>(tfLiteInterpreter, 0, inputValues);
-    armnnDelegate::FillInput<InputT>(armnnDelegateInterpreter, 0, inputValues);
-
-    // Run EnqueueWorkload
-    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data
-    auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
-    auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<OutputT>(tfLiteDelegateOutputId);
-    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
-    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<OutputT>(armnnDelegateOutputId);
-
-    for (size_t i = 0; i < expectedOutputValues.size(); i++)
-    {
-        CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]);
-        CHECK(tfLiteDelageOutputData[i] == expectedOutputValues[i]);
-        CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]);
-    }
+    // Setup interpreter with just TFLite Runtime.
+    auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+    CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+    CHECK(tfLiteInterpreter.FillInputTensor<InputT>(inputValues, 0) == kTfLiteOk);
+    CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
+    std::vector<OutputT> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<OutputT>(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<InputT>(inputValues, 0) == kTfLiteOk);
+    CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
+    std::vector<OutputT> armnnOutputValues = armnnInterpreter.GetOutputResult<OutputT>(0);
+    std::vector<int32_t> armnnOutputShape  = armnnInterpreter.GetOutputShape(0);
+
+    armnnDelegate::CompareOutputData<OutputT>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
+    armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
+
+    tfLiteInterpreter.Cleanup();
+    armnnInterpreter.Cleanup();
 }
 
 } // anonymous namespace
\ No newline at end of file