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, 34 insertions, 57 deletions

diff --git a/delegate/test/LogicalTestHelper.hpp b/delegate/test/LogicalTestHelper.hpp
index 2f2ae7bf40..7da8ad9bfc 100644
--- a/delegate/test/LogicalTestHelper.hpp
+++ b/delegate/test/LogicalTestHelper.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
@@ -120,26 +120,25 @@ std::vector<char> CreateLogicalBinaryTfLiteModel(tflite::BuiltinOperator logical
                     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());
 }
 
-template <typename T>
 void LogicalBinaryTest(tflite::BuiltinOperator logicalOperatorCode,
                        tflite::TensorType tensorType,
                        std::vector<armnn::BackendId>& backends,
                        std::vector<int32_t>& input0Shape,
                        std::vector<int32_t>& input1Shape,
                        std::vector<int32_t>& expectedOutputShape,
-                       std::vector<T>& input0Values,
-                       std::vector<T>& input1Values,
-                       std::vector<T>& expectedOutputValues,
+                       std::vector<bool>& input0Values,
+                       std::vector<bool>& input1Values,
+                       std::vector<bool>& expectedOutputValues,
                        float quantScale = 1.0f,
                        int quantOffset  = 0)
 {
-    using namespace tflite;
+    using namespace delegateTestInterpreter;
     std::vector<char> modelBuffer = CreateLogicalBinaryTfLiteModel(logicalOperatorCode,
                                                                    tensorType,
                                                                    input0Shape,
@@ -148,54 +147,32 @@ void LogicalBinaryTest(tflite::BuiltinOperator logicalOperatorCode,
                                                                    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 the armnn interpreter
-    armnnDelegate::FillInput(armnnDelegateInterpreter, 0, input0Values);
-    armnnDelegate::FillInput(armnnDelegateInterpreter, 1, input1Values);
-
-    // Set input data for the tflite interpreter
-    armnnDelegate::FillInput(tfLiteInterpreter, 0, input0Values);
-    armnnDelegate::FillInput(tfLiteInterpreter, 1, input1Values);
-
-    // Run EnqueWorkload
-    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
-    // Compare output data, comparing Boolean values is handled differently and needs to call the CompareData function
-    // directly. This is because Boolean types get converted to a bit representation in a vector.
-    auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
-    auto tfLiteDelegateOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId);
-    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
-    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId);
-
-    armnnDelegate::CompareData(expectedOutputValues, armnnDelegateOutputData, expectedOutputValues.size());
-    armnnDelegate::CompareData(expectedOutputValues, tfLiteDelegateOutputData, expectedOutputValues.size());
-    armnnDelegate::CompareData(tfLiteDelegateOutputData, armnnDelegateOutputData, expectedOutputValues.size());
-
-    armnnDelegateInterpreter.reset(nullptr);
-    tfLiteInterpreter.reset(nullptr);
+    // Setup interpreter with just TFLite Runtime.
+    auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+    CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+    CHECK(tfLiteInterpreter.FillInputTensor(input0Values, 0) == kTfLiteOk);
+    CHECK(tfLiteInterpreter.FillInputTensor(input1Values, 1) == kTfLiteOk);
+    CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
+    std::vector<bool>    tfLiteOutputValues = tfLiteInterpreter.GetOutputResult(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(input0Values, 0) == kTfLiteOk);
+    CHECK(armnnInterpreter.FillInputTensor(input1Values, 1) == kTfLiteOk);
+    CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
+    std::vector<bool>    armnnOutputValues = armnnInterpreter.GetOutputResult(0);
+    std::vector<int32_t> armnnOutputShape  = armnnInterpreter.GetOutputShape(0);
+
+    armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
+
+    armnnDelegate::CompareData(expectedOutputValues, armnnOutputValues, expectedOutputValues.size());
+    armnnDelegate::CompareData(expectedOutputValues, tfLiteOutputValues, expectedOutputValues.size());
+    armnnDelegate::CompareData(tfLiteOutputValues, armnnOutputValues, expectedOutputValues.size());
+
+    tfLiteInterpreter.Cleanup();
+    armnnInterpreter.Cleanup();
 }
 
 } // anonymous namespace
\ No newline at end of file