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
diff --git a/delegate/test/Pooling2dTestHelper.hpp b/delegate/test/Pooling2dTestHelper.hpp
index 6de85b6..d08a45b 100644
--- a/delegate/test/Pooling2dTestHelper.hpp
+++ b/delegate/test/Pooling2dTestHelper.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
@@ -106,7 +106,7 @@
modelDescription,
flatBufferBuilder.CreateVector(buffers, 3));
- flatBufferBuilder.Finish(flatbufferModel);
+ flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
@@ -129,7 +129,7 @@
float quantScale = 1.0f,
int quantOffset = 0)
{
- using namespace tflite;
+ using namespace delegateTestInterpreter;
std::vector<char> modelBuffer = CreatePooling2dTfLiteModel(poolingOperatorCode,
tensorType,
inputShape,
@@ -143,50 +143,27 @@
quantScale,
quantOffset);
- const Model* tfLiteModel = GetModel(modelBuffer.data());
- CHECK(tfLiteModel != nullptr);
- // Create TfLite Interpreters
- std::unique_ptr<Interpreter> armnnDelegateInterpreter;
- CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
- (&armnnDelegateInterpreter) == kTfLiteOk);
- CHECK(armnnDelegateInterpreter != nullptr);
- CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
+ // Setup interpreter with just TFLite Runtime.
+ auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+ CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+ CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
+ CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
+ std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
+ std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
- std::unique_ptr<Interpreter> tfLiteInterpreter;
- CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
- (&tfLiteInterpreter) == kTfLiteOk);
- CHECK(tfLiteInterpreter != nullptr);
- CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk);
+ // Setup interpreter with Arm NN Delegate applied.
+ auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
+ CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
+ CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
+ CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
+ std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
+ std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
- // 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);
+ armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
+ armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
- // Set input data
- auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0];
- auto tfLiteDelegateInputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInputId);
- for (unsigned int i = 0; i < inputValues.size(); ++i)
- {
- tfLiteDelegateInputData[i] = inputValues[i];
- }
-
- auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0];
- auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInputId);
- for (unsigned int i = 0; i < inputValues.size(); ++i)
- {
- armnnDelegateInputData[i] = inputValues[i];
- }
-
- // Run EnqueueWorkload
- CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
- CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
-
- armnnDelegate::CompareOutputData(tfLiteInterpreter, armnnDelegateInterpreter, outputShape, expectedOutputValues);
+ tfLiteInterpreter.Cleanup();
+ armnnInterpreter.Cleanup();
}
} // anonymous namespace