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/TransposeTestHelper.hpp b/delegate/test/TransposeTestHelper.hpp
index 99bb60b..57f4e29 100644
--- a/delegate/test/TransposeTestHelper.hpp
+++ b/delegate/test/TransposeTestHelper.hpp
@@ -5,15 +5,17 @@
#pragma once
+#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
@@ -76,102 +78,51 @@
flatBufferBuilder.CreateVector(&subgraph, 1),
modelDescription,
flatBufferBuilder.CreateVector(buffers, 4));
- flatBufferBuilder.Finish(flatbufferModel);
+ flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
}
-void TransposeFP32Test(std::vector<armnn::BackendId>& backends)
+template <typename T>
+void TransposeTest(std::vector<armnn::BackendId>& backends,
+ std::vector<int32_t>& inputShape,
+ std::vector<int32_t>& inputPermVecShape,
+ std::vector<int32_t>& outputShape,
+ std::vector<T>& inputValues,
+ std::vector<int32_t>& inputPermVec,
+ std::vector<T>& expectedOutputValues)
{
- using namespace tflite;
+ using namespace delegateTestInterpreter;
- // set test input data
- std::vector<int32_t> input0Shape {4, 2, 3};
- std::vector<int32_t> inputPermVecShape {3};
- std::vector<int32_t> outputShape {2, 3, 4};
-
- std::vector<float> input0Values = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
- 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23};
- std::vector<int32_t> inputPermVec = {2, 0, 1};
- std::vector<float> expectedOutputValues = {0, 3, 6, 9, 12, 15, 18, 21, 1, 4, 7, 10,
- 13, 16, 19, 22, 2, 5, 8, 11, 14, 17, 20, 23};
-
- // create model
+ // Create model
std::vector<char> modelBuffer = CreateTransposeTfLiteModel(::tflite::TensorType_FLOAT32,
- input0Shape,
+ inputShape,
inputPermVecShape,
outputShape,
inputPermVec);
- 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);
+ // Setup interpreter with just TFLite Runtime.
+ auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
+ CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
+ CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
+ CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(inputPermVec, 1) == 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.FillInputTensor<int32_t>(inputPermVec, 1) == 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 for tflite
- auto tfLiteInterpreterInput0Id = tfLiteInterpreter->inputs()[0];
- auto tfLiteInterpreterInput0Data = tfLiteInterpreter->typed_tensor<float>(tfLiteInterpreterInput0Id);
- for (unsigned int i = 0; i < input0Values.size(); ++i)
- {
- tfLiteInterpreterInput0Data[i] = input0Values[i];
- }
-
- auto tfLiteInterpreterInput1Id = tfLiteInterpreter->inputs()[1];
- auto tfLiteInterpreterInput1Data = tfLiteInterpreter->typed_tensor<int32_t>(tfLiteInterpreterInput1Id);
- for (unsigned int i = 0; i < inputPermVec.size(); ++i)
- {
- tfLiteInterpreterInput1Data[i] = inputPermVec[i];
- }
-
- //Set input data for armnn delegate
- auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0];
- auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInput0Id);
- for (unsigned int i = 0; i < input0Values.size(); ++i)
- {
- armnnDelegateInput0Data[i] = input0Values[i];
- }
-
- auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1];
- auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<int32_t>(armnnDelegateInput1Id);
- for (unsigned int i = 0; i < inputPermVec.size(); ++i)
- {
- armnnDelegateInput1Data[i] = inputPermVec[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 < expectedOutputValues.size(); ++i)
- {
- CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]);
- CHECK(tfLiteInterpreterOutputData[i] == expectedOutputValues[i]);
- CHECK(tfLiteInterpreterOutputData[i] == armnnDelegateOutputData[i]);
- }
-
- armnnDelegateInterpreter.reset(nullptr);
+ tfLiteInterpreter.Cleanup();
+ armnnInterpreter.Cleanup();
}
}