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-rw-r--r--delegate/src/test/ResizeTestHelper.hpp194
1 files changed, 0 insertions, 194 deletions
diff --git a/delegate/src/test/ResizeTestHelper.hpp b/delegate/src/test/ResizeTestHelper.hpp
deleted file mode 100644
index 6937a4ba43..0000000000
--- a/delegate/src/test/ResizeTestHelper.hpp
+++ /dev/null
@@ -1,194 +0,0 @@
-//
-// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include "TestUtils.hpp"
-
-#include <armnn_delegate.hpp>
-
-#include <flatbuffers/flatbuffers.h>
-#include <tensorflow/lite/interpreter.h>
-#include <tensorflow/lite/kernels/register.h>
-#include <tensorflow/lite/model.h>
-#include <tensorflow/lite/schema/schema_generated.h>
-#include <tensorflow/lite/version.h>
-
-#include <doctest/doctest.h>
-
-namespace
-{
-
-std::vector<char> CreateResizeTfLiteModel(tflite::BuiltinOperator operatorCode,
- tflite::TensorType inputTensorType,
- const std::vector <int32_t>& inputTensorShape,
- const std::vector <int32_t>& sizeTensorData,
- const std::vector <int32_t>& sizeTensorShape,
- const std::vector <int32_t>& outputTensorShape)
-{
- using namespace tflite;
- flatbuffers::FlatBufferBuilder flatBufferBuilder;
-
- std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
- buffers.push_back(CreateBuffer(flatBufferBuilder));
- buffers.push_back(CreateBuffer(flatBufferBuilder));
- buffers.push_back(CreateBuffer(flatBufferBuilder,
- flatBufferBuilder.CreateVector(
- reinterpret_cast<const uint8_t*>(sizeTensorData.data()),
- sizeof(int32_t) * sizeTensorData.size())));
- buffers.push_back(CreateBuffer(flatBufferBuilder));
-
- std::array<flatbuffers::Offset<Tensor>, 3> tensors;
- tensors[0] = CreateTensor(flatBufferBuilder,
- flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), inputTensorShape.size()),
- inputTensorType,
- 1,
- flatBufferBuilder.CreateString("input_tensor"));
-
- tensors[1] = CreateTensor(flatBufferBuilder,
- flatBufferBuilder.CreateVector<int32_t>(sizeTensorShape.data(),
- sizeTensorShape.size()),
- TensorType_INT32,
- 2,
- flatBufferBuilder.CreateString("size_input_tensor"));
-
- tensors[2] = CreateTensor(flatBufferBuilder,
- flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
- outputTensorShape.size()),
- inputTensorType,
- 3,
- flatBufferBuilder.CreateString("output_tensor"));
-
- // Create Operator
- tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE;
- flatbuffers::Offset<void> operatorBuiltinOption = 0;
- switch (operatorCode)
- {
- case BuiltinOperator_RESIZE_BILINEAR:
- {
- operatorBuiltinOption = CreateResizeBilinearOptions(flatBufferBuilder, false, false).Union();
- operatorBuiltinOptionsType = tflite::BuiltinOptions_ResizeBilinearOptions;
- break;
- }
- case BuiltinOperator_RESIZE_NEAREST_NEIGHBOR:
- {
- operatorBuiltinOption = CreateResizeNearestNeighborOptions(flatBufferBuilder, false, false).Union();
- operatorBuiltinOptionsType = tflite::BuiltinOptions_ResizeNearestNeighborOptions;
- break;
- }
- default:
- break;
- }
-
- const std::vector<int> operatorInputs{0, 1};
- const std::vector<int> operatorOutputs{2};
- flatbuffers::Offset <Operator> resizeOperator =
- CreateOperator(flatBufferBuilder,
- 0,
- flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
- flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
- operatorBuiltinOptionsType,
- operatorBuiltinOption);
-
- const std::vector<int> subgraphInputs{0, 1};
- const std::vector<int> subgraphOutputs{2};
- flatbuffers::Offset <SubGraph> subgraph =
- CreateSubGraph(flatBufferBuilder,
- flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
- flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
- flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
- flatBufferBuilder.CreateVector(&resizeOperator, 1));
-
- flatbuffers::Offset <flatbuffers::String> modelDescription =
- flatBufferBuilder.CreateString("ArmnnDelegate: Resize Biliniar Operator Model");
- flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, operatorCode);
-
- flatbuffers::Offset <Model> flatbufferModel =
- CreateModel(flatBufferBuilder,
- TFLITE_SCHEMA_VERSION,
- flatBufferBuilder.CreateVector(&opCode, 1),
- flatBufferBuilder.CreateVector(&subgraph, 1),
- modelDescription,
- flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
-
- flatBufferBuilder.Finish(flatbufferModel);
-
- return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
- flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
-}
-
-void ResizeFP32TestImpl(tflite::BuiltinOperator operatorCode,
- std::vector<armnn::BackendId>& backends,
- std::vector<float>& input1Values,
- std::vector<int32_t> input1Shape,
- std::vector<int32_t> input2NewShape,
- std::vector<int32_t> input2Shape,
- std::vector<float>& expectedOutputValues,
- std::vector<int32_t> expectedOutputShape)
-{
- using namespace tflite;
-
- std::vector<char> modelBuffer = CreateResizeTfLiteModel(operatorCode,
- ::tflite::TensorType_FLOAT32,
- input1Shape,
- input2NewShape,
- input2Shape,
- expectedOutputShape);
-
- const Model* tfLiteModel = GetModel(modelBuffer.data());
-
- // The model will be executed using tflite and using the armnn delegate so that the outputs
- // can be compared.
-
- // Create TfLite Interpreter with armnn delegate
- std::unique_ptr<Interpreter> armnnDelegateInterpreter;
- CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
- (&armnnDelegateInterpreter) == kTfLiteOk);
- CHECK(armnnDelegateInterpreter != nullptr);
- CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
-
- // Create TfLite Interpreter without armnn delegate
- 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, input1Values);
- armnnDelegate::FillInput(armnnDelegateInterpreter, 1, input2NewShape);
-
- // Set input data for the tflite interpreter
- armnnDelegate::FillInput(tfLiteInterpreter, 0, input1Values);
- armnnDelegate::FillInput(tfLiteInterpreter, 1, input2NewShape);
-
- // Run EnqueWorkload
- CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
- CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
-
- // Compare output data
- auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
- auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
- auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
- auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId);
- for (size_t i = 0; i < expectedOutputValues.size(); i++)
- {
- CHECK(expectedOutputValues[i] == doctest::Approx(armnnDelegateOutputData[i]));
- CHECK(armnnDelegateOutputData[i] == doctest::Approx(tfLiteDelageOutputData[i]));
- }
-
- armnnDelegateInterpreter.reset(nullptr);
-}
-
-} // anonymous namespace \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-25 20:11:11 +0000