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Diffstat (limited to 'delegate/src/test/ActivationTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/ActivationTestHelper.hpp | 130 |
1 files changed, 0 insertions, 130 deletions
diff --git a/delegate/src/test/ActivationTestHelper.hpp b/delegate/src/test/ActivationTestHelper.hpp deleted file mode 100644 index 6475083da0..0000000000 --- a/delegate/src/test/ActivationTestHelper.hpp +++ /dev/null @@ -1,130 +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> CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode, - tflite::TensorType tensorType, - const std::vector <int32_t>& tensorShape) -{ - using namespace tflite; - flatbuffers::FlatBufferBuilder flatBufferBuilder; - - std::array<flatbuffers::Offset<tflite::Buffer>, 1> buffers; - buffers[0] = CreateBuffer(flatBufferBuilder); - - std::array<flatbuffers::Offset<Tensor>, 2> tensors; - tensors[0] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()), - tensorType); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()), - tensorType); - - // create operator - const std::vector<int> operatorInputs{0}; - const std::vector<int> operatorOutputs{1}; - flatbuffers::Offset <Operator> unaryOperator = - CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size())); - - const std::vector<int> subgraphInputs{0}; - const std::vector<int> subgraphOutputs{1}; - 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(&unaryOperator, 1)); - - flatbuffers::Offset <flatbuffers::String> modelDescription = - flatBufferBuilder.CreateString("ArmnnDelegate: Activation Operator Model"); - flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, activationOperatorCode); - - flatbuffers::Offset <Model> flatbufferModel = - CreateModel(flatBufferBuilder, - TFLITE_SCHEMA_VERSION, - flatBufferBuilder.CreateVector(&operatorCode, 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 ActivationTest(tflite::BuiltinOperator activationOperatorCode, - std::vector<armnn::BackendId>& backends, - std::vector<float>& inputValues, - std::vector<float>& expectedOutputValues) -{ - using namespace tflite; - std::vector<int32_t> inputShape { { 4, 1, 4} }; - std::vector<char> modelBuffer = CreateActivationTfLiteModel(activationOperatorCode, - ::tflite::TensorType_FLOAT32, - inputShape); - - 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 - armnnDelegate::FillInput<float>(tfLiteInterpreter, 0, inputValues); - armnnDelegate::FillInput<float>(armnnDelegateInterpreter, 0, inputValues); - - // Run EnqueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - // Compare output data - armnnDelegate::CompareOutputData<float>(tfLiteInterpreter, - armnnDelegateInterpreter, - inputShape, - expectedOutputValues); - - tfLiteInterpreter.reset(nullptr); - armnnDelegateInterpreter.reset(nullptr); -} - -} // anonymous namespace
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