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author | Sadik Armagan <sadik.armagan@arm.com> | 2021-02-22 18:09:07 +0000 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2021-02-25 11:25:27 +0000 |
commit | 29b49cf1771620233f9c16dfa0214e6d8a64c4d7 (patch) | |
tree | 111ac8261a8ad97e01915d99fce80717facd1b3f /delegate/src/test/FillTestHelper.hpp | |
parent | 4018b21cd41437f1e1b2e528d5521136f39ff2b1 (diff) | |
download | armnn-29b49cf1771620233f9c16dfa0214e6d8a64c4d7.tar.gz |
IVGCVSW-5401 Implement the FILL operator
* Added FILL operator to TfLite ArmNN Delegate
* Added unit tests
Signed-off-by: David Monahan <david.monahan@arm.com>
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I335ef469ff773fa4305eb87f6e93ae9c03fc6997
Diffstat (limited to 'delegate/src/test/FillTestHelper.hpp')
-rw-r--r-- | delegate/src/test/FillTestHelper.hpp | 160 |
1 files changed, 160 insertions, 0 deletions
diff --git a/delegate/src/test/FillTestHelper.hpp b/delegate/src/test/FillTestHelper.hpp new file mode 100644 index 0000000000..e6890a2b2d --- /dev/null +++ b/delegate/src/test/FillTestHelper.hpp @@ -0,0 +1,160 @@ +// +// Copyright © 2021 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 +{ + +template <typename T> +std::vector<char> CreateFillTfLiteModel(tflite::BuiltinOperator fillOperatorCode, + tflite::TensorType tensorType, + const std::vector<int32_t>& inputShape, + const std::vector <int32_t>& tensorShape, + const std::vector<T> fillValue) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector({}))); + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(tensorShape.data()), + sizeof(int32_t) * tensorShape.size()))); + buffers.push_back( + CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(fillValue.data()), + sizeof(T) * fillValue.size()))); + + std::array<flatbuffers::Offset<Tensor>, 3> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(inputShape.data(), + inputShape.size()), + tflite::TensorType_INT32, + 1, + flatBufferBuilder.CreateString("dims")); + + std::vector<int32_t> fillShape = {}; + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(fillShape.data(), + fillShape.size()), + tensorType, + 2, + flatBufferBuilder.CreateString("value")); + + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), + tensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output")); + + tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_FillOptions; + flatbuffers::Offset<void> operatorBuiltinOptions = CreateFillOptions(flatBufferBuilder).Union(); + + // create operator + const std::vector<int> operatorInputs{ {0, 1} }; + const std::vector<int> operatorOutputs{ 2 }; + flatbuffers::Offset <Operator> fillOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + 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(&fillOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Fill Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, + fillOperatorCode); + + 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()); + +} + +template <typename T> +void FillTest(tflite::BuiltinOperator fillOperatorCode, + tflite::TensorType tensorType, + const std::vector<armnn::BackendId>& backends, + std::vector<int32_t >& inputShape, + std::vector<int32_t >& tensorShape, + std::vector<T>& expectedOutputValues, + T fillValue) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateFillTfLiteModel<T>(fillOperatorCode, + tensorType, + inputShape, + tensorShape, + {fillValue}); + + const Model* tfLiteModel = GetModel(modelBuffer.data()); + CHECK(tfLiteModel != nullptr); + + 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); + + // Run EnqueueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + + armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, armnnDelegateInterpreter, tensorShape, expectedOutputValues); +} + +} // anonymous namespace |