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-rw-r--r--delegate/src/test/SplitTestHelper.hpp86
1 files changed, 44 insertions, 42 deletions
diff --git a/delegate/src/test/SplitTestHelper.hpp b/delegate/src/test/SplitTestHelper.hpp
index 31fc7d5e46..3c5f50ffac 100644
--- a/delegate/src/test/SplitTestHelper.hpp
+++ b/delegate/src/test/SplitTestHelper.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -35,11 +35,12 @@ std::vector<char> CreateSplitTfLiteModel(tflite::TensorType tensorType,
using namespace tflite;
flatbuffers::FlatBufferBuilder flatBufferBuilder;
- std::array<flatbuffers::Offset<tflite::Buffer>, 2> buffers;
- buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
- buffers[1] = CreateBuffer(flatBufferBuilder,
- flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(axisData.data()),
- sizeof(int32_t) * axisData.size()));
+ 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*>(axisData.data()),
+ sizeof(int32_t) * axisData.size())));
auto quantizationParameters =
CreateQuantizationParameters(flatBufferBuilder,
@@ -53,27 +54,28 @@ std::vector<char> CreateSplitTfLiteModel(tflite::TensorType tensorType,
flatBufferBuilder.CreateVector<int32_t>(axisTensorShape.data(),
axisTensorShape.size()),
::tflite::TensorType_INT32,
- 1,
+ 2,
flatBufferBuilder.CreateString("axis"),
quantizationParameters);
tensors[1] = CreateTensor(flatBufferBuilder,
flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
inputTensorShape.size()),
tensorType,
- 0,
+ 1,
flatBufferBuilder.CreateString("input"),
quantizationParameters);
// Create output tensor
for (unsigned int i = 0; i < outputTensorShapes.size(); ++i)
{
+ buffers.push_back(CreateBuffer(flatBufferBuilder));
tensors[i + 2] = CreateTensor(flatBufferBuilder,
- flatBufferBuilder.CreateVector<int32_t>(outputTensorShapes[i].data(),
- outputTensorShapes[i].size()),
- tensorType,
- 0,
- flatBufferBuilder.CreateString("output"),
- quantizationParameters);
+ flatBufferBuilder.CreateVector<int32_t>(outputTensorShapes[i].data(),
+ outputTensorShapes[i].size()),
+ tensorType,
+ (i+3),
+ flatBufferBuilder.CreateString("output"),
+ quantizationParameters);
}
// create operator. Mean uses ReducerOptions.
@@ -109,7 +111,7 @@ std::vector<char> CreateSplitTfLiteModel(tflite::TensorType tensorType,
flatBufferBuilder.CreateVector(&operatorCode, 1),
flatBufferBuilder.CreateVector(&subgraph, 1),
modelDescription,
- flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
+ flatBufferBuilder.CreateVector(buffers));
flatBufferBuilder.Finish(flatbufferModel);
@@ -144,21 +146,21 @@ void SplitTest(tflite::TensorType tensorType,
// Create TfLite Interpreters
std::unique_ptr<Interpreter> armnnDelegate;
CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
- (&armnnDelegate) == kTfLiteOk);
+ (&armnnDelegate) == kTfLiteOk);
CHECK(armnnDelegate != nullptr);
CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
std::unique_ptr<Interpreter> tfLiteDelegate;
CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
- (&tfLiteDelegate) == kTfLiteOk);
+ (&tfLiteDelegate) == kTfLiteOk);
CHECK(tfLiteDelegate != nullptr);
CHECK(tfLiteDelegate->AllocateTensors() == kTfLiteOk);
// Create the ArmNN Delegate
armnnDelegate::DelegateOptions delegateOptions(backends);
std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
- theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
- armnnDelegate::TfLiteArmnnDelegateDelete);
+ theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
+ armnnDelegate::TfLiteArmnnDelegateDelete);
CHECK(theArmnnDelegate != nullptr);
// Modify armnnDelegateInterpreter to use armnnDelegate
@@ -210,11 +212,11 @@ std::vector<char> CreateSplitVTfLiteModel(tflite::TensorType tensorType,
sizeof(int32_t) * axisData.size()));
auto quantizationParameters =
- CreateQuantizationParameters(flatBufferBuilder,
- 0,
- 0,
- flatBufferBuilder.CreateVector<float>({ quantScale }),
- flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
+ CreateQuantizationParameters(flatBufferBuilder,
+ 0,
+ 0,
+ flatBufferBuilder.CreateVector<float>({ quantScale }),
+ flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
std::array<flatbuffers::Offset<Tensor>, 5> tensors;
tensors[0] = CreateTensor(flatBufferBuilder,
@@ -258,33 +260,33 @@ std::vector<char> CreateSplitVTfLiteModel(tflite::TensorType tensorType,
const std::vector<int> operatorInputs{ {0, 1, 2} };
const std::vector<int> operatorOutputs{ {3, 4} };
flatbuffers::Offset <Operator> controlOperator =
- CreateOperator(flatBufferBuilder,
- 0,
- flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
- flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
- operatorBuiltinOptionsType,
- operatorBuiltinOptions);
+ 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, 2} };
const std::vector<int> subgraphOutputs{ {3, 4} };
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(&controlOperator, 1));
+ 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(&controlOperator, 1));
flatbuffers::Offset <flatbuffers::String> modelDescription =
- flatBufferBuilder.CreateString("ArmnnDelegate: SPLIT_V Operator Model");
+ flatBufferBuilder.CreateString("ArmnnDelegate: SPLIT_V Operator Model");
flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, BuiltinOperator_SPLIT_V);
flatbuffers::Offset <Model> flatbufferModel =
- CreateModel(flatBufferBuilder,
- TFLITE_SCHEMA_VERSION,
- flatBufferBuilder.CreateVector(&operatorCode, 1),
- flatBufferBuilder.CreateVector(&subgraph, 1),
- modelDescription,
- flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
+ CreateModel(flatBufferBuilder,
+ TFLITE_SCHEMA_VERSION,
+ flatBufferBuilder.CreateVector(&operatorCode, 1),
+ flatBufferBuilder.CreateVector(&subgraph, 1),
+ modelDescription,
+ flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
flatBufferBuilder.Finish(flatbufferModel);
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-06 03:56:05 +0000