1 //
2 // Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #pragma once
7
8 #include "TestUtils.hpp"
9
10 #include <armnn_delegate.hpp>
11 #include <DelegateTestInterpreter.hpp>
12
13 #include <flatbuffers/flatbuffers.h>
14 #include <tensorflow/lite/kernels/register.h>
15 #include <tensorflow/lite/version.h>
16
17 #include <schema_generated.h>
18
19 #include <doctest/doctest.h>
20
21 namespace
22 {
CreateTransposeTfLiteModel(tflite::TensorType tensorType,const std::vector<int32_t> & input0TensorShape,const std::vector<int32_t> & inputPermVecShape,const std::vector<int32_t> & outputTensorShape,const std::vector<int32_t> & inputPermVec)23 std::vector<char> CreateTransposeTfLiteModel(tflite::TensorType tensorType,
24 const std::vector <int32_t>& input0TensorShape,
25 const std::vector <int32_t>& inputPermVecShape,
26 const std::vector <int32_t>& outputTensorShape,
27 const std::vector<int32_t>& inputPermVec)
28 {
29 using namespace tflite;
30 flatbuffers::FlatBufferBuilder flatBufferBuilder;
31 flatbuffers::Offset<tflite::Buffer> buffers[4]{
32 CreateBuffer(flatBufferBuilder),
33 CreateBuffer(flatBufferBuilder),
34 CreateBuffer(flatBufferBuilder,
35 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(inputPermVec.data()),
36 sizeof(int32_t) * inputPermVec.size())),
37 CreateBuffer(flatBufferBuilder)
38 };
39 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
40 tensors[0] = CreateTensor(flatBufferBuilder,
41 flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(),
42 input0TensorShape.size()),
43 tensorType, 1);
44 tensors[1] = CreateTensor(flatBufferBuilder,
45 flatBufferBuilder.CreateVector<int32_t>(inputPermVecShape.data(),
46 inputPermVecShape.size()),
47 tflite::TensorType_INT32, 2,
48 flatBufferBuilder.CreateString("permutation_vector"));
49 tensors[2] = CreateTensor(flatBufferBuilder,
50 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
51 outputTensorShape.size()),
52 tensorType,3);
53 const std::vector<int32_t> operatorInputs{0, 1};
54 const std::vector<int32_t> operatorOutputs{2};
55 flatbuffers::Offset <Operator> transposeOperator =
56 CreateOperator(flatBufferBuilder,
57 0,
58 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
59 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
60 BuiltinOptions_TransposeOptions,
61 CreateTransposeOptions(flatBufferBuilder).Union());
62 const std::vector<int> subgraphInputs{0, 1};
63 const std::vector<int> subgraphOutputs{2};
64 flatbuffers::Offset <SubGraph> subgraph =
65 CreateSubGraph(flatBufferBuilder,
66 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
67 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
68 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
69 flatBufferBuilder.CreateVector(&transposeOperator, 1));
70 flatbuffers::Offset <flatbuffers::String> modelDescription =
71 flatBufferBuilder.CreateString("ArmnnDelegate: Transpose Operator Model");
72 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
73 tflite::BuiltinOperator_TRANSPOSE);
74 flatbuffers::Offset <Model> flatbufferModel =
75 CreateModel(flatBufferBuilder,
76 TFLITE_SCHEMA_VERSION,
77 flatBufferBuilder.CreateVector(&operatorCode, 1),
78 flatBufferBuilder.CreateVector(&subgraph, 1),
79 modelDescription,
80 flatBufferBuilder.CreateVector(buffers, 4));
81 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
82 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
83 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
84 }
85
86 template <typename T>
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)87 void TransposeTest(std::vector<armnn::BackendId>& backends,
88 std::vector<int32_t>& inputShape,
89 std::vector<int32_t>& inputPermVecShape,
90 std::vector<int32_t>& outputShape,
91 std::vector<T>& inputValues,
92 std::vector<int32_t>& inputPermVec,
93 std::vector<T>& expectedOutputValues)
94 {
95 using namespace delegateTestInterpreter;
96
97 // Create model
98 std::vector<char> modelBuffer = CreateTransposeTfLiteModel(::tflite::TensorType_FLOAT32,
99 inputShape,
100 inputPermVecShape,
101 outputShape,
102 inputPermVec);
103
104 // Setup interpreter with just TFLite Runtime.
105 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
106 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
107 CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
108 CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(inputPermVec, 1) == kTfLiteOk);
109 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
110 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
111 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
112
113 // Setup interpreter with Arm NN Delegate applied.
114 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
115 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
116 CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
117 CHECK(armnnInterpreter.FillInputTensor<int32_t>(inputPermVec, 1) == kTfLiteOk);
118 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
119 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
120 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
121
122 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
123 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
124
125 tfLiteInterpreter.Cleanup();
126 armnnInterpreter.Cleanup();
127 }
128 }
129