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 {
23
CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & tensorShape)24 std::vector<char> CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode,
25 tflite::TensorType tensorType,
26 const std::vector <int32_t>& tensorShape)
27 {
28 using namespace tflite;
29 flatbuffers::FlatBufferBuilder flatBufferBuilder;
30
31 std::array<flatbuffers::Offset<tflite::Buffer>, 1> buffers;
32 buffers[0] = CreateBuffer(flatBufferBuilder);
33
34 std::array<flatbuffers::Offset<Tensor>, 2> tensors;
35 tensors[0] = CreateTensor(flatBufferBuilder,
36 flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
37 tensorType);
38 tensors[1] = CreateTensor(flatBufferBuilder,
39 flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
40 tensorType);
41
42 // create operator
43 const std::vector<int> operatorInputs{0};
44 const std::vector<int> operatorOutputs{1};
45 flatbuffers::Offset <Operator> unaryOperator =
46 CreateOperator(flatBufferBuilder,
47 0,
48 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
49 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
50
51 const std::vector<int> subgraphInputs{0};
52 const std::vector<int> subgraphOutputs{1};
53 flatbuffers::Offset <SubGraph> subgraph =
54 CreateSubGraph(flatBufferBuilder,
55 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
56 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
57 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
58 flatBufferBuilder.CreateVector(&unaryOperator, 1));
59
60 flatbuffers::Offset <flatbuffers::String> modelDescription =
61 flatBufferBuilder.CreateString("ArmnnDelegate: Activation Operator Model");
62 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, activationOperatorCode);
63
64 flatbuffers::Offset <Model> flatbufferModel =
65 CreateModel(flatBufferBuilder,
66 TFLITE_SCHEMA_VERSION,
67 flatBufferBuilder.CreateVector(&operatorCode, 1),
68 flatBufferBuilder.CreateVector(&subgraph, 1),
69 modelDescription,
70 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
71
72 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
73
74 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
75 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
76 }
77
ActivationTest(tflite::BuiltinOperator activationOperatorCode,std::vector<armnn::BackendId> & backends,std::vector<float> & inputValues,std::vector<float> & expectedOutputValues)78 void ActivationTest(tflite::BuiltinOperator activationOperatorCode,
79 std::vector<armnn::BackendId>& backends,
80 std::vector<float>& inputValues,
81 std::vector<float>& expectedOutputValues)
82 {
83 using namespace delegateTestInterpreter;
84 std::vector<int32_t> inputShape { { 4, 1, 4} };
85 std::vector<char> modelBuffer = CreateActivationTfLiteModel(activationOperatorCode,
86 ::tflite::TensorType_FLOAT32,
87 inputShape);
88
89 // Setup interpreter with just TFLite Runtime.
90 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
91 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
92 CHECK(tfLiteInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
93 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
94 std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0);
95 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
96
97 // Setup interpreter with Arm NN Delegate applied.
98 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
99 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
100 CHECK(armnnInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk);
101 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
102 std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0);
103 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
104
105 armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
106 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, inputShape);
107
108 tfLiteInterpreter.Cleanup();
109 armnnInterpreter.Cleanup();
110 }
111
112 } // anonymous namespace