1 //
2 // Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #pragma once
7
8 #include <armnn_delegate.hpp>
9
10 #include <flatbuffers/flatbuffers.h>
11 #include <tensorflow/lite/interpreter.h>
12 #include <tensorflow/lite/kernels/register.h>
13 #include <tensorflow/lite/model.h>
14 #include <tensorflow/lite/schema/schema_generated.h>
15 #include <tensorflow/lite/version.h>
16
17 #include <doctest/doctest.h>
18
19 namespace
20 {
21
CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & tensorShape)22 std::vector<char> CreateActivationTfLiteModel(tflite::BuiltinOperator activationOperatorCode,
23 tflite::TensorType tensorType,
24 const std::vector <int32_t>& tensorShape)
25 {
26 using namespace tflite;
27 flatbuffers::FlatBufferBuilder flatBufferBuilder;
28
29 std::array<flatbuffers::Offset<tflite::Buffer>, 1> buffers;
30 buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
31
32 std::array<flatbuffers::Offset<Tensor>, 2> tensors;
33 tensors[0] = CreateTensor(flatBufferBuilder,
34 flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
35 tensorType);
36 tensors[1] = CreateTensor(flatBufferBuilder,
37 flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()),
38 tensorType);
39
40 // create operator
41 const std::vector<int> operatorInputs{{0}};
42 const std::vector<int> operatorOutputs{{1}};
43 flatbuffers::Offset <Operator> unaryOperator =
44 CreateOperator(flatBufferBuilder,
45 0,
46 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
47 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
48
49 const std::vector<int> subgraphInputs{{0}};
50 const std::vector<int> subgraphOutputs{{1}};
51 flatbuffers::Offset <SubGraph> subgraph =
52 CreateSubGraph(flatBufferBuilder,
53 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
54 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
55 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
56 flatBufferBuilder.CreateVector(&unaryOperator, 1));
57
58 flatbuffers::Offset <flatbuffers::String> modelDescription =
59 flatBufferBuilder.CreateString("ArmnnDelegate: Activation Operator Model");
60 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, activationOperatorCode);
61
62 flatbuffers::Offset <Model> flatbufferModel =
63 CreateModel(flatBufferBuilder,
64 TFLITE_SCHEMA_VERSION,
65 flatBufferBuilder.CreateVector(&operatorCode, 1),
66 flatBufferBuilder.CreateVector(&subgraph, 1),
67 modelDescription,
68 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
69
70 flatBufferBuilder.Finish(flatbufferModel);
71
72 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
73 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
74 }
75
ActivationTest(tflite::BuiltinOperator activationOperatorCode,std::vector<armnn::BackendId> & backends,std::vector<float> & inputValues,std::vector<float> & expectedOutputValues)76 void ActivationTest(tflite::BuiltinOperator activationOperatorCode,
77 std::vector<armnn::BackendId>& backends,
78 std::vector<float>& inputValues,
79 std::vector<float>& expectedOutputValues)
80 {
81 using namespace tflite;
82 const std::vector<int32_t> inputShape { { 4, 1, 4} };
83 std::vector<char> modelBuffer = CreateActivationTfLiteModel(activationOperatorCode,
84 ::tflite::TensorType_FLOAT32,
85 inputShape);
86
87 const Model* tfLiteModel = GetModel(modelBuffer.data());
88 // Create TfLite Interpreters
89 std::unique_ptr<Interpreter> armnnDelegateInterpreter;
90 CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
91 (&armnnDelegateInterpreter) == kTfLiteOk);
92 CHECK(armnnDelegateInterpreter != nullptr);
93 CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
94
95 std::unique_ptr<Interpreter> tfLiteInterpreter;
96 CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
97 (&tfLiteInterpreter) == kTfLiteOk);
98 CHECK(tfLiteInterpreter != nullptr);
99 CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk);
100
101 // Create the ArmNN Delegate
102 armnnDelegate::DelegateOptions delegateOptions(backends);
103 std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
104 theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
105 armnnDelegate::TfLiteArmnnDelegateDelete);
106 CHECK(theArmnnDelegate != nullptr);
107 // Modify armnnDelegateInterpreter to use armnnDelegate
108 CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
109
110 // Set input data
111 auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0];
112 auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateInputId);
113 for (unsigned int i = 0; i < inputValues.size(); ++i)
114 {
115 tfLiteDelageInputData[i] = inputValues[i];
116 }
117
118 auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0];
119 auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInputId);
120 for (unsigned int i = 0; i < inputValues.size(); ++i)
121 {
122 armnnDelegateInputData[i] = inputValues[i];
123 }
124 // Run EnqueWorkload
125 CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
126 CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
127
128 // Compare output data
129 auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
130 auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
131 auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
132 auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId);
133 for (size_t i = 0; i < inputValues.size(); i++)
134 {
135 CHECK(expectedOutputValues[i] == doctest::Approx(armnnDelegateOutputData[i]));
136 CHECK(tfLiteDelageOutputData[i] == doctest::Approx(armnnDelegateOutputData[i]));
137 }
138 }
139
140 } // anonymous namespace