1 //
2 // Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #pragma once
6
7 #include <armnn/INetwork.hpp>
8
9 #include <CommonTestUtils.hpp>
10 #include <ResolveType.hpp>
11
12 #include <doctest/doctest.h>
13
14 namespace
15 {
16
17 template<typename armnn::DataType DataType>
CreateAdditionNetwork(const armnn::TensorShape & inputXShape,const armnn::TensorShape & inputYShape,const armnn::TensorShape & outputShape,const float qScale=1.0f,const int32_t qOffset=0)18 armnn::INetworkPtr CreateAdditionNetwork(const armnn::TensorShape& inputXShape,
19 const armnn::TensorShape& inputYShape,
20 const armnn::TensorShape& outputShape,
21 const float qScale = 1.0f,
22 const int32_t qOffset = 0)
23 {
24 using namespace armnn;
25
26 INetworkPtr network(INetwork::Create());
27
28 TensorInfo inputXTensorInfo(inputXShape, DataType, qScale, qOffset, true);
29 TensorInfo inputYTensorInfo(inputYShape, DataType, qScale, qOffset, true);
30
31 TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset);
32
33 ARMNN_NO_DEPRECATE_WARN_BEGIN
34 IConnectableLayer* addition = network->AddAdditionLayer("addition");
35 ARMNN_NO_DEPRECATE_WARN_END
36 IConnectableLayer* inputX = network->AddInputLayer(0, "inputX");
37 IConnectableLayer* inputY = network->AddInputLayer(1, "inputY");
38 IConnectableLayer* output = network->AddOutputLayer(0, "output");
39
40 Connect(inputX, addition, inputXTensorInfo, 0, 0);
41 Connect(inputY, addition, inputYTensorInfo, 0, 1);
42 Connect(addition, output, outputTensorInfo, 0, 0);
43
44 return network;
45 }
46
47 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
AdditionEndToEnd(const std::vector<armnn::BackendId> & backends)48 void AdditionEndToEnd(const std::vector<armnn::BackendId>& backends)
49 {
50 using namespace armnn;
51
52 const TensorShape& inputXShape = { 2, 2, 2 };
53 const TensorShape& inputYShape = { 2, 2, 2 };
54 const TensorShape& outputShape = { 2, 2, 2 };
55
56 INetworkPtr network = CreateAdditionNetwork<ArmnnType>(inputXShape, inputYShape, outputShape);
57
58 CHECK(network);
59
60 std::vector<T> inputXData{ 1, 2,
61 3, 4,
62
63 9, 10,
64 11, 12 };
65 std::vector<T> inputYData{ 5, 7,
66 6, 8,
67
68 13, 15,
69 14, 16 };
70 std::vector<T> expectedOutput{ 6, 9,
71 9, 12,
72
73 22, 25,
74 25, 28 };
75
76 std::map<int, std::vector<T>> inputTensorData = {{ 0, inputXData }, {1, inputYData}};
77 std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
78
79 EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
80 }
81
82 template<armnn::DataType ArmnnType>
AdditionEndToEndFloat16(const std::vector<armnn::BackendId> & backends)83 void AdditionEndToEndFloat16(const std::vector<armnn::BackendId>& backends)
84 {
85 using namespace armnn;
86 using namespace half_float::literal;
87 using Half = half_float::half;
88
89 const TensorShape& inputXShape = { 2, 2 };
90 const TensorShape& inputYShape = { 2, 2 };
91 const TensorShape& outputShape = { 2, 2 };
92
93 INetworkPtr network = CreateAdditionNetwork<ArmnnType>(inputXShape, inputYShape, outputShape);
94 CHECK(network);
95
96 std::vector<Half> inputXData{ 1._h, 2._h,
97 3._h, 4._h };
98 std::vector<Half> inputYData{ 5._h, 7._h,
99 6._h, 8._h };
100 std::vector<Half> expectedOutput{ 6._h, 9._h,
101 9._h, 12._h };
102
103 std::map<int, std::vector<Half>> inputTensorData = {{ 0, inputXData }, { 1, inputYData }};
104 std::map<int, std::vector<Half>> expectedOutputData = { { 0, expectedOutput } };
105
106 EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
107 }
108
109 } // anonymous namespace
110