1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #pragma once
6
7 #include <CommonTestUtils.hpp>
8
9 #include <ResolveType.hpp>
10
11 #include <armnn/INetwork.hpp>
12
13 #include <armnn/utility/NumericCast.hpp>
14
15 #include <doctest/doctest.h>
16
17 #include <vector>
18
19 namespace
20 {
21
22 template<armnn::DataType ArmnnTypeInput>
CreateComparisonNetwork(const std::vector<TensorShape> & inputShapes,const TensorShape & outputShape,ComparisonOperation operation,const float qScale=1.0f,const int32_t qOffset=0)23 INetworkPtr CreateComparisonNetwork(const std::vector<TensorShape>& inputShapes,
24 const TensorShape& outputShape,
25 ComparisonOperation operation,
26 const float qScale = 1.0f,
27 const int32_t qOffset = 0)
28 {
29 using namespace armnn;
30
31 INetworkPtr net(INetwork::Create());
32
33 ComparisonDescriptor descriptor(operation);
34 IConnectableLayer* comparisonLayer = net->AddComparisonLayer(descriptor, "comparison");
35
36 for (unsigned int i = 0; i < inputShapes.size(); ++i)
37 {
38 TensorInfo inputTensorInfo(inputShapes[i], ArmnnTypeInput, qScale, qOffset, true);
39 IConnectableLayer* input = net->AddInputLayer(armnn::numeric_cast<LayerBindingId>(i));
40 Connect(input, comparisonLayer, inputTensorInfo, 0, i);
41 }
42
43 TensorInfo outputTensorInfo(outputShape, DataType::Boolean, qScale, qOffset);
44 IConnectableLayer* output = net->AddOutputLayer(0, "output");
45 Connect(comparisonLayer, output, outputTensorInfo, 0, 0);
46
47 return net;
48 }
49
50 template<armnn::DataType ArmnnInType,
51 typename TInput = armnn::ResolveType<ArmnnInType>>
ComparisonSimpleEndToEnd(const std::vector<BackendId> & backends,ComparisonOperation operation,const std::vector<uint8_t> expectedOutput)52 void ComparisonSimpleEndToEnd(const std::vector<BackendId>& backends,
53 ComparisonOperation operation,
54 const std::vector<uint8_t> expectedOutput)
55 {
56 using namespace armnn;
57
58 const std::vector<TensorShape> inputShapes{{ 2, 2, 2, 2 }, { 2, 2, 2, 2 }};
59 const TensorShape& outputShape = { 2, 2, 2, 2 };
60
61 // Builds up the structure of the network
62 INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation);
63
64 CHECK(net);
65
66 const std::vector<TInput> input0({ 1, 1, 1, 1, 5, 5, 5, 5,
67 3, 3, 3, 3, 4, 4, 4, 4 });
68
69 const std::vector<TInput> input1({ 1, 1, 1, 1, 3, 3, 3, 3,
70 5, 5, 5, 5, 4, 4, 4, 4 });
71
72 std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }};
73 std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }};
74
75 EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends);
76 }
77
78 template<armnn::DataType ArmnnInType,
79 typename TInput = armnn::ResolveType<ArmnnInType>>
ComparisonBroadcastEndToEnd(const std::vector<BackendId> & backends,ComparisonOperation operation,const std::vector<uint8_t> expectedOutput)80 void ComparisonBroadcastEndToEnd(const std::vector<BackendId>& backends,
81 ComparisonOperation operation,
82 const std::vector<uint8_t> expectedOutput)
83 {
84 using namespace armnn;
85
86 const std::vector<TensorShape> inputShapes{{ 1, 2, 2, 3 }, { 1, 1, 1, 3 }};
87 const TensorShape& outputShape = { 1, 2, 2, 3 };
88
89 // Builds up the structure of the network
90 INetworkPtr net = CreateComparisonNetwork<ArmnnInType>(inputShapes, outputShape, operation);
91
92 const std::vector<TInput> input0({ 1, 2, 3, 1, 0, 6,
93 7, 8, 9, 10, 11, 12 });
94
95 const std::vector<TInput> input1({ 1, 1, 3 });
96
97 std::map<int, std::vector<TInput>> inputTensorData = {{ 0, input0 }, { 1, input1 }};
98 std::map<int, std::vector<uint8_t>> expectedOutputData = {{ 0, expectedOutput }};
99
100 EndToEndLayerTestImpl<ArmnnInType, DataType::Boolean>(move(net), inputTensorData, expectedOutputData, backends);
101 }
102
103 } // anonymous namespace
104