1 //
2 // Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #pragma once
6
7 #include <ResolveType.hpp>
8
9 #include <armnn/INetwork.hpp>
10
11 #include <doctest/doctest.h>
12 #include <CommonTestUtils.hpp>
13
14 namespace
15 {
16
17 template<typename armnn::DataType DataType>
CreateBatchMatMulNetwork(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 CreateBatchMatMulNetwork(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 BatchMatMulDescriptor batchMatMulDesc;
34 batchMatMulDesc.m_TransposeX = false;
35 batchMatMulDesc.m_TransposeY = true;
36
37 IConnectableLayer* batchMatMul = network->AddBatchMatMulLayer(batchMatMulDesc, "batchMatMul");
38 IConnectableLayer* inputX = network->AddInputLayer(0, "inputX");
39 IConnectableLayer* inputY = network->AddInputLayer(1, "inputY");
40 IConnectableLayer* output = network->AddOutputLayer(0, "output");
41
42 Connect(inputX, batchMatMul, inputXTensorInfo, 0, 0);
43 Connect(inputY, batchMatMul, inputYTensorInfo, 0, 1);
44 Connect(batchMatMul, output, outputTensorInfo, 0, 0);
45
46 return network;
47 }
48
49 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
BatchMatMulEndToEnd(const std::vector<armnn::BackendId> & backends)50 void BatchMatMulEndToEnd(const std::vector<armnn::BackendId>& backends)
51 {
52 using namespace armnn;
53
54 const TensorShape& inputXShape = { 2, 2, 2 };
55 const TensorShape& inputYShape = { 2, 2, 2 };
56 const TensorShape& outputShape = { 2, 2, 2 };
57
58 INetworkPtr network = CreateBatchMatMulNetwork<ArmnnType>(inputXShape, inputYShape, outputShape);
59
60 CHECK(network);
61
62 std::vector<T> inputXData{ 1, 2,
63 3, 4,
64
65 9, 10,
66 11, 12 };
67 std::vector<T> inputYData{ 5, 7,
68 6, 8,
69
70 13, 15,
71 14, 16 };
72 std::vector<T> expectedOutput{ 19, 22,
73 43, 50,
74
75 267, 286,
76 323, 346 };
77
78 std::map<int, std::vector<T>> inputTensorData = {{ 0, inputXData }, {1, inputYData}};
79 std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
80
81 EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
82 }
83
84 } // anonymous namespace