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Aron Virginas-Tar00d306e2019-08-28 18:08:46 +01001//
2// Copyright © 2017 Arm Ltd. All rights reserved.
3// SPDX-License-Identifier: MIT
4//
5
6#pragma once
7
8#include "LayerTestResult.hpp"
9
Aron Virginas-Tar48623a02019-10-22 10:00:28 +010010#include <QuantizeHelper.hpp>
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010011#include <ResolveType.hpp>
12
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010013
Matteo Martincighe5b8eb92019-11-28 15:45:42 +000014#include <armnn/backends/IBackendInternal.hpp>
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010015#include <backendsCommon/WorkloadFactory.hpp>
16
17#include <backendsCommon/test/TensorCopyUtils.hpp>
18#include <backendsCommon/test/WorkloadTestUtils.hpp>
19
20#include <test/TensorHelpers.hpp>
21
22template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
23LayerTestResult<T, 4> PreluTest(
24 armnn::IWorkloadFactory& workloadFactory,
25 const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
26{
Jan Eilers8eb25602020-03-09 12:13:48 +000027 IgnoreUnused(memoryManager);
Derek Lambertic374ff02019-12-10 21:57:35 +000028
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010029 armnn::TensorInfo inputTensorInfo ({ 1, 2, 2, 3 }, ArmnnType);
30 armnn::TensorInfo alphaTensorInfo ({ 1, 1, 1, 3 }, ArmnnType);
31 armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 3 }, ArmnnType);
32
33 if (armnn::IsQuantizedType<T>())
34 {
35 inputTensorInfo.SetQuantizationScale(0.25f);
36 inputTensorInfo.SetQuantizationOffset(128);
37 alphaTensorInfo.SetQuantizationScale(0.25f);
38 alphaTensorInfo.SetQuantizationOffset(50);
39 outputTensorInfo.SetQuantizationScale(0.5f);
40 outputTensorInfo.SetQuantizationOffset(120);
41 }
42
43 std::vector<float> inputData
44 {
45 // Expected quantized values:
46 // 128, 128, 128, 132, 132, 132, 124, 124, 124, 120, 120, 120
47 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -2.0f, -2.0f, -2.0f
48 };
49 std::vector<float> alphaData
50 {
51 // Expected quantized values:
52 // 50, 54, 58
53 0.0f, 1.0f, 2.0f
54 };
55 std::vector<float> outputExpectedData =
56 {
57 // Expected quantized values:
58 // 20, 120, 120, 122, 122, 122, 120, 118, 116, 120, 116, 112
59 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, -1.0f, -2.0f, 0.0f, -2.0f, -4.0f
60 };
61
Aron Virginas-Tar48623a02019-10-22 10:00:28 +010062 auto input = MakeTensor<T, 4>(inputTensorInfo,
63 armnnUtils::QuantizedVector<T>(inputData,
64 inputTensorInfo.GetQuantizationScale(),
65 inputTensorInfo.GetQuantizationOffset()));
66
67 auto alpha = MakeTensor<T, 4>(alphaTensorInfo,
68 armnnUtils::QuantizedVector<T>(alphaData,
69 alphaTensorInfo.GetQuantizationScale(),
70 alphaTensorInfo.GetQuantizationOffset()));
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010071
72 LayerTestResult<T, 4> result(outputTensorInfo);
Aron Virginas-Tar48623a02019-10-22 10:00:28 +010073 result.outputExpected =
74 MakeTensor<T, 4>(outputTensorInfo,
75 armnnUtils::QuantizedVector<T>(outputExpectedData,
76 outputTensorInfo.GetQuantizationScale(),
77 outputTensorInfo.GetQuantizationOffset()));
Aron Virginas-Tar00d306e2019-08-28 18:08:46 +010078
79 std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
80 std::unique_ptr <armnn::ITensorHandle> alphaHandle = workloadFactory.CreateTensorHandle(alphaTensorInfo);
81 std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
82
83 armnn::PreluQueueDescriptor descriptor;
84 armnn::WorkloadInfo info;
85 AddInputToWorkload (descriptor, info, inputTensorInfo, inputHandle.get());
86 AddInputToWorkload (descriptor, info, alphaTensorInfo, alphaHandle.get());
87 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
88
89 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePrelu(descriptor, info);
90
91 inputHandle->Allocate();
92 alphaHandle->Allocate();
93 outputHandle->Allocate();
94
95 CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
96 CopyDataToITensorHandle(alphaHandle.get(), &alpha[0][0][0][0]);
97
98 workload->Execute();
99
100 CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
101
102 return result;
103}