1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #pragma once
7
8 #include "LayerTestResult.hpp"
9
10 #include <QuantizeHelper.hpp>
11 #include <ResolveType.hpp>
12
13
14 #include <armnn/backends/IBackendInternal.hpp>
15 #include <backendsCommon/WorkloadFactory.hpp>
16
17 #include <backendsCommon/test/TensorCopyUtils.hpp>
18 #include <backendsCommon/test/WorkloadFactoryHelper.hpp>
19 #include <backendsCommon/test/WorkloadTestUtils.hpp>
20
21 #include <test/TensorHelpers.hpp>
22
23 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
PreluTest(armnn::IWorkloadFactory & workloadFactory,const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,const armnn::ITensorHandleFactory & tensorHandleFactory)24 LayerTestResult<T, 4> PreluTest(
25 armnn::IWorkloadFactory& workloadFactory,
26 const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
27 const armnn::ITensorHandleFactory& tensorHandleFactory)
28 {
29 IgnoreUnused(memoryManager);
30
31 armnn::TensorInfo inputTensorInfo ({ 1, 2, 2, 3 }, ArmnnType);
32 armnn::TensorInfo alphaTensorInfo ({ 1, 1, 1, 3 }, ArmnnType);
33 armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 3 }, ArmnnType);
34
35 if (armnn::IsQuantizedType<T>())
36 {
37 inputTensorInfo.SetQuantizationScale(0.25f);
38 inputTensorInfo.SetQuantizationOffset(128);
39 alphaTensorInfo.SetQuantizationScale(0.25f);
40 alphaTensorInfo.SetQuantizationOffset(50);
41 outputTensorInfo.SetQuantizationScale(0.5f);
42 outputTensorInfo.SetQuantizationOffset(120);
43 }
44
45 std::vector<float> inputData
46 {
47 // Expected quantized values:
48 // 128, 128, 128, 132, 132, 132, 124, 124, 124, 120, 120, 120
49 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -2.0f, -2.0f, -2.0f
50 };
51 std::vector<float> alphaData
52 {
53 // Expected quantized values:
54 // 50, 54, 58
55 0.0f, 1.0f, 2.0f
56 };
57 std::vector<float> outputExpectedData =
58 {
59 // Expected quantized values:
60 // 20, 120, 120, 122, 122, 122, 120, 118, 116, 120, 116, 112
61 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, -1.0f, -2.0f, 0.0f, -2.0f, -4.0f
62 };
63
64 auto input = MakeTensor<T, 4>(inputTensorInfo,
65 armnnUtils::QuantizedVector<T>(inputData,
66 inputTensorInfo.GetQuantizationScale(),
67 inputTensorInfo.GetQuantizationOffset()));
68
69 auto alpha = MakeTensor<T, 4>(alphaTensorInfo,
70 armnnUtils::QuantizedVector<T>(alphaData,
71 alphaTensorInfo.GetQuantizationScale(),
72 alphaTensorInfo.GetQuantizationOffset()));
73
74 LayerTestResult<T, 4> result(outputTensorInfo);
75 result.outputExpected =
76 MakeTensor<T, 4>(outputTensorInfo,
77 armnnUtils::QuantizedVector<T>(outputExpectedData,
78 outputTensorInfo.GetQuantizationScale(),
79 outputTensorInfo.GetQuantizationOffset()));
80
81 std::unique_ptr <armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
82 std::unique_ptr <armnn::ITensorHandle> alphaHandle = tensorHandleFactory.CreateTensorHandle(alphaTensorInfo);
83 std::unique_ptr <armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
84
85 armnn::PreluQueueDescriptor descriptor;
86 armnn::WorkloadInfo info;
87 AddInputToWorkload (descriptor, info, inputTensorInfo, inputHandle.get());
88 AddInputToWorkload (descriptor, info, alphaTensorInfo, alphaHandle.get());
89 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
90
91 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePrelu(descriptor, info);
92
93 inputHandle->Allocate();
94 alphaHandle->Allocate();
95 outputHandle->Allocate();
96
97 CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
98 CopyDataToITensorHandle(alphaHandle.get(), &alpha[0][0][0][0]);
99
100 workload->Execute();
101
102 CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
103
104 return result;
105 }
106