1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #pragma once
7
8 #include <armnnTestUtils/LayerTestResult.hpp>
9
10 #include <armnnUtils/QuantizeHelper.hpp>
11 #include <ResolveType.hpp>
12
13
14 #include <armnn/backends/IBackendInternal.hpp>
15 #include <armnn/backends/WorkloadFactory.hpp>
16
17 #include <armnnTestUtils/TensorCopyUtils.hpp>
18 #include <backendsCommon/test/WorkloadFactoryHelper.hpp>
19 #include <armnnTestUtils/WorkloadTestUtils.hpp>
20
21 #include <armnnTestUtils/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 std::vector<T> input = armnnUtils::QuantizedVector<T>(inputData,
65 inputTensorInfo.GetQuantizationScale(),
66 inputTensorInfo.GetQuantizationOffset());
67
68 std::vector<T> alpha = armnnUtils::QuantizedVector<T>(alphaData,
69 alphaTensorInfo.GetQuantizationScale(),
70 alphaTensorInfo.GetQuantizationOffset());
71
72 std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
73 std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>(outputExpectedData,
74 outputTensorInfo.GetQuantizationScale(),
75 outputTensorInfo.GetQuantizationOffset());
76
77 std::unique_ptr <armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
78 std::unique_ptr <armnn::ITensorHandle> alphaHandle = tensorHandleFactory.CreateTensorHandle(alphaTensorInfo);
79 std::unique_ptr <armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
80
81 armnn::PreluQueueDescriptor descriptor;
82 armnn::WorkloadInfo info;
83 AddInputToWorkload (descriptor, info, inputTensorInfo, inputHandle.get());
84 AddInputToWorkload (descriptor, info, alphaTensorInfo, alphaHandle.get());
85 AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
86
87 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Prelu,
88 descriptor,
89 info);
90
91 inputHandle->Allocate();
92 alphaHandle->Allocate();
93 outputHandle->Allocate();
94
95 CopyDataToITensorHandle(inputHandle.get(), input.data());
96 CopyDataToITensorHandle(alphaHandle.get(), alpha.data());
97
98 workload->Execute();
99
100 CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
101
102 return LayerTestResult<T, 4>(actualOutput,
103 expectedOutput,
104 outputHandle->GetShape(),
105 outputTensorInfo.GetShape());
106 }
107