1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
|
//
// Copyright © 2019 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "LayerTestResult.hpp"
#include <armnn/ArmNN.hpp>
#include <ResolveType.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/Workload.hpp>
#include <backendsCommon/WorkloadData.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <backendsCommon/test/DataTypeUtils.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
#include <test/TensorHelpers.hpp>
#include <memory>
std::unique_ptr<armnn::IWorkload> CreateWorkload(
const armnn::IWorkloadFactory& workloadFactory,
const armnn::WorkloadInfo& info,
const armnn::ElementwiseUnaryQueueDescriptor& descriptor);
template <std::size_t NumDims,
armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, NumDims> ElementwiseUnaryTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
armnn::UnaryOperation op,
const unsigned int shape[NumDims],
std::vector<float> values,
float quantScale,
int quantOffset,
const unsigned int outShape[NumDims],
std::vector<float> outValues,
const armnn::ITensorHandleFactory& tensorHandleFactory,
float outQuantScale,
int outQuantOffset)
{
armnn::TensorInfo inputTensorInfo{NumDims, shape, ArmnnType};
armnn::TensorInfo outputTensorInfo{NumDims, outShape, ArmnnType};
inputTensorInfo.SetQuantizationScale(quantScale);
inputTensorInfo.SetQuantizationOffset(quantOffset);
outputTensorInfo.SetQuantizationScale(outQuantScale);
outputTensorInfo.SetQuantizationOffset(outQuantOffset);
std::vector<T> input = ConvertToDataType<ArmnnType>(values, inputTensorInfo);
std::vector<T> expectedOutput = ConvertToDataType<ArmnnType>(outValues, inputTensorInfo);
std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::ElementwiseUnaryDescriptor desc(op);
armnn::ElementwiseUnaryQueueDescriptor qDesc;
qDesc.m_Parameters = desc;
armnn::WorkloadInfo info;
AddInputToWorkload(qDesc, info, inputTensorInfo, inputHandle.get());
AddOutputToWorkload(qDesc, info, outputTensorInfo, outputHandle.get());
auto workload = CreateWorkload(workloadFactory, info, qDesc);
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.data());
workload->PostAllocationConfigure();
ExecuteWorkload(*workload, memoryManager);
CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
return LayerTestResult<T, NumDims>(actualOutput,
expectedOutput,
outputHandle->GetShape(),
outputTensorInfo.GetShape());
}
template <std::size_t NumDims,
armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, NumDims> ElementwiseUnaryTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
armnn::UnaryOperation op,
const unsigned int shape[NumDims],
std::vector<float> values,
const unsigned int outShape[NumDims],
std::vector<float> outValues,
const armnn::ITensorHandleFactory& tensorHandleFactory,
float quantScale = 1.0f,
int quantOffset = 0)
{
return ElementwiseUnaryTestHelper<NumDims, ArmnnType>(
workloadFactory,
memoryManager,
op,
shape,
values,
quantScale,
quantOffset,
outShape,
outValues,
tensorHandleFactory,
quantScale,
quantOffset);
}
|