ArmNN
 22.02
ReduceSumTestImpl.cpp
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1 //
2 // Copyright © 2020 Samsung Electronics Co Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "ReduceSumTestImpl.hpp"
7 
8 #include <DataTypeUtils.hpp>
9 #include <armnnTestUtils/TensorCopyUtils.hpp>
10 #include <armnnTestUtils/WorkloadTestUtils.hpp>
11 
12 #include <armnnTestUtils/TensorHelpers.hpp>
13 
14 namespace
15 {
16 
17 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
18 LayerTestResult<float, 4> ReduceTestCommon(
19  armnn::IWorkloadFactory& workloadFactory,
20  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
21  const armnn::ITensorHandleFactory& tensorHandleFactory,
22  const armnn::TensorInfo inputTensorInfo,
23  const armnn::TensorInfo outputTensorInfo,
24  const std::vector<float>& inputData,
25  const std::vector<float>& outputData,
26  const std::vector<int32_t> vAxis,
27  const armnn::ReduceOperation reduceOperation,
28  bool keepDims = false)
29 {
30  IgnoreUnused(memoryManager);
31  auto inputTensor = ConvertToDataType<ArmnnType>(inputData, inputTensorInfo);
32 
33  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());
34 
35  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
36  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
37 
38  armnn::ReduceQueueDescriptor descriptor;
39  std::vector<uint32_t> updated_idx;
40  uint32_t resolvedAxis = 0;
41  for (uint32_t i = 0; i < vAxis.size(); ++i)
42  {
43  if (vAxis[i] < 0)
44  {
45  resolvedAxis = inputTensorInfo.GetNumDimensions() + static_cast<uint32_t>(vAxis[i]);
46  } else
47  {
48  resolvedAxis = static_cast<uint32_t>(vAxis[i]);
49  }
50 
51  updated_idx.push_back(resolvedAxis);
52  }
53 
54  descriptor.m_Parameters.m_vAxis = updated_idx;
55  descriptor.m_Parameters.m_ReduceOperation = reduceOperation;
56  descriptor.m_Parameters.m_KeepDims = keepDims;
57  armnn::WorkloadInfo info;
58 
59  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
60  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
61 
62  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Reduce,
63  descriptor,
64  info);
65 
66  inputHandle->Allocate();
67  outputHandle->Allocate();
68 
69  CopyDataToITensorHandle(inputHandle.get(), inputTensor.data());
70 
71  workload->Execute();
72 
73  CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
74 
75  return LayerTestResult<float, 4>(actualOutput,
76  outputData,
77  outputHandle->GetShape(),
78  outputTensorInfo.GetShape());
79 }
80 
81 } // namespace
82 
83 template<armnn::DataType ArmnnType, typename T>
84 LayerTestResult<float, 4> ReduceSumSimpleTest(
85  armnn::IWorkloadFactory& workloadFactory,
86  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
87  const armnn::ITensorHandleFactory& tensorHandleFactory)
88 {
89  const armnn::TensorShape inputShape{ 1, 1, 1, 5 };
90  const armnn::TensorShape outputShape{ 1, 1, 1, 1};
91 
92  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
93 
94  if (armnn::IsQuantizedType<T>())
95  {
96  inputTensorInfo.SetQuantizationScale(1.0f);
97  inputTensorInfo.SetQuantizationOffset(0);
98  }
99 
100  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
101 
102  std::vector<float> inputValues({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f });
103  std::vector<float> outputValues({ 34.0f });
104 
105  return ReduceTestCommon<ArmnnType>(workloadFactory,
106  memoryManager,
107  tensorHandleFactory,
108  inputTensorInfo,
109  outputTensorInfo,
110  inputValues,
111  outputValues,
112  { -1 },
113  armnn::ReduceOperation::Sum);
114 }
115 
116 template<armnn::DataType ArmnnType, typename T>
117 LayerTestResult<float, 4> ReduceSumSingleAxisTest1(
118  armnn::IWorkloadFactory& workloadFactory,
119  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
120  const armnn::ITensorHandleFactory& tensorHandleFactory)
121 {
122  const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
123  const armnn::TensorShape outputShape{ 1, 1, 2, 4};
124 
125  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
126 
127  if (armnn::IsQuantizedType<T>())
128  {
129  inputTensorInfo.SetQuantizationScale(1.0f);
130  inputTensorInfo.SetQuantizationOffset(0);
131  }
132 
133  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
134 
135  std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f,
136  5.0f, 6.0f, 7.0f, 8.0f,
137 
138  10.0f, 20.0f, 30.0f, 40.0f,
139  50.0f, 60.0f, 70.0f, 80.0f,
140 
141  100.0f, 200.0f, 300.0f, 400.0f,
142  500.0f, 600.0f, 700.0f, 800.0f });
143  std::vector<float> outputValues({ 111.0f, 222.0f, 333.0f, 444.0f,
144  555.0f, 666.0f, 777.0f, 888.0f });
145 
146  return ReduceTestCommon<ArmnnType>(workloadFactory,
147  memoryManager,
148  tensorHandleFactory,
149  inputTensorInfo,
150  outputTensorInfo,
151  inputValues,
152  outputValues,
153  { 1 },
154  armnn::ReduceOperation::Sum);
155 }
156 
157 template<armnn::DataType ArmnnType, typename T>
158 LayerTestResult<float, 4> ReduceSumSingleAxisTest2(
159  armnn::IWorkloadFactory& workloadFactory,
160  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
161  const armnn::ITensorHandleFactory& tensorHandleFactory)
162 {
163  const armnn::TensorShape inputShape{ 1, 6, 3, 4 };
164  const armnn::TensorShape outputShape{ 1, 1, 3, 4};
165 
166  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
167 
168  if (armnn::IsQuantizedType<T>())
169  {
170  inputTensorInfo.SetQuantizationScale(1.0f);
171  inputTensorInfo.SetQuantizationOffset(0);
172  }
173 
174  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
175 
176  std::vector<float> inputValues( {7, 8, 6, 1,
177  1, 1, 8, 7,
178  3, 7, 7, 7,
179 
180  6, 8, 4, 7,
181  3, 8, 7, 3,
182  5, 8, 8, 8,
183 
184 
185  7, 8, 2, 7,
186  3, 8, 5, 6,
187  8, 4, 2, 7,
188 
189  1, 6, 7, 2,
190  8, 3, 3, 1,
191  7, 6, 2, 6,
192 
193 
194  5, 3, 4, 8,
195  7, 8, 2, 4,
196  6, 6, 2, 8,
197 
198  2, 2, 7, 2,
199  5, 3, 6, 3,
200  6, 1, 8, 8});
201  std::vector<float> outputValues({ 28.0f, 35.0f, 30.0f, 27.0f,
202  27.0f, 31.0f, 31.0f, 24.0f,
203  35.0f, 32.0f, 29.0f, 44.0f});
204 
205  return ReduceTestCommon<ArmnnType>(workloadFactory,
206  memoryManager,
207  tensorHandleFactory,
208  inputTensorInfo,
209  outputTensorInfo,
210  inputValues,
211  outputValues,
212  { 1 },
213  armnn::ReduceOperation::Sum);
214 }
215 
216 template<armnn::DataType ArmnnType, typename T>
217 LayerTestResult<float, 4> ReduceSumSingleAxisTest3(
218  armnn::IWorkloadFactory& workloadFactory,
219  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
220  const armnn::ITensorHandleFactory& tensorHandleFactory)
221 {
222  const armnn::TensorShape inputShape{ 1, 6, 3, 4 };
223  const armnn::TensorShape outputShape{ 1, 6, 3, 1};
224 
225  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
226 
227  if (armnn::IsQuantizedType<T>())
228  {
229  inputTensorInfo.SetQuantizationScale(1.0f);
230  inputTensorInfo.SetQuantizationOffset(0);
231  }
232 
233  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
234 
235  std::vector<float> inputValues( {7, 8, 6, 1,
236  1, 1, 8, 7,
237  3, 7, 7, 7,
238 
239  6, 8, 4, 7,
240  3, 8, 7, 3,
241  5, 8, 8, 8,
242 
243 
244  7, 8, 2, 7,
245  3, 8, 5, 6,
246  8, 4, 2, 7,
247 
248  1, 6, 7, 2,
249  8, 3, 3, 1,
250  7, 6, 2, 6,
251 
252 
253  5, 3, 4, 8,
254  7, 8, 2, 4,
255  6, 6, 2, 8,
256 
257  2, 2, 7, 2,
258  5, 3, 6, 3,
259  6, 1, 8, 8});
260  std::vector<float> outputValues({ 22.0f, 17.0f, 24.0f,
261  25.0f, 21.0f, 29.0f,
262 
263  24.0f, 22.0f, 21.0f,
264  16.0f, 15.0f, 21.0f,
265 
266  20.0f, 21.0f, 22.0f,
267  13.0f, 17.0f, 23.0f});
268 
269  return ReduceTestCommon<ArmnnType>(workloadFactory,
270  memoryManager,
271  tensorHandleFactory,
272  inputTensorInfo,
273  outputTensorInfo,
274  inputValues,
275  outputValues,
276  { 3 },
277  armnn::ReduceOperation::Sum,
278  true);
279 }
280 
281 template<armnn::DataType ArmnnType, typename T>
282 LayerTestResult<float, 4> ReduceSumMultipleAxisTest(
283  armnn::IWorkloadFactory& workloadFactory,
284  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
285  const armnn::ITensorHandleFactory& tensorHandleFactory)
286 {
287  const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
288  const armnn::TensorShape outputShape{ 1, 1, 1, 4};
289 
290  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
291 
292  if (armnn::IsQuantizedType<T>())
293  {
294  inputTensorInfo.SetQuantizationScale(1.0f);
295  inputTensorInfo.SetQuantizationOffset(0);
296  }
297 
298  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
299 
300  std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f,
301  5.0f, 6.0f, 7.0f, 8.0f,
302 
303  10.0f, 20.0f, 30.0f, 40.0f,
304  50.0f, 60.0f, 70.0f, 80.0f,
305 
306  100.0f, 200.0f, 300.0f, 400.0f,
307  500.0f, 600.0f, 700.0f, 800.0f });
308  std::vector<float> outputValues({ 666.0f, 888.0f, 1110.0f, 1332.0f });
309 
310  return ReduceTestCommon<ArmnnType>(workloadFactory,
311  memoryManager,
312  tensorHandleFactory,
313  inputTensorInfo,
314  outputTensorInfo,
315  inputValues,
316  outputValues,
317  { 1, 2 },
318  armnn::ReduceOperation::Sum);
319 }
320 
321 // Explicit template specializations
322 
323 template LayerTestResult<float, 4>
324 ReduceSumSimpleTest<armnn::DataType::Float32>(
325  armnn::IWorkloadFactory& workloadFactory,
326  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
327  const armnn::ITensorHandleFactory& tensorHandleFactory);
328 
329 template LayerTestResult<float, 4>
330 ReduceSumSingleAxisTest1<armnn::DataType::Float32>(
331  armnn::IWorkloadFactory& workloadFactory,
332  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
333  const armnn::ITensorHandleFactory& tensorHandleFactory);
334 
335 template LayerTestResult<float, 4>
336 ReduceSumSingleAxisTest2<armnn::DataType::Float32>(
337  armnn::IWorkloadFactory& workloadFactory,
338  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
339  const armnn::ITensorHandleFactory& tensorHandleFactory);
340 
341 template LayerTestResult<float, 4>
342 ReduceSumSingleAxisTest3<armnn::DataType::Float32>(
343  armnn::IWorkloadFactory& workloadFactory,
344  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
345  const armnn::ITensorHandleFactory& tensorHandleFactory);
346 
347 template LayerTestResult<float, 4>
348 ReduceSumMultipleAxisTest<armnn::DataType::Float32>(
349  armnn::IWorkloadFactory& workloadFactory,
350  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
351  const armnn::ITensorHandleFactory& tensorHandleFactory);
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
ReduceSumMultipleAxisTest
LayerTestResult< float, 4 > ReduceSumMultipleAxisTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:282
ReduceSumSimpleTest
LayerTestResult< float, 4 > ReduceSumSimpleTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:84
ReduceSumSingleAxisTest1
LayerTestResult< float, 4 > ReduceSumSingleAxisTest1(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:117
armnn::ReduceDescriptor::m_KeepDims
bool m_KeepDims
if true then output shape has no change.
Definition: Descriptors.hpp:1499
armnn::ReduceDescriptor::m_ReduceOperation
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
Definition: Descriptors.hpp:1503
armnn::IgnoreUnused
void IgnoreUnused(Ts &&...)
Definition: IgnoreUnused.hpp:14
ReduceSumTestImpl.hpp
armnn::ReduceOperation
ReduceOperation
Definition: Types.hpp:130
armnn::IBackendInternal::IMemoryManagerSharedPtr
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
Definition: IBackendInternal.hpp:96
CopyDataFromITensorHandle
void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)
Definition: TensorCopyUtils.cpp:14
armnn::TensorInfo::SetQuantizationScale
void SetQuantizationScale(float scale)
Definition: Tensor.cpp:475
ReduceSumSingleAxisTest3
LayerTestResult< float, 4 > ReduceSumSingleAxisTest3(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:217
armnn::ReduceDescriptor::m_vAxis
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
Definition: Descriptors.hpp:1501
CopyDataToITensorHandle
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
Definition: TensorCopyUtils.cpp:9
armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16
armnn::TensorInfo::SetQuantizationOffset
void SetQuantizationOffset(int32_t offset)
Definition: Tensor.cpp:491
armnn::IWorkloadFactory::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
Definition: WorkloadFactory.cpp:1541
armnn::TensorInfo::GetNumDimensions
unsigned int GetNumDimensions() const
Definition: Tensor.hpp:195
armnn::ITensorHandleFactory::CreateTensorHandle
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0
ReduceSumSingleAxisTest2
LayerTestResult< float, 4 > ReduceSumSingleAxisTest2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:158
armnn::TensorInfo::GetNumElements
unsigned int GetNumElements() const
Definition: Tensor.hpp:196