ArmNN
 21.02
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 <backendsCommon/test/DataTypeUtils.hpp>
9 #include <backendsCommon/test/TensorCopyUtils.hpp>
10 #include <backendsCommon/test/WorkloadTestUtils.hpp>
11 
12 #include <test/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 = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
32 
33  LayerTestResult<float, 4> result(outputTensorInfo);
34  result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData);
35 
36  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
37  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
38 
39  armnn::ReduceQueueDescriptor descriptor;
40  std::vector<uint32_t> updated_idx;
41  uint32_t resolvedAxis = 0;
42  for (uint32_t i = 0; i < vAxis.size(); ++i)
43  {
44  if (vAxis[i] < 0)
45  {
46  resolvedAxis = inputTensorInfo.GetNumDimensions() + static_cast<uint32_t>(vAxis[i]);
47  } else
48  {
49  resolvedAxis = static_cast<uint32_t>(vAxis[i]);
50  }
51 
52  updated_idx.push_back(resolvedAxis);
53  }
54 
55  descriptor.m_Parameters.m_vAxis = updated_idx;
56  descriptor.m_Parameters.m_ReduceOperation = reduceOperation;
57  descriptor.m_Parameters.m_KeepDims = keepDims;
58  armnn::WorkloadInfo info;
59 
60  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
61  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
62 
63  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateReduce(descriptor, info);
64 
65  inputHandle->Allocate();
66  outputHandle->Allocate();
67 
68  CopyDataToITensorHandle(inputHandle.get(), inputTensor.origin());
69 
70  workload->Execute();
71 
72  CopyDataFromITensorHandle(result.output.origin(), outputHandle.get());
73 
74  return result;
75 }
76 
77 } // namespace
78 
79 template<armnn::DataType ArmnnType, typename T>
80 LayerTestResult<float, 4> ReduceSumSimpleTest(
81  armnn::IWorkloadFactory& workloadFactory,
82  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
83  const armnn::ITensorHandleFactory& tensorHandleFactory)
84 {
85  const armnn::TensorShape inputShape{ 1, 1, 1, 5 };
86  const armnn::TensorShape outputShape{ 1, 1, 1, 1};
87 
88  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
89 
90  if (armnn::IsQuantizedType<T>())
91  {
92  inputTensorInfo.SetQuantizationScale(1.0f);
93  inputTensorInfo.SetQuantizationOffset(0);
94  }
95 
96  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
97 
98  std::vector<float> inputValues({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f });
99  std::vector<float> outputValues({ 34.0f });
100 
101  return ReduceTestCommon<ArmnnType>(workloadFactory,
102  memoryManager,
103  tensorHandleFactory,
104  inputTensorInfo,
105  outputTensorInfo,
106  inputValues,
107  outputValues,
108  { -1 },
109  armnn::ReduceOperation::Sum);
110 }
111 
112 template<armnn::DataType ArmnnType, typename T>
113 LayerTestResult<float, 4> ReduceSumSingleAxisTest1(
114  armnn::IWorkloadFactory& workloadFactory,
115  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
116  const armnn::ITensorHandleFactory& tensorHandleFactory)
117 {
118  const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
119  const armnn::TensorShape outputShape{ 1, 1, 2, 4};
120 
121  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
122 
123  if (armnn::IsQuantizedType<T>())
124  {
125  inputTensorInfo.SetQuantizationScale(1.0f);
126  inputTensorInfo.SetQuantizationOffset(0);
127  }
128 
129  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
130 
131  std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f,
132  5.0f, 6.0f, 7.0f, 8.0f,
133 
134  10.0f, 20.0f, 30.0f, 40.0f,
135  50.0f, 60.0f, 70.0f, 80.0f,
136 
137  100.0f, 200.0f, 300.0f, 400.0f,
138  500.0f, 600.0f, 700.0f, 800.0f });
139  std::vector<float> outputValues({ 111.0f, 222.0f, 333.0f, 444.0f,
140  555.0f, 666.0f, 777.0f, 888.0f });
141 
142  return ReduceTestCommon<ArmnnType>(workloadFactory,
143  memoryManager,
144  tensorHandleFactory,
145  inputTensorInfo,
146  outputTensorInfo,
147  inputValues,
148  outputValues,
149  { 1 },
150  armnn::ReduceOperation::Sum);
151 }
152 
153 template<armnn::DataType ArmnnType, typename T>
154 LayerTestResult<float, 4> ReduceSumSingleAxisTest2(
155  armnn::IWorkloadFactory& workloadFactory,
156  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
157  const armnn::ITensorHandleFactory& tensorHandleFactory)
158 {
159  const armnn::TensorShape inputShape{ 1, 6, 3, 4 };
160  const armnn::TensorShape outputShape{ 1, 1, 3, 4};
161 
162  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
163 
164  if (armnn::IsQuantizedType<T>())
165  {
166  inputTensorInfo.SetQuantizationScale(1.0f);
167  inputTensorInfo.SetQuantizationOffset(0);
168  }
169 
170  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
171 
172  std::vector<float> inputValues( {7, 8, 6, 1,
173  1, 1, 8, 7,
174  3, 7, 7, 7,
175 
176  6, 8, 4, 7,
177  3, 8, 7, 3,
178  5, 8, 8, 8,
179 
180 
181  7, 8, 2, 7,
182  3, 8, 5, 6,
183  8, 4, 2, 7,
184 
185  1, 6, 7, 2,
186  8, 3, 3, 1,
187  7, 6, 2, 6,
188 
189 
190  5, 3, 4, 8,
191  7, 8, 2, 4,
192  6, 6, 2, 8,
193 
194  2, 2, 7, 2,
195  5, 3, 6, 3,
196  6, 1, 8, 8});
197  std::vector<float> outputValues({ 28.0f, 35.0f, 30.0f, 27.0f,
198  27.0f, 31.0f, 31.0f, 24.0f,
199  35.0f, 32.0f, 29.0f, 44.0f});
200 
201  return ReduceTestCommon<ArmnnType>(workloadFactory,
202  memoryManager,
203  tensorHandleFactory,
204  inputTensorInfo,
205  outputTensorInfo,
206  inputValues,
207  outputValues,
208  { 1 },
209  armnn::ReduceOperation::Sum);
210 }
211 
212 template<armnn::DataType ArmnnType, typename T>
213 LayerTestResult<float, 4> ReduceSumSingleAxisTest3(
214  armnn::IWorkloadFactory& workloadFactory,
215  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
216  const armnn::ITensorHandleFactory& tensorHandleFactory)
217 {
218  const armnn::TensorShape inputShape{ 1, 6, 3, 4 };
219  const armnn::TensorShape outputShape{ 1, 6, 3, 1};
220 
221  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
222 
223  if (armnn::IsQuantizedType<T>())
224  {
225  inputTensorInfo.SetQuantizationScale(1.0f);
226  inputTensorInfo.SetQuantizationOffset(0);
227  }
228 
229  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
230 
231  std::vector<float> inputValues( {7, 8, 6, 1,
232  1, 1, 8, 7,
233  3, 7, 7, 7,
234 
235  6, 8, 4, 7,
236  3, 8, 7, 3,
237  5, 8, 8, 8,
238 
239 
240  7, 8, 2, 7,
241  3, 8, 5, 6,
242  8, 4, 2, 7,
243 
244  1, 6, 7, 2,
245  8, 3, 3, 1,
246  7, 6, 2, 6,
247 
248 
249  5, 3, 4, 8,
250  7, 8, 2, 4,
251  6, 6, 2, 8,
252 
253  2, 2, 7, 2,
254  5, 3, 6, 3,
255  6, 1, 8, 8});
256  std::vector<float> outputValues({ 22.0f, 17.0f, 24.0f,
257  25.0f, 21.0f, 29.0f,
258 
259  24.0f, 22.0f, 21.0f,
260  16.0f, 15.0f, 21.0f,
261 
262  20.0f, 21.0f, 22.0f,
263  13.0f, 17.0f, 23.0f});
264 
265  return ReduceTestCommon<ArmnnType>(workloadFactory,
266  memoryManager,
267  tensorHandleFactory,
268  inputTensorInfo,
269  outputTensorInfo,
270  inputValues,
271  outputValues,
272  { 3 },
273  armnn::ReduceOperation::Sum,
274  true);
275 }
276 
277 template<armnn::DataType ArmnnType, typename T>
278 LayerTestResult<float, 4> ReduceSumMultipleAxisTest(
279  armnn::IWorkloadFactory& workloadFactory,
280  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
281  const armnn::ITensorHandleFactory& tensorHandleFactory)
282 {
283  const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
284  const armnn::TensorShape outputShape{ 1, 1, 1, 4};
285 
286  armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
287 
288  if (armnn::IsQuantizedType<T>())
289  {
290  inputTensorInfo.SetQuantizationScale(1.0f);
291  inputTensorInfo.SetQuantizationOffset(0);
292  }
293 
294  armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
295 
296  std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f,
297  5.0f, 6.0f, 7.0f, 8.0f,
298 
299  10.0f, 20.0f, 30.0f, 40.0f,
300  50.0f, 60.0f, 70.0f, 80.0f,
301 
302  100.0f, 200.0f, 300.0f, 400.0f,
303  500.0f, 600.0f, 700.0f, 800.0f });
304  std::vector<float> outputValues({ 666.0f, 888.0f, 1110.0f, 1332.0f });
305 
306  return ReduceTestCommon<ArmnnType>(workloadFactory,
307  memoryManager,
308  tensorHandleFactory,
309  inputTensorInfo,
310  outputTensorInfo,
311  inputValues,
312  outputValues,
313  { 1, 2 },
314  armnn::ReduceOperation::Sum);
315 }
316 
317 // Explicit template specializations
318 
319 template LayerTestResult<float, 4>
320 ReduceSumSimpleTest<armnn::DataType::Float32>(
321  armnn::IWorkloadFactory& workloadFactory,
322  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
323  const armnn::ITensorHandleFactory& tensorHandleFactory);
324 
325 template LayerTestResult<float, 4>
326 ReduceSumSingleAxisTest1<armnn::DataType::Float32>(
327  armnn::IWorkloadFactory& workloadFactory,
328  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
329  const armnn::ITensorHandleFactory& tensorHandleFactory);
330 
331 template LayerTestResult<float, 4>
332 ReduceSumSingleAxisTest2<armnn::DataType::Float32>(
333  armnn::IWorkloadFactory& workloadFactory,
334  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
335  const armnn::ITensorHandleFactory& tensorHandleFactory);
336 
337 template LayerTestResult<float, 4>
338 ReduceSumSingleAxisTest3<armnn::DataType::Float32>(
339  armnn::IWorkloadFactory& workloadFactory,
340  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
341  const armnn::ITensorHandleFactory& tensorHandleFactory);
342 
343 template LayerTestResult<float, 4>
344 ReduceSumMultipleAxisTest<armnn::DataType::Float32>(
345  armnn::IWorkloadFactory& workloadFactory,
346  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
347  const armnn::ITensorHandleFactory& tensorHandleFactory);
TensorCopyUtils.hpp
ReduceSumMultipleAxisTest
LayerTestResult< float, 4 > ReduceSumMultipleAxisTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:278
ReduceSumSimpleTest
LayerTestResult< float, 4 > ReduceSumSimpleTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:80
ReduceSumSingleAxisTest1
LayerTestResult< float, 4 > ReduceSumSingleAxisTest1(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:113
WorkloadTestUtils.hpp
armnn::ReduceDescriptor::m_KeepDims
bool m_KeepDims
if true then output shape has no change.
Definition: Descriptors.hpp:1320
armnn::ReduceDescriptor::m_ReduceOperation
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
Definition: Descriptors.hpp:1324
armnn::IgnoreUnused
void IgnoreUnused(Ts &&...)
Definition: IgnoreUnused.hpp:14
ReduceSumTestImpl.hpp
TensorHelpers.hpp
armnn::ReduceOperation
ReduceOperation
Definition: Types.hpp:111
armnn::IBackendInternal::IMemoryManagerSharedPtr
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
Definition: IBackendInternal.hpp:92
armnn::TensorInfo::SetQuantizationScale
void SetQuantizationScale(float scale)
Definition: Tensor.cpp:464
ReduceSumSingleAxisTest3
LayerTestResult< float, 4 > ReduceSumSingleAxisTest3(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:213
CopyDataFromITensorHandle
void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)
Definition: TensorCopyUtils.cpp:14
armnn::ReduceDescriptor::m_vAxis
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
Definition: Descriptors.hpp:1322
DataTypeUtils.hpp
armnn::WorkloadInfo
Contains information about inputs and outputs to a layer.
Definition: WorkloadInfo.hpp:16
armnn::TensorInfo::SetQuantizationOffset
void SetQuantizationOffset(int32_t offset)
Definition: Tensor.cpp:480
ReduceSumSingleAxisTest2
LayerTestResult< float, 4 > ReduceSumSingleAxisTest2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)
Definition: ReduceSumTestImpl.cpp:154
CopyDataToITensorHandle
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
Definition: TensorCopyUtils.cpp:9