ArmNN
 20.08
L2NormalizationTestImpl.cpp
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1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "L2NormalizationTestImpl.hpp"
7 
8 #include <QuantizeHelper.hpp>
9 #include <ResolveType.hpp>
10 
11 #include <armnnUtils/TensorUtils.hpp>
12 #include <armnnUtils/Permute.hpp>
13 
14 #include <backendsCommon/test/TensorCopyUtils.hpp>
15 #include <backendsCommon/test/WorkloadTestUtils.hpp>
16 
17 #include <test/TensorHelpers.hpp>
18 
19 namespace
20 {
21 
22 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
23 LayerTestResult<T, 4> L2NormalizationTestImpl(
24  armnn::IWorkloadFactory& workloadFactory,
25  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
26  const armnn::TensorShape& inputOutputTensorShape,
27  float scale,
28  int32_t offset,
29  const std::vector<float>& inputValues,
30  float outScale,
31  int32_t outOffset,
32  const std::vector<float>& expectedOutputValues,
33  const armnn::DataLayout layout,
34  float epsilon = 1e-12f)
35 {
36  IgnoreUnused(memoryManager);
37  const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, ArmnnType, scale, offset);
38  const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, ArmnnType, outScale, outOffset);
39 
40  // at this point if we require it permute the input data
41  const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
42  std::vector<float> inputData = inputValues;
43  if (layout == armnn::DataLayout::NHWC)
44  {
45  std::vector<float> tmp(inputData.size());
46  armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
47  inputData = tmp;
48  }
49 
50  auto inputTensor = MakeTensor<T, 4>(inputTensorInfo,
51  armnnUtils::QuantizedVector<T>(inputData,
52  inputTensorInfo.GetQuantizationScale(),
53  inputTensorInfo.GetQuantizationOffset()));
54 
55  std::vector<float> expectedOutputData = expectedOutputValues;
56  if (layout == armnn::DataLayout::NHWC)
57  {
58  std::vector<float> tmp(expectedOutputData.size());
59  armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputData.data(), tmp.data(),
60  sizeof(float));
61  expectedOutputData = tmp;
62  }
63 
64  LayerTestResult<T, 4> result(outputTensorInfo);
65  result.outputExpected =
66  MakeTensor<T, 4>(outputTensorInfo,
67  armnnUtils::QuantizedVector<T>(expectedOutputData,
68  outputTensorInfo.GetQuantizationScale(),
69  outputTensorInfo.GetQuantizationOffset()));
70 
71  ARMNN_NO_DEPRECATE_WARN_BEGIN
72  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
73  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
74  ARMNN_NO_DEPRECATE_WARN_END
75 
76  armnn::L2NormalizationQueueDescriptor descriptor;
77  descriptor.m_Parameters.m_Eps = epsilon;
78  descriptor.m_Parameters.m_DataLayout = layout;
79  armnn::WorkloadInfo info;
80 
81  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
82  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
83 
84  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateL2Normalization(descriptor, info);
85 
86  inputHandle->Allocate();
87  outputHandle->Allocate();
88 
89  CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]);
90 
91  workload->PostAllocationConfigure();
92  ExecuteWorkload(*workload, memoryManager);
93 
94  CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
95 
96  return result;
97 }
98 
99 float CalcInvL2Norm(std::initializer_list<float> elements)
100 {
101  const float reduction = std::accumulate(elements.begin(), elements.end(), 0.0f,
102  [](float acc, float element) { return acc + element * element; });
103  return 1.0f / sqrtf(reduction);
104 }
105 
106 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
107 LayerTestResult<T, 4> L2NormalizationEpsilonTestCommon(
108  armnn::IWorkloadFactory& workloadFactory,
109  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
110  float scale,
111  int32_t offset,
112  float outScale,
113  int32_t outOffset,
114  const armnn::DataLayout layout,
115  float epsilon)
116 {
117  // Width: 1
118  // Height: 1
119  // Channels: 3
120  // BatchSize: 1
121  unsigned int numberOfBatches = 1;
122  unsigned int numberOfChannels = 3;
123  unsigned int height = 1;
124  unsigned int width = 1;
125 
126  const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape(
127  numberOfBatches, numberOfChannels, height, width, layout);
128 
129  // 0.0000001^2 + 0.00000002^2 + 0.00000003^2 < 1e-12
130  std::vector<float> inputValues
131  {
132  // Batch 0, Channel 0, Height (1) x Width (1)
133  0.00000001f,
134 
135  // Batch 0, Channel 1, Height (1) x Width (1)
136  0.00000002f,
137 
138  // Batch 0, Channel 2, Height (1) x Width (1)
139  0.00000003f,
140  };
141 
142  const float approxInvL2Norm = 1.f / sqrtf(epsilon);
143  std::vector<float> expectedOutputValues
144  {
145  // Batch 0, Channel 0, Height (1) x Width (1)
146  0.00000001f * approxInvL2Norm,
147  0.00000002f * approxInvL2Norm,
148  0.00000003f * approxInvL2Norm,
149  };
150 
151  return L2NormalizationTestImpl<ArmnnType>(
152  workloadFactory,
153  memoryManager,
154  inputOutputShape,
155  scale,
156  offset,
157  inputValues,
158  outScale,
159  outOffset,
160  expectedOutputValues,
161  layout,
162  epsilon);
163 }
164 
165 
166 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
167 LayerTestResult<T, 4> L2Normalization1dTestCommon(
168  armnn::IWorkloadFactory& workloadFactory,
169  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
170  float scale,
171  int32_t offset,
172  float outScale,
173  int32_t outOffset,
174  const armnn::DataLayout layout)
175 {
176  // Width: 1
177  // Height: 1
178  // Channels: 10
179  // BatchSize: 1
180  unsigned int numberOfBatches = 1;
181  unsigned int numberOfChannels = 10;
182  unsigned int height = 1;
183  unsigned int width = 1;
184 
185 
186  const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape(
187  numberOfBatches, numberOfChannels, height, width, layout);
188  std::vector<float> inputValues
189  {
190  // Batch 0, Channel 0, Height (1) x Width (1)
191  1.0f,
192 
193  // Batch 0, Channel 1, Height (1) x Width (1)
194  2.0f,
195 
196  // Batch 0, Channel 2, Height (1) x Width (1)
197  3.0f,
198 
199  // Batch 0, Channel 3, Height (1) x Width (1)
200  4.0f,
201 
202  // Batch 0, Channel 4, Height (1) x Width (1)
203  5.0f,
204 
205  // Batch 0, Channel 5, Height (1) x Width (1)
206  6.0f,
207 
208  // Batch 0, Channel 6, Height (1) x Width (1)
209  7.0f,
210 
211  // Batch 0, Channel 7, Height (1) x Width (1)
212  8.0f,
213 
214  // Batch 0, Channel 8, Height (1) x Width (1)
215  9.0f,
216 
217  // Batch 0, Channel 9, Height (1) x Width (1)
218  10.0f
219  };
220  const float approxInvL2Norm = 0.050964719f;
221  std::vector<float> expectedOutputValues
222  {
223  // Batch 0, Channel 0, Height (1) x Width (1)
224  1.0f * approxInvL2Norm,
225  2.0f * approxInvL2Norm,
226  3.0f * approxInvL2Norm,
227  4.0f * approxInvL2Norm,
228  5.0f * approxInvL2Norm,
229  6.0f * approxInvL2Norm,
230  7.0f * approxInvL2Norm,
231  8.0f * approxInvL2Norm,
232  9.0f * approxInvL2Norm,
233  10.0f * approxInvL2Norm
234  };
235 
236 
237  return L2NormalizationTestImpl<ArmnnType>(
238  workloadFactory,
239  memoryManager,
240  inputOutputShape,
241  scale,
242  offset,
243  inputValues,
244  outScale,
245  outOffset,
246  expectedOutputValues,
247  layout);
248 }
249 
250 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
251 LayerTestResult<T, 4> L2Normalization2dTestCommon(
252  armnn::IWorkloadFactory& workloadFactory,
253  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
254  float scale,
255  int32_t offset,
256  float outScale,
257  int32_t outOffset,
258  const armnn::DataLayout layout)
259 {
260  // Width: 5
261  // Height: 1
262  // Channels: 2
263  // BatchSize: 1
264  unsigned int numberOfBatches = 1;
265  unsigned int numberOfChannels = 2;
266  unsigned int height = 1;
267  unsigned int width = 5;
268 
269  const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape(
270  numberOfBatches, numberOfChannels, height, width, layout);
271  std::vector<float> inputValues
272  {
273  // Batch 0, Channel 0, Height (1) x Width (5)
274  1.0f, 3.0f, 5.0f, 7.0f, 9.0f,
275 
276  // Batch 0, Channel 1, Height (1) x Width (5)
277  2.0f, 4.0f, 6.0f, 8.0f, 10.0f
278  };
279  std::vector<float> expectedOutputValues
280  {
281  // Batch 0, Channel 0, Height (1) x Width (5)
282  1.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
283  3.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
284  5.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
285  7.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
286  9.0f * CalcInvL2Norm({ 9.0f, 10.0f }),
287 
288  // Batch 0, Channel 1, Height (1) x Width (5)
289  2.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
290  4.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
291  6.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
292  8.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
293  10.0f * CalcInvL2Norm({ 9.0f, 10.0f })
294  };
295 
296  return L2NormalizationTestImpl<ArmnnType>(
297  workloadFactory,
298  memoryManager,
299  inputOutputShape,
300  scale,
301  offset,
302  inputValues,
303  outScale,
304  outOffset,
305  expectedOutputValues,
306  layout);
307 }
308 
309 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
310 LayerTestResult<T, 4> L2Normalization3dTestCommon(
311  armnn::IWorkloadFactory& workloadFactory,
312  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
313  float scale,
314  int32_t offset,
315  float outScale,
316  int32_t outOffset,
317  const armnn::DataLayout layout)
318 {
319  // Width: 3
320  // Height: 4
321  // Channels: 2
322  // BatchSize: 1
323  unsigned int numberOfBatches = 1;
324  unsigned int numberOfChannels = 2;
325  unsigned int height = 4;
326  unsigned int width = 3;
327 
328  const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape(
329  numberOfBatches, numberOfChannels, height, width, layout);
330  std::vector<float> inputValues
331  {
332  // Batch 0, Channel 0, Height (4) x Width (3)
333  119.0f, 21.0f, 150.0f,
334  149.0f, 32.0f, 179.0f,
335  15.0f, 227.0f, 141.0f,
336  147.0f, 199.0f, 220.0f,
337 
338  // Batch 0, Channel 1, Height (4) x Width (3)
339  110.0f, 140.0f, 73.0f,
340  211.0f, 212.0f, 89.0f,
341  24.0f, 138.0f, 188.0f,
342  162.0f, 12.0f, 161.0f
343  };
344  std::vector<float> expectedOutputValues
345  {
346  // Batch 0, Channel 0, Height (4) x Width (3)
347  119.0f * CalcInvL2Norm({ 119.0f, 110.0f }),
348  21.0f * CalcInvL2Norm({ 21.0f, 140.0f }),
349  150.0f * CalcInvL2Norm({ 150.0f, 73.0f }),
350  149.0f * CalcInvL2Norm({ 149.0f, 211.0f }),
351  32.0f * CalcInvL2Norm({ 32.0f, 212.0f }),
352  179.0f * CalcInvL2Norm({ 179.0f, 89.0f }),
353  15.0f * CalcInvL2Norm({ 15.0f, 24.0f }),
354  227.0f * CalcInvL2Norm({ 227.0f, 138.0f }),
355  141.0f * CalcInvL2Norm({ 141.0f, 188.0f }),
356  147.0f * CalcInvL2Norm({ 147.0f, 162.0f }),
357  199.0f * CalcInvL2Norm({ 199.0f, 12.0f }),
358  220.0f * CalcInvL2Norm({ 220.0f, 161.0f }),
359 
360  // Batch 0, Channel 1, Height (4) x Width (3)
361  110.0f * CalcInvL2Norm({ 119.0f, 110.0f }),
362  140.0f * CalcInvL2Norm({ 21.0f, 140.0f }),
363  73.0f * CalcInvL2Norm({ 150.0f, 73.0f }),
364  211.0f * CalcInvL2Norm({ 149.0f, 211.0f }),
365  212.0f * CalcInvL2Norm({ 32.0f, 212.0f }),
366  89.0f * CalcInvL2Norm({ 179.0f, 89.0f }),
367  24.0f * CalcInvL2Norm({ 15.0f, 24.0f }),
368  138.0f * CalcInvL2Norm({ 227.0f, 138.0f }),
369  188.0f * CalcInvL2Norm({ 141.0f, 188.0f }),
370  162.0f * CalcInvL2Norm({ 147.0f, 162.0f }),
371  12.0f * CalcInvL2Norm({ 199.0f, 12.0f }),
372  161.0f * CalcInvL2Norm({ 220.0f, 161.0f })
373  };
374 
375  return L2NormalizationTestImpl<ArmnnType>(
376  workloadFactory,
377  memoryManager,
378  inputOutputShape,
379  scale,
380  offset,
381  inputValues,
382  outScale,
383  outOffset,
384  expectedOutputValues,
385  layout);
386 }
387 
388 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
389 LayerTestResult<T, 4> L2Normalization4dTestCommon(
390  armnn::IWorkloadFactory& workloadFactory,
391  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
392  float scale,
393  int32_t offset,
394  float outScale,
395  int32_t outOffset,
396  const armnn::DataLayout layout)
397 {
398  // Width: 3
399  // Height: 4
400  // Channels: 3
401  // BatchSize: 2
402  unsigned int numberOfBatches = 2;
403  unsigned int numberOfChannels = 3;
404  unsigned int height = 4;
405  unsigned int width = 3;
406 
407  const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape(
408  numberOfBatches, numberOfChannels, height, width, layout);
409  std::vector<float> inputValues
410  {
411  // Batch 0, Channel 0, Height (4) x Width (3)
412  235.0f, 46.0f, 178.0f,
413  100.0f, 123.0f, 19.0f,
414  172.0f, 74.0f, 250.0f,
415  6.0f, 195.0f, 80.0f,
416 
417  // Batch 0, Channel 1, Height (4) x Width (3)
418  113.0f, 95.0f, 202.0f,
419  77.0f, 114.0f, 71.0f,
420  122.0f, 246.0f, 166.0f,
421  82.0f, 28.0f, 37.0f,
422 
423  // Batch 0, Channel 2, Height (4) x Width (3)
424  56.0f, 170.0f, 162.0f,
425  194.0f, 89.0f, 254.0f,
426  12.0f, 209.0f, 200.0f,
427  1.0f, 64.0f, 54.0f,
428 
429  // Batch 1, Channel 0, Height (4) x Width (3)
430  67.0f, 90.0f, 49.0f,
431  7.0f, 163.0f, 18.0f,
432  25.0f, 117.0f, 103.0f,
433  247.0f, 59.0f, 189.0f,
434 
435  // Batch 1, Channel 1, Height (4) x Width (3)
436  239.0f, 104.0f, 199.0f,
437  17.0f, 124.0f, 153.0f,
438  222.0f, 217.0f, 75.0f,
439  32.0f, 126.0f, 21.0f,
440 
441  // Batch 1, Channel 2, Height (4) x Width (3)
442  97.0f, 145.0f, 215.0f,
443  115.0f, 116.0f, 238.0f,
444  226.0f, 16.0f, 132.0f,
445  92.0f, 125.0f, 88.0f
446  };
447  std::vector<float> expectedOutputValues
448  {
449  // Batch 0, Channel 0, Height (4) x Width (3)
450  235.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }),
451  46.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }),
452  178.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }),
453  100.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }),
454  123.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }),
455  19.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }),
456  172.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }),
457  74.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }),
458  250.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }),
459  6.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }),
460  195.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }),
461  80.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }),
462 
463  // Batch 0, Channel 1, Height (4) x Width (3)
464  113.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }),
465  95.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }),
466  202.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }),
467  77.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }),
468  114.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }),
469  71.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }),
470  122.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }),
471  246.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }),
472  166.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }),
473  82.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }),
474  28.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }),
475  37.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }),
476 
477  // Batch 0, Channel 2, Height (4) x Width (3)
478  56.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }),
479  170.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }),
480  162.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }),
481  194.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }),
482  89.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }),
483  254.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }),
484  12.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }),
485  209.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }),
486  200.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }),
487  1.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }),
488  64.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }),
489  54.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }),
490 
491  // Batch 1, Channel 0, Height (4) x Width (3)
492  67.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }),
493  90.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }),
494  49.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }),
495  7.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }),
496  163.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }),
497  18.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }),
498  25.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }),
499  117.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }),
500  103.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }),
501  247.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }),
502  59.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }),
503  189.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }),
504 
505  // Batch 1, Channel 1, Height (4) x Width (3)
506  239.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }),
507  104.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }),
508  199.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }),
509  17.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }),
510  124.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }),
511  153.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }),
512  222.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }),
513  217.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }),
514  75.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }),
515  32.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }),
516  126.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }),
517  21.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }),
518 
519  // Batch 1, Channel 2, Height (4) x Width (3)
520  97.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }),
521  145.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }),
522  215.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }),
523  115.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }),
524  116.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }),
525  238.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }),
526  226.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }),
527  16.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }),
528  132.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }),
529  92.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }),
530  125.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }),
531  88.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f })
532  };
533 
534  return L2NormalizationTestImpl<ArmnnType>(
535  workloadFactory,
536  memoryManager,
537  inputOutputShape,
538  scale,
539  offset,
540  inputValues,
541  outScale,
542  outOffset,
543  expectedOutputValues,
544  layout);
545 }
546 
547 } // anonymous namespace
548 
549 LayerTestResult<float, 4> L2NormalizationDefaultEpsilonTest(
550  armnn::IWorkloadFactory& workloadFactory,
551  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
552  const armnn::DataLayout layout)
553 {
554  // Dummy descriptor to get the default value of epsilon.
555  armnn::L2NormalizationDescriptor descriptor;
556 
557  return L2NormalizationEpsilonTestCommon<armnn::DataType::Float32>(
558  workloadFactory,
559  memoryManager,
560  0.f,
561  0,
562  0.f,
563  0,
564  layout,
565  descriptor.m_Eps);
566 }
567 
568 LayerTestResult<float, 4> L2NormalizationNonDefaultEpsilonTest(
569  armnn::IWorkloadFactory& workloadFactory,
570  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
571  const armnn::DataLayout layout)
572 {
573  return L2NormalizationEpsilonTestCommon<armnn::DataType::Float32>(
574  workloadFactory,
575  memoryManager,
576  0.f,
577  0,
578  0.f,
579  0,
580  layout,
581  1e-9f);
582 }
583 
584 LayerTestResult<float, 4> L2Normalization1dTest(
585  armnn::IWorkloadFactory& workloadFactory,
586  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
587  const armnn::DataLayout layout)
588 {
589  return L2Normalization1dTestCommon<armnn::DataType::Float32>(
590  workloadFactory,
591  memoryManager,
592  0.f,
593  0,
594  0.f,
595  0,
596  layout);
597 }
598 
599 LayerTestResult<int16_t, 4> L2Normalization1dInt16Test(
600  armnn::IWorkloadFactory& workloadFactory,
601  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
602  const armnn::DataLayout layout)
603 {
604  return L2Normalization1dTestCommon<armnn::DataType::QSymmS16>(
605  workloadFactory,
606  memoryManager,
607  1.f,
608  0,
609  1.f,
610  0,
611  layout);
612 }
613 
614 LayerTestResult<uint8_t, 4> L2Normalization1dUint8Test(
615  armnn::IWorkloadFactory& workloadFactory,
616  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
617  const armnn::DataLayout layout)
618 {
619  return L2Normalization1dTestCommon<armnn::DataType::QAsymmU8>(
620  workloadFactory,
621  memoryManager,
622  1.f,
623  0,
624  1.f / 128,
625  128,
626  layout);
627 }
628 
629 LayerTestResult<float, 4> L2Normalization2dTest(
630  armnn::IWorkloadFactory& workloadFactory,
631  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
632  const armnn::DataLayout layout)
633 {
634  return L2Normalization2dTestCommon<armnn::DataType::Float32>(
635  workloadFactory,
636  memoryManager,
637  0.f,
638  0,
639  0.f,
640  0,
641  layout);
642 }
643 
644 LayerTestResult<int16_t, 4> L2Normalization2dInt16Test(
645  armnn::IWorkloadFactory& workloadFactory,
646  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
647  const armnn::DataLayout layout)
648 {
649  return L2Normalization1dTestCommon<armnn::DataType::QSymmS16>(
650  workloadFactory,
651  memoryManager,
652  1.f,
653  0,
654  1.f,
655  0,
656  layout);
657 }
658 
659 LayerTestResult<uint8_t, 4> L2Normalization2dUint8Test(
660  armnn::IWorkloadFactory& workloadFactory,
661  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
662  const armnn::DataLayout layout)
663 {
664  return L2Normalization1dTestCommon<armnn::DataType::QAsymmU8>(
665  workloadFactory,
666  memoryManager,
667  1.f,
668  0,
669  1.f / 128,
670  128,
671  layout);
672 }
673 
674 LayerTestResult<float, 2> L2Normalization2dShapeTest(
675  armnn::IWorkloadFactory& workloadFactory,
676  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
677 {
678  const armnn::DataLayout layout = armnn::DataLayout::NHWC;
679  const armnn::TensorShape inputOutputTensorShape = armnn::TensorShape({ 5, 2 });
680 
681  std::vector<float> inputData
682  {
683  1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f
684  };
685  std::vector<float> expectedOutputData
686  {
687  1.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
688  2.0f * CalcInvL2Norm({ 1.0f, 2.0f }),
689  3.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
690  4.0f * CalcInvL2Norm({ 3.0f, 4.0f }),
691  5.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
692  6.0f * CalcInvL2Norm({ 5.0f, 6.0f }),
693  7.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
694  8.0f * CalcInvL2Norm({ 7.0f, 8.0f }),
695  9.0f * CalcInvL2Norm({ 9.0f, 10.0f }),
696  10.0f * CalcInvL2Norm({ 9.0f, 10.0f })
697  };
698 
699  const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32, 0.f, 0);
700  const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32, 0.f, 0);
701 
702  auto inputTensor = MakeTensor<float, 2>(inputTensorInfo, inputData);
703 
704  LayerTestResult<float, 2> result(outputTensorInfo);
705  result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, expectedOutputData);
706 
707  ARMNN_NO_DEPRECATE_WARN_BEGIN
708  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
709  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
710  ARMNN_NO_DEPRECATE_WARN_END
711 
712  armnn::L2NormalizationQueueDescriptor descriptor;
713  descriptor.m_Parameters.m_Eps = 1e-12f;
714  descriptor.m_Parameters.m_DataLayout = layout;
715  armnn::WorkloadInfo info;
716 
717  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
718  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
719 
720  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateL2Normalization(descriptor, info);
721 
722  inputHandle->Allocate();
723  outputHandle->Allocate();
724 
725  CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
726 
727  workload->PostAllocationConfigure();
728  ExecuteWorkload(*workload, memoryManager);
729 
730  CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
731 
732  return result;
733 }
734 
735 LayerTestResult<float, 4> L2Normalization3dTest(
736  armnn::IWorkloadFactory& workloadFactory,
737  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
738  const armnn::DataLayout layout)
739 {
740  return L2Normalization3dTestCommon<armnn::DataType::Float32>(
741  workloadFactory,
742  memoryManager,
743  0.f,
744  0,
745  0.f,
746  0,
747  layout);
748 }
749 
750 LayerTestResult<int16_t, 4> L2Normalization3dInt16Test(
751  armnn::IWorkloadFactory& workloadFactory,
752  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
753  const armnn::DataLayout layout)
754 {
755  return L2Normalization1dTestCommon<armnn::DataType::QSymmS16>(
756  workloadFactory,
757  memoryManager,
758  1.f,
759  0,
760  1.f,
761  0,
762  layout);
763 }
764 
765 LayerTestResult<uint8_t, 4> L2Normalization3dUint8Test(
766  armnn::IWorkloadFactory& workloadFactory,
767  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
768  const armnn::DataLayout layout)
769 {
770  return L2Normalization1dTestCommon<armnn::DataType::QAsymmU8>(
771  workloadFactory,
772  memoryManager,
773  1.f,
774  0,
775  1.f / 128,
776  128,
777  layout);
778 }
779 
780 LayerTestResult<float, 4> L2Normalization4dTest(
781  armnn::IWorkloadFactory& workloadFactory,
782  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
783  const armnn::DataLayout layout)
784 {
785  return L2Normalization4dTestCommon<armnn::DataType::Float32>(
786  workloadFactory,
787  memoryManager,
788  0.f,
789  0,
790  0.f,
791  0,
792  layout);
793 }
794 
795 LayerTestResult<int16_t, 4> L2Normalization4dInt16Test(
796  armnn::IWorkloadFactory& workloadFactory,
797  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
798  const armnn::DataLayout layout)
799 {
800  return L2Normalization1dTestCommon<armnn::DataType::QSymmS16>(
801  workloadFactory,
802  memoryManager,
803  1.f,
804  0,
805  1.f,
806  0,
807  layout);
808 }
809 
810 LayerTestResult<uint8_t, 4> L2Normalization4dUint8Test(
811  armnn::IWorkloadFactory& workloadFactory,
812  const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
813  const armnn::DataLayout layout)
814 {
815  return L2Normalization1dTestCommon<armnn::DataType::QAsymmU8>(
816  workloadFactory,
817  memoryManager,
818  1.f,
819  0,
820  1.f / 128,
821  128,
822  layout);
823 }
armnn::L2NormalizationDescriptor::m_Eps
float m_Eps
Used to avoid dividing by zero.
Definition: Descriptors.hpp:612
TensorCopyUtils.hpp
armnn::IWorkloadFactory::CreateL2Normalization
virtual std::unique_ptr< IWorkload > CreateL2Normalization(const L2NormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const
Definition: WorkloadFactory.cpp:1399
armnn::DataLayout
DataLayout
Definition: Types.hpp:49
ARMNN_NO_DEPRECATE_WARN_BEGIN
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
Definition: Deprecated.hpp:33
QuantizeHelper.hpp
WorkloadTestUtils.hpp
ResolveType.hpp
L2Normalization1dTest
LayerTestResult< float, 4 > L2Normalization1dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:584
armnn::IgnoreUnused
void IgnoreUnused(Ts &&...)
Definition: IgnoreUnused.hpp:14
L2Normalization3dUint8Test
LayerTestResult< uint8_t, 4 > L2Normalization3dUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:765
L2Normalization4dUint8Test
LayerTestResult< uint8_t, 4 > L2Normalization4dUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:810
L2Normalization2dTest
LayerTestResult< float, 4 > L2Normalization2dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:629
L2NormalizationDefaultEpsilonTest
LayerTestResult< float, 4 > L2NormalizationDefaultEpsilonTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:549
armnnUtils::Permute
void Permute(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)
Definition: Permute.cpp:131
TensorHelpers.hpp
Permute.hpp
ARMNN_NO_DEPRECATE_WARN_END
#define ARMNN_NO_DEPRECATE_WARN_END
Definition: Deprecated.hpp:34
armnn::L2NormalizationDescriptor
A L2NormalizationDescriptor for the L2NormalizationLayer.
Definition: Descriptors.hpp:599
armnn::IBackendInternal::IMemoryManagerSharedPtr
std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr
Definition: IBackendInternal.hpp:90
L2Normalization2dInt16Test
LayerTestResult< int16_t, 4 > L2Normalization2dInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:644
L2Normalization3dInt16Test
LayerTestResult< int16_t, 4 > L2Normalization3dInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:750
armnnUtils::GetTensorShape
armnn::TensorShape GetTensorShape(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, const armnn::DataLayout dataLayout)
Definition: TensorUtils.cpp:19
L2Normalization1dUint8Test
LayerTestResult< uint8_t, 4 > L2Normalization1dUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:614
CopyDataFromITensorHandle
void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)
Definition: TensorCopyUtils.cpp:14
L2Normalization2dUint8Test
LayerTestResult< uint8_t, 4 > L2Normalization2dUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:659
armnn::IWorkloadFactory::CreateTensorHandle
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0
L2NormalizationTestImpl.hpp
L2Normalization2dShapeTest
LayerTestResult< float, 2 > L2Normalization2dShapeTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
Definition: L2NormalizationTestImpl.cpp:674
L2Normalization4dInt16Test
LayerTestResult< int16_t, 4 > L2Normalization4dInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:795
TensorUtils.hpp
L2NormalizationNonDefaultEpsilonTest
LayerTestResult< float, 4 > L2NormalizationNonDefaultEpsilonTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:568
armnn::WorkloadInfo
Contains information about inputs and outputs to a layer.
Definition: WorkloadInfo.hpp:16
L2Normalization3dTest
LayerTestResult< float, 4 > L2Normalization3dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:735
L2Normalization4dTest
LayerTestResult< float, 4 > L2Normalization4dTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:780
CopyDataToITensorHandle
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)
Definition: TensorCopyUtils.cpp:9
L2Normalization1dInt16Test
LayerTestResult< int16_t, 4 > L2Normalization1dInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout)
Definition: L2NormalizationTestImpl.cpp:599