Ryan OShea | de36e4a | 2020-03-13 16:26:19 +0000 | [diff] [blame] | 1 | <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> |
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| 84 | <a href="#func-members">Functions</a> </div> |
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| 86 | <div class="title">BatchNormalizationTestImpl.cpp File Reference</div> </div> |
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| 88 | <div class="contents"> |
| 89 | <div class="textblock"><code>#include "<a class="el" href="_batch_normalization_test_impl_8hpp_source.html">BatchNormalizationTestImpl.hpp</a>"</code><br /> |
| 90 | <code>#include <<a class="el" href="_quantize_helper_8hpp_source.html">QuantizeHelper.hpp</a>></code><br /> |
| 91 | <code>#include <<a class="el" href="_resolve_type_8hpp_source.html">ResolveType.hpp</a>></code><br /> |
| 92 | <code>#include <<a class="el" href="_data_layout_indexed_8hpp_source.html">armnnUtils/DataLayoutIndexed.hpp</a>></code><br /> |
| 93 | <code>#include <<a class="el" href="_cpu_tensor_handle_8hpp_source.html">backendsCommon/CpuTensorHandle.hpp</a>></code><br /> |
| 94 | <code>#include <<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.html">armnn/backends/IBackendInternal.hpp</a>></code><br /> |
| 95 | <code>#include <<a class="el" href="_workload_factory_8hpp_source.html">backendsCommon/WorkloadFactory.hpp</a>></code><br /> |
| 96 | <code>#include <<a class="el" href="_tensor_copy_utils_8hpp_source.html">backendsCommon/test/TensorCopyUtils.hpp</a>></code><br /> |
| 97 | <code>#include <<a class="el" href="_workload_test_utils_8hpp_source.html">backendsCommon/test/WorkloadTestUtils.hpp</a>></code><br /> |
| 98 | <code>#include <<a class="el" href="_tensor_helpers_8hpp_source.html">test/TensorHelpers.hpp</a>></code><br /> |
| 99 | </div> |
| 100 | <p><a href="_batch_normalization_test_impl_8cpp_source.html">Go to the source code of this file.</a></p> |
| 101 | <table class="memberdecls"> |
| 102 | <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> |
| 103 | Functions</h2></td></tr> |
| 104 | <tr class="memitem:a95e3411d80e0eac3844844c017f03861"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a95e3411d80e0eac3844844c017f03861">BatchNormFloat32Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 105 | <tr class="separator:a95e3411d80e0eac3844844c017f03861"><td class="memSeparator" colspan="2"> </td></tr> |
| 106 | <tr class="memitem:a449a360cd864483064ae2991db8edcd8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a449a360cd864483064ae2991db8edcd8">BatchNormFloat32NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 107 | <tr class="separator:a449a360cd864483064ae2991db8edcd8"><td class="memSeparator" colspan="2"> </td></tr> |
| 108 | <tr class="memitem:a0fe6b55e33196820f9bf4759647c17df"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< <a class="el" href="namespacearmnn.html#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a0fe6b55e33196820f9bf4759647c17df">BatchNormFloat16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 109 | <tr class="separator:a0fe6b55e33196820f9bf4759647c17df"><td class="memSeparator" colspan="2"> </td></tr> |
| 110 | <tr class="memitem:a7615443ac0887d4c282f53f7e49d889c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< <a class="el" href="namespacearmnn.html#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a7615443ac0887d4c282f53f7e49d889c">BatchNormFloat16NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 111 | <tr class="separator:a7615443ac0887d4c282f53f7e49d889c"><td class="memSeparator" colspan="2"> </td></tr> |
| 112 | <tr class="memitem:ae90e750efd98b6fb3db4bd586df3daff"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#ae90e750efd98b6fb3db4bd586df3daff">BatchNormUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 113 | <tr class="separator:ae90e750efd98b6fb3db4bd586df3daff"><td class="memSeparator" colspan="2"> </td></tr> |
| 114 | <tr class="memitem:a168bb6829b7b1bd091ab3800a055f7ee"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a168bb6829b7b1bd091ab3800a055f7ee">BatchNormUint8NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 115 | <tr class="separator:a168bb6829b7b1bd091ab3800a055f7ee"><td class="memSeparator" colspan="2"> </td></tr> |
| 116 | <tr class="memitem:aa3fcd011e2fba798b1d5c8d4d2ee9ad8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#aa3fcd011e2fba798b1d5c8d4d2ee9ad8">BatchNormInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 117 | <tr class="separator:aa3fcd011e2fba798b1d5c8d4d2ee9ad8"><td class="memSeparator" colspan="2"> </td></tr> |
| 118 | <tr class="memitem:a40379f76fb69d26e8543dd1494674335"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a40379f76fb69d26e8543dd1494674335">BatchNormInt16NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 119 | <tr class="separator:a40379f76fb69d26e8543dd1494674335"><td class="memSeparator" colspan="2"> </td></tr> |
| 120 | <tr class="memitem:a39988d3dc5c636fa49e8192f26d72554"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_batch_normalization_test_impl_8cpp.html#a39988d3dc5c636fa49e8192f26d72554">CompareBatchNormTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, <a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &refWorkloadFactory)</td></tr> |
| 121 | <tr class="separator:a39988d3dc5c636fa49e8192f26d72554"><td class="memSeparator" colspan="2"> </td></tr> |
| 122 | </table> |
| 123 | <h2 class="groupheader">Function Documentation</h2> |
| 124 | <a id="a7615443ac0887d4c282f53f7e49d889c"></a> |
| 125 | <h2 class="memtitle"><span class="permalink"><a href="#a7615443ac0887d4c282f53f7e49d889c">◆ </a></span>BatchNormFloat16NhwcTest()</h2> |
| 126 | |
| 127 | <div class="memitem"> |
| 128 | <div class="memproto"> |
| 129 | <table class="memname"> |
| 130 | <tr> |
| 131 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><<a class="el" href="namespacearmnn.html#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4> BatchNormFloat16NhwcTest </td> |
| 132 | <td>(</td> |
| 133 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 134 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 135 | </tr> |
| 136 | <tr> |
| 137 | <td class="paramkey"></td> |
| 138 | <td></td> |
| 139 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 140 | <td class="paramname"><em>memoryManager</em> </td> |
| 141 | </tr> |
| 142 | <tr> |
| 143 | <td></td> |
| 144 | <td>)</td> |
| 145 | <td></td><td></td> |
| 146 | </tr> |
| 147 | </table> |
| 148 | </div><div class="memdoc"> |
| 149 | |
| 150 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00349">349</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 151 | |
| 152 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 153 | <div class="fragment"><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> {</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  std::vector<float> inputValues</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  {</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  1.f, 1.f,</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  4.f, 1.f,</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span> </div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  4.f, 4.f,</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  2.f, 1.f,</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  1.f, -2.f,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  6.f, 4.f</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  };</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  {</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  1.f, 3.f,</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  4.f, 3.f,</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  4.f, 4.f,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  2.f, 3.f,</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  1.f, 2.f,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  6.f, 4.f</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  };</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float16>(</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  workloadFactory,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  memoryManager,</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  inputOutputShape,</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  inputValues,</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  expectedOutputValues,</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  0.f,</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  0,</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 154 | <div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> |
| 155 | </div><!-- fragment --> |
| 156 | </div> |
| 157 | </div> |
| 158 | <a id="a0fe6b55e33196820f9bf4759647c17df"></a> |
| 159 | <h2 class="memtitle"><span class="permalink"><a href="#a0fe6b55e33196820f9bf4759647c17df">◆ </a></span>BatchNormFloat16Test()</h2> |
| 160 | |
| 161 | <div class="memitem"> |
| 162 | <div class="memproto"> |
| 163 | <table class="memname"> |
| 164 | <tr> |
| 165 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><<a class="el" href="namespacearmnn.html#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>, 4> BatchNormFloat16Test </td> |
| 166 | <td>(</td> |
| 167 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 168 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 169 | </tr> |
| 170 | <tr> |
| 171 | <td class="paramkey"></td> |
| 172 | <td></td> |
| 173 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 174 | <td class="paramname"><em>memoryManager</em> </td> |
| 175 | </tr> |
| 176 | <tr> |
| 177 | <td></td> |
| 178 | <td>)</td> |
| 179 | <td></td><td></td> |
| 180 | </tr> |
| 181 | </table> |
| 182 | </div><div class="memdoc"> |
| 183 | |
| 184 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00303">303</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 185 | |
| 186 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> |
| 187 | <div class="fragment"><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  std::vector<float> inputValues</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  {</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  1.f, 4.f,</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  4.f, 2.f,</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  1.f, 6.f,</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  1.f, 1.f,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  4.f, 1.f,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  -2.f, 4.f</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  };</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  {</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  1.f, 4.f,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  4.f, 2.f,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  1.f, 6.f,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  3.f, 3.f,</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  4.f, 3.f,</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  2.f, 4.f</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  };</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float16>(</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  workloadFactory,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  memoryManager,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  inputOutputShape,</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  inputValues,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  expectedOutputValues,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  0.f,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  0,</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> }</div><div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> |
| 188 | <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 189 | </div><!-- fragment --> |
| 190 | </div> |
| 191 | </div> |
| 192 | <a id="a449a360cd864483064ae2991db8edcd8"></a> |
| 193 | <h2 class="memtitle"><span class="permalink"><a href="#a449a360cd864483064ae2991db8edcd8">◆ </a></span>BatchNormFloat32NhwcTest()</h2> |
| 194 | |
| 195 | <div class="memitem"> |
| 196 | <div class="memproto"> |
| 197 | <table class="memname"> |
| 198 | <tr> |
| 199 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><float, 4> BatchNormFloat32NhwcTest </td> |
| 200 | <td>(</td> |
| 201 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 202 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 203 | </tr> |
| 204 | <tr> |
| 205 | <td class="paramkey"></td> |
| 206 | <td></td> |
| 207 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 208 | <td class="paramname"><em>memoryManager</em> </td> |
| 209 | </tr> |
| 210 | <tr> |
| 211 | <td></td> |
| 212 | <td>)</td> |
| 213 | <td></td><td></td> |
| 214 | </tr> |
| 215 | </table> |
| 216 | </div><div class="memdoc"> |
| 217 | |
| 218 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00253">253</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 219 | |
| 220 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 221 | <div class="fragment"><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  std::vector<float> inputValues</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  {</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  1.f, 1.f,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  4.f, 1.f,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  4.f, 4.f,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  2.f, 1.f,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  1.f, -2.f,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  6.f, 4.f</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  };</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  1.f, 3.f,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  4.f, 3.f,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  4.f, 4.f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  2.f, 3.f,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  1.f, 2.f,</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  6.f, 4.f</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  };</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  workloadFactory,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  memoryManager,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  inputOutputShape,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  inputValues,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  expectedOutputValues,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  0.f,</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  0,</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 222 | <div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> |
| 223 | </div><!-- fragment --> |
| 224 | </div> |
| 225 | </div> |
| 226 | <a id="a95e3411d80e0eac3844844c017f03861"></a> |
| 227 | <h2 class="memtitle"><span class="permalink"><a href="#a95e3411d80e0eac3844844c017f03861">◆ </a></span>BatchNormFloat32Test()</h2> |
| 228 | |
| 229 | <div class="memitem"> |
| 230 | <div class="memproto"> |
| 231 | <table class="memname"> |
| 232 | <tr> |
| 233 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><float, 4> BatchNormFloat32Test </td> |
| 234 | <td>(</td> |
| 235 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 236 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 237 | </tr> |
| 238 | <tr> |
| 239 | <td class="paramkey"></td> |
| 240 | <td></td> |
| 241 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 242 | <td class="paramname"><em>memoryManager</em> </td> |
| 243 | </tr> |
| 244 | <tr> |
| 245 | <td></td> |
| 246 | <td>)</td> |
| 247 | <td></td><td></td> |
| 248 | </tr> |
| 249 | </table> |
| 250 | </div><div class="memdoc"> |
| 251 | |
| 252 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00207">207</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 253 | |
| 254 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> |
| 255 | <div class="fragment"><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  std::vector<float> inputValues</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  {</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  1.f, 4.f,</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  4.f, 2.f,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  1.f, 6.f,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  1.f, 1.f,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  4.f, 1.f,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  -2.f, 4.f</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  };</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  1.f, 4.f,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  4.f, 2.f,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  1.f, 6.f,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  3.f, 3.f,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  4.f, 3.f,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  2.f, 4.f</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  };</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  workloadFactory,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  memoryManager,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  inputOutputShape,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  inputValues,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  expectedOutputValues,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  0.f,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  0,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> }</div><div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> |
| 256 | <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 257 | </div><!-- fragment --> |
| 258 | </div> |
| 259 | </div> |
| 260 | <a id="a40379f76fb69d26e8543dd1494674335"></a> |
| 261 | <h2 class="memtitle"><span class="permalink"><a href="#a40379f76fb69d26e8543dd1494674335">◆ </a></span>BatchNormInt16NhwcTest()</h2> |
| 262 | |
| 263 | <div class="memitem"> |
| 264 | <div class="memproto"> |
| 265 | <table class="memname"> |
| 266 | <tr> |
| 267 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><int16_t, 4> BatchNormInt16NhwcTest </td> |
| 268 | <td>(</td> |
| 269 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 270 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 271 | </tr> |
| 272 | <tr> |
| 273 | <td class="paramkey"></td> |
| 274 | <td></td> |
| 275 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 276 | <td class="paramname"><em>memoryManager</em> </td> |
| 277 | </tr> |
| 278 | <tr> |
| 279 | <td></td> |
| 280 | <td>)</td> |
| 281 | <td></td><td></td> |
| 282 | </tr> |
| 283 | </table> |
| 284 | </div><div class="memdoc"> |
| 285 | |
| 286 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00537">537</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 287 | |
| 288 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 289 | <div class="fragment"><div class="line"><a name="l00540"></a><span class="lineno"> 540</span> {</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> </div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  std::vector<float> inputValues</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  {</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  1.f, 1.f,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  4.f, 1.f,</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  4.f, 4.f,</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  2.f, 1.f,</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  1.f, -2.f,</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  6.f, 4.f</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  };</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  {</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  1.f, 3.f,</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  4.f, 3.f,</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span> </div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  4.f, 4.f,</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  2.f, 3.f,</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span> </div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  1.f, 2.f,</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  6.f, 4.f</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  };</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  workloadFactory,</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  memoryManager,</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  inputOutputShape,</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  inputValues,</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  expectedOutputValues,</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  1.f / 20.f,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  50,</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 290 | <div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> |
| 291 | </div><!-- fragment --> |
| 292 | </div> |
| 293 | </div> |
| 294 | <a id="aa3fcd011e2fba798b1d5c8d4d2ee9ad8"></a> |
| 295 | <h2 class="memtitle"><span class="permalink"><a href="#aa3fcd011e2fba798b1d5c8d4d2ee9ad8">◆ </a></span>BatchNormInt16Test()</h2> |
| 296 | |
| 297 | <div class="memitem"> |
| 298 | <div class="memproto"> |
| 299 | <table class="memname"> |
| 300 | <tr> |
| 301 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><int16_t, 4> BatchNormInt16Test </td> |
| 302 | <td>(</td> |
| 303 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 304 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 305 | </tr> |
| 306 | <tr> |
| 307 | <td class="paramkey"></td> |
| 308 | <td></td> |
| 309 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 310 | <td class="paramname"><em>memoryManager</em> </td> |
| 311 | </tr> |
| 312 | <tr> |
| 313 | <td></td> |
| 314 | <td>)</td> |
| 315 | <td></td><td></td> |
| 316 | </tr> |
| 317 | </table> |
| 318 | </div><div class="memdoc"> |
| 319 | |
| 320 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00491">491</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 321 | |
| 322 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> |
| 323 | <div class="fragment"><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> {</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  std::vector<float> inputValues</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  {</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  1.f, 4.f,</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  4.f, 2.f,</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  1.f, 6.f,</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> </div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  1.f, 1.f,</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  4.f, 1.f,</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  -2.f, 4.f</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  };</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  {</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  1.f, 4.f,</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  4.f, 2.f,</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  1.f, 6.f,</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span> </div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  3.f, 3.f,</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  4.f, 3.f,</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  2.f, 4.f</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  };</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  workloadFactory,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  memoryManager,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  inputOutputShape,</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  inputValues,</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  expectedOutputValues,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  1.f / 20.f,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  50,</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div><div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> |
| 324 | <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 325 | </div><!-- fragment --> |
| 326 | </div> |
| 327 | </div> |
| 328 | <a id="a168bb6829b7b1bd091ab3800a055f7ee"></a> |
| 329 | <h2 class="memtitle"><span class="permalink"><a href="#a168bb6829b7b1bd091ab3800a055f7ee">◆ </a></span>BatchNormUint8NhwcTest()</h2> |
| 330 | |
| 331 | <div class="memitem"> |
| 332 | <div class="memproto"> |
| 333 | <table class="memname"> |
| 334 | <tr> |
| 335 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><uint8_t, 4> BatchNormUint8NhwcTest </td> |
| 336 | <td>(</td> |
| 337 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 338 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 339 | </tr> |
| 340 | <tr> |
| 341 | <td class="paramkey"></td> |
| 342 | <td></td> |
| 343 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 344 | <td class="paramname"><em>memoryManager</em> </td> |
| 345 | </tr> |
| 346 | <tr> |
| 347 | <td></td> |
| 348 | <td>)</td> |
| 349 | <td></td><td></td> |
| 350 | </tr> |
| 351 | </table> |
| 352 | </div><div class="memdoc"> |
| 353 | |
| 354 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00445">445</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 355 | |
| 356 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
| 357 | <div class="fragment"><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> {</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> </div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 3, 2, 2 };</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  std::vector<float> inputValues</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  {</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  1.f, 1.f,</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  4.f, 1.f,</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  4.f, 4.f,</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  2.f, 1.f,</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  1.f, -2.f,</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  6.f, 4.f</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  };</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  {</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="comment">// Batch 0, Height 0, Width (2) x Channel (2)</span></div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  1.f, 3.f,</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  4.f, 3.f,</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span> </div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="comment">// Batch 0, Height 1, Width (2) x Channel (2)</span></div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  4.f, 4.f,</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  2.f, 3.f,</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> </div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="comment">// Batch 0, Height 2, Width (2) x Channel (2)</span></div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  1.f, 2.f,</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  6.f, 4.f</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  };</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span> </div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  workloadFactory,</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  memoryManager,</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  inputOutputShape, inputValues, expectedOutputValues,</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  1.f/20.f, 50, <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 358 | <div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> |
| 359 | </div><!-- fragment --> |
| 360 | </div> |
| 361 | </div> |
| 362 | <a id="ae90e750efd98b6fb3db4bd586df3daff"></a> |
| 363 | <h2 class="memtitle"><span class="permalink"><a href="#ae90e750efd98b6fb3db4bd586df3daff">◆ </a></span>BatchNormUint8Test()</h2> |
| 364 | |
| 365 | <div class="memitem"> |
| 366 | <div class="memproto"> |
| 367 | <table class="memname"> |
| 368 | <tr> |
| 369 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><uint8_t, 4> BatchNormUint8Test </td> |
| 370 | <td>(</td> |
| 371 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 372 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 373 | </tr> |
| 374 | <tr> |
| 375 | <td class="paramkey"></td> |
| 376 | <td></td> |
| 377 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 378 | <td class="paramname"><em>memoryManager</em> </td> |
| 379 | </tr> |
| 380 | <tr> |
| 381 | <td></td> |
| 382 | <td>)</td> |
| 383 | <td></td><td></td> |
| 384 | </tr> |
| 385 | </table> |
| 386 | </div><div class="memdoc"> |
| 387 | |
| 388 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00399">399</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 389 | |
| 390 | <p class="reference">References <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> |
| 391 | <div class="fragment"><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="comment">// BatchSize: 1</span></div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="comment">// Height: 3</span></div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> inputOutputShape{ 1, 2, 3, 2 };</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  std::vector<float> inputValues</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  {</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  1.f, 4.f,</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  4.f, 2.f,</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  1.f, 6.f,</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  1.f, 1.f,</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  4.f, 1.f,</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  -2.f, 4.f</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  };</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  {</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="comment">// Batch 0, Channel 0, Height (3) x Width (2)</span></div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  1.f, 4.f,</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  4.f, 2.f,</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  1.f, 6.f,</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="comment">// Batch 0, Channel 1, Height (3) x Width (2)</span></div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  3.f, 3.f,</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  4.f, 3.f,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  2.f, 4.f</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  };</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">return</span> BatchNormTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  workloadFactory,</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  memoryManager,</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  inputOutputShape,</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  inputValues,</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  expectedOutputValues,</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  1.f / 20.f,</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  50,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> }</div><div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> |
| 392 | <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 393 | </div><!-- fragment --> |
| 394 | </div> |
| 395 | </div> |
| 396 | <a id="a39988d3dc5c636fa49e8192f26d72554"></a> |
| 397 | <h2 class="memtitle"><span class="permalink"><a href="#a39988d3dc5c636fa49e8192f26d72554">◆ </a></span>CompareBatchNormTest()</h2> |
| 398 | |
| 399 | <div class="memitem"> |
| 400 | <div class="memproto"> |
| 401 | <table class="memname"> |
| 402 | <tr> |
| 403 | <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a><float,4> CompareBatchNormTest </td> |
| 404 | <td>(</td> |
| 405 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 406 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 407 | </tr> |
| 408 | <tr> |
| 409 | <td class="paramkey"></td> |
| 410 | <td></td> |
| 411 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 412 | <td class="paramname"><em>memoryManager</em>, </td> |
| 413 | </tr> |
| 414 | <tr> |
| 415 | <td class="paramkey"></td> |
| 416 | <td></td> |
| 417 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> & </td> |
| 418 | <td class="paramname"><em>refWorkloadFactory</em> </td> |
| 419 | </tr> |
| 420 | <tr> |
| 421 | <td></td> |
| 422 | <td>)</td> |
| 423 | <td></td><td></td> |
| 424 | </tr> |
| 425 | </table> |
| 426 | </div><div class="memdoc"> |
| 427 | |
| 428 | <p class="definition">Definition at line <a class="el" href="_batch_normalization_test_impl_8cpp_source.html#l00587">587</a> of file <a class="el" href="_batch_normalization_test_impl_8cpp_source.html">BatchNormalizationTestImpl.cpp</a>.</p> |
| 429 | |
| 430 | <p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01100">IWorkloadFactory::CreateBatchNormalization()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_workload_data_8hpp_source.html#l00281">BatchNormalizationQueueDescriptor::m_Beta</a>, <a class="el" href="_descriptors_8hpp_source.html#l00623">BatchNormalizationDescriptor::m_Eps</a>, <a class="el" href="_workload_data_8hpp_source.html#l00282">BatchNormalizationQueueDescriptor::m_Gamma</a>, <a class="el" href="_workload_data_8hpp_source.html#l00279">BatchNormalizationQueueDescriptor::m_Mean</a>, <a class="el" href="_workload_data_8hpp_source.html#l00049">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, and <a class="el" href="_workload_data_8hpp_source.html#l00280">BatchNormalizationQueueDescriptor::m_Variance</a>.</p> |
| 431 | <div class="fragment"><div class="line"><a name="l00591"></a><span class="lineno"> 591</span> {</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 2;</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 3;</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 5;</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span> </div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> tensorInfo;</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span> </div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, channels, height, width};</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tensorShape[] = {channels};</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span> </div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  tensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(1, tensorShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span> </div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keyword">auto</span> input = MakeRandomTensor<float, 4>(inputTensorInfo, 21312);</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span> </div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keyword">auto</span> mean = MakeRandomTensor<float, 1>(tensorInfo, 123);</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keyword">auto</span> variance = MakeRandomTensor<float, 1>(tensorInfo, 234, 0.0f);</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keyword">auto</span> beta = MakeRandomTensor<float, 1>(tensorInfo, 123);</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="keyword">auto</span> gamma = MakeRandomTensor<float, 1>(tensorInfo, 345);</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span> </div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <a class="code" href="struct_layer_test_result.html">LayerTestResult<float,4></a> ret(outputTensorInfo);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span> </div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> </div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span> </div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html">armnn::BatchNormalizationQueueDescriptor</a> data;</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a> meanTensor(tensorInfo);</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a> varianceTensor(tensorInfo);</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a> betaTensor(tensorInfo);</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a> gammaTensor(tensorInfo);</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span> </div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&meanTensor, &mean[0]);</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&varianceTensor, &variance[0]);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&betaTensor, &beta[0]);</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&gammaTensor, &gamma[0]);</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html#a40051a7aa82f25df43cc4244de04a7ec">m_Mean</a> = &meanTensor;</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html#a8cd8696bb773a02714d3fc095794ec54">m_Variance</a> = &varianceTensor;</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html#ad5f8f205ba69eb186688ca1c2aec207c">m_Beta</a> = &betaTensor;</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  data.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html#afbe59e02a5464703b865ea1ccfff49fd">m_Gamma</a> = &gammaTensor;</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.01f;</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span> </div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.html">armnn::BatchNormalizationQueueDescriptor</a> refData = data;</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#abe1e0d40e23195022c0bc10a8aab55ea">CreateBatchNormalization</a>(data, info);</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#abe1e0d40e23195022c0bc10a8aab55ea">CreateBatchNormalization</a>(refData, refInfo);</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> </div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  inputHandle->Allocate();</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  outputHandle->Allocate();</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  inputHandleRef->Allocate();</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  outputHandleRef->Allocate();</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span> </div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandleRef.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  workload->Execute();</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  workloadRef->PostAllocationConfigure();</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  workloadRef->Execute();</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span> </div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.outputExpected[0][0][0][0], outputHandleRef.get());</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span> </div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span> }</div><div class="ttc" id="_tensor_copy_utils_8cpp_html_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.html#l00019">TensorCopyUtils.cpp:19</a></div></div> |
| 432 | <div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.html#l00009">TensorCopyUtils.cpp:9</a></div></div> |
| 433 | <div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 434 | <div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00049">WorkloadData.hpp:49</a></div></div> |
| 435 | <div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.html">armnn::BatchNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00269">WorkloadData.hpp:269</a></div></div> |
| 436 | <div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 437 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> |
| 438 | <div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_html_a40051a7aa82f25df43cc4244de04a7ec"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.html#a40051a7aa82f25df43cc4244de04a7ec">armnn::BatchNormalizationQueueDescriptor::m_Mean</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Mean</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00279">WorkloadData.hpp:279</a></div></div> |
| 439 | <div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div> |
| 440 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_html_abe1e0d40e23195022c0bc10a8aab55ea"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#abe1e0d40e23195022c0bc10a8aab55ea">armnn::IWorkloadFactory::CreateBatchNormalization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateBatchNormalization(const BatchNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01100">WorkloadFactory.cpp:1100</a></div></div> |
| 441 | <div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.html#l00014">TensorCopyUtils.cpp:14</a></div></div> |
| 442 | <div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_html_a8cd8696bb773a02714d3fc095794ec54"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.html#a8cd8696bb773a02714d3fc095794ec54">armnn::BatchNormalizationQueueDescriptor::m_Variance</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Variance</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00280">WorkloadData.hpp:280</a></div></div> |
| 443 | <div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div> |
| 444 | <div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 445 | <div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">armnn::BatchNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Value to add to the variance. Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00623">Descriptors.hpp:623</a></div></div> |
| 446 | <div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_html_afbe59e02a5464703b865ea1ccfff49fd"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.html#afbe59e02a5464703b865ea1ccfff49fd">armnn::BatchNormalizationQueueDescriptor::m_Gamma</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Gamma</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00282">WorkloadData.hpp:282</a></div></div> |
| 447 | <div class="ttc" id="classarmnn_1_1_scoped_cpu_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_scoped_cpu_tensor_handle.html">armnn::ScopedCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.html#l00106">CpuTensorHandle.hpp:106</a></div></div> |
| 448 | <div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_html_ad5f8f205ba69eb186688ca1c2aec207c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.html#ad5f8f205ba69eb186688ca1c2aec207c">armnn::BatchNormalizationQueueDescriptor::m_Beta</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Beta</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00281">WorkloadData.hpp:281</a></div></div> |
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