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| author | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
|---|---|---|
| committer | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
| commit | ae050524109f1ce827962665436ef7430f2ac479 (patch) | |
| tree | a087fe0c77570971dd7979f2757426c24e91afc7 /23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml | |
| parent | 8d2ca734165a068478df7cffa46185680b05cd20 (diff) | |
| download | armnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz | |
IVGCVSW-7255 Update Doxygen Documentation and publish on GitHub.
* Updating Doxygen documentation for 23.02 release.
Signed-off-by: David Monahan <david.monahan@arm.com>
Change-Id: I545574ff7664b4595d2fe6a91a3c35d2ad55df82
Diffstat (limited to '23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml')
| -rw-r--r-- | 23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml | 136 |
1 files changed, 99 insertions, 37 deletions
diff --git a/23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml b/23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml index fc1decf332..7373a15dd8 100644 --- a/23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml +++ b/23.02/classarmnn_1_1_neon_batch_normalization_workload.xhtml @@ -8,7 +8,7 @@ <head> <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> <meta http-equiv="X-UA-Compatible" content="IE=9"/> -<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="generator" content="Doxygen 1.8.17"/> <meta name="robots" content="NOINDEX, NOFOLLOW" /> <meta name="viewport" content="width=device-width, initial-scale=1"/> <title>ArmNN: NeonBatchNormalizationWorkload Class Reference</title> @@ -19,9 +19,6 @@ <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtreedata.js"></script> <script type="text/javascript" src="navtree.js"></script> -<script type="text/javascript"> - $(document).ready(initResizable); -</script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/searchdata.js"></script> <script type="text/javascript" src="search/search.js"></script> @@ -30,7 +27,8 @@ extensions: ["tex2jax.js"], jax: ["input/TeX","output/HTML-CSS"], }); -</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +</script> +<script type="text/javascript" async="async" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> <link href="doxygen.css" rel="stylesheet" type="text/css" /> <link href="stylesheet.css" rel="stylesheet" type="text/css"/> </head> @@ -51,18 +49,21 @@ </table> </div> <!-- end header part --> -<!-- Generated by Doxygen 1.8.13 --> +<!-- Generated by Doxygen 1.8.17 --> <script type="text/javascript"> +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ var searchBox = new SearchBox("searchBox", "search",false,'Search'); +/* @license-end */ </script> <script type="text/javascript" src="menudata.js"></script> <script type="text/javascript" src="menu.js"></script> <script type="text/javascript"> +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ $(function() { initMenu('',true,false,'search.php','Search'); $(document).ready(function() { init_search(); }); }); -</script> +/* @license-end */</script> <div id="main-nav"></div> </div><!-- top --> <div id="side-nav" class="ui-resizable side-nav-resizable"> @@ -76,7 +77,9 @@ $(function() { </div> </div> <script type="text/javascript"> -$(document).ready(function(){initNavTree('classarmnn_1_1_neon_batch_normalization_workload.xhtml','');}); +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ +$(document).ready(function(){initNavTree('classarmnn_1_1_neon_batch_normalization_workload.xhtml',''); initResizable(); }); +/* @license-end */ </script> <div id="doc-content"> <!-- window showing the filter options --> @@ -111,13 +114,13 @@ Inheritance diagram for NeonBatchNormalizationWorkload:</div> <map id="NeonBatchNormalizationWorkload_map" name="NeonBatchNormalizationWorkload_map"> <area href="classarmnn_1_1_neon_base_workload.xhtml" alt="NeonBaseWorkload< BatchNormalizationQueueDescriptor >" shape="rect" coords="0,112,352,136"/> <area href="classarmnn_1_1_base_workload.xhtml" alt="BaseWorkload< BatchNormalizationQueueDescriptor >" shape="rect" coords="0,56,352,80"/> -<area href="classarmnn_1_1_i_workload.xhtml" title="Workload interface to enqueue a layer computation. " alt="IWorkload" shape="rect" coords="0,0,352,24"/> -</map> - </div></div> +<area href="classarmnn_1_1_i_workload.xhtml" title="Workload interface to enqueue a layer computation." alt="IWorkload" shape="rect" coords="0,0,352,24"/> + </map> +</div></div> <table class="memberdecls"> <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> Public Member Functions</h2></td></tr> -<tr class="memitem:a8044a4d50d30c30e405ab785946bef12"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_batch_normalization_workload.xhtml#a8044a4d50d30c30e405ab785946bef12">NeonBatchNormalizationWorkload</a> (const <a class="el" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">BatchNormalizationQueueDescriptor</a> &descriptor, const <a class="el" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &<a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</td></tr> +<tr class="memitem:a8044a4d50d30c30e405ab785946bef12"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_batch_normalization_workload.xhtml#a8044a4d50d30c30e405ab785946bef12">NeonBatchNormalizationWorkload</a> (const <a class="el" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">BatchNormalizationQueueDescriptor</a> &descriptor, const <a class="el" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &info)</td></tr> <tr class="separator:a8044a4d50d30c30e405ab785946bef12"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ae071e8822437c78baea75c3aef3a263a"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_batch_normalization_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">Execute</a> () const override</td></tr> <tr class="separator:ae071e8822437c78baea75c3aef3a263a"><td class="memSeparator" colspan="2"> </td></tr> @@ -144,6 +147,10 @@ Public Member Functions</h2></td></tr> <tr class="inherit_header pub_methods_classarmnn_1_1_i_workload"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarmnn_1_1_i_workload')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classarmnn_1_1_i_workload.xhtml">IWorkload</a></td></tr> <tr class="memitem:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a69c83c02ae8de866bc7a46c49e69c1ba">~IWorkload</a> ()</td></tr> <tr class="separator:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a00f887eb14b9ed163d795b31c4964965 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual arm::pipe::ProfilingGuid </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a00f887eb14b9ed163d795b31c4964965">GetGuid</a> () const =0</td></tr> +<tr class="separator:a00f887eb14b9ed163d795b31c4964965 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a9cc47a21a60b5e47247cde5e660e29ce inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a9cc47a21a60b5e47247cde5e660e29ce">SupportsTensorHandleReplacement</a> () const =0</td></tr> +<tr class="separator:a9cc47a21a60b5e47247cde5e660e29ce inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#ab81312bd5e64cbae2803de9f243bdb32">RegisterDebugCallback</a> (const <a class="el" href="namespacearmnn.xhtml#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a> &)</td></tr> <tr class="separator:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a2d2834d1029217934f504e3e59579081 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="classarmnn_1_1_optional.xhtml">armnn::Optional</a>< <a class="el" href="structarmnn_1_1_memory_requirements.xhtml">armnn::MemoryRequirements</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a2d2834d1029217934f504e3e59579081">GetMemoryRequirements</a> ()</td></tr> @@ -191,26 +198,61 @@ Additional Inherited Members</h2></td></tr> </div><div class="memdoc"> <p class="definition">Definition at line <a class="el" href="_neon_batch_normalization_workload_8cpp_source.xhtml#l00059">59</a> of file <a class="el" href="_neon_batch_normalization_workload_8cpp_source.xhtml">NeonBatchNormalizationWorkload.cpp</a>.</p> - -<p class="reference">References <a class="el" href="_profiling_8hpp_source.xhtml#l00227">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>, <a class="el" href="_workload_8hpp_source.xhtml#l00083">BaseWorkload< BatchNormalizationQueueDescriptor >::m_Data</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00026">QueueDescriptor::m_Inputs</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00027">QueueDescriptor::m_Outputs</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00066">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, and <a class="el" href="_workload_data_8cpp_source.xhtml#l00475">QueueDescriptor::ValidateInputsOutputs()</a>.</p> -<div class="fragment"><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  : NeonBaseWorkload<BatchNormalizationQueueDescriptor>(descriptor, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Report Profiling Details</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload_Construct"</span>,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  descriptor.m_Parameters,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  this->GetGuid());</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload"</span>, 1, 1);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])->GetTensor();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])->GetTensor();</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  input.info()->set_data_layout(aclDataLayout);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  output.info()->set_data_layout(aclDataLayout);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  m_Mean = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  BuildArmComputeTensor(*m_Mean, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">m_Mean</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  m_Variance = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  BuildArmComputeTensor(*m_Variance, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">m_Variance</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  m_Gamma = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  BuildArmComputeTensor(*m_Gamma, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">m_Gamma</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  m_Beta = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  BuildArmComputeTensor(*m_Beta, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">m_Beta</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">ConvertAdditionalInfoToAclActivationLayerInfo</a>(descriptor);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">auto</span> layer = std::make_unique<arm_compute::NEBatchNormalizationLayer>();</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  layer->configure(&input,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  &output,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  m_Mean.get(),</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  m_Variance.get(),</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  m_Beta.get(),</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  m_Gamma.get(),</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a>,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  activationInfo);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  m_Layer.reset(layer.release());</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Mean, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">m_Mean</a>);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Variance, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">m_Variance</a>);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Gamma, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">m_Gamma</a>);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Beta, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">m_Beta</a>);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="comment">// Force Compute Library to perform the necessary copying and reshaping, after which</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// delete all the input tensors that will no longer be needed</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  m_Layer->prepare();</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  FreeUnusedTensors();</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> }</div><div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00062">Types.hpp:62</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_abfb0841058a8190d30851f07eca3991f"><div class="ttname"><a href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">armnn::ConvertAdditionalInfoToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &queueDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00103">ArmComputeUtils.hpp:103</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a744e5178444c4b7bc4d516f4bbee8fcd"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">armnn::BatchNormalizationQueueDescriptor::m_Variance</a></div><div class="ttdeci">const ConstTensorHandle * m_Variance</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00317">WorkloadData.hpp:317</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#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.xhtml#l00809">Descriptors.hpp:809</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00811">Descriptors.hpp:811</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00475">WorkloadData.cpp:475</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#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.xhtml#l00066">WorkloadData.hpp:66</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.xhtml#l00040">TensorHandle.hpp:40</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload< BatchNormalizationQueueDescriptor >::m_Data</a></div><div class="ttdeci">BatchNormalizationQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a611208865d55ea576cc89ac86d7c19b7"><div class="ttname"><a href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, TensorInfo tensorInfo, const ITensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00060">NeonWorkloadUtils.hpp:60</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a96ee5ab4a7d2d8a4634b77d4eb9a949f"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">armnn::BatchNormalizationQueueDescriptor::m_Gamma</a></div><div class="ttdeci">const ConstTensorHandle * m_Gamma</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00319">WorkloadData.hpp:319</a></div></div> -<div class="ttc" id="_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a0ae7224f556b0d008d060f847c8f8901"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">armnn::BatchNormalizationQueueDescriptor::m_Mean</a></div><div class="ttdeci">const ConstTensorHandle * m_Mean</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00316">WorkloadData.hpp:316</a></div></div> -<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml_addb90eb7f4baa493fce64fdb7f140018"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">armnn::BatchNormalizationQueueDescriptor::m_Beta</a></div><div class="ttdeci">const ConstTensorHandle * m_Beta</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00318">WorkloadData.hpp:318</a></div></div> +<div class="fragment"><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  : NeonBaseWorkload<BatchNormalizationQueueDescriptor>(descriptor, info)</div> +<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> {</div> +<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Report Profiling Details</span></div> +<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload_Construct"</span>,</div> +<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  descriptor.m_Parameters,</div> +<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  info,</div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  this->GetGuid());</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  </div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload"</span>, 1, 1);</div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  </div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])->GetTensor();</div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])->GetTensor();</div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  </div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div> +<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  input.info()->set_data_layout(aclDataLayout);</div> +<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  output.info()->set_data_layout(aclDataLayout);</div> +<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  </div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  m_Mean = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  BuildArmComputeTensor(*m_Mean, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">m_Mean</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  </div> +<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  m_Variance = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  BuildArmComputeTensor(*m_Variance, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">m_Variance</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  </div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  m_Gamma = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  BuildArmComputeTensor(*m_Gamma, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">m_Gamma</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  </div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  m_Beta = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  BuildArmComputeTensor(*m_Beta, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">m_Beta</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  </div> +<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> arm_compute::ActivationLayerInfo activationInfo = <a class="code" href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">ConvertAdditionalInfoToAclActivationLayerInfo</a>(descriptor);</div> +<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  </div> +<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">auto</span> layer = std::make_unique<arm_compute::NEBatchNormalizationLayer>();</div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  layer->configure(&input,</div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  &output,</div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  m_Mean.get(),</div> +<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  m_Variance.get(),</div> +<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  m_Beta.get(),</div> +<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  m_Gamma.get(),</div> +<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a>,</div> +<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  activationInfo);</div> +<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  m_Layer.reset(layer.release());</div> +<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  </div> +<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Mean, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">m_Mean</a>);</div> +<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Variance, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">m_Variance</a>);</div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Gamma, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">m_Gamma</a>);</div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_Beta, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">m_Beta</a>);</div> +<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  </div> +<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="comment">// Force Compute Library to perform the necessary copying and reshaping, after which</span></div> +<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// delete all the input tensors that will no longer be needed</span></div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  m_Layer->prepare();</div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  FreeUnusedTensors();</div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> }</div> </div><!-- fragment --> +<p class="reference">References <a class="el" href="_profiling_8hpp_source.xhtml#l00227">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_workload_8hpp_source.xhtml#l00083">BaseWorkload< BatchNormalizationQueueDescriptor >::m_Data</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00026">QueueDescriptor::m_Inputs</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00027">QueueDescriptor::m_Outputs</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00066">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, and <a class="el" href="_workload_data_8cpp_source.xhtml#l00475">QueueDescriptor::ValidateInputsOutputs()</a>.</p> + </div> </div> <h2 class="groupheader">Member Function Documentation</h2> @@ -240,11 +282,13 @@ Additional Inherited Members</h2></td></tr> <p>Implements <a class="el" href="classarmnn_1_1_i_workload.xhtml#a72ae00e6604850c8798c5e0d825ee7e4">IWorkload</a>.</p> <p class="definition">Definition at line <a class="el" href="_neon_batch_normalization_workload_8cpp_source.xhtml#l00114">114</a> of file <a class="el" href="_neon_batch_normalization_workload_8cpp_source.xhtml">NeonBatchNormalizationWorkload.cpp</a>.</p> - -<p class="reference">References <a class="el" href="_neon_workload_utils_8hpp_source.xhtml#l00024">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>, and <a class="el" href="_workload_8hpp_source.xhtml#l00061">BaseWorkload< BatchNormalizationQueueDescriptor >::GetGuid()</a>.</p> -<div class="fragment"><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload_Execute"</span>, this-><a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  m_Layer->run();</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> }</div><div class="ttc" id="classarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload< BatchNormalizationQueueDescriptor >::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div> -<div class="ttc" id="_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div> +<div class="fragment"><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div> +<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">"NeonBatchNormalizationWorkload_Execute"</span>, this-><a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div> +<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  m_Layer->run();</div> +<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> }</div> </div><!-- fragment --> +<p class="reference">References <a class="el" href="_neon_workload_utils_8hpp_source.xhtml#l00024">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>, and <a class="el" href="_workload_8hpp_source.xhtml#l00061">BaseWorkload< BatchNormalizationQueueDescriptor >::GetGuid()</a>.</p> + </div> </div> <hr/>The documentation for this class was generated from the following files:<ul> @@ -253,13 +297,31 @@ Additional Inherited Members</h2></td></tr> </ul> </div><!-- contents --> </div><!-- doc-content --> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a744e5178444c4b7bc4d516f4bbee8fcd"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a744e5178444c4b7bc4d516f4bbee8fcd">armnn::BatchNormalizationQueueDescriptor::m_Variance</a></div><div class="ttdeci">const ConstTensorHandle * m_Variance</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00317">WorkloadData.hpp:317</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload< BatchNormalizationQueueDescriptor >::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00811">Descriptors.hpp:811</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00475">WorkloadData.cpp:475</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00062">Types.hpp:62</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_queue_descriptor_xhtml_addb90eb7f4baa493fce64fdb7f140018"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#addb90eb7f4baa493fce64fdb7f140018">armnn::BatchNormalizationQueueDescriptor::m_Beta</a></div><div class="ttdeci">const ConstTensorHandle * m_Beta</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00318">WorkloadData.hpp:318</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload< BatchNormalizationQueueDescriptor >::m_Data</a></div><div class="ttdeci">BatchNormalizationQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a611208865d55ea576cc89ac86d7c19b7"><div class="ttname"><a href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, TensorInfo tensorInfo, const ITensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00060">NeonWorkloadUtils.hpp:60</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a96ee5ab4a7d2d8a4634b77d4eb9a949f"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a96ee5ab4a7d2d8a4634b77d4eb9a949f">armnn::BatchNormalizationQueueDescriptor::m_Gamma</a></div><div class="ttdeci">const ConstTensorHandle * m_Gamma</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00319">WorkloadData.hpp:319</a></div></div> +<div class="ttc" id="a_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_queue_descriptor_xhtml_a0ae7224f556b0d008d060f847c8f8901"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml#a0ae7224f556b0d008d060f847c8f8901">armnn::BatchNormalizationQueueDescriptor::m_Mean</a></div><div class="ttdeci">const ConstTensorHandle * m_Mean</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00316">WorkloadData.hpp:316</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.xhtml#l00040">TensorHandle.hpp:40</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_abfb0841058a8190d30851f07eca3991f"><div class="ttname"><a href="namespacearmnn.xhtml#abfb0841058a8190d30851f07eca3991f">armnn::ConvertAdditionalInfoToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &queueDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.xhtml#l00103">ArmComputeUtils.hpp:103</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#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.xhtml#l00066">WorkloadData.hpp:66</a></div></div> +<div class="ttc" id="a_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#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.xhtml#l00809">Descriptors.hpp:809</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="navelem"><a class="el" href="namespacearmnn.xhtml">armnn</a></li><li class="navelem"><a class="el" href="classarmnn_1_1_neon_batch_normalization_workload.xhtml">NeonBatchNormalizationWorkload</a></li> - <li class="footer">Generated on Fri Feb 24 2023 10:24:31 for ArmNN by + <li class="footer">Generated on Wed Mar 22 2023 15:53:06 for ArmNN by <a href="http://www.doxygen.org/index.html"> - <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.17 </li> </ul> </div> </body> |