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| <div class="title">LoadedNetwork.cpp</div> </div> |
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| <div class="contents"> |
| <a href="_loaded_network_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div> |
| <div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.</span></div> |
| <div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div> |
| <div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div> |
| <div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div> |
| <div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_loaded_network_8hpp.html">LoadedNetwork.hpp</a>"</span></div> |
| <div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_layer_8hpp.html">Layer.hpp</a>"</span></div> |
| <div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_graph_8hpp.html">Graph.hpp</a>"</span></div> |
| <div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_profiling_8hpp.html">Profiling.hpp</a>"</span></div> |
| <div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_heap_profiling_8hpp.html">HeapProfiling.hpp</a>"</span></div> |
| <div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_working_mem_handle_8hpp.html">WorkingMemHandle.hpp</a>"</span></div> |
| <div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "<a class="code" href="_execution_data_8hpp.html">ExecutionData.hpp</a>"</span></div> |
| <div class="line"><a name="l00013"></a><span class="lineno"> 13</span>  </div> |
| <div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_backend_helper_8hpp.html">armnn/BackendHelper.hpp</a>></span></div> |
| <div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_backend_registry_8hpp.html">armnn/BackendRegistry.hpp</a>></span></div> |
| <div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_logging_8hpp.html">armnn/Logging.hpp</a>></span></div> |
| <div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  </div> |
| <div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_tensor_handle_8hpp.html">armnn/backends/TensorHandle.hpp</a>></span></div> |
| <div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <<a class="code" href="_i_backend_internal_8hpp.html">armnn/backends/IBackendInternal.hpp</a>></span></div> |
| <div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <<a class="code" href="_i_memory_manager_8hpp.html">armnn/backends/IMemoryManager.hpp</a>></span></div> |
| <div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <<a class="code" href="_mem_copy_workload_8hpp.html">armnn/backends/MemCopyWorkload.hpp</a>></span></div> |
| <div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  </div> |
| <div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include <<a class="code" href="_arm_n_n_profiling_8hpp.html">armnn/profiling/ArmNNProfiling.hpp</a>></span></div> |
| <div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  </div> |
| <div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.html">armnn/utility/Assert.hpp</a>></span></div> |
| <div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  </div> |
| <div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <<a class="code" href="_mem_sync_workload_8hpp.html">backendsCommon/MemSyncWorkload.hpp</a>></span></div> |
| <div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  </div> |
| <div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <common/include/Processes.hpp></span></div> |
| <div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  </div> |
| <div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <fmt/format.h></span></div> |
| <div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  </div> |
| <div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div> |
| <div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div> |
| <div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  </div> |
| <div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">using namespace </span><a class="code" href="namespacestd.html">std</a>;</div> |
| <div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">using namespace </span><a class="code" href="namespacearm_1_1pipe.html">arm::pipe</a>;</div> |
| <div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  </div> |
| <div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">namespace</span></div> |
| <div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div> |
| <div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  </div> |
| <div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ExceptionType></div> |
| <div class="line"><a name="l00043"></a><span class="lineno"> 43</span> std::string ToErrorMessage(<span class="keyword">const</span> <span class="keywordtype">char</span> * prefix, <span class="keyword">const</span> ExceptionType & error)</div> |
| <div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div> |
| <div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  std::stringstream ss;</div> |
| <div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  ss << prefix << <span class="stringliteral">" "</span> << <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>.what();</div> |
| <div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">return</span> ss.str();</div> |
| <div class="line"><a name="l00048"></a><span class="lineno"> 48</span> }</div> |
| <div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  </div> |
| <div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keywordtype">void</span> AddLayerStructure(std::unique_ptr<TimelineUtilityMethods>& timelineUtils,</div> |
| <div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> Layer& layer,</div> |
| <div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  ProfilingGuid networkGuid)</div> |
| <div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div> |
| <div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// Add layer to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  std::string layerName = layer.GetNameStr().empty() ? <span class="stringliteral">"<Unnamed>"</span> : layer.GetNameStr();</div> |
| <div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  timelineUtils->CreateNamedTypedChildEntity(layer.GetGuid(),</div> |
| <div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  networkGuid,</div> |
| <div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  layerName,</div> |
| <div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  LabelsAndEventClasses::LAYER_GUID);</div> |
| <div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& input : layer.GetInputSlots())</div> |
| <div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  {</div> |
| <div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">const</span> IOutputSlot* source = input.GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">if</span> (!source)</div> |
| <div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {</div> |
| <div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Null source found on input to layer \""</span> + layerName + <span class="stringliteral">"\"."</span>);</div> |
| <div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  }</div> |
| <div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  timelineUtils->CreateConnectionRelationship(ProfilingRelationshipType::RetentionLink,</div> |
| <div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  source->GetOwningLayerGuid(),</div> |
| <div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  layer.GetGuid());</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> }</div> |
| <div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  </div> |
| <div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="keywordtype">void</span> AddWorkloadStructure(std::unique_ptr<TimelineUtilityMethods>& timelineUtils,</div> |
| <div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  std::unique_ptr<IWorkload>& workload,</div> |
| <div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">const</span> Layer& layer)</div> |
| <div class="line"><a name="l00076"></a><span class="lineno"> 76</span> {</div> |
| <div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// Add workload to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  timelineUtils->CreateTypedEntity(workload->GetGuid(), LabelsAndEventClasses::WORKLOAD_GUID);</div> |
| <div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  timelineUtils->MarkEntityWithLabel(workload->GetGuid(),</div> |
| <div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  layer.GetBackendId().Get(),</div> |
| <div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  LabelsAndEventClasses::BACKENDID_GUID);</div> |
| <div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  </div> |
| <div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// Link the workload to the layer</span></div> |
| <div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  timelineUtils->CreateRelationship(ProfilingRelationshipType::RetentionLink,</div> |
| <div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  layer.GetGuid(),</div> |
| <div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  workload->GetGuid(),</div> |
| <div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  LabelsAndEventClasses::CHILD_GUID);</div> |
| <div class="line"><a name="l00088"></a><span class="lineno"> 88</span> }</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="comment">// anonymous</span></div> |
| <div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"></span> </div> |
| <div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="comment">/**</span></div> |
| <div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"> * This function performs a sanity check to ensure that the combination of input and output memory source matches the</span></div> |
| <div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> * values for importEnabled and exportEnabled that were specified during optimization. During optimization the tensor</span></div> |
| <div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> * handle factories are chosen based on whether import and export are enabled. If the user then specifies something</span></div> |
| <div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> * incompatible here it can lead to problems.</span></div> |
| <div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"> *</span></div> |
| <div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"> * @param optimizedOptions</span></div> |
| <div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="comment"> * @param networkProperties</span></div> |
| <div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> */</span></div> |
| <div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a52928589effc0b9cbb170a93ea792d47"> 101</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a52928589effc0b9cbb170a93ea792d47">ValidateSourcesMatchOptimizedNetwork</a>(std::vector<BackendOptions> optimizedOptions,</div> |
| <div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_network_properties.html">INetworkProperties</a>& networkProperties)</div> |
| <div class="line"><a name="l00103"></a><span class="lineno"> 103</span> {</div> |
| <div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// Find the "Global" backend options. During the optimize phase the values of importEnabled and exportEnabled are</span></div> |
| <div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="comment">// added as backend options.</span></div> |
| <div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> vector<BackendOptions>::iterator& backendItr =</div> |
| <div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  find_if(optimizedOptions.begin(), optimizedOptions.end(), [](<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_backend_options.html">BackendOptions</a>& backend) {</div> |
| <div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  if (backend.GetBackendId().Get() == <span class="stringliteral">"Global"</span>)</div> |
| <div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div> |
| <div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  return true;</div> |
| <div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  }</div> |
| <div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  {</div> |
| <div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  return false;</div> |
| <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>  });</div> |
| <div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordtype">bool</span> importEnabled = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordtype">bool</span> exportEnabled = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">if</span> (backendItr != optimizedOptions.end())</div> |
| <div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  {</div> |
| <div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// Find the importEnabled and exportEnabled values.</span></div> |
| <div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < backendItr->GetOptionCount(); i++)</div> |
| <div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  {</div> |
| <div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">const</span> BackendOptions::BackendOption& option = backendItr->GetOption(i);</div> |
| <div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">if</span> (option.GetName() == <span class="stringliteral">"ImportEnabled"</span>)</div> |
| <div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  {</div> |
| <div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  importEnabled = option.GetValue().AsBool();</div> |
| <div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  }</div> |
| <div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">if</span> (option.GetName() == <span class="stringliteral">"ExportEnabled"</span>)</div> |
| <div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div> |
| <div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  exportEnabled = option.GetValue().AsBool();</div> |
| <div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  }</div> |
| <div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  }</div> |
| <div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  }</div> |
| <div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  </div> |
| <div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// Now that we have values for import and export compare them to the MemorySource variables.</span></div> |
| <div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// Any value of MemorySource that's not "Undefined" implies that we need to do an import of some kind.</span></div> |
| <div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">if</span> ((networkProperties.m_InputSource == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a> && importEnabled) ||</div> |
| <div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  (networkProperties.m_InputSource != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a> && !importEnabled))</div> |
| <div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  {</div> |
| <div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">auto</span> message = fmt::format(<span class="stringliteral">"The input memory source specified, '{0}',"</span>, networkProperties.m_InputSource);</div> |
| <div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">if</span> (!importEnabled)</div> |
| <div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  {</div> |
| <div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  message.append(<span class="stringliteral">" requires that memory import be enabled. However, "</span></div> |
| <div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="stringliteral">"it was disabled when this network was optimized."</span>);</div> |
| <div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div> |
| <div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  {</div> |
| <div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  message.append(<span class="stringliteral">" requires that memory import be disabled. However, "</span></div> |
| <div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="stringliteral">"it was enabled when this network was optimized."</span>);</div> |
| <div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  }</div> |
| <div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">throw</span> InvalidArgumentException(message);</div> |
| <div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  }</div> |
| <div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  </div> |
| <div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span> ((networkProperties.m_OutputSource == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a> && exportEnabled) ||</div> |
| <div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  (networkProperties.m_OutputSource != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a> && !exportEnabled))</div> |
| <div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  {</div> |
| <div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">auto</span> message = fmt::format(<span class="stringliteral">"The output memory source specified, '{0}',"</span>, networkProperties.m_OutputSource);</div> |
| <div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">if</span> (!exportEnabled)</div> |
| <div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  {</div> |
| <div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  message.append(<span class="stringliteral">" requires that memory export be enabled. However, "</span></div> |
| <div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="stringliteral">"it was disabled when this network was optimized."</span>);</div> |
| <div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div> |
| <div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {</div> |
| <div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  message.append(<span class="stringliteral">" requires that memory export be disabled. However, "</span></div> |
| <div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="stringliteral">"it was enabled when this network was optimized."</span>);</div> |
| <div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  }</div> |
| <div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">throw</span> InvalidArgumentException(message);</div> |
| <div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  }</div> |
| <div class="line"><a name="l00171"></a><span class="lineno"> 171</span> } <span class="comment">// anonymous</span></div> |
| <div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  </div> |
| <div class="line"><a name="l00173"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#af75dd30cff3d42ff35ddd2b625b7e9ae"> 173</a></span> std::unique_ptr<LoadedNetwork> <a class="code" href="classarmnn_1_1_loaded_network.html#af75dd30cff3d42ff35ddd2b625b7e9ae">LoadedNetwork::MakeLoadedNetwork</a>(std::unique_ptr<IOptimizedNetwork> net,</div> |
| <div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  std::string& errorMessage,</div> |
| <div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_network_properties.html">INetworkProperties</a>& networkProperties,</div> |
| <div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  arm::pipe::IProfilingService* profilingService)</div> |
| <div class="line"><a name="l00177"></a><span class="lineno"> 177</span> {</div> |
| <div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  std::unique_ptr<LoadedNetwork> loadedNetwork;</div> |
| <div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  </div> |
| <div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">auto</span> Fail = [&](<span class="keyword">const</span> std::exception& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) -> std::unique_ptr<LoadedNetwork></div> |
| <div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div> |
| <div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  errorMessage = ToErrorMessage(<span class="stringliteral">"An error occurred when preparing the network workloads: "</span>, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << errorMessage;</div> |
| <div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  </div> |
| <div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">return</span> std::unique_ptr<LoadedNetwork>();</div> |
| <div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  };</div> |
| <div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  </div> |
| <div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  {</div> |
| <div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  loadedNetwork.reset(<span class="keyword">new</span> <a class="code" href="classarmnn_1_1_loaded_network.html">LoadedNetwork</a>(std::move(net), networkProperties, profilingService));</div> |
| <div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  }</div> |
| <div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_runtime_exception.html">armnn::RuntimeException</a>& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  {</div> |
| <div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">return</span> Fail(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  }</div> |
| <div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  {</div> |
| <div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">return</span> Fail(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div> |
| <div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::runtime_error& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div> |
| <div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">return</span> Fail(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div> |
| <div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  </div> |
| <div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">return</span> loadedNetwork;</div> |
| <div class="line"><a name="l00206"></a><span class="lineno"> 206</span> }</div> |
| <div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  </div> |
| <div class="line"><a name="l00208"></a><span class="lineno"> 208</span> LoadedNetwork::LoadedNetwork(std::unique_ptr<IOptimizedNetwork> net,</div> |
| <div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_network_properties.html">INetworkProperties</a>& networkProperties,</div> |
| <div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  arm::pipe::IProfilingService* profilingService) :</div> |
| <div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  m_OptimizedNetwork(<a class="code" href="namespacestd.html">std</a>::move(net)),</div> |
| <div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  m_NetworkProperties(networkProperties),</div> |
| <div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  m_TensorHandleFactoryRegistry(),</div> |
| <div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  m_ProfilingService(profilingService)</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>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadedNetwork"</span>);</div> |
| <div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="comment">// Get the profiler and register it for the current thread.</span></div> |
| <div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keyword">const</span> std::shared_ptr<IProfiler>& profiler = m_OptimizedNetwork->GetProfiler();</div> |
| <div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="classarmnn_1_1_profiler_manager.html#a93857080c2523bf3395e7aa7e6024d5c">ProfilerManager::GetInstance</a>().<a class="code" href="classarmnn_1_1_profiler_manager.html#a7b1e3e5bf386004541be2b5b22443208">RegisterProfiler</a>(profiler.get());</div> |
| <div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  </div> |
| <div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  profiler->EnableProfiling(networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a7e26a8e7f1878d82bef452ef3531eaeb">m_ProfilingEnabled</a>);</div> |
| <div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  </div> |
| <div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  profiler->EnableNetworkDetailsToStdOut(networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#abbc76b61436b870aed2c8592690e9a70">m_OutputNetworkDetailsMethod</a>);</div> |
| <div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  </div> |
| <div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="comment">// We need to check that the memory sources match up with the values of import and export specified during the</span></div> |
| <div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="comment">// optimize phase. If they don't this will throw an exception.</span></div> |
| <div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="namespacearmnn.html#a52928589effc0b9cbb170a93ea792d47">ValidateSourcesMatchOptimizedNetwork</a>(m_OptimizedNetwork.get()->pOptimizedNetworkImpl->GetModelOptions(),</div> |
| <div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  m_NetworkProperties);</div> |
| <div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  </div> |
| <div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">//First create tensor handlers, backends and workload factories.</span></div> |
| <div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">//Handlers are created before workloads are.</span></div> |
| <div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="comment">//Because workload creation can modify some of the handlers,</span></div> |
| <div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="comment">//(for example the splitter and concat layers).</span></div> |
| <div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  </div> |
| <div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordtype">bool</span> useExternalMemoryManager = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordtype">bool</span> useInternalMemoryManager = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div> |
| <div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="comment">// Ensure Topological order</span></div> |
| <div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  order.<a class="code" href="classarmnn_1_1_graph.html#ac3b4675f7a50a0f242880fb044aa8dec">SetLayersOutOfOrder</a>();</div> |
| <div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  order.<a class="code" href="classarmnn_1_1_graph.html#af497e16cf92179b5e55543741351b8bf">TopologicalSort</a>();</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">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  {</div> |
| <div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  m_IsInputImported = std::vector<bool>(order.<a class="code" href="classarmnn_1_1_graph.html#a8d8179a4a0703602a5d7dbb6e92eaf69">GetNumInputs</a>(), <span class="keyword">false</span>);</div> |
| <div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  m_IsOutputImported = std::vector<bool>(order.<a class="code" href="classarmnn_1_1_graph.html#a604654b453ec291a503d62a0beb849d3">GetNumOutputs</a>(), <span class="keyword">false</span>);</div> |
| <div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  }</div> |
| <div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  </div> |
| <div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  {</div> |
| <div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keyword">auto</span> <span class="keyword">const</span>& backendId = layer->GetBackendId();</div> |
| <div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">if</span> (m_Backends.count(backendId) == 0)</div> |
| <div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  {</div> |
| <div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">auto</span> createBackend = <a class="code" href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.html#afc0c63ca8db8957b58826f6d7bd231b2">GetFactory</a>(backendId);</div> |
| <div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">auto</span> it = m_Backends.emplace(std::make_pair(backendId, createBackend()));</div> |
| <div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  </div> |
| <div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  IBackendInternal* backend = it.first->second.get();</div> |
| <div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  </div> |
| <div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="comment">// If we're doing async execution verify that the backend supports it and ExternallyManagedMemory.</span></div> |
| <div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">if</span> (networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  {</div> |
| <div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a406399d2a16ead98e4e93cdd57adead4">HasMatchingCapability</a>(BackendOptions::BackendOption{<span class="stringliteral">"AsyncExecution"</span>, <span class="keyword">true</span>},</div> |
| <div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  backend->GetCapabilities()))</div> |
| <div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div> |
| <div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  std::string er = backend->GetId();</div> |
| <div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  er += <span class="stringliteral">" does not support AsyncExecution"</span>;</div> |
| <div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">throw</span> BackendCapabilityException(er);</div> |
| <div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  }</div> |
| <div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a406399d2a16ead98e4e93cdd57adead4">HasMatchingCapability</a>(BackendOptions::BackendOption{<span class="stringliteral">"ExternallyManagedMemory"</span>, <span class="keyword">true</span>},</div> |
| <div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  backend->GetCapabilities()))</div> |
| <div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  {</div> |
| <div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  std::string er = backend->GetId();</div> |
| <div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  er += <span class="stringliteral">" does not support ExternallyManagedMemory\n"</span>;</div> |
| <div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  er += <span class="stringliteral">"AsyncEnabled networks require all backends to support ExternallyManagedMemory"</span>;</div> |
| <div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">throw</span> BackendCapabilityException(er);</div> |
| <div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  }</div> |
| <div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  m_SupportsExternallyManagedMemory[backend->GetId()] = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  useExternalMemoryManager = <span class="keyword">true</span>;</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="keywordflow">else</span></div> |
| <div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  {</div> |
| <div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  m_SupportsExternallyManagedMemory[backend->GetId()] = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  useInternalMemoryManager = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  }</div> |
| <div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  </div> |
| <div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <a class="code" href="classarmnn_1_1_i_backend_internal.html#a72ca1cf423bda4b0a9ffb789627126de">IBackendInternal::IWorkloadFactoryPtr</a> workloadFactory;</div> |
| <div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">if</span> (backend->SupportsTensorAllocatorAPI())</div> |
| <div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  {</div> |
| <div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  workloadFactory = backend->CreateWorkloadFactory(</div> |
| <div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  m_TensorHandleFactoryRegistry,</div> |
| <div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  m_OptimizedNetwork->pOptimizedNetworkImpl->GetModelOptions(),</div> |
| <div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">static_cast<</span><a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a><span class="keyword">></span>(m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>),</div> |
| <div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">static_cast<</span><a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a><span class="keyword">></span>(m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>));</div> |
| <div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  }</div> |
| <div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  {</div> |
| <div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  m_BackendMemoryMangers.emplace_back(backend->CreateMemoryManager());</div> |
| <div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  workloadFactory = backend->CreateWorkloadFactory(</div> |
| <div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  m_BackendMemoryMangers.back(), m_OptimizedNetwork->pOptimizedNetworkImpl->GetModelOptions());</div> |
| <div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  }</div> |
| <div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  m_WorkloadFactories[backendId ] = std::move(workloadFactory);</div> |
| <div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  }</div> |
| <div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  }</div> |
| <div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  </div> |
| <div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  {</div> |
| <div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  {</div> |
| <div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keyword">auto</span>& workloadFactory = GetWorkloadFactory(*layer);</div> |
| <div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordtype">bool</span> supportsExternalManager = m_SupportsExternallyManagedMemory[layer->GetBackendId()];</div> |
| <div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  </div> |
| <div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">switch</span> (layer->GetType())</div> |
| <div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  {</div> |
| <div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div> |
| <div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">LayerType::MemImport</a>:</div> |
| <div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  {</div> |
| <div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="comment">// If IsImportEnabled is true then we need to set IsMemoryManaged</span></div> |
| <div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="comment">// to false when creating TensorHandles</span></div> |
| <div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  layer->CreateTensorHandles(m_TensorHandleFactoryRegistry,</div> |
| <div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  workloadFactory,</div> |
| <div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  !supportsExternalManager &&</div> |
| <div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>));</div> |
| <div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">break</span>;</div> |
| <div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  }</div> |
| <div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>:</div> |
| <div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  {</div> |
| <div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  layer->CreateTensorHandles(m_TensorHandleFactoryRegistry, workloadFactory, <span class="keyword">true</span>);</div> |
| <div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">break</span>;</div> |
| <div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  }</div> |
| <div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">default</span>:</div> |
| <div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  {</div> |
| <div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="comment">// Look for a layer with 1 OutputSlot which has 1 connection and that connection is an Output Layer</span></div> |
| <div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="comment">// If Export is enabled disable memory management so we can export, otherwise we do a copy</span></div> |
| <div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">if</span> ((layer->GetNumOutputSlots() == 1) &&</div> |
| <div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  (layer->GetOutputSlots()[0].GetNumConnections() == 1) &&</div> |
| <div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  (layer->GetOutputSlots()[0].GetConnection(0)->GetOwningLayer().GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>))</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>  layer->CreateTensorHandles(m_TensorHandleFactoryRegistry,</div> |
| <div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  workloadFactory,</div> |
| <div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  !supportsExternalManager &&</div> |
| <div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>));</div> |
| <div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  }</div> |
| <div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div> |
| <div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  layer->CreateTensorHandles(m_TensorHandleFactoryRegistry,</div> |
| <div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  workloadFactory,</div> |
| <div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  !supportsExternalManager);</div> |
| <div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  }</div> |
| <div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  }</div> |
| <div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  }</div> |
| <div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  }</div> |
| <div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  }</div> |
| <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>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div> |
| <div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div> |
| <div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">if</span> (timelineUtils)</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>  timelineUtils->CreateTypedEntity(networkGuid, LabelsAndEventClasses::NETWORK_GUID);</div> |
| <div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// Mark the network with a start of life event</span></div> |
| <div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  timelineUtils->RecordEvent(networkGuid, LabelsAndEventClasses::ARMNN_PROFILING_SOL_EVENT_CLASS);</div> |
| <div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="comment">// and with the process ID</span></div> |
| <div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordtype">int</span> processID = arm::pipe::GetCurrentProcessId();</div> |
| <div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  std::stringstream ss;</div> |
| <div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  ss << processID;</div> |
| <div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  timelineUtils->MarkEntityWithLabel(networkGuid, ss.str(), LabelsAndEventClasses::PROCESS_ID_GUID);</div> |
| <div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  }</div> |
| <div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  </div> |
| <div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  std::vector<IWorkload*> ConstWorkloads;</div> |
| <div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  </div> |
| <div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="comment">//Then create workloads.</span></div> |
| <div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  {</div> |
| <div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadNetwork_CreateWorkloads"</span>);</div> |
| <div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer: order)</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="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  {</div> |
| <div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="comment">// Add layer to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  AddLayerStructure(timelineUtils, *layer, networkGuid);</div> |
| <div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  }</div> |
| <div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  </div> |
| <div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">const</span> IWorkloadFactory& workloadFactory = GetWorkloadFactory(*layer);</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="keywordflow">switch</span> (layer->GetType())</div> |
| <div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  {</div> |
| <div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div> |
| <div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</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="comment">// Inputs and outputs are treated in a special way - see EnqueueInput() and EnqueueOutput().</span></div> |
| <div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">break</span>;</div> |
| <div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  }</div> |
| <div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordflow">default</span>:</div> |
| <div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  {</div> |
| <div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keyword">auto</span> workload = layer->CreateWorkload(workloadFactory);</div> |
| <div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  </div> |
| <div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">if</span> (!workload)</div> |
| <div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  {</div> |
| <div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* <span class="keyword">const</span> layerName =</div> |
| <div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  layer->GetNameStr().length() != 0 ? layer->GetName() : <span class="stringliteral">"<Unnamed>"</span>;</div> |
| <div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">throw</span> InvalidArgumentException(</div> |
| <div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  fmt::format(<span class="stringliteral">"No workload created for layer (name: '{0}' type: '{1}') (compute '{2}')"</span>,</div> |
| <div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  layerName, <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(layer->GetType()), layer->GetBackendId().Get()</div> |
| <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>  }</div> |
| <div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  </div> |
| <div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  {</div> |
| <div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="comment">// Add workload to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  AddWorkloadStructure(timelineUtils, workload, *layer);</div> |
| <div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  }</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">// For async networks ConstantWorkloads are managed exclusively by LoadedNetwork</span></div> |
| <div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="comment">// and are separated out from the other workloads</span></div> |
| <div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordflow">if</span>((networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a> || useExternalMemoryManager) &&</div> |
| <div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</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>  m_ConstantTensorHandles[layer->GetGuid()] =</div> |
| <div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  layer->GetOutputSlot(0).GetOutputHandler().GetData();</div> |
| <div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  m_ConstantWorkloads[layer->GetGuid()] = std::move(workload);</div> |
| <div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  }</div> |
| <div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  {</div> |
| <div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  m_WorkloadQueue.push_back(std::move(workload));</div> |
| <div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  </div> |
| <div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  {</div> |
| <div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="comment">// Place the Constant Workloads into a queue so that they can be executed first</span></div> |
| <div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  ConstWorkloads.push_back(m_WorkloadQueue.back().get());</div> |
| <div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  }</div> |
| <div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  }</div> |
| <div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="comment">// release the constant data in the layer.</span></div> |
| <div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  layer->ReleaseConstantData();</div> |
| <div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordflow">break</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>  }</div> |
| <div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  }</div> |
| <div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  }</div> |
| <div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  </div> |
| <div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="comment">// Gather information about workloads for inputs & outputs</span></div> |
| <div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a> && m_WorkloadQueue.size() != 0)</div> |
| <div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  {</div> |
| <div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> noOfInputs = armnn::numeric_cast<int>(order.GetNumInputs());</div> |
| <div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  </div> |
| <div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="comment">// Get indices of all workloads connected to each input and</span></div> |
| <div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="comment">// check if they support tensor handle replacement</span></div> |
| <div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* layer: order.GetInputLayers())</div> |
| <div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  {</div> |
| <div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = layer->GetBindingId();</div> |
| <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="keywordtype">bool</span> supportsReplacement = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  </div> |
| <div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span> inputSlot: layer->GetOutputSlot(0).GetConnections())</div> |
| <div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  {</div> |
| <div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">auto</span> workloadIndex = std::distance(order.begin(), order.GetPosInGraph(inputSlot->GetOwningLayer()));</div> |
| <div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  workloadIndex -= noOfInputs;</div> |
| <div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  </div> |
| <div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  m_InputWorkloadSlotPairs[bindingId].emplace_back(WorkloadIndices{</div> |
| <div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  armnn::numeric_cast<unsigned int>(workloadIndex), inputSlot->GetSlotIndex()});</div> |
| <div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  </div> |
| <div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="comment">// Avoid if input is connected directly to an output</span></div> |
| <div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">if</span> (inputSlot->GetOwningLayer().GetType() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div> |
| <div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  {</div> |
| <div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="keyword">auto</span> workload = m_WorkloadQueue[m_InputWorkloadSlotPairs[bindingId].back().m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  supportsReplacement &= workload->SupportsTensorHandleReplacement();</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>  }</div> |
| <div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  </div> |
| <div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = layer->GetOutputSlot(0).GetTensorHandleFactoryId();</div> |
| <div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="comment">// Get matching import factory Id</span></div> |
| <div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> importFactoryId =</div> |
| <div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#aeef3a1178e2dfe2ca2461d89cd47fff6">GetMatchingImportFactoryId</a>(factoryId);</div> |
| <div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  </div> |
| <div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  ITensorHandleFactory *importFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(importFactoryId);</div> |
| <div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  </div> |
| <div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">if</span> (supportsReplacement && importFactory)</div> |
| <div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  {</div> |
| <div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  m_PreImportedInputHandles.emplace_back(</div> |
| <div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  bindingId, importFactory->CreateTensorHandle(layer->GetOutputSlot(0).GetTensorInfo(), <span class="keyword">false</span>));</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="keywordflow">else</span></div> |
| <div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  {</div> |
| <div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  m_PreImportedInputHandles.emplace_back(bindingId, <span class="keyword">nullptr</span>);</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>  </div> |
| <div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="comment">// Get indices of all workloads connected to each output and</span></div> |
| <div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="comment">// check if they support tensor handle replacement</span></div> |
| <div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* layer: order.GetOutputLayers())</div> |
| <div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  {</div> |
| <div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = layer->GetBindingId();</div> |
| <div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  </div> |
| <div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keyword">const</span> <span class="keyword">auto</span> outputSlot = layer->GetInputSlot(0).GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keyword">auto</span>& indices = m_OutputWorkloadSlotPairs[bindingId];</div> |
| <div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  </div> |
| <div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="comment">// Avoid if output is connected directly to an input</span></div> |
| <div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">if</span> (outputSlot->GetOwningLayer().GetType() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  {</div> |
| <div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keyword">auto</span> workloadIndex = std::distance(order.begin(), order.GetPosInGraph(outputSlot->GetOwningLayer()));</div> |
| <div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  workloadIndex -= noOfInputs;</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>  indices.m_OutputSlotIndices = WorkloadIndices{numeric_cast<unsigned int>(workloadIndex),</div> |
| <div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  outputSlot->CalculateIndexOnOwner()};</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="keywordtype">bool</span> supportsReplacement = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <span class="keyword">auto</span> outputWorkload = m_WorkloadQueue[indices.m_OutputSlotIndices.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  supportsReplacement &= outputWorkload->SupportsTensorHandleReplacement();</div> |
| <div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  </div> |
| <div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> &inputSlot: outputSlot->GetConnections())</div> |
| <div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  {</div> |
| <div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="keywordflow">if</span> (inputSlot->GetOwningLayer().GetType() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div> |
| <div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  {</div> |
| <div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keyword">auto</span> inWorkloadIndex = std::distance(order.begin(),</div> |
| <div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  order.GetPosInGraph(inputSlot->GetOwningLayer()));</div> |
| <div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  inWorkloadIndex -= noOfInputs;</div> |
| <div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  indices.m_InputSlotIndices.emplace_back(</div> |
| <div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  WorkloadIndices{numeric_cast<unsigned int>(inWorkloadIndex),</div> |
| <div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  inputSlot->GetSlotIndex()});</div> |
| <div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keyword">auto</span> inputWorkload = m_WorkloadQueue[indices.m_InputSlotIndices.back().m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  supportsReplacement &= inputWorkload->SupportsTensorHandleReplacement();</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>  }</div> |
| <div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  </div> |
| <div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = outputSlot->GetTensorHandleFactoryId();</div> |
| <div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="comment">// Get matching import factory Id</span></div> |
| <div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> importFactoryId =</div> |
| <div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#aeef3a1178e2dfe2ca2461d89cd47fff6">GetMatchingImportFactoryId</a>(factoryId);</div> |
| <div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  ITensorHandleFactory *importFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(importFactoryId);</div> |
| <div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  </div> |
| <div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keywordflow">if</span> (supportsReplacement && importFactory)</div> |
| <div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  {</div> |
| <div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  m_PreImportedOutputHandles.emplace_back(</div> |
| <div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  bindingId, importFactory->CreateTensorHandle(outputSlot->GetTensorInfo(), <span class="keyword">false</span>));</div> |
| <div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  }</div> |
| <div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  {</div> |
| <div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  m_PreImportedOutputHandles.emplace_back(bindingId, <span class="keyword">nullptr</span>);</div> |
| <div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  }</div> |
| <div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  }</div> |
| <div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  }</div> |
| <div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  }</div> |
| <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="keywordflow">for</span> (<span class="keyword">auto</span>&& workloadFactory : m_WorkloadFactories)</div> |
| <div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  {</div> |
| <div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  workloadFactory.second->AfterWorkloadsCreated();</div> |
| <div class="line"><a name="l00544"></a><span class="lineno"> 544</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="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  {</div> |
| <div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="comment">// Commit to send the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  }</div> |
| <div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  </div> |
| <div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordflow">if</span> (useExternalMemoryManager)</div> |
| <div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  {</div> |
| <div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">if</span> (networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  {</div> |
| <div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  CreateMemoryProfileAsync();</div> |
| <div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  }</div> |
| <div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  {</div> |
| <div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  CreateMemoryProfile();</div> |
| <div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  }</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="keyword">auto</span> backendStrategyMap = <a class="code" href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.html#a8a7a14a6f1f1078e1b9d31c60d09e007">GetMemoryOptimizerStrategies</a>();</div> |
| <div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& backendMemoryProfile : m_MemBlockMap)</div> |
| <div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  {</div> |
| <div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="keyword">const</span> BackendId& backendId = backendMemoryProfile.first;</div> |
| <div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordflow">if</span> (backendStrategyMap.find(backendId) != backendStrategyMap.end())</div> |
| <div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  {</div> |
| <div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  m_MemBinMap[backendId] = backendStrategyMap[backendId]->Optimize(backendMemoryProfile.second);</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="keywordflow">else</span></div> |
| <div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  {</div> |
| <div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  m_MemBinMap[backendId] = m_ConstantStrategy->Optimize(backendMemoryProfile.second);</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>  </div> |
| <div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  {</div> |
| <div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  m_ExternalMemoryManager = CreateExternalMemoryManger(m_TensorMemory);</div> |
| <div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  </div> |
| <div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="comment">// Sort m_TensorMemory, so it's order matches m_Tensorhandles</span></div> |
| <div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  std::sort(m_TensorMemory.begin(), m_TensorMemory.end(),</div> |
| <div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  [](<span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& lhs,</div> |
| <div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& rhs)</div> |
| <div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  {</div> |
| <div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  return lhs.first->m_OutputSlotId < rhs.first->m_OutputSlotId;</div> |
| <div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  });</div> |
| <div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  }</div> |
| <div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  }</div> |
| <div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  </div> |
| <div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="comment">// Now that the intermediate tensor memory has been set-up,</span></div> |
| <div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="comment">// do any post allocation configuration for each workload.</span></div> |
| <div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  {</div> |
| <div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keywordflow">if</span> (useInternalMemoryManager)</div> |
| <div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  {</div> |
| <div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="comment">// Set up memory.</span></div> |
| <div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().AllocateDynamicBuffers();</div> |
| <div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  }</div> |
| <div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  </div> |
| <div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> &workload : m_WorkloadQueue)</div> |
| <div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  {</div> |
| <div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  workload->PostAllocationConfigure();</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>  }</div> |
| <div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  </div> |
| <div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">if</span> (useExternalMemoryManager)</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="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</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>  AllocateAndExecuteConstantWorkloads();</div> |
| <div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  }</div> |
| <div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  {</div> |
| <div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  AllocateAndExecuteConstantWorkloadsAsync();</div> |
| <div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  }</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>  <span class="comment">// If synchronous, execute all constant layer workloads</span></div> |
| <div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keywordflow">if</span> (!networkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</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>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> workload: ConstWorkloads)</div> |
| <div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  {</div> |
| <div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  workload->Execute();</div> |
| <div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  }</div> |
| <div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  }</div> |
| <div class="line"><a name="l00626"></a><span class="lineno"> 626</span> }</div> |
| <div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  </div> |
| <div class="line"><a name="l00628"></a><span class="lineno"> 628</span> <span class="keywordtype">void</span> LoadedNetwork::AllocateAndExecuteConstantWorkloads()</div> |
| <div class="line"><a name="l00629"></a><span class="lineno"> 629</span> {</div> |
| <div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadNetwork_AllocateAndExecuteConstants"</span>);</div> |
| <div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& pair : m_ConstantWorkloads)</div> |
| <div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  {</div> |
| <div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keyword">auto</span> tensorHandle = m_ConstantTensorHandles[pair.first];</div> |
| <div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  tensorHandle->Allocate();</div> |
| <div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  pair.second->Execute();</div> |
| <div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  }</div> |
| <div class="line"><a name="l00637"></a><span class="lineno"> 637</span> }</div> |
| <div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  </div> |
| <div class="line"><a name="l00639"></a><span class="lineno"> 639</span> <span class="keywordtype">void</span> LoadedNetwork::AllocateAndExecuteConstantWorkloadsAsync()</div> |
| <div class="line"><a name="l00640"></a><span class="lineno"> 640</span> {</div> |
| <div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadNetwork_AllocateAndExecuteConstants"</span>);</div> |
| <div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div> |
| <div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  {</div> |
| <div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  {</div> |
| <div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& outSlot = layer->GetOutputSlots()[0];</div> |
| <div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <span class="keyword">const</span> <span class="keyword">auto</span> factoryId = outSlot.GetTensorHandleFactoryId();</div> |
| <div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <span class="keywordflow">if</span> (factoryId == <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>)</div> |
| <div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  {</div> |
| <div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"factoryId must not be of type \"Legacy\"."</span>);</div> |
| <div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  }</div> |
| <div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <span class="keyword">auto</span>& workloadFactory = GetWorkloadFactory(*layer);</div> |
| <div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  </div> |
| <div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  layer->CreateTensorHandles(m_TensorHandleFactoryRegistry, workloadFactory);</div> |
| <div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  ITensorHandle* tensorHandle = outSlot.GetOutputHandler().GetData();</div> |
| <div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  </div> |
| <div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  m_ConstantTensorHandles[layer->GetGuid()] = tensorHandle;</div> |
| <div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  tensorHandle->Allocate();</div> |
| <div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  </div> |
| <div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <span class="keyword">auto</span>& backend = m_Backends.at(layer->GetBackendId());</div> |
| <div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  </div> |
| <div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  WorkingMemDescriptor memDesc;</div> |
| <div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  memDesc.m_Outputs.push_back(tensorHandle);</div> |
| <div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  </div> |
| <div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  ExecutionData executionData = backend->CreateExecutionData(memDesc);</div> |
| <div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  m_ConstantWorkloads[layer->GetGuid()]->ExecuteAsync(executionData);</div> |
| <div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  }</div> |
| <div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  }</div> |
| <div class="line"><a name="l00670"></a><span class="lineno"> 670</span> }</div> |
| <div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  </div> |
| <div class="line"><a name="l00672"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#ae41171032a9c106c1fd4b5991045eb0b"> 672</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_loaded_network.html#ae41171032a9c106c1fd4b5991045eb0b">LoadedNetwork::SendNetworkStructure</a>(arm::pipe::IProfilingService& profilingService)</div> |
| <div class="line"><a name="l00673"></a><span class="lineno"> 673</span> {</div> |
| <div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadNetwork_SendNetworkStructure"</span>);</div> |
| <div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div> |
| <div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  </div> |
| <div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  TimelineUtilityMethods::GetTimelineUtils(profilingService);</div> |
| <div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  </div> |
| <div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  timelineUtils->CreateTypedEntity(networkGuid, LabelsAndEventClasses::NETWORK_GUID);</div> |
| <div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  </div> |
| <div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  {</div> |
| <div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  <span class="comment">// Add layer to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  AddLayerStructure(timelineUtils, *layer, networkGuid);</div> |
| <div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <span class="keywordflow">switch</span> (layer->GetType())</div> |
| <div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  {</div> |
| <div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div> |
| <div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</div> |
| <div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  {</div> |
| <div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="comment">// Inputs and outputs are treated in a special way - see EnqueueInput() and EnqueueOutput().</span></div> |
| <div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <span class="keywordflow">break</span>;</div> |
| <div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  }</div> |
| <div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <span class="keywordflow">default</span>:</div> |
| <div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  {</div> |
| <div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& workload : m_WorkloadQueue)</div> |
| <div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  {</div> |
| <div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="comment">// Add workload to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  AddWorkloadStructure(timelineUtils, workload, *layer);</div> |
| <div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  }</div> |
| <div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">break</span>;</div> |
| <div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  }</div> |
| <div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  }</div> |
| <div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  }</div> |
| <div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <span class="comment">// Commit to send the post-optimisation network structure</span></div> |
| <div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l00708"></a><span class="lineno"> 708</span> }</div> |
| <div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  </div> |
| <div class="line"><a name="l00710"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#ad90f4f6c9360c5cb64c164b9ddcb3130"> 710</a></span> ProfilingGuid <a class="code" href="classarmnn_1_1_loaded_network.html#ad90f4f6c9360c5cb64c164b9ddcb3130">LoadedNetwork::GetNetworkGuid</a>()</div> |
| <div class="line"><a name="l00711"></a><span class="lineno"> 711</span> {</div> |
| <div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keywordflow">return</span> m_OptimizedNetwork->GetGuid();</div> |
| <div class="line"><a name="l00713"></a><span class="lineno"> 713</span> }</div> |
| <div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  </div> |
| <div class="line"><a name="l00715"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#af616683424cb40d83b5a923db7f06f11"> 715</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="classarmnn_1_1_loaded_network.html#af616683424cb40d83b5a923db7f06f11">LoadedNetwork::GetInputTensorInfo</a>(<a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId)<span class="keyword"> const</span></div> |
| <div class="line"><a name="l00716"></a><span class="lineno"> 716</span> <span class="keyword"></span>{</div> |
| <div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& inputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetInputLayers())</div> |
| <div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  {</div> |
| <div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <span class="keywordflow">if</span> (inputLayer->GetNumOutputSlots() != 1)</div> |
| <div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  {</div> |
| <div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"Input layer should have exactly 1 output slot"</span>);</div> |
| <div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  }</div> |
| <div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  </div> |
| <div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <span class="keywordflow">if</span> (inputLayer->GetBindingId() == layerId)</div> |
| <div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  {</div> |
| <div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">return</span> inputLayer->GetOutputSlot(0).GetTensorInfo();</div> |
| <div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  }</div> |
| <div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  }</div> |
| <div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  </div> |
| <div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"No input layer is associated with id {}"</span>, layerId));</div> |
| <div class="line"><a name="l00731"></a><span class="lineno"> 731</span> }</div> |
| <div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  </div> |
| <div class="line"><a name="l00733"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a2b6b57945bc68f659e08d28c8a015e91"> 733</a></span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="classarmnn_1_1_loaded_network.html#a2b6b57945bc68f659e08d28c8a015e91">LoadedNetwork::GetOutputTensorInfo</a>(<a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId)<span class="keyword"> const</span></div> |
| <div class="line"><a name="l00734"></a><span class="lineno"> 734</span> <span class="keyword"></span>{</div> |
| <div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& outputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetOutputLayers())</div> |
| <div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  {</div> |
| <div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <span class="keywordflow">if</span> (outputLayer->GetNumInputSlots() != 1)</div> |
| <div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  {</div> |
| <div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"Output layer should have exactly 1 input slot"</span>);</div> |
| <div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  }</div> |
| <div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  </div> |
| <div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="keywordflow">if</span> (!outputLayer->GetInputSlot(0).GetConnection())</div> |
| <div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  {</div> |
| <div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"Input slot on Output layer must be connected"</span>);</div> |
| <div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  }</div> |
| <div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  </div> |
| <div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="keywordflow">if</span> (outputLayer->GetBindingId() == layerId)</div> |
| <div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  {</div> |
| <div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keywordflow">return</span> outputLayer->GetInputSlot(0).GetTensorInfo();</div> |
| <div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  }</div> |
| <div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  }</div> |
| <div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  </div> |
| <div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"No output layer is associated with id {}"</span>, layerId));</div> |
| <div class="line"><a name="l00754"></a><span class="lineno"> 754</span> }</div> |
| <div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  </div> |
| <div class="line"><a name="l00756"></a><span class="lineno"> 756</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html">IWorkloadFactory</a>& LoadedNetwork::GetWorkloadFactory(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">Layer</a>& layer)<span class="keyword"> const</span></div> |
| <div class="line"><a name="l00757"></a><span class="lineno"> 757</span> <span class="keyword"></span>{</div> |
| <div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html">IWorkloadFactory</a>* workloadFactory = <span class="keyword">nullptr</span>;</div> |
| <div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  </div> |
| <div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <span class="keyword">auto</span> it = m_WorkloadFactories.find(layer.<a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div> |
| <div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <span class="keywordflow">if</span> (it == m_WorkloadFactories.end())</div> |
| <div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  {</div> |
| <div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_runtime_exception.html">RuntimeException</a>(fmt::format(<span class="stringliteral">"No workload factory for {0} to be used for layer: {1}"</span>,</div> |
| <div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  layer.<a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>().<a class="code" href="classarmnn_1_1_backend_id.html#af7445617163d3f07c47b92ae56c6cf8b">Get</a>(),</div> |
| <div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  layer.<a class="code" href="classarmnn_1_1_layer.html#a9a97cb6d32661a57fc33bd29b8e41ff4">GetNameStr</a>()),</div> |
| <div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div> |
| <div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  }</div> |
| <div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  </div> |
| <div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  workloadFactory = it->second.get();</div> |
| <div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  </div> |
| <div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <span class="keywordflow">if</span> (!workloadFactory)</div> |
| <div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  {</div> |
| <div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"No workload factory"</span>);</div> |
| <div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  }</div> |
| <div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  </div> |
| <div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="keywordflow">return</span> *workloadFactory;</div> |
| <div class="line"><a name="l00777"></a><span class="lineno"> 777</span> }</div> |
| <div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  </div> |
| <div class="line"><a name="l00779"></a><span class="lineno"> 779</span> <span class="keyword">namespace </span>{</div> |
| <div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  </div> |
| <div class="line"><a name="l00781"></a><span class="lineno"> 781</span> <span class="comment">// Non-copyable class owning accelerator-specific tensor data.</span></div> |
| <div class="line"><a name="l00782"></a><span class="lineno"> 782</span> <span class="keyword">class </span>TensorPin</div> |
| <div class="line"><a name="l00783"></a><span class="lineno"> 783</span> {</div> |
| <div class="line"><a name="l00784"></a><span class="lineno"> 784</span> <span class="keyword">public</span>:</div> |
| <div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  TensorPin(std::unique_ptr<ITensorHandle> handle, <span class="keyword">const</span> TensorInfo& info, <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>)</div> |
| <div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  : m_TensorHandle(<a class="code" href="namespacestd.html">std</a>::move(handle))</div> |
| <div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  , m_TensorInfo(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div> |
| <div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  , m_Id(id)</div> |
| <div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  {</div> |
| <div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  }</div> |
| <div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  </div> |
| <div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  ITensorHandle* GetTensorHandle()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_TensorHandle.get(); }</div> |
| <div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <span class="keyword">const</span> TensorInfo& <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_TensorInfo; }</div> |
| <div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> GetBindingId()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> m_Id; }</div> |
| <div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  </div> |
| <div class="line"><a name="l00796"></a><span class="lineno"> 796</span> <span class="keyword">private</span>:</div> |
| <div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  std::unique_ptr<ITensorHandle> m_TensorHandle;</div> |
| <div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  TensorInfo m_TensorInfo;</div> |
| <div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> m_Id;</div> |
| <div class="line"><a name="l00800"></a><span class="lineno"> 800</span> };</div> |
| <div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  </div> |
| <div class="line"><a name="l00802"></a><span class="lineno"> 802</span> <span class="keyword">static</span> <span class="keyword">const</span> TensorPin& GetTensorPin(<a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>,</div> |
| <div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keyword">const</span> std::vector<TensorPin>& pins,</div> |
| <div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <span class="keywordtype">char</span> <span class="keyword">const</span>* bindingPointDesc)</div> |
| <div class="line"><a name="l00805"></a><span class="lineno"> 805</span> {</div> |
| <div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">auto</span> it = std::find_if(pins.begin(), pins.end(),</div> |
| <div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  [<span class="keywordtype">id</span>](<span class="keyword">const</span> TensorPin& pin)</div> |
| <div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  {</div> |
| <div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  return pin.GetBindingId() == id;</div> |
| <div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  });</div> |
| <div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  </div> |
| <div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <span class="keywordflow">if</span> (it != pins.end())</div> |
| <div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  {</div> |
| <div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="keywordflow">return</span> *it;</div> |
| <div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  }</div> |
| <div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  {</div> |
| <div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"No tensor supplied for {0} {1}"</span>, bindingPointDesc, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  }</div> |
| <div class="line"><a name="l00820"></a><span class="lineno"> 820</span> }</div> |
| <div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  </div> |
| <div class="line"><a name="l00822"></a><span class="lineno"> 822</span> <span class="comment">// Stores data that needs to be kept accessible for the entire execution of a workload.</span></div> |
| <div class="line"><a name="l00823"></a><span class="lineno"> 823</span> <span class="keyword">class </span>WorkloadData</div> |
| <div class="line"><a name="l00824"></a><span class="lineno"> 824</span> {</div> |
| <div class="line"><a name="l00825"></a><span class="lineno"> 825</span> <span class="keyword">public</span>:</div> |
| <div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  WorkloadData(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors, <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors)</div> |
| <div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  {</div> |
| <div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  m_InputTensorPins.reserve(inputTensors.size());</div> |
| <div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  m_OutputTensorPins.reserve(outputTensors.size());</div> |
| <div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  </div> |
| <div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputTensorPair : inputTensors)</div> |
| <div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  {</div> |
| <div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  <span class="keyword">auto</span> inputTensor = inputTensorPair.second;</div> |
| <div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  </div> |
| <div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.GetInfo(),inputTensor.GetMemoryArea());</div> |
| <div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId = inputTensorPair.first;</div> |
| <div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  </div> |
| <div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  m_InputTensorPins.emplace_back(std::move(tensorHandle), inputTensor.GetInfo(), layerId);</div> |
| <div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  }</div> |
| <div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  </div> |
| <div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputTensorPair : outputTensors)</div> |
| <div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  {</div> |
| <div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">auto</span> outputTensor = outputTensorPair.second;</div> |
| <div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  </div> |
| <div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  std::make_unique<PassthroughTensorHandle>(outputTensor.GetInfo(), outputTensor.GetMemoryArea());</div> |
| <div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId = outputTensorPair.first;</div> |
| <div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  </div> |
| <div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  m_OutputTensorPins.emplace_back(std::move(tensorHandle), outputTensor.GetInfo(), layerId);</div> |
| <div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  }</div> |
| <div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  }</div> |
| <div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  </div> |
| <div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="keyword">const</span> TensorPin& GetInputTensorPin(<a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>)<span class="keyword"> const</span></div> |
| <div class="line"><a name="l00855"></a><span class="lineno"> 855</span> <span class="keyword"> </span>{</div> |
| <div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keywordflow">return</span> GetTensorPin(<span class="keywordtype">id</span>, m_InputTensorPins, <span class="stringliteral">"input"</span>);</div> |
| <div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  }</div> |
| <div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  </div> |
| <div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <span class="keyword">const</span> TensorPin& GetOutputTensorPin(<a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>)<span class="keyword"> const</span></div> |
| <div class="line"><a name="l00860"></a><span class="lineno"> 860</span> <span class="keyword"> </span>{</div> |
| <div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <span class="keywordflow">return</span> GetTensorPin(<span class="keywordtype">id</span>, m_OutputTensorPins, <span class="stringliteral">"output"</span>);</div> |
| <div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  }</div> |
| <div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  </div> |
| <div class="line"><a name="l00864"></a><span class="lineno"> 864</span> <span class="keyword">private</span>:</div> |
| <div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  </div> |
| <div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  std::vector<TensorPin> m_InputTensorPins;</div> |
| <div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  std::vector<TensorPin> m_OutputTensorPins;</div> |
| <div class="line"><a name="l00868"></a><span class="lineno"> 868</span> };</div> |
| <div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  </div> |
| <div class="line"><a name="l00870"></a><span class="lineno"> 870</span> }</div> |
| <div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  </div> |
| <div class="line"><a name="l00872"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a87880cba8611688cc57bec8f913958e8"> 872</a></span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_loaded_network.html#a87880cba8611688cc57bec8f913958e8">LoadedNetwork::EnqueueWorkload</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors,</div> |
| <div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors,</div> |
| <div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  std::vector<ImportedInputId> preImportedInputIds,</div> |
| <div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  std::vector<ImportedOutputId> preImportedOutputIds)</div> |
| <div class="line"><a name="l00876"></a><span class="lineno"> 876</span> {</div> |
| <div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div> |
| <div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  </div> |
| <div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <span class="comment">// Walk graph to determine the order of execution.</span></div> |
| <div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <span class="keywordflow">if</span> (graph.<a class="code" href="classarmnn_1_1_graph.html#afdf8eb85585a798ad0e936bde884d87b">GetNumLayers</a>() < 2)</div> |
| <div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  {</div> |
| <div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) << <span class="stringliteral">"IRuntime::EnqueueWorkload()::Less than two nodes in graph"</span>;</div> |
| <div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</a>;</div> |
| <div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  }</div> |
| <div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  </div> |
| <div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <span class="comment">// Data that must be kept alive for the entire execution of the workload.</span></div> |
| <div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  WorkloadData workloadData(inputTensors, outputTensors);</div> |
| <div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  </div> |
| <div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <span class="comment">// Input tensors can be provided as parameters or pre imported. Either way the number of</span></div> |
| <div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="comment">// tensors should match the number of inputs.</span></div> |
| <div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <span class="keywordflow">if</span> (graph.<a class="code" href="classarmnn_1_1_graph.html#a8d8179a4a0703602a5d7dbb6e92eaf69">GetNumInputs</a>() != (inputTensors.size() + preImportedInputIds.size()))</div> |
| <div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  {</div> |
| <div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Number of inputs provided does not match network."</span>);</div> |
| <div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  }</div> |
| <div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  </div> |
| <div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="comment">// For each input to the network, call EnqueueInput with the data passed by the user.</span></div> |
| <div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  {</div> |
| <div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareInputs"</span>);</div> |
| <div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  m_InputQueue.clear();</div> |
| <div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  m_InputQueue.reserve(graph.<a class="code" href="classarmnn_1_1_graph.html#a8d8179a4a0703602a5d7dbb6e92eaf69">GetNumInputs</a>());</div> |
| <div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  </div> |
| <div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0;</div> |
| <div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> importedInputIdIndex = 0;</div> |
| <div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  std::sort(preImportedInputIds.begin(), preImportedInputIds.end());</div> |
| <div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>* inputLayer : graph.<a class="code" href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>())</div> |
| <div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  {</div> |
| <div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keywordflow">if</span> (importedInputIdIndex < preImportedInputIds.size() &&</div> |
| <div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  inputIndex == preImportedInputIds[importedInputIdIndex])</div> |
| <div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  {</div> |
| <div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  <span class="comment">// Only replace tensorhandles if they have not already been replaced</span></div> |
| <div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="keywordflow">if</span> (!m_IsInputImported[inputIndex])</div> |
| <div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  {</div> |
| <div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  <span class="keyword">auto</span> outputTensorHandle = m_PreImportedInputHandles[inputIndex].m_TensorHandle.get();</div> |
| <div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  </div> |
| <div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: m_InputWorkloadSlotPairs[inputLayer->GetBindingId()])</div> |
| <div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  {</div> |
| <div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <span class="keyword">auto</span> workload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  workload->ReplaceInputTensorHandle(outputTensorHandle, workloadInfo.m_SlotIndex);</div> |
| <div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  }</div> |
| <div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  m_IsInputImported[inputIndex] = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  }</div> |
| <div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  importedInputIdIndex++;</div> |
| <div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  }</div> |
| <div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  {</div> |
| <div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <span class="keywordflow">if</span> (m_IsInputImported[inputIndex])</div> |
| <div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  {</div> |
| <div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <a class="code" href="classarmnn_1_1_output_handler.html">OutputHandler</a>& handler = <span class="keyword">const_cast<</span><a class="code" href="classarmnn_1_1_output_handler.html">OutputHandler</a>&<span class="keyword">></span>(inputLayer->GetOutputHandler(0));</div> |
| <div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  </div> |
| <div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: m_InputWorkloadSlotPairs[inputLayer->GetBindingId()])</div> |
| <div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  {</div> |
| <div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <span class="keyword">auto</span> workload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  workload->ReplaceInputTensorHandle(handler.<a class="code" href="classarmnn_1_1_output_handler.html#afe3429ac30b180c11f01ea0f9f546f0e">GetData</a>(), workloadInfo.m_SlotIndex);</div> |
| <div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  }</div> |
| <div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  </div> |
| <div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  m_IsInputImported[inputIndex] = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  }</div> |
| <div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  </div> |
| <div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="comment">// InputTensorHandle is not imported yet, process to enqueue input</span></div> |
| <div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keyword">const</span> TensorPin& pin = workloadData.GetInputTensorPin(inputLayer->GetBindingId());</div> |
| <div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  EnqueueInput(*inputLayer, pin.GetTensorHandle(), pin.GetTensorInfo());</div> |
| <div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  }</div> |
| <div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  inputIndex++;</div> |
| <div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  }</div> |
| <div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  }</div> |
| <div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="comment">// For each output to the network, call EnqueueOutput with the data passed by the user.</span></div> |
| <div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  {</div> |
| <div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareOutputs"</span>);</div> |
| <div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  m_OutputQueue.clear();</div> |
| <div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  m_OutputQueue.reserve(graph.<a class="code" href="classarmnn_1_1_graph.html#a604654b453ec291a503d62a0beb849d3">GetNumOutputs</a>());</div> |
| <div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  </div> |
| <div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <span class="keywordflow">if</span> (preImportedOutputIds.size() > graph.<a class="code" href="classarmnn_1_1_graph.html#a604654b453ec291a503d62a0beb849d3">GetNumOutputs</a>())</div> |
| <div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  {</div> |
| <div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Invalid number of preImportedOutputIds"</span>);</div> |
| <div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  }</div> |
| <div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  </div> |
| <div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div> |
| <div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> importedOutputIdIndex = 0;</div> |
| <div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  std::sort(preImportedOutputIds.begin(), preImportedOutputIds.end());</div> |
| <div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>* outputLayer : graph.<a class="code" href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">GetOutputLayers</a>())</div> |
| <div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  {</div> |
| <div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  <span class="keywordflow">if</span> (importedOutputIdIndex < preImportedOutputIds.size() &&</div> |
| <div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  outputIndex == preImportedOutputIds[importedOutputIdIndex])</div> |
| <div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  {</div> |
| <div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  <span class="comment">// Only replace tensorhandles if they have not already been replaced</span></div> |
| <div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* inputTensorHandle = m_PreImportedOutputHandles[outputIndex].m_TensorHandle.get();</div> |
| <div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  </div> |
| <div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  <span class="keywordflow">if</span> (!m_IsOutputImported[outputIndex])</div> |
| <div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  {</div> |
| <div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = outputLayer->GetBindingId();</div> |
| <div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& indices = m_OutputWorkloadSlotPairs[bindingId];</div> |
| <div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  </div> |
| <div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <span class="keyword">auto</span> outputWorkload = m_WorkloadQueue[indices.m_OutputSlotIndices.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  </div> |
| <div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  outputWorkload->ReplaceOutputTensorHandle(inputTensorHandle,</div> |
| <div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  indices.m_OutputSlotIndices.m_SlotIndex);</div> |
| <div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  </div> |
| <div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: indices.m_InputSlotIndices)</div> |
| <div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  {</div> |
| <div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <span class="keyword">auto</span> inputWorkload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  inputWorkload->ReplaceInputTensorHandle(inputTensorHandle, workloadInfo.m_SlotIndex);</div> |
| <div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  }</div> |
| <div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  m_IsOutputImported[outputIndex] = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  }</div> |
| <div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  </div> |
| <div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  <span class="keywordflow">if</span> (!inputTensorHandle)</div> |
| <div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  {</div> |
| <div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Data should have been allocated."</span>);</div> |
| <div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  }</div> |
| <div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  </div> |
| <div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  <a class="code" href="structarmnn_1_1_mem_sync_queue_descriptor.html">MemSyncQueueDescriptor</a> syncDesc;</div> |
| <div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  syncDesc.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>.push_back(inputTensorHandle);</div> |
| <div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  <a class="code" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div> |
| <div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos.push_back(outputLayer->GetInputSlot(0).GetTensorInfo());</div> |
| <div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  </div> |
| <div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <span class="keyword">auto</span> syncWorkload = std::make_unique<SyncMemGenericWorkload>(syncDesc, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div> |
| <div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <span class="keywordflow">if</span> (!syncWorkload)</div> |
| <div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  {</div> |
| <div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"No sync workload created"</span>);</div> |
| <div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  }</div> |
| <div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  </div> |
| <div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  m_OutputQueue.push_back(std::move(syncWorkload));</div> |
| <div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  importedOutputIdIndex++;</div> |
| <div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  }</div> |
| <div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  {</div> |
| <div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="keywordflow">if</span> (m_IsOutputImported[outputIndex])</div> |
| <div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  {</div> |
| <div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = outputLayer->GetBindingId();</div> |
| <div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& indices = m_OutputWorkloadSlotPairs[bindingId];</div> |
| <div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  </div> |
| <div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <span class="keyword">auto</span> outputWorkload = m_WorkloadQueue[indices.m_OutputSlotIndices.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_handler.html">OutputHandler</a>& outputHandler =</div> |
| <div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  outputLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetOutputHandler();</div> |
| <div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  </div> |
| <div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  outputWorkload->ReplaceOutputTensorHandle(</div> |
| <div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  outputHandler.<a class="code" href="classarmnn_1_1_output_handler.html#afe3429ac30b180c11f01ea0f9f546f0e">GetData</a>(), indices.m_OutputSlotIndices.m_SlotIndex);</div> |
| <div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  </div> |
| <div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: indices.m_InputSlotIndices)</div> |
| <div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  {</div> |
| <div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <span class="keyword">auto</span> inputWorkload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div> |
| <div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  inputWorkload->ReplaceInputTensorHandle(outputHandler.<a class="code" href="classarmnn_1_1_output_handler.html#afe3429ac30b180c11f01ea0f9f546f0e">GetData</a>(), workloadInfo.m_SlotIndex);</div> |
| <div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  }</div> |
| <div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  m_IsOutputImported[outputIndex] = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  }</div> |
| <div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  </div> |
| <div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  <span class="keyword">const</span> TensorPin& pin = workloadData.GetOutputTensorPin(outputLayer->GetBindingId());</div> |
| <div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  <span class="comment">// OutputTensorHandle is not imported yet, process to enqueue Output</span></div> |
| <div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  EnqueueOutput(*outputLayer, pin.GetTensorHandle(), pin.GetTensorInfo());</div> |
| <div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  }</div> |
| <div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  outputIndex++;</div> |
| <div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  }</div> |
| <div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  }</div> |
| <div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  </div> |
| <div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div> |
| <div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  ProfilingGuid inferenceGuid = m_ProfilingService->GetNextGuid();</div> |
| <div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  {</div> |
| <div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  <span class="comment">// Add inference timeline trace if profiling is enabled.</span></div> |
| <div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div> |
| <div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  timelineUtils->CreateTypedEntity(inferenceGuid, LabelsAndEventClasses::INFERENCE_GUID);</div> |
| <div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  timelineUtils->CreateRelationship(ProfilingRelationshipType::RetentionLink,</div> |
| <div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  networkGuid,</div> |
| <div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  inferenceGuid,</div> |
| <div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  LabelsAndEventClasses::EXECUTION_OF_GUID);</div> |
| <div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  timelineUtils->RecordEvent(inferenceGuid, LabelsAndEventClasses::ARMNN_PROFILING_SOL_EVENT_CLASS);</div> |
| <div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  }</div> |
| <div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  </div> |
| <div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <span class="keywordtype">bool</span> executionSucceeded = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  </div> |
| <div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>  {</div> |
| <div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <span class="keywordflow">if</span> (m_ProfilingService->IsProfilingEnabled())</div> |
| <div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  {</div> |
| <div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  m_ProfilingService->IncrementCounterValue(INFERENCES_RUN);</div> |
| <div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  }</div> |
| <div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"Execute"</span>);</div> |
| <div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  <a class="code" href="_heap_profiling_8hpp.html#aeeb927880fc4ffc2eea754a67d884a53">ARMNN_SCOPED_HEAP_PROFILING</a>(<span class="stringliteral">"Executing"</span>);</div> |
| <div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  executionSucceeded = <a class="code" href="classarmnn_1_1_loaded_network.html#a95b1c23f6f296a0c39383bef20fdd46a">Execute</a>(timelineUtils, inferenceGuid);</div> |
| <div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  }</div> |
| <div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  </div> |
| <div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  {</div> |
| <div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  <span class="comment">// Add end of life of the inference timeline if profiling is enabled.</span></div> |
| <div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  timelineUtils->RecordEvent(inferenceGuid, LabelsAndEventClasses::ARMNN_PROFILING_EOL_EVENT_CLASS);</div> |
| <div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  }</div> |
| <div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  </div> |
| <div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <span class="keywordflow">return</span> executionSucceeded ? <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a> : <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</a>;</div> |
| <div class="line"><a name="l01070"></a><span class="lineno"> 1070</span> }</div> |
| <div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  </div> |
| <div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> <span class="keywordtype">void</span> LoadedNetwork::EnqueueInput(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>& layer, <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& tensorInfo)</div> |
| <div class="line"><a name="l01073"></a><span class="lineno"> 1073</span> {</div> |
| <div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  {</div> |
| <div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"EnqueueInput: given layer not an InputLayer"</span>);</div> |
| <div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  }</div> |
| <div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  </div> |
| <div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  <span class="keywordflow">if</span> (tensorHandle == <span class="keyword">nullptr</span>)</div> |
| <div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  {</div> |
| <div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"EnqueueInput: tensorHandle must not be NULL"</span>);</div> |
| <div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  }</div> |
| <div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>  </div> |
| <div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  <a class="code" href="namespacearmnn.html#a2231ac018fe2c465f2d42fef597d67e7">InputQueueDescriptor</a> inputQueueDescriptor;</div> |
| <div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  WorkloadInfo <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div> |
| <div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  </div> |
| <div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  inputQueueDescriptor.m_Inputs.push_back(tensorHandle);</div> |
| <div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos.push_back(tensorInfo);</div> |
| <div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  </div> |
| <div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.html#a1594bddc87d6477df300317658f566bb">GetNumOutputSlots</a>() != 1)</div> |
| <div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  {</div> |
| <div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"Can only handle Input Layer with one output"</span>);</div> |
| <div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  }</div> |
| <div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  </div> |
| <div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  <span class="keyword">const</span> OutputHandler& handler = layer.<a class="code" href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">GetOutputHandler</a>();</div> |
| <div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  <span class="keyword">const</span> TensorInfo& outputTensorInfo = handler.<a class="code" href="classarmnn_1_1_output_handler.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</div> |
| <div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  ITensorHandle* outputTensorHandle = handler.GetData();</div> |
| <div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  </div> |
| <div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <span class="keywordflow">if</span> (!outputTensorHandle)</div> |
| <div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  {</div> |
| <div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Data should have been allocated."</span>);</div> |
| <div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  }</div> |
| <div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  </div> |
| <div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  inputQueueDescriptor.m_Outputs.push_back(outputTensorHandle);</div> |
| <div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_OutputTensorInfos.push_back(outputTensorInfo);</div> |
| <div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  </div> |
| <div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a> importFlags = outputTensorHandle->GetImportFlags();</div> |
| <div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keywordtype">bool</span> needMemCopy = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  <span class="keywordflow">if</span> ((m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)) <span class="comment">// Try import the input tensor</span></div> |
| <div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  {</div> |
| <div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(importFlags, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>))</div> |
| <div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  {</div> |
| <div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  needMemCopy = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <span class="comment">// This assumes a CPU Tensor handle</span></div> |
| <div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  <span class="keywordtype">void</span>* mem = tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a9afbc055a017adf1bc38ee137bca6e90">Map</a>(<span class="keyword">false</span>);</div> |
| <div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  <span class="keywordflow">if</span> (outputTensorHandle->Import(mem, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>))</div> |
| <div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  {</div> |
| <div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div> |
| <div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  <span class="keywordflow">return</span>; <span class="comment">// No need for a workload since the import has been done.</span></div> |
| <div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  }</div> |
| <div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div> |
| <div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"EnqueueInput: Memory Import failed"</span>);</div> |
| <div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  }</div> |
| <div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  }</div> |
| <div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <span class="keywordflow">if</span> (needMemCopy)</div> |
| <div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  {</div> |
| <div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <span class="comment">// Create a mem copy workload for input since we did not import</span></div> |
| <div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  std::unique_ptr<IWorkload> inputWorkload = std::make_unique<CopyMemGenericWorkload>(inputQueueDescriptor, info);</div> |
| <div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  </div> |
| <div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <span class="keywordflow">if</span> (!inputWorkload)</div> |
| <div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  {</div> |
| <div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"No input workload created"</span>);</div> |
| <div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  }</div> |
| <div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  </div> |
| <div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div> |
| <div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  {</div> |
| <div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  <span class="comment">// Add Input Workload to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  AddWorkloadStructure(timelineUtils, inputWorkload, layer);</div> |
| <div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  }</div> |
| <div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  </div> |
| <div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  m_InputQueue.push_back(std::move(inputWorkload));</div> |
| <div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  }</div> |
| <div class="line"><a name="l01146"></a><span class="lineno"> 1146</span> }</div> |
| <div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  </div> |
| <div class="line"><a name="l01148"></a><span class="lineno"> 1148</span> <span class="keywordtype">void</span> LoadedNetwork::EnqueueOutput(<span class="keyword">const</span> BindableLayer& layer, ITensorHandle* tensorHandle, <span class="keyword">const</span> TensorInfo& tensorInfo)</div> |
| <div class="line"><a name="l01149"></a><span class="lineno"> 1149</span> {</div> |
| <div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  <span class="keywordflow">if</span> (layer.GetType() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div> |
| <div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  {</div> |
| <div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"EnqueueOutput: given layer not an OutputLayer"</span>);</div> |
| <div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  }</div> |
| <div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  </div> |
| <div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  <span class="keywordflow">if</span> (tensorHandle == <span class="keyword">nullptr</span>)</div> |
| <div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  {</div> |
| <div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"EnqueueOutput: tensorHandle must not be NULL"</span>);</div> |
| <div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  }</div> |
| <div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  </div> |
| <div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="namespacearmnn.html#a37a1a6b381ccc76df203fee023234996">OutputQueueDescriptor</a> outputQueueDescriptor;</div> |
| <div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  WorkloadInfo <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div> |
| <div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  </div> |
| <div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  outputQueueDescriptor.m_Outputs.push_back(tensorHandle);</div> |
| <div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_OutputTensorInfos.push_back(tensorInfo);</div> |
| <div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  </div> |
| <div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="keywordflow">if</span> (layer.GetNumInputSlots() != 1)</div> |
| <div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  {</div> |
| <div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"Output Layer should have exactly one input."</span>);</div> |
| <div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  }</div> |
| <div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  </div> |
| <div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  <span class="comment">// Gets the output handler from the previous node.</span></div> |
| <div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  <span class="keyword">const</span> OutputHandler& outputHandler = layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetOutputHandler();</div> |
| <div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  </div> |
| <div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  <span class="keyword">const</span> TensorInfo& inputTensorInfo = outputHandler.GetTensorInfo();</div> |
| <div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  ITensorHandle* inputTensorHandle = outputHandler.GetData();</div> |
| <div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  <span class="keywordflow">if</span> (!inputTensorHandle)</div> |
| <div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  {</div> |
| <div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Data should have been allocated."</span>);</div> |
| <div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  }</div> |
| <div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  </div> |
| <div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  <span class="comment">// Try import the output tensor.</span></div> |
| <div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  <span class="comment">// Note: We can only import the output pointer if all of the following hold true:</span></div> |
| <div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  <span class="comment">// a) The imported pointer is aligned sufficiently</span></div> |
| <div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  <span class="comment">// b) The tensor has zero padding</span></div> |
| <div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  <span class="comment">// c) There is only one connection to the OutputSlot and it is to an OutputLayer.</span></div> |
| <div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  <span class="comment">// d) The output pointer is allocated via malloc. (Other types will be supported in a later release)</span></div> |
| <div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <span class="comment">// e) m_NetworkProperties.m_OutputSource != MemorySource::Undefined</span></div> |
| <div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  <span class="keywordtype">bool</span> needMemCopy = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  <span class="keywordflow">if</span> (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a> &&</div> |
| <div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  (layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetNumConnections() == 1))</div> |
| <div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  {</div> |
| <div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  <span class="keywordflow">if</span>(layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetOwningLayer().GetType() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  {</div> |
| <div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  <a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a> importFlags = inputTensorHandle->GetImportFlags();</div> |
| <div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(importFlags, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>))</div> |
| <div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  {</div> |
| <div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  needMemCopy = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  <span class="keywordtype">void</span> *mem = tensorHandle->Map(<span class="keyword">false</span>);</div> |
| <div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  <span class="keywordtype">bool</span> importOk = inputTensorHandle->Import(mem, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>);</div> |
| <div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  tensorHandle->Unmap();</div> |
| <div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  </div> |
| <div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  <span class="keywordflow">if</span> (importOk)</div> |
| <div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  {</div> |
| <div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <span class="comment">// Insert synchronization workload</span></div> |
| <div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  MemSyncQueueDescriptor syncDesc;</div> |
| <div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  syncDesc.m_Inputs.push_back(inputTensorHandle);</div> |
| <div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos.push_back(inputTensorInfo);</div> |
| <div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  <span class="keyword">auto</span> syncWorkload = std::make_unique<SyncMemGenericWorkload>(syncDesc, info);</div> |
| <div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  <span class="keywordflow">if</span> (!syncWorkload)</div> |
| <div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  {</div> |
| <div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"No sync workload created"</span>);</div> |
| <div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  }</div> |
| <div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  m_OutputQueue.push_back(std::move(syncWorkload));</div> |
| <div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  }</div> |
| <div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  {</div> |
| <div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <span class="keywordflow">throw</span> MemoryExportException(<span class="stringliteral">"EnqueueOutput: Memory Export failed"</span>);</div> |
| <div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  }</div> |
| <div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  }</div> |
| <div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  }</div> |
| <div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  }</div> |
| <div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <span class="keywordflow">if</span> (needMemCopy)</div> |
| <div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  {</div> |
| <div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  <span class="comment">// If we got here then we didn't export the memory, so add an output workload which performs a memcopy.</span></div> |
| <div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  outputQueueDescriptor.m_Inputs.push_back(inputTensorHandle);</div> |
| <div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos.push_back(inputTensorInfo);</div> |
| <div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  </div> |
| <div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  std::unique_ptr<IWorkload> outputWorkload =</div> |
| <div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  std::make_unique<CopyMemGenericWorkload>(outputQueueDescriptor, info);</div> |
| <div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  <span class="keywordflow">if</span> (!outputWorkload)</div> |
| <div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  {</div> |
| <div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"No output workload created"</span>);</div> |
| <div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  }</div> |
| <div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  </div> |
| <div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div> |
| <div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  {</div> |
| <div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <span class="comment">// Add Output Workload to the post-optimisation network structure</span></div> |
| <div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  AddWorkloadStructure(timelineUtils, outputWorkload, layer);</div> |
| <div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  }</div> |
| <div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  </div> |
| <div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  m_OutputQueue.push_back(std::move(outputWorkload));</div> |
| <div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  }</div> |
| <div class="line"><a name="l01246"></a><span class="lineno"> 1246</span> }</div> |
| <div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  </div> |
| <div class="line"><a name="l01248"></a><span class="lineno"> 1248</span> <span class="keywordtype">void</span> LoadedNetwork::AllocateWorkingMemory(</div> |
| <div class="line"><a name="l01249"></a><span class="lineno"> 1249</span> #<span class="keywordflow">if</span> !defined(ARMNN_DISABLE_THREADS)</div> |
| <div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  std::lock_guard<std::mutex>& lock</div> |
| <div class="line"><a name="l01251"></a><span class="lineno"> 1251</span> #endif</div> |
| <div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  )</div> |
| <div class="line"><a name="l01253"></a><span class="lineno"> 1253</span> {</div> |
| <div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"Working Memory Allocation"</span>);</div> |
| <div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  </div> |
| <div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> <span class="preprocessor">#if !defined(ARMNN_DISABLE_THREADS)</span></div> |
| <div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <span class="comment">// this unused parameter makes sure we can only call this function with a valid lock</span></div> |
| <div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  <a class="code" href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(lock);</div> |
| <div class="line"><a name="l01259"></a><span class="lineno"> 1259</span> <span class="preprocessor">#endif</span></div> |
| <div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <span class="keywordflow">if</span> (m_IsWorkingMemAllocated)</div> |
| <div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  {</div> |
| <div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  <span class="keywordflow">return</span>;</div> |
| <div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  }</div> |
| <div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  </div> |
| <div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <span class="keywordflow">if</span> (m_ExternalMemoryManager)</div> |
| <div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  {</div> |
| <div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  m_ExternalMemoryManager->Allocate();</div> |
| <div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  </div> |
| <div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_TensorMemory.size(); ++i)</div> |
| <div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  {</div> |
| <div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  m_Tensorhandles[i]->Import(m_TensorMemory[i].first->m_Data, m_TensorMemory[i].second);</div> |
| <div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>  }</div> |
| <div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  }</div> |
| <div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  </div> |
| <div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& memoryManager : m_BackendMemoryMangers)</div> |
| <div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  {</div> |
| <div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  <span class="keywordflow">if</span> (memoryManager)</div> |
| <div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>  {</div> |
| <div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  memoryManager->Acquire();</div> |
| <div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  }</div> |
| <div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  }</div> |
| <div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#a46d1634d1bfbf6920adc98569ba10a94">AquireMemory</a>();</div> |
| <div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  m_IsWorkingMemAllocated = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01284"></a><span class="lineno"> 1284</span> }</div> |
| <div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>  </div> |
| <div class="line"><a name="l01286"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#aaf8558a23ae9be6e7ea165989f1fa808"> 1286</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_loaded_network.html#aaf8558a23ae9be6e7ea165989f1fa808">LoadedNetwork::FreeWorkingMemory</a>()</div> |
| <div class="line"><a name="l01287"></a><span class="lineno"> 1287</span> {</div> |
| <div class="line"><a name="l01288"></a><span class="lineno"> 1288</span> <span class="preprocessor">#if !defined(ARMNN_DISABLE_THREADS)</span></div> |
| <div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  std::lock_guard<std::mutex> lockGuard(m_WorkingMemMutex);</div> |
| <div class="line"><a name="l01290"></a><span class="lineno"> 1290</span> <span class="preprocessor">#endif</span></div> |
| <div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  </div> |
| <div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  <span class="keywordflow">if</span> (!m_IsWorkingMemAllocated)</div> |
| <div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  {</div> |
| <div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  <span class="keywordflow">return</span>;</div> |
| <div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  }</div> |
| <div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  </div> |
| <div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  <span class="keywordflow">if</span> (m_ExternalMemoryManager)</div> |
| <div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  {</div> |
| <div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  m_ExternalMemoryManager->Deallocate();</div> |
| <div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>  }</div> |
| <div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  </div> |
| <div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  <span class="comment">// Informs the memory managers to release memory in its respective memory group</span></div> |
| <div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& memoryManager : m_BackendMemoryMangers)</div> |
| <div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  {</div> |
| <div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  <span class="keywordflow">if</span> (memoryManager)</div> |
| <div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  {</div> |
| <div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  memoryManager->Release();</div> |
| <div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  }</div> |
| <div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  }</div> |
| <div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>  m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#a69ca23561f4f8a887f19c6580cbd34c8">ReleaseMemory</a>();</div> |
| <div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  m_IsWorkingMemAllocated = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01312"></a><span class="lineno"> 1312</span> }</div> |
| <div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  </div> |
| <div class="line"><a name="l01314"></a><span class="lineno"> 1314</span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_loaded_network.html#a95b1c23f6f296a0c39383bef20fdd46a">LoadedNetwork::Execute</a>(std::unique_ptr<TimelineUtilityMethods>& timelineUtils,</div> |
| <div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>  ProfilingGuid inferenceGuid)</div> |
| <div class="line"><a name="l01316"></a><span class="lineno"> 1316</span> {</div> |
| <div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <span class="keywordtype">bool</span> success = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  </div> |
| <div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  <span class="keyword">auto</span> Fail = [&](<span class="keyword">const</span> std::exception& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  {</div> |
| <div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(error) << <span class="stringliteral">"An error occurred attempting to execute a workload: "</span> << <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>.what();</div> |
| <div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  success = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  };</div> |
| <div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  </div> |
| <div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  {</div> |
| <div class="line"><a name="l01327"></a><span class="lineno"> 1327</span> <span class="preprocessor">#if !defined(ARMNN_DISABLE_THREADS)</span></div> |
| <div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>  std::lock_guard<std::mutex> lockGuard(m_WorkingMemMutex);</div> |
| <div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  AllocateWorkingMemory(lockGuard);</div> |
| <div class="line"><a name="l01330"></a><span class="lineno"> 1330</span> <span class="preprocessor">#else</span></div> |
| <div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  AllocateWorkingMemory();</div> |
| <div class="line"><a name="l01332"></a><span class="lineno"> 1332</span> <span class="preprocessor">#endif</span></div> |
| <div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  </div> |
| <div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  ProfilingDynamicGuid workloadInferenceID(0);</div> |
| <div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <span class="keyword">auto</span> ExecuteQueue = [&timelineUtils, &workloadInferenceID, &inferenceGuid](<a class="code" href="classarmnn_1_1_loaded_network.html#a48fe2df41d914c38c913160956acc706">WorkloadQueue</a>& queue)</div> |
| <div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  {</div> |
| <div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& workload : queue)</div> |
| <div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  {</div> |
| <div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  <span class="keywordflow">if</span>(timelineUtils)</div> |
| <div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  {</div> |
| <div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  workloadInferenceID = timelineUtils->RecordWorkloadInferenceAndStartOfLifeEvent(workload->GetGuid(),</div> |
| <div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  inferenceGuid);</div> |
| <div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  }</div> |
| <div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  workload->Execute();</div> |
| <div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  <span class="keywordflow">if</span>(timelineUtils)</div> |
| <div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  {</div> |
| <div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  timelineUtils->RecordEndOfLifeEvent(workloadInferenceID);</div> |
| <div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  }</div> |
| <div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  }</div> |
| <div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  };</div> |
| <div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  </div> |
| <div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  ExecuteQueue(m_InputQueue);</div> |
| <div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  ExecuteQueue(m_WorkloadQueue);</div> |
| <div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  ExecuteQueue(m_OutputQueue);</div> |
| <div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  }</div> |
| <div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> RuntimeException& error)</div> |
| <div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  {</div> |
| <div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  Fail(error);</div> |
| <div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  }</div> |
| <div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::runtime_error& error)</div> |
| <div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  {</div> |
| <div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  Fail(error);</div> |
| <div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  }</div> |
| <div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>  </div> |
| <div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  <span class="keywordflow">return</span> success;</div> |
| <div class="line"><a name="l01366"></a><span class="lineno"> 1366</span> }</div> |
| <div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  </div> |
| <div class="line"><a name="l01368"></a><span class="lineno"> 1368</span> <span class="keywordtype">void</span> LoadedNetwork::EnqueueInput(<span class="keyword">const</span> ConstTensor& inputTensor, ITensorHandle* inputTensorHandle)</div> |
| <div class="line"><a name="l01369"></a><span class="lineno"> 1369</span> {</div> |
| <div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  <span class="keywordflow">if</span> (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>) <span class="comment">// Try import the input tensor</span></div> |
| <div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  {</div> |
| <div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>  <a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a> importFlags = inputTensorHandle->GetImportFlags();</div> |
| <div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(importFlags, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>) )</div> |
| <div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>  {</div> |
| <div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.GetInfo(),</div> |
| <div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  inputTensor.GetMemoryArea());</div> |
| <div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  <span class="keywordtype">void</span>* mem = tensorHandle->Map(<span class="keyword">false</span>);</div> |
| <div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>  </div> |
| <div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>  <span class="keywordflow">if</span> (inputTensorHandle->Import(mem, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>))</div> |
| <div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>  {</div> |
| <div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  tensorHandle->Unmap();</div> |
| <div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  <span class="keywordflow">return</span>;</div> |
| <div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  }</div> |
| <div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  tensorHandle->Unmap();</div> |
| <div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"EnqueueInput: Memory Import failed"</span>);</div> |
| <div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  }</div> |
| <div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  {</div> |
| <div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"EnqueueInput: Memory Import failed, backend does not support Import"</span>);</div> |
| <div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  }</div> |
| <div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>  }</div> |
| <div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  {</div> |
| <div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"CopyInput"</span>);</div> |
| <div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.GetInfo(), inputTensor.GetMemoryArea());</div> |
| <div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  </div> |
| <div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  <span class="keyword">auto</span> copyFunc = [](<span class="keywordtype">void</span>* dst, <span class="keyword">const</span> <span class="keywordtype">void</span>* src, <span class="keywordtype">size_t</span> size)</div> |
| <div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  {</div> |
| <div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  memcpy(dst, src, size);</div> |
| <div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  };</div> |
| <div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  </div> |
| <div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <a class="code" href="namespacearmnn.html#a92c91193007aa49f4732d6dba5397f8d">CopyTensorContentsGeneric</a>(tensorHandle.get(), inputTensorHandle, copyFunc);</div> |
| <div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  }</div> |
| <div class="line"><a name="l01406"></a><span class="lineno"> 1406</span> }</div> |
| <div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  </div> |
| <div class="line"><a name="l01408"></a><span class="lineno"> 1408</span> <span class="comment">// Note: We can only import the output pointer if all of the following hold true:</span></div> |
| <div class="line"><a name="l01409"></a><span class="lineno"> 1409</span> <span class="comment">// a) The imported pointer is aligned sufficiently</span></div> |
| <div class="line"><a name="l01410"></a><span class="lineno"> 1410</span> <span class="comment">// b) The tensor has zero padding</span></div> |
| <div class="line"><a name="l01411"></a><span class="lineno"> 1411</span> <span class="comment">// c) There is only one connection to the OutputSlot and it is to an OutputLayer.</span></div> |
| <div class="line"><a name="l01412"></a><span class="lineno"> 1412</span> <span class="comment">// d) The output pointer is allocated via malloc. (Other types will be supported in a later release)</span></div> |
| <div class="line"><a name="l01413"></a><span class="lineno"> 1413</span> <span class="comment">// e) m_IsExportEnabled must be set to true</span></div> |
| <div class="line"><a name="l01414"></a><span class="lineno"> 1414</span> <span class="keywordtype">void</span> LoadedNetwork::ImportOutputTensor(<span class="keyword">const</span> Tensor& outputTensor, ITensorHandle* outputTensorHandle)</div> |
| <div class="line"><a name="l01415"></a><span class="lineno"> 1415</span> {</div> |
| <div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  <span class="keywordflow">if</span> (!outputTensorHandle)</div> |
| <div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  {</div> |
| <div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Data should have been allocated."</span>);</div> |
| <div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  }</div> |
| <div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>  </div> |
| <div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <a class="code" href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">MemorySourceFlags</a> importFlags = outputTensorHandle->GetImportFlags();</div> |
| <div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(importFlags, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>))</div> |
| <div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>  {</div> |
| <div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  std::make_unique<PassthroughTensorHandle>(outputTensor.GetInfo(),</div> |
| <div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  outputTensor.GetMemoryArea());</div> |
| <div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  </div> |
| <div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  <span class="keywordtype">void</span>* mem = tensorHandle->Map(<span class="keyword">false</span>);</div> |
| <div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  <span class="keywordtype">bool</span> importOk = outputTensorHandle->Import(mem, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>);</div> |
| <div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>  tensorHandle->Unmap();</div> |
| <div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  </div> |
| <div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  <span class="keywordflow">if</span> (!importOk)</div> |
| <div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  {</div> |
| <div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>  <span class="keywordflow">throw</span> MemoryExportException(<span class="stringliteral">"ImportOutputTensor: Memory Export failed"</span>);</div> |
| <div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  }</div> |
| <div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  }</div> |
| <div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  {</div> |
| <div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  <span class="keywordflow">throw</span> MemoryExportException(<span class="stringliteral">"ImportOutputTensor: Memory Export failed, attempting to export Input Layer"</span>);</div> |
| <div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  }</div> |
| <div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>  </div> |
| <div class="line"><a name="l01442"></a><span class="lineno"> 1442</span> }</div> |
| <div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  </div> |
| <div class="line"><a name="l01444"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a5acae80f1d8fd03cdb3878bd356683d7"> 1444</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a5acae80f1d8fd03cdb3878bd356683d7">CopyToOutputTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor.html">Tensor</a>& outputTensor, <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* outputTensorHandle)</div> |
| <div class="line"><a name="l01445"></a><span class="lineno"> 1445</span> {</div> |
| <div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"CopyOutput"</span>);</div> |
| <div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  <span class="keyword">auto</span> copyFunc = [](<span class="keywordtype">void</span>* dst, <span class="keyword">const</span> <span class="keywordtype">void</span>* src, <span class="keywordtype">size_t</span> size)</div> |
| <div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  {</div> |
| <div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  memcpy(dst, src, size);</div> |
| <div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  };</div> |
| <div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  </div> |
| <div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  std::unique_ptr<ITensorHandle> tensorHandle =</div> |
| <div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  std::make_unique<PassthroughTensorHandle>(outputTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(),</div> |
| <div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  outputTensor.<a class="code" href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">GetMemoryArea</a>());</div> |
| <div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  </div> |
| <div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>  <a class="code" href="namespacearmnn.html#a92c91193007aa49f4732d6dba5397f8d">CopyTensorContentsGeneric</a>(outputTensorHandle, tensorHandle.get(), copyFunc);</div> |
| <div class="line"><a name="l01457"></a><span class="lineno"> 1457</span> }</div> |
| <div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  </div> |
| <div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  </div> |
| <div class="line"><a name="l01460"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a9ef4b4b6c421b5fd4b62274e63d08f11"> 1460</a></span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.html#a9ef4b4b6c421b5fd4b62274e63d08f11">GetInputTensor</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId, <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors)</div> |
| <div class="line"><a name="l01461"></a><span class="lineno"> 1461</span> {</div> |
| <div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputTensorPair : inputTensors)</div> |
| <div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  {</div> |
| <div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span> = inputTensorPair.first;</div> |
| <div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> == layerId)</div> |
| <div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  {</div> |
| <div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  <span class="keywordflow">return</span> inputTensorPair.second;</div> |
| <div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  }</div> |
| <div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  }</div> |
| <div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Input does not exist."</span>);</div> |
| <div class="line"><a name="l01471"></a><span class="lineno"> 1471</span> }</div> |
| <div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  </div> |
| <div class="line"><a name="l01473"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ac624e40d8096e61c73b246934f18afd0"> 1473</a></span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor.html">armnn::Tensor</a> <a class="code" href="namespacearmnn.html#ac624e40d8096e61c73b246934f18afd0">GetOutputTensor</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId, <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors)</div> |
| <div class="line"><a name="l01474"></a><span class="lineno"> 1474</span> {</div> |
| <div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputTensorPair : outputTensors)</div> |
| <div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  {</div> |
| <div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span> = outputTensorPair.first;</div> |
| <div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> == layerId)</div> |
| <div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  {</div> |
| <div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  <span class="keywordflow">return</span> outputTensorPair.second;</div> |
| <div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  }</div> |
| <div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>  }</div> |
| <div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Output does not exist."</span>);</div> |
| <div class="line"><a name="l01484"></a><span class="lineno"> 1484</span> }</div> |
| <div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  </div> |
| <div class="line"><a name="l01486"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a704bd570f39deda992bccdc639640dc7"> 1486</a></span> std::vector<ImportedInputId> <a class="code" href="classarmnn_1_1_loaded_network.html#a704bd570f39deda992bccdc639640dc7">LoadedNetwork::ImportInputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors,</div> |
| <div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> forceImportMemorySource)</div> |
| <div class="line"><a name="l01488"></a><span class="lineno"> 1488</span> {</div> |
| <div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>  <span class="keywordflow">if</span> (!m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  {</div> |
| <div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>  <span class="comment">// Cannot import if import is not enabled and forceImportMemorySource is undefined</span></div> |
| <div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  <span class="keywordflow">if</span> (forceImportMemorySource == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div> |
| <div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>  {</div> |
| <div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportInputs: Memory Import failed, NetworkProperties.m_ImportEnabled"</span>);</div> |
| <div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  }</div> |
| <div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>  <span class="comment">// The number of pre imported tensors should not exceed the number of inputs.</span></div> |
| <div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  <span class="keywordflow">if</span> (inputTensors.size() > m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetNumInputs())</div> |
| <div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  {</div> |
| <div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportInputs: The number of tensors provided exceeds the number of inputs."</span>);</div> |
| <div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  }</div> |
| <div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  </div> |
| <div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  std::vector<ImportedInputId> importedInputs;</div> |
| <div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0;</div> |
| <div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>* inputLayer : graph.<a class="code" href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>())</div> |
| <div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  {</div> |
| <div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  <span class="keyword">auto</span> outputTensorHandle = m_PreImportedInputHandles[inputIndex].m_TensorHandle.get();</div> |
| <div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  </div> |
| <div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>  <span class="keywordflow">if</span> (!outputTensorHandle)</div> |
| <div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  {</div> |
| <div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  inputIndex++;</div> |
| <div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  }</div> |
| <div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  </div> |
| <div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  <span class="keyword">auto</span> layerBindingId = inputLayer->GetBindingId();</div> |
| <div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  <span class="keyword">auto</span> it = std::find_if(inputTensors.begin(), inputTensors.end(), [=](<span class="keyword">const</span> <span class="keyword">auto</span>& inputTensor)</div> |
| <div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  {</div> |
| <div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  return inputTensor.first == layerBindingId;</div> |
| <div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  });</div> |
| <div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>  </div> |
| <div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  <span class="keywordflow">if</span> (it == inputTensors.end())</div> |
| <div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  {</div> |
| <div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>  inputIndex++;</div> |
| <div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  }</div> |
| <div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  </div> |
| <div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& inputTensor = *it;</div> |
| <div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  std::unique_ptr<ITensorHandle> passThroughTensorHandle =</div> |
| <div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.second.GetInfo(),</div> |
| <div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  inputTensor.second.GetMemoryArea());</div> |
| <div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  </div> |
| <div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>  {</div> |
| <div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>  <span class="keywordflow">if</span> (outputTensorHandle->CanBeImported(passThroughTensorHandle->Map(), forceImportMemorySource)</div> |
| <div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  && (outputTensorHandle->Import(passThroughTensorHandle->Map(), forceImportMemorySource)))</div> |
| <div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>  {</div> |
| <div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  importedInputs.push_back(inputIndex);</div> |
| <div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  }</div> |
| <div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  passThroughTensorHandle->Unmap();</div> |
| <div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>  }</div> |
| <div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  <span class="keywordflow">catch</span>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>& exception)</div> |
| <div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  {</div> |
| <div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << <span class="stringliteral">"An error occurred attempting to import input_"</span></div> |
| <div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  << inputIndex << <span class="stringliteral">" : "</span> << exception.<a class="code" href="classarmnn_1_1_exception.html#abf843cbb29dec939d0731e491bab6f70">what</a>();</div> |
| <div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  passThroughTensorHandle->Unmap();</div> |
| <div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  }</div> |
| <div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  inputIndex++;</div> |
| <div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  }</div> |
| <div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  </div> |
| <div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  <span class="keywordflow">return</span> importedInputs;</div> |
| <div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  }</div> |
| <div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  {</div> |
| <div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  <span class="comment">// Import when the import of network properties is enabled</span></div> |
| <div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  std::vector<ImportedInputId> importedInputs;</div> |
| <div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  </div> |
| <div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputTensor : inputTensors)</div> |
| <div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  {</div> |
| <div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  <span class="keyword">auto</span> layerBindingId = inputTensor.first;</div> |
| <div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  <span class="keyword">auto</span> it = std::find_if(graph.<a class="code" href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_input_layers_accessor.html#af6f3e2b0ee65cd102e20c9f734160b90">begin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_input_layers_accessor.html#a39ebf520b6f30ab8776bdcb99ee38b93">end</a>(), [=](<span class="keyword">auto</span>* layer)</div> |
| <div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  {</div> |
| <div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  return layer->GetBindingId() == layerBindingId;</div> |
| <div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  });</div> |
| <div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  </div> |
| <div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>  <span class="keywordflow">if</span> (it == graph.<a class="code" href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_input_layers_accessor.html#a39ebf520b6f30ab8776bdcb99ee38b93">end</a>())</div> |
| <div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  {</div> |
| <div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(fmt::format(</div> |
| <div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  <span class="stringliteral">"ImportInputs: Memory Import failed, unknown LayerBindingId: {}"</span>, layerBindingId));</div> |
| <div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  }</div> |
| <div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>  </div> |
| <div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* layer = *it;</div> |
| <div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  {</div> |
| <div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"ImportInputs: given layer not an InputLayer"</span>);</div> |
| <div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  }</div> |
| <div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  </div> |
| <div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  <span class="keyword">auto</span>& backend = m_Backends.at(layer-><a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div> |
| <div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a406399d2a16ead98e4e93cdd57adead4">HasMatchingCapability</a>(<a class="code" href="structarmnn_1_1_backend_options_1_1_backend_option.html">BackendOptions::BackendOption</a>{<span class="stringliteral">"PreImportIOTensors"</span>, <span class="keyword">true</span>},</div> |
| <div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  backend->GetCapabilities()))</div> |
| <div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  {</div> |
| <div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  std::string er = backend->GetId();</div> |
| <div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  er += <span class="stringliteral">" does not have PreImportIOTensors capability"</span>;</div> |
| <div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_backend_capability_exception.html">BackendCapabilityException</a>(er);</div> |
| <div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  }</div> |
| <div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  </div> |
| <div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.html">OutputSlot</a>& outputSlot = layer-><a class="code" href="classarmnn_1_1_layer.html#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>()[0];</div> |
| <div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  </div> |
| <div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = outputSlot.<a class="code" href="classarmnn_1_1_output_slot.html#af303cf872a3f95e29992e45224e4cf8e">GetTensorHandleFactoryId</a>();</div> |
| <div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& tensorInfo = outputSlot.<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div> |
| <div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>  </div> |
| <div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html">ITensorHandleFactory</a>* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div> |
| <div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  <span class="keywordflow">if</span> (!handleFactory)</div> |
| <div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  {</div> |
| <div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"handleFactory must not be null."</span>);</div> |
| <div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  }</div> |
| <div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>  </div> |
| <div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>  ImportedTensorHandlePin importedTensorHandlePin{layerBindingId,</div> |
| <div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>  handleFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(tensorInfo, <span class="keyword">false</span>)};</div> |
| <div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  </div> |
| <div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle = importedTensorHandlePin.m_TensorHandle.get();</div> |
| <div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  </div> |
| <div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a55cddc2dbb32d680cd85b635ba370e48">GetImportFlags</a>(), forceImportMemorySource))</div> |
| <div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>  {</div> |
| <div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(</div> |
| <div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  fmt::format(<span class="stringliteral">"ImportInputs: Memory Import failed, backend: "</span></div> |
| <div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>  <span class="stringliteral">"{} does not support importing from source {}"</span></div> |
| <div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>  , factoryId, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>));</div> |
| <div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  }</div> |
| <div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>  </div> |
| <div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>  std::unique_ptr<ITensorHandle> passThroughTensorHandle =</div> |
| <div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.second.GetInfo(),</div> |
| <div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>  inputTensor.second.GetMemoryArea());</div> |
| <div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>  </div> |
| <div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>  <span class="keywordflow">if</span> (tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a4f81a9eff30c9b9fe76f5b83af470ba7">Import</a>(passThroughTensorHandle->Map(), forceImportMemorySource))</div> |
| <div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>  {</div> |
| <div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  importedInputs.push_back(m_CurImportedInputId++);</div> |
| <div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  passThroughTensorHandle->Unmap();</div> |
| <div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>  }</div> |
| <div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  {</div> |
| <div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  passThroughTensorHandle->Unmap();</div> |
| <div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportInputs: Memory Import failed"</span>);</div> |
| <div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  }</div> |
| <div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>  </div> |
| <div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>  m_PreImportedInputHandles.push_back(std::move(importedTensorHandlePin));</div> |
| <div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>  }</div> |
| <div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>  <span class="keywordflow">return</span> importedInputs;</div> |
| <div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>  }</div> |
| <div class="line"><a name="l01630"></a><span class="lineno"> 1630</span> }</div> |
| <div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>  </div> |
| <div class="line"><a name="l01632"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#ac88d932e6e015a59551322b25796b11a"> 1632</a></span> std::vector<ImportedOutputId> <a class="code" href="classarmnn_1_1_loaded_network.html#ac88d932e6e015a59551322b25796b11a">LoadedNetwork::ImportOutputs</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors,</div> |
| <div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> forceImportMemorySource)</div> |
| <div class="line"><a name="l01634"></a><span class="lineno"> 1634</span> {</div> |
| <div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>  <span class="keywordflow">if</span> (!m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div> |
| <div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>  {</div> |
| <div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  <span class="comment">// Cannot import if import is not enabled and forceImportMemorySource is undefined</span></div> |
| <div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  <span class="keywordflow">if</span> (forceImportMemorySource == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div> |
| <div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  {</div> |
| <div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportOutputs: Memory Import failed, NetworkProperties.m_ImportEnabled"</span>);</div> |
| <div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>  }</div> |
| <div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  <span class="comment">// If forceImportMemorySource is defined, try import if memory is aligned</span></div> |
| <div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  <span class="keywordflow">if</span> (outputTensors.size() != m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetNumOutputs())</div> |
| <div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  {</div> |
| <div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportOutputs: Force Import failed, incorrect number of tensors"</span>);</div> |
| <div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  }</div> |
| <div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  std::vector<ImportedOutputId> importedOutputs;</div> |
| <div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  </div> |
| <div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div> |
| <div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>* <span class="keyword">const</span> outputLayer : graph.<a class="code" href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">GetOutputLayers</a>())</div> |
| <div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  {</div> |
| <div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>  <span class="keyword">auto</span> inputTensorHandle = m_PreImportedOutputHandles[outputIndex].m_TensorHandle.get();</div> |
| <div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  <span class="keywordflow">if</span> (!inputTensorHandle)</div> |
| <div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>  {</div> |
| <div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  outputIndex++;</div> |
| <div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  }</div> |
| <div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  </div> |
| <div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  <span class="keyword">auto</span> layerBindingId = outputLayer->GetBindingId();</div> |
| <div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>  <span class="keyword">auto</span> it = std::find_if(outputTensors.begin(), outputTensors.end(), [=] (<span class="keyword">const</span> <span class="keyword">auto</span>& outputTensor)</div> |
| <div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  {</div> |
| <div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>  return outputTensor.first == layerBindingId;</div> |
| <div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  });</div> |
| <div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  </div> |
| <div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  <span class="keywordflow">if</span> (it == outputTensors.end())</div> |
| <div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  {</div> |
| <div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  outputIndex++;</div> |
| <div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>  }</div> |
| <div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>  </div> |
| <div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>  <span class="keyword">const</span> <span class="keyword">auto</span> outputTensor = *it;</div> |
| <div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>  {</div> |
| <div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>  <span class="comment">// Check if the output memory can be imported</span></div> |
| <div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  <span class="keywordflow">if</span> (inputTensorHandle->CanBeImported(outputTensor.second.GetMemoryArea(), forceImportMemorySource)</div> |
| <div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>  && inputTensorHandle->Import(outputTensor.second.GetMemoryArea(), forceImportMemorySource))</div> |
| <div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>  {</div> |
| <div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  importedOutputs.push_back(outputIndex);</div> |
| <div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>  }</div> |
| <div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>  }</div> |
| <div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>  <span class="keywordflow">catch</span>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>& exception)</div> |
| <div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>  {</div> |
| <div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << <span class="stringliteral">"An error occurred attempting to import output_"</span></div> |
| <div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>  << outputIndex << <span class="stringliteral">" : "</span> << exception.<a class="code" href="classarmnn_1_1_exception.html#abf843cbb29dec939d0731e491bab6f70">what</a>();</div> |
| <div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>  }</div> |
| <div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>  outputIndex++;</div> |
| <div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  }</div> |
| <div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>  <span class="keywordflow">return</span> importedOutputs;</div> |
| <div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  }</div> |
| <div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>  </div> |
| <div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>  std::vector<ImportedOutputId> importedOutputs;</div> |
| <div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>  </div> |
| <div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& outputTensor : outputTensors)</div> |
| <div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>  {</div> |
| <div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  <span class="keyword">auto</span> layerBindingId = outputTensor.first;</div> |
| <div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>  <span class="keyword">auto</span> it = std::find_if(graph.<a class="code" href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">GetOutputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_output_layers_accessor.html#a660efe3cd8761bd55b70ae83a7ea4334">begin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">GetOutputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_output_layers_accessor.html#ad2a661f37e89422e29dc70b3e4cc7185">end</a>(), [=](<span class="keyword">auto</span>* layer)</div> |
| <div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>  {</div> |
| <div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>  return layer->GetBindingId() == layerBindingId;</div> |
| <div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>  });</div> |
| <div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  </div> |
| <div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>  <span class="keywordflow">if</span> (it == graph.<a class="code" href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">GetOutputLayers</a>().<a class="code" href="structarmnn_1_1_graph_1_1_output_layers_accessor.html#ad2a661f37e89422e29dc70b3e4cc7185">end</a>())</div> |
| <div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>  {</div> |
| <div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(fmt::format(<span class="stringliteral">"ImportOutputs: Memory Import failed, unknown LayerBindingId: {}"</span>,</div> |
| <div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>  layerBindingId));</div> |
| <div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>  }</div> |
| <div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  </div> |
| <div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* layer = *it;</div> |
| <div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div> |
| <div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>  {</div> |
| <div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"ImportOutputs: given layer not an OutputLayer"</span>);</div> |
| <div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>  }</div> |
| <div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>  </div> |
| <div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>  <span class="keyword">auto</span>& backend = m_Backends.at(layer-><a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div> |
| <div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a406399d2a16ead98e4e93cdd57adead4">HasMatchingCapability</a>(<a class="code" href="structarmnn_1_1_backend_options_1_1_backend_option.html">BackendOptions::BackendOption</a>{<span class="stringliteral">"PreImportIOTensors"</span>, <span class="keyword">true</span>},</div> |
| <div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  backend->GetCapabilities()))</div> |
| <div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>  {</div> |
| <div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>  std::string er = backend->GetId();</div> |
| <div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>  er += <span class="stringliteral">" does not have PreImportIOTensors capability"</span>;</div> |
| <div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_backend_capability_exception.html">BackendCapabilityException</a>(er);</div> |
| <div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>  }</div> |
| <div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>  </div> |
| <div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_input_slot.html">InputSlot</a>& inputSlot = layer-><a class="code" href="classarmnn_1_1_layer.html#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>()[0];</div> |
| <div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = inputSlot.<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-><a class="code" href="classarmnn_1_1_output_slot.html#af303cf872a3f95e29992e45224e4cf8e">GetTensorHandleFactoryId</a>();</div> |
| <div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& tensorInfo = inputSlot.<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div> |
| <div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>  </div> |
| <div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html">ITensorHandleFactory</a>* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div> |
| <div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  <span class="keywordflow">if</span> (!handleFactory)</div> |
| <div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  {</div> |
| <div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"handleFactory must not be null."</span>);</div> |
| <div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>  }</div> |
| <div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>  </div> |
| <div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  ImportedTensorHandlePin importedTensorHandlePin{layerBindingId,</div> |
| <div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>  handleFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(tensorInfo, <span class="keyword">false</span>)};</div> |
| <div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>  </div> |
| <div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle = importedTensorHandlePin.m_TensorHandle.get();</div> |
| <div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  </div> |
| <div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a55cddc2dbb32d680cd85b635ba370e48">GetImportFlags</a>(), forceImportMemorySource))</div> |
| <div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>  {</div> |
| <div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(fmt::format(<span class="stringliteral">"ImportInputs: Memory Import failed, backend: "</span></div> |
| <div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>  <span class="stringliteral">"{} does not support importing from source {}"</span></div> |
| <div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>  , factoryId, forceImportMemorySource));</div> |
| <div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>  }</div> |
| <div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  </div> |
| <div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  <span class="keywordflow">if</span> (tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a4f81a9eff30c9b9fe76f5b83af470ba7">Import</a>(outputTensor.second.GetMemoryArea(), forceImportMemorySource))</div> |
| <div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  {</div> |
| <div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>  importedOutputs.push_back(m_CurImportedOutputId++);</div> |
| <div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>  }</div> |
| <div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>  {</div> |
| <div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_memory_import_exception.html">MemoryImportException</a>(<span class="stringliteral">"ImportInputs: Memory Import failed"</span>);</div> |
| <div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>  }</div> |
| <div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>  </div> |
| <div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  m_PreImportedOutputHandles.push_back(std::move(importedTensorHandlePin));</div> |
| <div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>  }</div> |
| <div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>  </div> |
| <div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>  <span class="keywordflow">return</span> importedOutputs;</div> |
| <div class="line"><a name="l01759"></a><span class="lineno"> 1759</span> }</div> |
| <div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>  </div> |
| <div class="line"><a name="l01761"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#aa792fd8b43401e3d6665110cdb0af27b"> 1761</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_loaded_network.html#aa792fd8b43401e3d6665110cdb0af27b">LoadedNetwork::ClearImportedInputs</a>(<span class="keyword">const</span> std::vector<ImportedInputId> inputIds)</div> |
| <div class="line"><a name="l01762"></a><span class="lineno"> 1762</span> {</div> |
| <div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> <span class="keywordtype">id</span> : inputIds)</div> |
| <div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>  {</div> |
| <div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> > m_PreImportedInputHandles.size())</div> |
| <div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>  {</div> |
| <div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"ClearImportedInputs::Unknown ImportedInputId: {}"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  }</div> |
| <div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  </div> |
| <div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>  <span class="keyword">auto</span>& importedTensorHandle = m_PreImportedInputHandles[id].m_TensorHandle;</div> |
| <div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>  <span class="keywordflow">if</span> (!importedTensorHandle)</div> |
| <div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>  {</div> |
| <div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(</div> |
| <div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  fmt::format(<span class="stringliteral">"ClearImportedInputs::ImportedInput with id: {} has already been deleted"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>  }</div> |
| <div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>  <span class="comment">// Call Unimport then destroy the tensorHandle</span></div> |
| <div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  importedTensorHandle->Unimport();</div> |
| <div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>  importedTensorHandle = {};</div> |
| <div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>  }</div> |
| <div class="line"><a name="l01780"></a><span class="lineno"> 1780</span> }</div> |
| <div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>  </div> |
| <div class="line"><a name="l01782"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#af06f742ce80985a8fbbbc028c20259b1"> 1782</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_loaded_network.html#af06f742ce80985a8fbbbc028c20259b1">LoadedNetwork::ClearImportedOutputs</a>(<span class="keyword">const</span> std::vector<ImportedOutputId> outputIds)</div> |
| <div class="line"><a name="l01783"></a><span class="lineno"> 1783</span> {</div> |
| <div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> <span class="keywordtype">id</span> : outputIds)</div> |
| <div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>  {</div> |
| <div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> > m_PreImportedOutputHandles.size())</div> |
| <div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>  {</div> |
| <div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">"ClearImportedOutputs::Unknown ImportedOutputId: {}"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  }</div> |
| <div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>  </div> |
| <div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  <span class="keyword">auto</span>& importedTensorHandle = m_PreImportedOutputHandles[id].m_TensorHandle;</div> |
| <div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  <span class="keywordflow">if</span> (!importedTensorHandle)</div> |
| <div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>  {</div> |
| <div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(</div> |
| <div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>  fmt::format(<span class="stringliteral">"ClearImportedOutputs::ImportedOutput with id: {} has already been deleted"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  }</div> |
| <div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>  <span class="comment">// Call Unimport then destroy the tensorHandle</span></div> |
| <div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>  importedTensorHandle->Unimport();</div> |
| <div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>  importedTensorHandle = {};</div> |
| <div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>  }</div> |
| <div class="line"><a name="l01801"></a><span class="lineno"> 1801</span> }</div> |
| <div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  </div> |
| <div class="line"><a name="l01803"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a95b1c23f6f296a0c39383bef20fdd46a"> 1803</a></span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_loaded_network.html#a95b1c23f6f296a0c39383bef20fdd46a">LoadedNetwork::Execute</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors,</div> |
| <div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors,</div> |
| <div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  <a class="code" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.html">IWorkingMemHandle</a>& iWorkingMemHandle,</div> |
| <div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>  std::vector<ImportedInputId> preImportedInputs,</div> |
| <div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>  std::vector<ImportedOutputId> preImportedOutputs)</div> |
| <div class="line"><a name="l01808"></a><span class="lineno"> 1808</span> {</div> |
| <div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div> |
| <div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>  </div> |
| <div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>  <span class="keywordflow">if</span> (inputTensors.size() + preImportedInputs.size() != graph.<a class="code" href="classarmnn_1_1_graph.html#a8d8179a4a0703602a5d7dbb6e92eaf69">GetNumInputs</a>())</div> |
| <div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>  {</div> |
| <div class="line"><a name="l01813"></a><span class="lineno"> 1813</span>  <span class="keywordflow">if</span> (preImportedInputs.empty())</div> |
| <div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>  {</div> |
| <div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"LoadedNetwork::Execute: Number of inputs provided does not match network."</span>);</div> |
| <div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>  }</div> |
| <div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>  {</div> |
| <div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div> |
| <div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>  <span class="stringliteral">"Number of inputs + preImportedInputs provided does not match network."</span>);</div> |
| <div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>  }</div> |
| <div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>  }</div> |
| <div class="line"><a name="l01823"></a><span class="lineno"> 1823</span>  </div> |
| <div class="line"><a name="l01824"></a><span class="lineno"> 1824</span>  <span class="keywordflow">if</span> (outputTensors.size() + preImportedOutputs.size() != graph.<a class="code" href="classarmnn_1_1_graph.html#a604654b453ec291a503d62a0beb849d3">GetNumOutputs</a>())</div> |
| <div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>  {</div> |
| <div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>  <span class="keywordflow">if</span> (preImportedOutputs.empty())</div> |
| <div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  {</div> |
| <div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div> |
| <div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>  <span class="stringliteral">"Number of outputs provided does not match network."</span>);</div> |
| <div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>  }</div> |
| <div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>  {</div> |
| <div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div> |
| <div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>  <span class="stringliteral">"Number of outputs + preImportedOutputs provided does not match network."</span>);</div> |
| <div class="line"><a name="l01835"></a><span class="lineno"> 1835</span>  }</div> |
| <div class="line"><a name="l01836"></a><span class="lineno"> 1836</span>  }</div> |
| <div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>  </div> |
| <div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>  <a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html">WorkingMemHandle</a>& workingMemHandle = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html">WorkingMemHandle</a>&<span class="keyword">></span>(iWorkingMemHandle);</div> |
| <div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>  <span class="comment">// Collect all the given LayerBindingIds and check them for duplicates and unknowns.</span></div> |
| <div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>  std::vector<LayerBindingId>& bindingIds = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#abdfaf46d2e4cd003c0f13cdb1f1e6a20">GetBindingIdVector</a>();</div> |
| <div class="line"><a name="l01841"></a><span class="lineno"> 1841</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = 0;</div> |
| <div class="line"><a name="l01842"></a><span class="lineno"> 1842</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair : inputTensors)</div> |
| <div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>  {</div> |
| <div class="line"><a name="l01844"></a><span class="lineno"> 1844</span>  bindingIds[index++] = pair.first;</div> |
| <div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>  }</div> |
| <div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span> : preImportedInputs)</div> |
| <div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>  {</div> |
| <div class="line"><a name="l01848"></a><span class="lineno"> 1848</span>  bindingIds[index++] = ValidateImportedInputID(<span class="keywordtype">id</span>);</div> |
| <div class="line"><a name="l01849"></a><span class="lineno"> 1849</span>  }</div> |
| <div class="line"><a name="l01850"></a><span class="lineno"> 1850</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair : outputTensors)</div> |
| <div class="line"><a name="l01851"></a><span class="lineno"> 1851</span>  {</div> |
| <div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>  bindingIds[index++] = pair.first;</div> |
| <div class="line"><a name="l01853"></a><span class="lineno"> 1853</span>  }</div> |
| <div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span> : preImportedOutputs)</div> |
| <div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  {</div> |
| <div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>  bindingIds[index++] = ValidateImportedOutputID(<span class="keywordtype">id</span>);</div> |
| <div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>  }</div> |
| <div class="line"><a name="l01858"></a><span class="lineno"> 1858</span>  </div> |
| <div class="line"><a name="l01859"></a><span class="lineno"> 1859</span>  workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab35a0f45d4b1bdad5c8e6614c7bf8d18">ValidateBindingIds</a>();</div> |
| <div class="line"><a name="l01860"></a><span class="lineno"> 1860</span>  </div> |
| <div class="line"><a name="l01861"></a><span class="lineno"> 1861</span>  <span class="keyword">auto</span> resetMemHandle = [&]()</div> |
| <div class="line"><a name="l01862"></a><span class="lineno"> 1862</span>  {</div> |
| <div class="line"><a name="l01863"></a><span class="lineno"> 1863</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span>: preImportedInputs)</div> |
| <div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>  {</div> |
| <div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedInputHandles[id].m_LayerBindingId;</div> |
| <div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>  </div> |
| <div class="line"><a name="l01867"></a><span class="lineno"> 1867</span>  <span class="keyword">auto</span> inputHandle = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab0ba2e3d5e666b99e28a485d117ddfc3">GetInputHandle</a>(layerBindingId);</div> |
| <div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>  <span class="keyword">auto</span> inputConnections = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ae65834ecb69e3bc6a41ca1a57e4b63ab">GetInputConnections</a>(layerBindingId);</div> |
| <div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : inputConnections)</div> |
| <div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>  {</div> |
| <div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>  *it = inputHandle;</div> |
| <div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>  }</div> |
| <div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>  }</div> |
| <div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>  </div> |
| <div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span>: preImportedOutputs)</div> |
| <div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>  {</div> |
| <div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedOutputHandles[id].m_LayerBindingId;</div> |
| <div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>  </div> |
| <div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>  <span class="keyword">auto</span> outputHandle = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ad5e03a241b63b19580f8fdd08c3647b7">GetOutputHandle</a>(layerBindingId);</div> |
| <div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>  <span class="keyword">auto</span> outputConnections = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a39754dbf5b5cb692d3ba97f23b23962f">GetOutputConnection</a>(layerBindingId);</div> |
| <div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>  </div> |
| <div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : outputConnections)</div> |
| <div class="line"><a name="l01883"></a><span class="lineno"> 1883</span>  {</div> |
| <div class="line"><a name="l01884"></a><span class="lineno"> 1884</span>  *it = outputHandle;</div> |
| <div class="line"><a name="l01885"></a><span class="lineno"> 1885</span>  }</div> |
| <div class="line"><a name="l01886"></a><span class="lineno"> 1886</span>  }</div> |
| <div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>  };</div> |
| <div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>  </div> |
| <div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div> |
| <div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div> |
| <div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>  ProfilingGuid inferenceGuid = m_ProfilingService->GetNextGuid();</div> |
| <div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>  {</div> |
| <div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>  <span class="comment">// Add inference timeline trace if profiling is enabled.</span></div> |
| <div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div> |
| <div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>  timelineUtils->CreateTypedEntity(inferenceGuid,LabelsAndEventClasses::INFERENCE_GUID);</div> |
| <div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>  timelineUtils->CreateRelationship(ProfilingRelationshipType::RetentionLink,</div> |
| <div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>  networkGuid,</div> |
| <div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>  inferenceGuid,</div> |
| <div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>  LabelsAndEventClasses::EXECUTION_OF_GUID);</div> |
| <div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>  timelineUtils->RecordEvent(inferenceGuid,LabelsAndEventClasses::ARMNN_PROFILING_SOL_EVENT_CLASS);</div> |
| <div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>  }</div> |
| <div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>  </div> |
| <div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>  <span class="keywordtype">bool</span> executionSucceeded = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l01905"></a><span class="lineno"> 1905</span>  </div> |
| <div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>  {</div> |
| <div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>  <span class="comment">// Add end of life of the inference timeline if profiling is enabled.</span></div> |
| <div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>  timelineUtils->RecordEvent(inferenceGuid,LabelsAndEventClasses::ARMNN_PROFILING_EOL_EVENT_CLASS);</div> |
| <div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>  timelineUtils->Commit();</div> |
| <div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>  }</div> |
| <div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>  </div> |
| <div class="line"><a name="l01913"></a><span class="lineno"> 1913</span>  <span class="keywordflow">if</span> (!workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a1a573373f4505385578f830caebf6adb">IsAllocated</a>())</div> |
| <div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>  {</div> |
| <div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>  workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a8518772c5d692e334a76617582b10b92">Allocate</a>();</div> |
| <div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>  }</div> |
| <div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>  </div> |
| <div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>  {</div> |
| <div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareInputs"</span>);</div> |
| <div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair : inputTensors)</div> |
| <div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>  {</div> |
| <div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>  EnqueueInput(pair.second, workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab0ba2e3d5e666b99e28a485d117ddfc3">GetInputHandle</a>(pair.first));</div> |
| <div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  }</div> |
| <div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>  </div> |
| <div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>  <span class="comment">// Swap in the pre-imported inputs if any</span></div> |
| <div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span> : preImportedInputs)</div> |
| <div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>  {</div> |
| <div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>  <span class="keyword">const</span> ImportedTensorHandlePin& importedInputPin = m_PreImportedInputHandles[id];</div> |
| <div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedInputHandles[id].m_LayerBindingId;</div> |
| <div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& preimportedHandle = importedInputPin.m_TensorHandle;</div> |
| <div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>  </div> |
| <div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>  <span class="keyword">auto</span> inputConnections = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ae65834ecb69e3bc6a41ca1a57e4b63ab">GetInputConnections</a>(layerBindingId);</div> |
| <div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : inputConnections)</div> |
| <div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>  {</div> |
| <div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>  *it = preimportedHandle.get();</div> |
| <div class="line"><a name="l01936"></a><span class="lineno"> 1936</span>  }</div> |
| <div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>  }</div> |
| <div class="line"><a name="l01938"></a><span class="lineno"> 1938</span>  }</div> |
| <div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>  {</div> |
| <div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareOutputs"</span>);</div> |
| <div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>  <span class="keywordflow">if</span> (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div> |
| <div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>  {</div> |
| <div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair: outputTensors)</div> |
| <div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  {</div> |
| <div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>  ImportOutputTensor(pair.second, workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ad5e03a241b63b19580f8fdd08c3647b7">GetOutputHandle</a>(pair.first));</div> |
| <div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>  }</div> |
| <div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>  }</div> |
| <div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>  </div> |
| <div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.html#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span> : preImportedOutputs)</div> |
| <div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>  {</div> |
| <div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>  <span class="keyword">const</span> ImportedTensorHandlePin& importedOutputPin = m_PreImportedOutputHandles[id];</div> |
| <div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedOutputHandles[id].m_LayerBindingId;</div> |
| <div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& preimportedHandle = importedOutputPin.m_TensorHandle;</div> |
| <div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>  </div> |
| <div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>  <span class="keyword">auto</span> outputConnections = workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a39754dbf5b5cb692d3ba97f23b23962f">GetOutputConnection</a>(layerBindingId);</div> |
| <div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : outputConnections)</div> |
| <div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>  {</div> |
| <div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>  *it = preimportedHandle.get();</div> |
| <div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>  }</div> |
| <div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>  }</div> |
| <div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>  }</div> |
| <div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>  </div> |
| <div class="line"><a name="l01963"></a><span class="lineno"> 1963</span>  <span class="keyword">auto</span> Fail = [&](<span class="keyword">const</span> std::exception& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>  {</div> |
| <div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << <span class="stringliteral">"An error occurred attempting to execute a workload: "</span> << <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>.what();</div> |
| <div class="line"><a name="l01966"></a><span class="lineno"> 1966</span>  executionSucceeded = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l01967"></a><span class="lineno"> 1967</span>  };</div> |
| <div class="line"><a name="l01968"></a><span class="lineno"> 1968</span>  ProfilingDynamicGuid workloadInferenceID(0);</div> |
| <div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>  </div> |
| <div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>  {</div> |
| <div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_WorkloadQueue.size(); ++i)</div> |
| <div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  {</div> |
| <div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  <span class="keyword">auto</span>& workload = m_WorkloadQueue[i];</div> |
| <div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  {</div> |
| <div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>  workloadInferenceID = timelineUtils->RecordWorkloadInferenceAndStartOfLifeEvent(workload->GetGuid(),</div> |
| <div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>  inferenceGuid);</div> |
| <div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>  }</div> |
| <div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>  </div> |
| <div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>  workload->ExecuteAsync(workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab522849a917e9095c462e5e5980316be">GetExecutionDataAt</a>(i).second);</div> |
| <div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>  </div> |
| <div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>  <span class="keywordflow">if</span> (timelineUtils)</div> |
| <div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>  {</div> |
| <div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>  timelineUtils->RecordEndOfLifeEvent(workloadInferenceID);</div> |
| <div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>  }</div> |
| <div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>  }</div> |
| <div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>  }</div> |
| <div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_runtime_exception.html">RuntimeException</a>& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>  {</div> |
| <div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>  resetMemHandle();</div> |
| <div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>  Fail(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  }</div> |
| <div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::runtime_error& <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div> |
| <div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>  {</div> |
| <div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>  resetMemHandle();</div> |
| <div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>  Fail(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div> |
| <div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>  }</div> |
| <div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>  <span class="keywordflow">catch</span> (...)</div> |
| <div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>  {</div> |
| <div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>  resetMemHandle();</div> |
| <div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>  <span class="keywordflow">throw</span>;</div> |
| <div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>  }</div> |
| <div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>  </div> |
| <div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>  <span class="keywordflow">if</span> (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div> |
| <div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>  {</div> |
| <div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair: outputTensors)</div> |
| <div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>  {</div> |
| <div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>  <a class="code" href="namespacearmnn.html#a5acae80f1d8fd03cdb3878bd356683d7">CopyToOutputTensor</a>(pair.second, workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ad5e03a241b63b19580f8fdd08c3647b7">GetOutputHandle</a>(pair.first));</div> |
| <div class="line"><a name="l02010"></a><span class="lineno"> 2010</span>  }</div> |
| <div class="line"><a name="l02011"></a><span class="lineno"> 2011</span>  }</div> |
| <div class="line"><a name="l02012"></a><span class="lineno"> 2012</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02013"></a><span class="lineno"> 2013</span>  {</div> |
| <div class="line"><a name="l02014"></a><span class="lineno"> 2014</span>  <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"SyncMemGeneric_Execute"</span>);</div> |
| <div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>  workingMemHandle.<a class="code" href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a7487c3835e842582920969f2663bcc30">MemSyncOutputs</a>();</div> |
| <div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>  }</div> |
| <div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>  </div> |
| <div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>  resetMemHandle();</div> |
| <div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>  </div> |
| <div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>  <span class="keywordflow">return</span> executionSucceeded ? <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a> : <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</a>;</div> |
| <div class="line"><a name="l02021"></a><span class="lineno"> 2021</span> }</div> |
| <div class="line"><a name="l02022"></a><span class="lineno"> 2022</span> <span class="comment"></span> </div> |
| <div class="line"><a name="l02023"></a><span class="lineno"> 2023</span> <span class="comment">/// Create a new unique WorkingMemHandle object. Create multiple handles if you wish to have</span></div> |
| <div class="line"><a name="l02024"></a><span class="lineno"> 2024</span> <span class="comment">/// overlapped Execution by calling this function from different threads.</span></div> |
| <div class="line"><a name="l02025"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a16e72675c37a8f251cf02951e222d4ab"> 2025</a></span> <span class="comment"></span>std::unique_ptr<IWorkingMemHandle> <a class="code" href="classarmnn_1_1_loaded_network.html#a16e72675c37a8f251cf02951e222d4ab">LoadedNetwork::CreateWorkingMemHandle</a>(<a class="code" href="namespacearmnn.html#a0d8160388a127c1a23b37bc88dc6e2ec">NetworkId</a> networkId)</div> |
| <div class="line"><a name="l02026"></a><span class="lineno"> 2026</span> {</div> |
| <div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>  <a class="code" href="classarmnn_1_1_graph.html">Graph</a>& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div> |
| <div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>  </div> |
| <div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  <span class="comment">// Tensors that will need to be allocated internally within armnn</span></div> |
| <div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>  std::vector<std::unique_ptr<ITensorHandle>> managedTensorHandles;</div> |
| <div class="line"><a name="l02031"></a><span class="lineno"> 2031</span>  <span class="comment">// Tensors that will be allocated externally by the user</span></div> |
| <div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>  std::vector<std::unique_ptr<ITensorHandle>> unmanagedTensorHandles;</div> |
| <div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>  </div> |
| <div class="line"><a name="l02034"></a><span class="lineno"> 2034</span>  std::vector<WorkingMemDescriptor> workingMemDescriptors;</div> |
| <div class="line"><a name="l02035"></a><span class="lineno"> 2035</span>  std::vector<std::pair<BackendId, ExecutionData>> executionDataVec;</div> |
| <div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>  </div> |
| <div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>  <span class="keyword">auto</span> GetTensorHandle = [&](<a class="code" href="classarmnn_1_1_layer.html">Layer</a>* layer, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.html">OutputSlot</a>& outputSlot)</div> |
| <div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>  {</div> |
| <div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = outputSlot.GetTensorHandleFactoryId();</div> |
| <div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& tensorInfo = outputSlot.GetTensorInfo();</div> |
| <div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>  </div> |
| <div class="line"><a name="l02042"></a><span class="lineno"> 2042</span>  <span class="keywordflow">if</span> (factoryId == <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>)</div> |
| <div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>  {</div> |
| <div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>  <a class="code" href="classarmnn_1_1_backend_id.html">BackendId</a> <span class="keywordtype">id</span> = layer-><a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>();</div> |
| <div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>  <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div> |
| <div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>  <span class="keywordflow">return</span> m_WorkloadFactories.at(<span class="keywordtype">id</span>)->CreateTensorHandle(tensorInfo, <span class="keyword">false</span>);</div> |
| <div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>  <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div> |
| <div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>  }</div> |
| <div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02050"></a><span class="lineno"> 2050</span>  {</div> |
| <div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html">ITensorHandleFactory</a>* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div> |
| <div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>  <span class="keywordflow">if</span> (!handleFactory)</div> |
| <div class="line"><a name="l02053"></a><span class="lineno"> 2053</span>  {</div> |
| <div class="line"><a name="l02054"></a><span class="lineno"> 2054</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"handleFactory must not be null."</span>);</div> |
| <div class="line"><a name="l02055"></a><span class="lineno"> 2055</span>  }</div> |
| <div class="line"><a name="l02056"></a><span class="lineno"> 2056</span>  <span class="keywordflow">return</span> handleFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.html#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(tensorInfo, <span class="keyword">false</span>);</div> |
| <div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>  }</div> |
| <div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>  };</div> |
| <div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>  </div> |
| <div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>  <span class="keyword">struct </span>HandleInfo</div> |
| <div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>  {</div> |
| <div class="line"><a name="l02062"></a><span class="lineno"> 2062</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* m_TensorHandle;</div> |
| <div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>  </div> |
| <div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>  <span class="keywordtype">bool</span> m_IsInputLayerHandle = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>  <span class="keywordtype">bool</span> m_IsOutputLayerHandle = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>  </div> |
| <div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>  <a class="code" href="structarmnn_1_1experimental_1_1_working_mem_handle_1_1_input_mem_descriptor_coords.html">WorkingMemHandle::InputMemDescriptorCoords</a> m_InputMemDescriptorCoords;</div> |
| <div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>  <a class="code" href="structarmnn_1_1experimental_1_1_working_mem_handle_1_1_output_mem_descriptor_coords.html">WorkingMemHandle::OutputMemDescriptorCoords</a> m_OutputMemDescriptorCoords;</div> |
| <div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>  };</div> |
| <div class="line"><a name="l02070"></a><span class="lineno"> 2070</span>  </div> |
| <div class="line"><a name="l02071"></a><span class="lineno"> 2071</span>  std::unordered_map<const OutputSlot*, HandleInfo> outputToHandleInfoMap;</div> |
| <div class="line"><a name="l02072"></a><span class="lineno"> 2072</span>  </div> |
| <div class="line"><a name="l02073"></a><span class="lineno"> 2073</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex = 0;</div> |
| <div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>  {</div> |
| <div class="line"><a name="l02076"></a><span class="lineno"> 2076</span>  <span class="comment">// Constant layers execution and management is handled during loaded network construction</span></div> |
| <div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>  <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>  {</div> |
| <div class="line"><a name="l02079"></a><span class="lineno"> 2079</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02080"></a><span class="lineno"> 2080</span>  }</div> |
| <div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>  </div> |
| <div class="line"><a name="l02082"></a><span class="lineno"> 2082</span>  <a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html">WorkingMemDescriptor</a> workingMemDescriptor;</div> |
| <div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>  </div> |
| <div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>  <span class="keywordtype">bool</span> isMemoryManaged = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>  <span class="keywordtype">bool</span> isInputLayer = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  <span class="keywordtype">bool</span> isOutputLayer = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  <span class="keywordtype">bool</span> isConnectedToOutputLayer = <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>  </div> |
| <div class="line"><a name="l02089"></a><span class="lineno"> 2089</span>  <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> || layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">LayerType::MemImport</a>)</div> |
| <div class="line"><a name="l02090"></a><span class="lineno"> 2090</span>  {</div> |
| <div class="line"><a name="l02091"></a><span class="lineno"> 2091</span>  <span class="comment">// Input layers/workloads will not be executed so the descriptor is not added to workingMemDescriptors</span></div> |
| <div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>  <span class="comment">// However we will still need to manage the tensorHandle</span></div> |
| <div class="line"><a name="l02093"></a><span class="lineno"> 2093</span>  isInputLayer = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>  isMemoryManaged = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02095"></a><span class="lineno"> 2095</span>  }</div> |
| <div class="line"><a name="l02096"></a><span class="lineno"> 2096</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div> |
| <div class="line"><a name="l02097"></a><span class="lineno"> 2097</span>  {</div> |
| <div class="line"><a name="l02098"></a><span class="lineno"> 2098</span>  isOutputLayer = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02099"></a><span class="lineno"> 2099</span>  }</div> |
| <div class="line"><a name="l02100"></a><span class="lineno"> 2100</span>  </div> |
| <div class="line"><a name="l02101"></a><span class="lineno"> 2101</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex = 0;</div> |
| <div class="line"><a name="l02102"></a><span class="lineno"> 2102</span>  <span class="comment">// Create a tensor handle for each output slot of a layer</span></div> |
| <div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>  <span class="comment">// Once we create it, we start managing its lifetime</span></div> |
| <div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& slot : layer-><a class="code" href="classarmnn_1_1_layer.html#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>())</div> |
| <div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>  {</div> |
| <div class="line"><a name="l02106"></a><span class="lineno"> 2106</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < slot.GetNumConnections(); ++i)</div> |
| <div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>  {</div> |
| <div class="line"><a name="l02108"></a><span class="lineno"> 2108</span>  <span class="keywordflow">if</span> ((slot.GetConnection(i)->GetOwningLayer().GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>))</div> |
| <div class="line"><a name="l02109"></a><span class="lineno"> 2109</span>  {</div> |
| <div class="line"><a name="l02110"></a><span class="lineno"> 2110</span>  <span class="keywordflow">if</span> (!isConnectedToOutputLayer)</div> |
| <div class="line"><a name="l02111"></a><span class="lineno"> 2111</span>  {</div> |
| <div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>  isConnectedToOutputLayer = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>  <span class="comment">// If Export is enabled disable memory management, so we can export, otherwise we do a copy</span></div> |
| <div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>  isMemoryManaged = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> == <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02115"></a><span class="lineno"> 2115</span>  }</div> |
| <div class="line"><a name="l02116"></a><span class="lineno"> 2116</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>  {</div> |
| <div class="line"><a name="l02118"></a><span class="lineno"> 2118</span>  <span class="comment">// Importing in this case would likely cause unexpected behaviour, so we disallow it.</span></div> |
| <div class="line"><a name="l02119"></a><span class="lineno"> 2119</span>  <a class="code" href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) <<</div> |
| <div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>  fmt::format(<span class="stringliteral">"Layer name: '{0}' guid: '{1}' has two or more OutputLayers connected to it. "</span></div> |
| <div class="line"><a name="l02121"></a><span class="lineno"> 2121</span>  <span class="stringliteral">"This will prevent importing on the connected OutputLayers."</span>,</div> |
| <div class="line"><a name="l02122"></a><span class="lineno"> 2122</span>  layer-><a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>(), layer-><a class="code" href="classarmnn_1_1_layer.html#a8dc12f0ee5b232d397bd18ced1a72a64">GetGuid</a>());</div> |
| <div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>  isMemoryManaged = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>  }</div> |
| <div class="line"><a name="l02125"></a><span class="lineno"> 2125</span>  }</div> |
| <div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>  }</div> |
| <div class="line"><a name="l02127"></a><span class="lineno"> 2127</span>  </div> |
| <div class="line"><a name="l02128"></a><span class="lineno"> 2128</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle;</div> |
| <div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>  <span class="keywordflow">if</span> (isMemoryManaged)</div> |
| <div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>  {</div> |
| <div class="line"><a name="l02131"></a><span class="lineno"> 2131</span>  managedTensorHandles.emplace_back(GetTensorHandle(layer, slot));</div> |
| <div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>  tensorHandle = managedTensorHandles.back().get();</div> |
| <div class="line"><a name="l02133"></a><span class="lineno"> 2133</span>  }</div> |
| <div class="line"><a name="l02134"></a><span class="lineno"> 2134</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>  {</div> |
| <div class="line"><a name="l02136"></a><span class="lineno"> 2136</span>  unmanagedTensorHandles.emplace_back(GetTensorHandle(layer, slot));</div> |
| <div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>  tensorHandle = unmanagedTensorHandles.back().get();</div> |
| <div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>  }</div> |
| <div class="line"><a name="l02139"></a><span class="lineno"> 2139</span>  </div> |
| <div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>  workingMemDescriptor.<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>.push_back(tensorHandle);</div> |
| <div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>  </div> |
| <div class="line"><a name="l02142"></a><span class="lineno"> 2142</span>  HandleInfo& handleInfo = outputToHandleInfoMap[&slot];</div> |
| <div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>  handleInfo.m_TensorHandle = tensorHandle;</div> |
| <div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>  </div> |
| <div class="line"><a name="l02145"></a><span class="lineno"> 2145</span>  <span class="comment">// Store the coordinates of the current layer's OutputSlot that is connected to the OutputLayer</span></div> |
| <div class="line"><a name="l02146"></a><span class="lineno"> 2146</span>  <span class="keywordflow">if</span> (isConnectedToOutputLayer)</div> |
| <div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>  {</div> |
| <div class="line"><a name="l02148"></a><span class="lineno"> 2148</span>  handleInfo.m_IsOutputLayerHandle = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02149"></a><span class="lineno"> 2149</span>  handleInfo.m_OutputMemDescriptorCoords.m_OutputSlotCoords = {layerIndex, slotIndex};</div> |
| <div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>  }</div> |
| <div class="line"><a name="l02151"></a><span class="lineno"> 2151</span>  <span class="comment">// Store the LayerBindingId of the InputLayer</span></div> |
| <div class="line"><a name="l02152"></a><span class="lineno"> 2152</span>  <span class="keywordflow">if</span> (isInputLayer)</div> |
| <div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>  {</div> |
| <div class="line"><a name="l02154"></a><span class="lineno"> 2154</span>  handleInfo.m_IsInputLayerHandle = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>*<span class="keyword">></span>(layer)->GetBindingId();</div> |
| <div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>  handleInfo.m_InputMemDescriptorCoords.m_LayerBindingId = bindingId;</div> |
| <div class="line"><a name="l02157"></a><span class="lineno"> 2157</span>  }</div> |
| <div class="line"><a name="l02158"></a><span class="lineno"> 2158</span>  slotIndex++;</div> |
| <div class="line"><a name="l02159"></a><span class="lineno"> 2159</span>  }</div> |
| <div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>  <span class="comment">// Loop through the input slots in the same layer and decrement the reference counter associated</span></div> |
| <div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>  <span class="comment">// to each tensor handle we encounter.</span></div> |
| <div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>  <span class="comment">// Once it reaches zero, the lifetime of the tensor handle has ended, and we mark its memory as available</span></div> |
| <div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>  <span class="comment">// so that the next tensor handle with a non overlapping lifetime can share its memory.</span></div> |
| <div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& slot : layer-><a class="code" href="classarmnn_1_1_layer.html#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>())</div> |
| <div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>  {</div> |
| <div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>  <span class="keywordflow">if</span> (!slot.GetConnection())</div> |
| <div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>  {</div> |
| <div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a>(<span class="stringliteral">"slot must be a valid input slot."</span>);</div> |
| <div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>  }</div> |
| <div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>  </div> |
| <div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>  <span class="keyword">auto</span> outputSlot = slot.GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>  <span class="keyword">auto</span> key = outputSlot->GetOwningLayer().GetGuid();</div> |
| <div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>  </div> |
| <div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>  <span class="comment">// Constant layers execution and management is handled during loaded network construction</span></div> |
| <div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>  <span class="keyword">auto</span> found = m_ConstantTensorHandles.find(key);</div> |
| <div class="line"><a name="l02176"></a><span class="lineno"> 2176</span>  <span class="keywordflow">if</span> (found != m_ConstantTensorHandles.end())</div> |
| <div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>  {</div> |
| <div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* tensorHandle = found->second;</div> |
| <div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>  <span class="keywordflow">if</span> (slot.IsTensorInfoOverridden())</div> |
| <div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>  {</div> |
| <div class="line"><a name="l02181"></a><span class="lineno"> 2181</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* decorated = tensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a82d949cbbc7667d9f13e3f2a474cad36">DecorateTensorHandle</a>(slot.GetTensorInfo()).get();</div> |
| <div class="line"><a name="l02182"></a><span class="lineno"> 2182</span>  <span class="keywordflow">if</span> (decorated)</div> |
| <div class="line"><a name="l02183"></a><span class="lineno"> 2183</span>  {</div> |
| <div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>  tensorHandle = decorated;</div> |
| <div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>  }</div> |
| <div class="line"><a name="l02186"></a><span class="lineno"> 2186</span>  }</div> |
| <div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>  workingMemDescriptor.<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>.push_back(tensorHandle);</div> |
| <div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>  </div> |
| <div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>  <span class="comment">// Odd case where a constant layer is connected to an output layer</span></div> |
| <div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>  <span class="comment">// We will need to create a HandleInfo to track it</span></div> |
| <div class="line"><a name="l02191"></a><span class="lineno"> 2191</span>  <span class="keywordflow">if</span> (isOutputLayer)</div> |
| <div class="line"><a name="l02192"></a><span class="lineno"> 2192</span>  {</div> |
| <div class="line"><a name="l02193"></a><span class="lineno"> 2193</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>*<span class="keyword">></span>(layer)->GetBindingId();</div> |
| <div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>  </div> |
| <div class="line"><a name="l02195"></a><span class="lineno"> 2195</span>  HandleInfo& handleInfo = outputToHandleInfoMap[outputSlot];</div> |
| <div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>  handleInfo.m_TensorHandle = tensorHandle;</div> |
| <div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>  handleInfo.m_IsOutputLayerHandle = <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>  handleInfo.m_OutputMemDescriptorCoords.m_LayerBindingIds.push_back(bindingId);</div> |
| <div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, 0});</div> |
| <div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>  }</div> |
| <div class="line"><a name="l02201"></a><span class="lineno"> 2201</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>  }</div> |
| <div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>  </div> |
| <div class="line"><a name="l02204"></a><span class="lineno"> 2204</span>  HandleInfo& handleInfo = outputToHandleInfoMap.at(outputSlot);</div> |
| <div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>  </div> |
| <div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* inputTensorHandle = handleInfo.m_TensorHandle;</div> |
| <div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>  <span class="keywordflow">if</span> (slot.IsTensorInfoOverridden())</div> |
| <div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>  {</div> |
| <div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle.html">ITensorHandle</a>* decorated = inputTensorHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.html#a82d949cbbc7667d9f13e3f2a474cad36">DecorateTensorHandle</a>(slot.GetTensorInfo()).get();</div> |
| <div class="line"><a name="l02210"></a><span class="lineno"> 2210</span>  <span class="keywordflow">if</span> (decorated)</div> |
| <div class="line"><a name="l02211"></a><span class="lineno"> 2211</span>  {</div> |
| <div class="line"><a name="l02212"></a><span class="lineno"> 2212</span>  inputTensorHandle = decorated;</div> |
| <div class="line"><a name="l02213"></a><span class="lineno"> 2213</span>  }</div> |
| <div class="line"><a name="l02214"></a><span class="lineno"> 2214</span>  }</div> |
| <div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>  workingMemDescriptor.<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>.push_back(inputTensorHandle);</div> |
| <div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>  </div> |
| <div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>  <span class="comment">// Store the LayerBindingId of the OutputLayer</span></div> |
| <div class="line"><a name="l02218"></a><span class="lineno"> 2218</span>  <span class="keywordflow">if</span> (isOutputLayer)</div> |
| <div class="line"><a name="l02219"></a><span class="lineno"> 2219</span>  {</div> |
| <div class="line"><a name="l02220"></a><span class="lineno"> 2220</span>  <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_bindable_layer.html">BindableLayer</a>*<span class="keyword">></span>(layer)->GetBindingId();</div> |
| <div class="line"><a name="l02221"></a><span class="lineno"> 2221</span>  handleInfo.m_OutputMemDescriptorCoords.m_LayerBindingIds.push_back(bindingId);</div> |
| <div class="line"><a name="l02222"></a><span class="lineno"> 2222</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, 0});</div> |
| <div class="line"><a name="l02223"></a><span class="lineno"> 2223</span>  }</div> |
| <div class="line"><a name="l02224"></a><span class="lineno"> 2224</span>  <span class="comment">// In this case the layer is not an Output Layer but shares its input tensorhandle with an OutputLayer</span></div> |
| <div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>  <span class="comment">// It will need to be updated as well, if we swap out the tensorhandle</span></div> |
| <div class="line"><a name="l02226"></a><span class="lineno"> 2226</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (handleInfo.m_IsOutputLayerHandle)</div> |
| <div class="line"><a name="l02227"></a><span class="lineno"> 2227</span>  {</div> |
| <div class="line"><a name="l02228"></a><span class="lineno"> 2228</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, slot.GetSlotIndex()});</div> |
| <div class="line"><a name="l02229"></a><span class="lineno"> 2229</span>  }</div> |
| <div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>  </div> |
| <div class="line"><a name="l02231"></a><span class="lineno"> 2231</span>  <span class="comment">// Store the coordinates of the InputSlots connected to the InputLayer</span></div> |
| <div class="line"><a name="l02232"></a><span class="lineno"> 2232</span>  <span class="comment">// There can be more than one InputSlot connected to an InputLayer, so we use a vector</span></div> |
| <div class="line"><a name="l02233"></a><span class="lineno"> 2233</span>  <span class="keywordflow">if</span> (handleInfo.m_IsInputLayerHandle)</div> |
| <div class="line"><a name="l02234"></a><span class="lineno"> 2234</span>  {</div> |
| <div class="line"><a name="l02235"></a><span class="lineno"> 2235</span>  std::pair<LayerGuid, unsigned int> connectionLocation{layerIndex, slot.GetSlotIndex()};</div> |
| <div class="line"><a name="l02236"></a><span class="lineno"> 2236</span>  handleInfo.m_InputMemDescriptorCoords.m_InputSlotCoords.emplace_back(connectionLocation);</div> |
| <div class="line"><a name="l02237"></a><span class="lineno"> 2237</span>  }</div> |
| <div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>  }</div> |
| <div class="line"><a name="l02239"></a><span class="lineno"> 2239</span>  </div> |
| <div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>  <span class="comment">// Input/Output layers/workloads will not be executed, so the descriptor is not added to workingMemDescriptors</span></div> |
| <div class="line"><a name="l02241"></a><span class="lineno"> 2241</span>  <span class="comment">// However we will still need to manage the tensorHandle</span></div> |
| <div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>  <span class="keywordflow">if</span> (!isInputLayer)</div> |
| <div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>  {</div> |
| <div class="line"><a name="l02244"></a><span class="lineno"> 2244</span>  <span class="comment">// Simply auto initialise ExecutionData here, so it's added only for the layer that require execution.</span></div> |
| <div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>  <span class="comment">// The memory and data will be allocated/assigned for the void* in WorkingMemHandle::Allocate.</span></div> |
| <div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>  std::pair<BackendId, ExecutionData> dataPair;</div> |
| <div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>  dataPair.first = layer-><a class="code" href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>();</div> |
| <div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>  </div> |
| <div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>  executionDataVec.push_back(dataPair);</div> |
| <div class="line"><a name="l02250"></a><span class="lineno"> 2250</span>  workingMemDescriptors.push_back(workingMemDescriptor);</div> |
| <div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>  </div> |
| <div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>  layerIndex++;</div> |
| <div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>  }</div> |
| <div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>  }</div> |
| <div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>  </div> |
| <div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>  std::vector<std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>> tensorMemory;</div> |
| <div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>  </div> |
| <div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>  <span class="keyword">auto</span> externalMemoryManager = CreateExternalMemoryManger(tensorMemory);</div> |
| <div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>  </div> |
| <div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>  <span class="comment">// Sort m_TensorMemory, so it's order matches the outputSlot order</span></div> |
| <div class="line"><a name="l02261"></a><span class="lineno"> 2261</span>  std::sort(tensorMemory.begin(), tensorMemory.end(),</div> |
| <div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>  [](<span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& lhs,</div> |
| <div class="line"><a name="l02263"></a><span class="lineno"> 2263</span>  <span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& rhs)</div> |
| <div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>  {</div> |
| <div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>  return lhs.first->m_OutputSlotId < rhs.first->m_OutputSlotId;</div> |
| <div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>  });</div> |
| <div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>  </div> |
| <div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>  std::vector<WorkingMemHandle::InputMemDescriptorCoords> inputConnectionsInfo;</div> |
| <div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>  std::vector<WorkingMemHandle::OutputMemDescriptorCoords> outputConnectionsInfo;</div> |
| <div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>  </div> |
| <div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& handleInfo: outputToHandleInfoMap)</div> |
| <div class="line"><a name="l02272"></a><span class="lineno"> 2272</span>  {</div> |
| <div class="line"><a name="l02273"></a><span class="lineno"> 2273</span>  <span class="keywordflow">if</span> (handleInfo.second.m_IsOutputLayerHandle)</div> |
| <div class="line"><a name="l02274"></a><span class="lineno"> 2274</span>  {</div> |
| <div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>  outputConnectionsInfo.emplace_back(handleInfo.second.m_OutputMemDescriptorCoords);</div> |
| <div class="line"><a name="l02276"></a><span class="lineno"> 2276</span>  }</div> |
| <div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>  </div> |
| <div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>  <span class="keywordflow">if</span> (handleInfo.second.m_IsInputLayerHandle)</div> |
| <div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>  {</div> |
| <div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>  inputConnectionsInfo.emplace_back(handleInfo.second.m_InputMemDescriptorCoords);</div> |
| <div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>  }</div> |
| <div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>  }</div> |
| <div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>  </div> |
| <div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>  <span class="keywordflow">return</span> std::make_unique<WorkingMemHandle>(networkId,</div> |
| <div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>  inputConnectionsInfo,</div> |
| <div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>  outputConnectionsInfo,</div> |
| <div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>  workingMemDescriptors,</div> |
| <div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>  std::move(externalMemoryManager),</div> |
| <div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>  std::move(tensorMemory),</div> |
| <div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>  std::move(managedTensorHandles),</div> |
| <div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>  std::move(unmanagedTensorHandles),</div> |
| <div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>  executionDataVec,</div> |
| <div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>  &m_Backends);</div> |
| <div class="line"><a name="l02294"></a><span class="lineno"> 2294</span> }</div> |
| <div class="line"><a name="l02295"></a><span class="lineno"> 2295</span>  </div> |
| <div class="line"><a name="l02296"></a><span class="lineno"><a class="line" href="classarmnn_1_1_loaded_network.html#a091ea8d2d804c8902f3120fdf2a36512"> 2296</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_loaded_network.html#a091ea8d2d804c8902f3120fdf2a36512">LoadedNetwork::RegisterDebugCallback</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a>& func)</div> |
| <div class="line"><a name="l02297"></a><span class="lineno"> 2297</span> {</div> |
| <div class="line"><a name="l02298"></a><span class="lineno"> 2298</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& workloadPtr: m_WorkloadQueue)</div> |
| <div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>  {</div> |
| <div class="line"><a name="l02300"></a><span class="lineno"> 2300</span>  workloadPtr.get()->RegisterDebugCallback(func);</div> |
| <div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>  }</div> |
| <div class="line"><a name="l02302"></a><span class="lineno"> 2302</span> }</div> |
| <div class="line"><a name="l02303"></a><span class="lineno"> 2303</span>  </div> |
| <div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>  </div> |
| <div class="line"><a name="l02305"></a><span class="lineno"> 2305</span> <span class="keywordtype">void</span> LoadedNetwork::CreateMemoryProfileAsync()</div> |
| <div class="line"><a name="l02306"></a><span class="lineno"> 2306</span> {</div> |
| <div class="line"><a name="l02307"></a><span class="lineno"> 2307</span>  <span class="keyword">struct </span>PartialBlock</div> |
| <div class="line"><a name="l02308"></a><span class="lineno"> 2308</span>  {</div> |
| <div class="line"><a name="l02309"></a><span class="lineno"> 2309</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_StartOfLife;</div> |
| <div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_Lifetime;</div> |
| <div class="line"><a name="l02311"></a><span class="lineno"> 2311</span>  </div> |
| <div class="line"><a name="l02312"></a><span class="lineno"> 2312</span>  <span class="keywordtype">size_t</span> m_MemSize;</div> |
| <div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_Index;</div> |
| <div class="line"><a name="l02314"></a><span class="lineno"> 2314</span>  </div> |
| <div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>  <a class="code" href="classarmnn_1_1_backend_id.html">BackendId</a> m_BackendId;</div> |
| <div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>  };</div> |
| <div class="line"><a name="l02317"></a><span class="lineno"> 2317</span>  </div> |
| <div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>  <span class="keyword">auto</span> align = [](<span class="keywordtype">size_t</span> numToAlign)</div> |
| <div class="line"><a name="l02319"></a><span class="lineno"> 2319</span>  {</div> |
| <div class="line"><a name="l02320"></a><span class="lineno"> 2320</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> alignment = <span class="keyword">sizeof</span>(float);</div> |
| <div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>  <span class="keywordflow">return</span> ((numToAlign + alignment - 1) / alignment) * alignment;</div> |
| <div class="line"><a name="l02322"></a><span class="lineno"> 2322</span>  };</div> |
| <div class="line"><a name="l02323"></a><span class="lineno"> 2323</span>  </div> |
| <div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>  std::unordered_map<const OutputSlot*, PartialBlock> memBlockTrackerMap;</div> |
| <div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>  </div> |
| <div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> inputImportingEnabled = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> outputImportingEnabled = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02328"></a><span class="lineno"> 2328</span>  </div> |
| <div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timestep = 0;</div> |
| <div class="line"><a name="l02330"></a><span class="lineno"> 2330</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div> |
| <div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>  Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>  </div> |
| <div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>  {</div> |
| <div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>& layerType = layer->GetType();</div> |
| <div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>  <span class="comment">// Don't manage memory if importing.</span></div> |
| <div class="line"><a name="l02337"></a><span class="lineno"> 2337</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> && inputImportingEnabled)</div> |
| <div class="line"><a name="l02338"></a><span class="lineno"> 2338</span>  {</div> |
| <div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>  }</div> |
| <div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>  <span class="comment">// Don't manage memory if importing.</span></div> |
| <div class="line"><a name="l02342"></a><span class="lineno"> 2342</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a> && outputImportingEnabled</div> |
| <div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>  && layer->GetInputSlot(0).GetConnectedOutputSlot()->GetNumConnections() == 1)</div> |
| <div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>  {</div> |
| <div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02346"></a><span class="lineno"> 2346</span>  }</div> |
| <div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>  <span class="comment">// Because Constant Layer memory can not be shared, the memory must persist for the lifetime of execution,</span></div> |
| <div class="line"><a name="l02348"></a><span class="lineno"> 2348</span>  <span class="comment">// management is done separately.</span></div> |
| <div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>  {</div> |
| <div class="line"><a name="l02351"></a><span class="lineno"> 2351</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02352"></a><span class="lineno"> 2352</span>  }</div> |
| <div class="line"><a name="l02353"></a><span class="lineno"> 2353</span>  </div> |
| <div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>  BackendId backendId = layer->GetBackendId();</div> |
| <div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& outputSlot : layer->GetOutputSlots())</div> |
| <div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>  {</div> |
| <div class="line"><a name="l02357"></a><span class="lineno"> 2357</span>  <span class="keywordflow">if</span> (!m_SupportsExternallyManagedMemory[backendId])</div> |
| <div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>  {</div> |
| <div class="line"><a name="l02359"></a><span class="lineno"> 2359</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02360"></a><span class="lineno"> 2360</span>  }</div> |
| <div class="line"><a name="l02361"></a><span class="lineno"> 2361</span>  </div> |
| <div class="line"><a name="l02362"></a><span class="lineno"> 2362</span>  PartialBlock partialBlock;</div> |
| <div class="line"><a name="l02363"></a><span class="lineno"> 2363</span>  </div> |
| <div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>  partialBlock.m_StartOfLife = timestep;</div> |
| <div class="line"><a name="l02365"></a><span class="lineno"> 2365</span>  </div> |
| <div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>  <span class="keywordtype">size_t</span> alignedSize = align(outputSlot.GetOutputHandler().GetTensorInfo().GetNumBytes());</div> |
| <div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>  partialBlock.m_MemSize = alignedSize;</div> |
| <div class="line"><a name="l02368"></a><span class="lineno"> 2368</span>  partialBlock.m_Index = outputIndex++;</div> |
| <div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>  partialBlock.m_Lifetime = outputSlot.GetNumConnections();</div> |
| <div class="line"><a name="l02370"></a><span class="lineno"> 2370</span>  partialBlock.m_BackendId = backendId;</div> |
| <div class="line"><a name="l02371"></a><span class="lineno"> 2371</span>  </div> |
| <div class="line"><a name="l02372"></a><span class="lineno"> 2372</span>  <span class="keywordflow">if</span> (partialBlock.m_Lifetime == 0)</div> |
| <div class="line"><a name="l02373"></a><span class="lineno"> 2373</span>  {</div> |
| <div class="line"><a name="l02374"></a><span class="lineno"> 2374</span>  m_MemBlockMap[partialBlock.m_BackendId].emplace_back(partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>  partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02376"></a><span class="lineno"> 2376</span>  partialBlock.m_MemSize,</div> |
| <div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>  0,</div> |
| <div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>  partialBlock.m_Index);</div> |
| <div class="line"><a name="l02379"></a><span class="lineno"> 2379</span>  }</div> |
| <div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02381"></a><span class="lineno"> 2381</span>  {</div> |
| <div class="line"><a name="l02382"></a><span class="lineno"> 2382</span>  memBlockTrackerMap[&outputSlot] = partialBlock;</div> |
| <div class="line"><a name="l02383"></a><span class="lineno"> 2383</span>  }</div> |
| <div class="line"><a name="l02384"></a><span class="lineno"> 2384</span>  }</div> |
| <div class="line"><a name="l02385"></a><span class="lineno"> 2385</span>  </div> |
| <div class="line"><a name="l02386"></a><span class="lineno"> 2386</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& inputSlot : layer->GetInputSlots())</div> |
| <div class="line"><a name="l02387"></a><span class="lineno"> 2387</span>  {</div> |
| <div class="line"><a name="l02388"></a><span class="lineno"> 2388</span>  <span class="keyword">const</span> Layer& connectedInputLayer = inputSlot.GetConnectedOutputSlot()->GetOwningLayer();</div> |
| <div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>& owningLayerType = connectedInputLayer.GetType();</div> |
| <div class="line"><a name="l02390"></a><span class="lineno"> 2390</span>  </div> |
| <div class="line"><a name="l02391"></a><span class="lineno"> 2391</span>  <span class="keywordflow">if</span> (owningLayerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l02392"></a><span class="lineno"> 2392</span>  {</div> |
| <div class="line"><a name="l02393"></a><span class="lineno"> 2393</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02394"></a><span class="lineno"> 2394</span>  }</div> |
| <div class="line"><a name="l02395"></a><span class="lineno"> 2395</span>  <span class="keywordflow">if</span> (inputImportingEnabled && owningLayerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l02396"></a><span class="lineno"> 2396</span>  {</div> |
| <div class="line"><a name="l02397"></a><span class="lineno"> 2397</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02398"></a><span class="lineno"> 2398</span>  }</div> |
| <div class="line"><a name="l02399"></a><span class="lineno"> 2399</span>  </div> |
| <div class="line"><a name="l02400"></a><span class="lineno"> 2400</span>  <span class="keyword">auto</span> outputSlot = inputSlot.GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l02401"></a><span class="lineno"> 2401</span>  </div> |
| <div class="line"><a name="l02402"></a><span class="lineno"> 2402</span>  PartialBlock& partialBlock = memBlockTrackerMap.at(outputSlot);</div> |
| <div class="line"><a name="l02403"></a><span class="lineno"> 2403</span>  </div> |
| <div class="line"><a name="l02404"></a><span class="lineno"> 2404</span>  <span class="keyword">auto</span>& lifetime = partialBlock.m_Lifetime;</div> |
| <div class="line"><a name="l02405"></a><span class="lineno"> 2405</span>  --lifetime;</div> |
| <div class="line"><a name="l02406"></a><span class="lineno"> 2406</span>  </div> |
| <div class="line"><a name="l02407"></a><span class="lineno"> 2407</span>  <span class="keywordflow">if</span> (lifetime == 0)</div> |
| <div class="line"><a name="l02408"></a><span class="lineno"> 2408</span>  {</div> |
| <div class="line"><a name="l02409"></a><span class="lineno"> 2409</span>  m_MemBlockMap[partialBlock.m_BackendId].emplace_back(partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02410"></a><span class="lineno"> 2410</span>  timestep,</div> |
| <div class="line"><a name="l02411"></a><span class="lineno"> 2411</span>  partialBlock.m_MemSize,</div> |
| <div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>  0,</div> |
| <div class="line"><a name="l02413"></a><span class="lineno"> 2413</span>  partialBlock.m_Index);</div> |
| <div class="line"><a name="l02414"></a><span class="lineno"> 2414</span>  }</div> |
| <div class="line"><a name="l02415"></a><span class="lineno"> 2415</span>  }</div> |
| <div class="line"><a name="l02416"></a><span class="lineno"> 2416</span>  ++timestep;</div> |
| <div class="line"><a name="l02417"></a><span class="lineno"> 2417</span>  }</div> |
| <div class="line"><a name="l02418"></a><span class="lineno"> 2418</span> }</div> |
| <div class="line"><a name="l02419"></a><span class="lineno"> 2419</span>  </div> |
| <div class="line"><a name="l02420"></a><span class="lineno"> 2420</span> <span class="keywordtype">void</span> LoadedNetwork::CreateMemoryProfile()</div> |
| <div class="line"><a name="l02421"></a><span class="lineno"> 2421</span> {</div> |
| <div class="line"><a name="l02422"></a><span class="lineno"> 2422</span>  <span class="comment">// Finds the first TensorHandle ancestor of a SubTensorHandle. If the ITensorHandle provided</span></div> |
| <div class="line"><a name="l02423"></a><span class="lineno"> 2423</span>  <span class="comment">// is a TensorHandle, the function just returns it</span></div> |
| <div class="line"><a name="l02424"></a><span class="lineno"> 2424</span>  <span class="keyword">auto</span> TraceSubTensorHandleAncestry = [](ITensorHandle* <span class="keyword">const</span> subTensorHandle)</div> |
| <div class="line"><a name="l02425"></a><span class="lineno"> 2425</span>  {</div> |
| <div class="line"><a name="l02426"></a><span class="lineno"> 2426</span>  ITensorHandle* ancestor = subTensorHandle;</div> |
| <div class="line"><a name="l02427"></a><span class="lineno"> 2427</span>  <span class="keywordflow">while</span> (ancestor && ancestor->GetParent())</div> |
| <div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>  {</div> |
| <div class="line"><a name="l02429"></a><span class="lineno"> 2429</span>  ancestor = ancestor->GetParent();</div> |
| <div class="line"><a name="l02430"></a><span class="lineno"> 2430</span>  }</div> |
| <div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>  <span class="keywordflow">return</span> ancestor;</div> |
| <div class="line"><a name="l02432"></a><span class="lineno"> 2432</span>  };</div> |
| <div class="line"><a name="l02433"></a><span class="lineno"> 2433</span>  </div> |
| <div class="line"><a name="l02434"></a><span class="lineno"> 2434</span>  <span class="keyword">struct </span>PartialBlock</div> |
| <div class="line"><a name="l02435"></a><span class="lineno"> 2435</span>  {</div> |
| <div class="line"><a name="l02436"></a><span class="lineno"> 2436</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_StartOfLife;</div> |
| <div class="line"><a name="l02437"></a><span class="lineno"> 2437</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_Lifetime;</div> |
| <div class="line"><a name="l02438"></a><span class="lineno"> 2438</span>  </div> |
| <div class="line"><a name="l02439"></a><span class="lineno"> 2439</span>  <span class="keywordtype">size_t</span> m_MemSize;</div> |
| <div class="line"><a name="l02440"></a><span class="lineno"> 2440</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> m_Index;</div> |
| <div class="line"><a name="l02441"></a><span class="lineno"> 2441</span>  </div> |
| <div class="line"><a name="l02442"></a><span class="lineno"> 2442</span>  BackendId m_BackendId;</div> |
| <div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>  };</div> |
| <div class="line"><a name="l02444"></a><span class="lineno"> 2444</span>  </div> |
| <div class="line"><a name="l02445"></a><span class="lineno"> 2445</span>  <span class="keyword">auto</span> align = [](<span class="keywordtype">size_t</span> numToAlign)</div> |
| <div class="line"><a name="l02446"></a><span class="lineno"> 2446</span>  {</div> |
| <div class="line"><a name="l02447"></a><span class="lineno"> 2447</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> alignment = <span class="keyword">sizeof</span>(float);</div> |
| <div class="line"><a name="l02448"></a><span class="lineno"> 2448</span>  <span class="keywordflow">return</span> ((numToAlign + alignment - 1) / alignment) * alignment;</div> |
| <div class="line"><a name="l02449"></a><span class="lineno"> 2449</span>  };</div> |
| <div class="line"><a name="l02450"></a><span class="lineno"> 2450</span>  </div> |
| <div class="line"><a name="l02451"></a><span class="lineno"> 2451</span>  std::unordered_map<ITensorHandle*, PartialBlock> memBlockTrackerMap;</div> |
| <div class="line"><a name="l02452"></a><span class="lineno"> 2452</span>  </div> |
| <div class="line"><a name="l02453"></a><span class="lineno"> 2453</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> inputImportingEnabled = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02454"></a><span class="lineno"> 2454</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> outputImportingEnabled = m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a> != <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>;</div> |
| <div class="line"><a name="l02455"></a><span class="lineno"> 2455</span>  </div> |
| <div class="line"><a name="l02456"></a><span class="lineno"> 2456</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timestep = 0;</div> |
| <div class="line"><a name="l02457"></a><span class="lineno"> 2457</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div> |
| <div class="line"><a name="l02458"></a><span class="lineno"> 2458</span>  Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div> |
| <div class="line"><a name="l02459"></a><span class="lineno"> 2459</span>  </div> |
| <div class="line"><a name="l02460"></a><span class="lineno"> 2460</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div> |
| <div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>  {</div> |
| <div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>& layerType = layer->GetType();</div> |
| <div class="line"><a name="l02463"></a><span class="lineno"> 2463</span>  <span class="comment">// Don't manage memory if importing.</span></div> |
| <div class="line"><a name="l02464"></a><span class="lineno"> 2464</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> && inputImportingEnabled)</div> |
| <div class="line"><a name="l02465"></a><span class="lineno"> 2465</span>  {</div> |
| <div class="line"><a name="l02466"></a><span class="lineno"> 2466</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02467"></a><span class="lineno"> 2467</span>  }</div> |
| <div class="line"><a name="l02468"></a><span class="lineno"> 2468</span>  <span class="comment">// Don't manage memory if importing.</span></div> |
| <div class="line"><a name="l02469"></a><span class="lineno"> 2469</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a> && outputImportingEnabled</div> |
| <div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>  && layer->GetInputSlot(0).GetConnectedOutputSlot()->GetNumConnections() == 1)</div> |
| <div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>  {</div> |
| <div class="line"><a name="l02472"></a><span class="lineno"> 2472</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02473"></a><span class="lineno"> 2473</span>  }</div> |
| <div class="line"><a name="l02474"></a><span class="lineno"> 2474</span>  <span class="comment">// Because Constant Layer memory can not be shared, the memory must persist for the lifetime of execution,</span></div> |
| <div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>  <span class="comment">// management is done separately.</span></div> |
| <div class="line"><a name="l02476"></a><span class="lineno"> 2476</span>  <span class="keywordflow">if</span> (layerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l02477"></a><span class="lineno"> 2477</span>  {</div> |
| <div class="line"><a name="l02478"></a><span class="lineno"> 2478</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02479"></a><span class="lineno"> 2479</span>  }</div> |
| <div class="line"><a name="l02480"></a><span class="lineno"> 2480</span>  </div> |
| <div class="line"><a name="l02481"></a><span class="lineno"> 2481</span>  BackendId backendId = layer->GetBackendId();</div> |
| <div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& outputSlot : layer->GetOutputSlots())</div> |
| <div class="line"><a name="l02483"></a><span class="lineno"> 2483</span>  {</div> |
| <div class="line"><a name="l02484"></a><span class="lineno"> 2484</span>  <span class="keywordflow">if</span> (!m_SupportsExternallyManagedMemory[backendId])</div> |
| <div class="line"><a name="l02485"></a><span class="lineno"> 2485</span>  {</div> |
| <div class="line"><a name="l02486"></a><span class="lineno"> 2486</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02487"></a><span class="lineno"> 2487</span>  }</div> |
| <div class="line"><a name="l02488"></a><span class="lineno"> 2488</span>  </div> |
| <div class="line"><a name="l02489"></a><span class="lineno"> 2489</span>  ITensorHandle* tensorHandle = outputSlot.GetOutputHandler().GetData();</div> |
| <div class="line"><a name="l02490"></a><span class="lineno"> 2490</span>  tensorHandle = TraceSubTensorHandleAncestry(tensorHandle);</div> |
| <div class="line"><a name="l02491"></a><span class="lineno"> 2491</span>  </div> |
| <div class="line"><a name="l02492"></a><span class="lineno"> 2492</span>  <span class="keywordflow">if</span> (memBlockTrackerMap.find(tensorHandle) == memBlockTrackerMap.end())</div> |
| <div class="line"><a name="l02493"></a><span class="lineno"> 2493</span>  {</div> |
| <div class="line"><a name="l02494"></a><span class="lineno"> 2494</span>  PartialBlock partialBlock;</div> |
| <div class="line"><a name="l02495"></a><span class="lineno"> 2495</span>  </div> |
| <div class="line"><a name="l02496"></a><span class="lineno"> 2496</span>  partialBlock.m_StartOfLife = timestep;</div> |
| <div class="line"><a name="l02497"></a><span class="lineno"> 2497</span>  </div> |
| <div class="line"><a name="l02498"></a><span class="lineno"> 2498</span>  <span class="keywordtype">size_t</span> alignedSize = align(outputSlot.GetOutputHandler().GetTensorInfo().GetNumBytes());</div> |
| <div class="line"><a name="l02499"></a><span class="lineno"> 2499</span>  partialBlock.m_MemSize = alignedSize;</div> |
| <div class="line"><a name="l02500"></a><span class="lineno"> 2500</span>  partialBlock.m_Index = outputIndex++;</div> |
| <div class="line"><a name="l02501"></a><span class="lineno"> 2501</span>  partialBlock.m_Lifetime = outputSlot.GetNumConnections();</div> |
| <div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>  partialBlock.m_BackendId = backendId;</div> |
| <div class="line"><a name="l02503"></a><span class="lineno"> 2503</span>  </div> |
| <div class="line"><a name="l02504"></a><span class="lineno"> 2504</span>  <span class="keywordflow">if</span> (partialBlock.m_Lifetime == 0)</div> |
| <div class="line"><a name="l02505"></a><span class="lineno"> 2505</span>  {</div> |
| <div class="line"><a name="l02506"></a><span class="lineno"> 2506</span>  m_MemBlockMap[partialBlock.m_BackendId].emplace_back(partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>  partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02508"></a><span class="lineno"> 2508</span>  partialBlock.m_MemSize,</div> |
| <div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>  0,</div> |
| <div class="line"><a name="l02510"></a><span class="lineno"> 2510</span>  partialBlock.m_Index);</div> |
| <div class="line"><a name="l02511"></a><span class="lineno"> 2511</span>  }</div> |
| <div class="line"><a name="l02512"></a><span class="lineno"> 2512</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02513"></a><span class="lineno"> 2513</span>  {</div> |
| <div class="line"><a name="l02514"></a><span class="lineno"> 2514</span>  memBlockTrackerMap[tensorHandle] = partialBlock;</div> |
| <div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>  }</div> |
| <div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>  m_Tensorhandles.push_back(tensorHandle);</div> |
| <div class="line"><a name="l02517"></a><span class="lineno"> 2517</span>  </div> |
| <div class="line"><a name="l02518"></a><span class="lineno"> 2518</span>  }</div> |
| <div class="line"><a name="l02519"></a><span class="lineno"> 2519</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02520"></a><span class="lineno"> 2520</span>  {</div> |
| <div class="line"><a name="l02521"></a><span class="lineno"> 2521</span>  memBlockTrackerMap.at(tensorHandle).m_Lifetime += outputSlot.GetNumConnections();</div> |
| <div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>  }</div> |
| <div class="line"><a name="l02523"></a><span class="lineno"> 2523</span>  }</div> |
| <div class="line"><a name="l02524"></a><span class="lineno"> 2524</span>  </div> |
| <div class="line"><a name="l02525"></a><span class="lineno"> 2525</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& inputSlot : layer->GetInputSlots())</div> |
| <div class="line"><a name="l02526"></a><span class="lineno"> 2526</span>  {</div> |
| <div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>  <span class="keyword">const</span> Layer& connectedInputLayer = inputSlot.GetConnectedOutputSlot()->GetOwningLayer();</div> |
| <div class="line"><a name="l02528"></a><span class="lineno"> 2528</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>& owningLayerType = connectedInputLayer.GetType();</div> |
| <div class="line"><a name="l02529"></a><span class="lineno"> 2529</span>  </div> |
| <div class="line"><a name="l02530"></a><span class="lineno"> 2530</span>  <span class="keywordflow">if</span> (owningLayerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div> |
| <div class="line"><a name="l02531"></a><span class="lineno"> 2531</span>  {</div> |
| <div class="line"><a name="l02532"></a><span class="lineno"> 2532</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02533"></a><span class="lineno"> 2533</span>  }</div> |
| <div class="line"><a name="l02534"></a><span class="lineno"> 2534</span>  <span class="keywordflow">if</span> (inputImportingEnabled && owningLayerType == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div> |
| <div class="line"><a name="l02535"></a><span class="lineno"> 2535</span>  {</div> |
| <div class="line"><a name="l02536"></a><span class="lineno"> 2536</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02537"></a><span class="lineno"> 2537</span>  }</div> |
| <div class="line"><a name="l02538"></a><span class="lineno"> 2538</span>  <span class="keywordflow">if</span> (!m_SupportsExternallyManagedMemory[connectedInputLayer.GetBackendId()])</div> |
| <div class="line"><a name="l02539"></a><span class="lineno"> 2539</span>  {</div> |
| <div class="line"><a name="l02540"></a><span class="lineno"> 2540</span>  <span class="keywordflow">continue</span>;</div> |
| <div class="line"><a name="l02541"></a><span class="lineno"> 2541</span>  }</div> |
| <div class="line"><a name="l02542"></a><span class="lineno"> 2542</span>  </div> |
| <div class="line"><a name="l02543"></a><span class="lineno"> 2543</span>  <span class="keyword">auto</span> outputSlot = inputSlot.GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l02544"></a><span class="lineno"> 2544</span>  </div> |
| <div class="line"><a name="l02545"></a><span class="lineno"> 2545</span>  ITensorHandle* tensorHandle = outputSlot->GetOutputHandler().GetData();</div> |
| <div class="line"><a name="l02546"></a><span class="lineno"> 2546</span>  tensorHandle = TraceSubTensorHandleAncestry(tensorHandle);</div> |
| <div class="line"><a name="l02547"></a><span class="lineno"> 2547</span>  </div> |
| <div class="line"><a name="l02548"></a><span class="lineno"> 2548</span>  PartialBlock& partialBlock = memBlockTrackerMap.at(tensorHandle);</div> |
| <div class="line"><a name="l02549"></a><span class="lineno"> 2549</span>  </div> |
| <div class="line"><a name="l02550"></a><span class="lineno"> 2550</span>  <span class="keyword">auto</span>& lifetime = partialBlock.m_Lifetime;</div> |
| <div class="line"><a name="l02551"></a><span class="lineno"> 2551</span>  --lifetime;</div> |
| <div class="line"><a name="l02552"></a><span class="lineno"> 2552</span>  </div> |
| <div class="line"><a name="l02553"></a><span class="lineno"> 2553</span>  <span class="keywordflow">if</span> (lifetime == 0)</div> |
| <div class="line"><a name="l02554"></a><span class="lineno"> 2554</span>  {</div> |
| <div class="line"><a name="l02555"></a><span class="lineno"> 2555</span>  m_MemBlockMap[partialBlock.m_BackendId].emplace_back(partialBlock.m_StartOfLife,</div> |
| <div class="line"><a name="l02556"></a><span class="lineno"> 2556</span>  timestep,</div> |
| <div class="line"><a name="l02557"></a><span class="lineno"> 2557</span>  partialBlock.m_MemSize,</div> |
| <div class="line"><a name="l02558"></a><span class="lineno"> 2558</span>  0,</div> |
| <div class="line"><a name="l02559"></a><span class="lineno"> 2559</span>  partialBlock.m_Index);</div> |
| <div class="line"><a name="l02560"></a><span class="lineno"> 2560</span>  }</div> |
| <div class="line"><a name="l02561"></a><span class="lineno"> 2561</span>  }</div> |
| <div class="line"><a name="l02562"></a><span class="lineno"> 2562</span>  ++timestep;</div> |
| <div class="line"><a name="l02563"></a><span class="lineno"> 2563</span>  }</div> |
| <div class="line"><a name="l02564"></a><span class="lineno"> 2564</span>  </div> |
| <div class="line"><a name="l02565"></a><span class="lineno"> 2565</span> }</div> |
| <div class="line"><a name="l02566"></a><span class="lineno"> 2566</span>  </div> |
| <div class="line"><a name="l02567"></a><span class="lineno"> 2567</span> std::unique_ptr<MemoryManager> LoadedNetwork::CreateExternalMemoryManger(</div> |
| <div class="line"><a name="l02568"></a><span class="lineno"> 2568</span>  std::vector<std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>>& tensorMemoryVec)</div> |
| <div class="line"><a name="l02569"></a><span class="lineno"> 2569</span> {</div> |
| <div class="line"><a name="l02570"></a><span class="lineno"> 2570</span>  std::unique_ptr<MemoryManager> memoryManager = std::make_unique<MemoryManager>();</div> |
| <div class="line"><a name="l02571"></a><span class="lineno"> 2571</span>  <span class="keyword">auto</span> allocatorMap = <a class="code" href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.html#a6dea5df9078a3e9b44176175043237f6">GetAllocators</a>();</div> |
| <div class="line"><a name="l02572"></a><span class="lineno"> 2572</span>  </div> |
| <div class="line"><a name="l02573"></a><span class="lineno"> 2573</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& backend : m_MemBinMap)</div> |
| <div class="line"><a name="l02574"></a><span class="lineno"> 2574</span>  {</div> |
| <div class="line"><a name="l02575"></a><span class="lineno"> 2575</span>  std::vector<BufferStorage> bufferStorageVec;</div> |
| <div class="line"><a name="l02576"></a><span class="lineno"> 2576</span>  </div> |
| <div class="line"><a name="l02577"></a><span class="lineno"> 2577</span>  std::shared_ptr<ICustomAllocator> backendAllocator;</div> |
| <div class="line"><a name="l02578"></a><span class="lineno"> 2578</span>  <span class="keywordflow">if</span> (allocatorMap.find(backend.first) != allocatorMap.end())</div> |
| <div class="line"><a name="l02579"></a><span class="lineno"> 2579</span>  {</div> |
| <div class="line"><a name="l02580"></a><span class="lineno"> 2580</span>  backendAllocator = allocatorMap[backend.first];</div> |
| <div class="line"><a name="l02581"></a><span class="lineno"> 2581</span>  }</div> |
| <div class="line"><a name="l02582"></a><span class="lineno"> 2582</span>  <span class="keywordflow">else</span></div> |
| <div class="line"><a name="l02583"></a><span class="lineno"> 2583</span>  {</div> |
| <div class="line"><a name="l02584"></a><span class="lineno"> 2584</span>  backendAllocator = m_Backends[backend.first]->GetDefaultAllocator();</div> |
| <div class="line"><a name="l02585"></a><span class="lineno"> 2585</span>  }</div> |
| <div class="line"><a name="l02586"></a><span class="lineno"> 2586</span>  </div> |
| <div class="line"><a name="l02587"></a><span class="lineno"> 2587</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& memBin : backend.second)</div> |
| <div class="line"><a name="l02588"></a><span class="lineno"> 2588</span>  {</div> |
| <div class="line"><a name="l02589"></a><span class="lineno"> 2589</span>  BufferStorage bufferStorage;</div> |
| <div class="line"><a name="l02590"></a><span class="lineno"> 2590</span>  bufferStorage.m_BufferSize = memBin.m_MemSize;</div> |
| <div class="line"><a name="l02591"></a><span class="lineno"> 2591</span>  bufferStorage.m_TensorMemoryVector.reserve(memBin.m_MemBlocks.size());</div> |
| <div class="line"><a name="l02592"></a><span class="lineno"> 2592</span>  </div> |
| <div class="line"><a name="l02593"></a><span class="lineno"> 2593</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& memBlock : memBin.m_MemBlocks)</div> |
| <div class="line"><a name="l02594"></a><span class="lineno"> 2594</span>  {</div> |
| <div class="line"><a name="l02595"></a><span class="lineno"> 2595</span>  <span class="keyword">auto</span> tensorMemory = std::make_shared<TensorMemory>(TensorMemory{memBlock.m_Offset, memBlock.m_Index});</div> |
| <div class="line"><a name="l02596"></a><span class="lineno"> 2596</span>  </div> |
| <div class="line"><a name="l02597"></a><span class="lineno"> 2597</span>  tensorMemoryVec.emplace_back(tensorMemory, backendAllocator->GetMemorySourceType());</div> |
| <div class="line"><a name="l02598"></a><span class="lineno"> 2598</span>  bufferStorage.m_TensorMemoryVector.emplace_back(tensorMemory);</div> |
| <div class="line"><a name="l02599"></a><span class="lineno"> 2599</span>  }</div> |
| <div class="line"><a name="l02600"></a><span class="lineno"> 2600</span>  </div> |
| <div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>  bufferStorageVec.emplace_back(std::move(bufferStorage));</div> |
| <div class="line"><a name="l02602"></a><span class="lineno"> 2602</span>  }</div> |
| <div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>  </div> |
| <div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>  memoryManager->StoreMemToAllocate(bufferStorageVec, backendAllocator, 4);</div> |
| <div class="line"><a name="l02605"></a><span class="lineno"> 2605</span>  }</div> |
| <div class="line"><a name="l02606"></a><span class="lineno"> 2606</span>  </div> |
| <div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>  <span class="keywordflow">return</span> memoryManager;</div> |
| <div class="line"><a name="l02608"></a><span class="lineno"> 2608</span> }</div> |
| <div class="line"><a name="l02609"></a><span class="lineno"> 2609</span>  </div> |
| <div class="line"><a name="l02610"></a><span class="lineno"> 2610</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> LoadedNetwork::ValidateImportedInputID(<a class="code" href="namespacearmnn.html#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span>)</div> |
| <div class="line"><a name="l02611"></a><span class="lineno"> 2611</span> {</div> |
| <div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>  {</div> |
| <div class="line"><a name="l02614"></a><span class="lineno"> 2614</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& importedTensorHandlePin = m_PreImportedInputHandles.at(<span class="keywordtype">id</span>);</div> |
| <div class="line"><a name="l02615"></a><span class="lineno"> 2615</span>  <span class="keywordflow">if</span> (!importedTensorHandlePin.m_TensorHandle)</div> |
| <div class="line"><a name="l02616"></a><span class="lineno"> 2616</span>  {</div> |
| <div class="line"><a name="l02617"></a><span class="lineno"> 2617</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"LoadedNetwork::Execute:"</span></div> |
| <div class="line"><a name="l02618"></a><span class="lineno"> 2618</span>  <span class="stringliteral">"PreImportedInput: {} has been deleted"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l02619"></a><span class="lineno"> 2619</span>  }</div> |
| <div class="line"><a name="l02620"></a><span class="lineno"> 2620</span>  <span class="keywordflow">return</span> importedTensorHandlePin.m_LayerBindingId;</div> |
| <div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>  }</div> |
| <div class="line"><a name="l02622"></a><span class="lineno"> 2622</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::out_of_range&)</div> |
| <div class="line"><a name="l02623"></a><span class="lineno"> 2623</span>  {</div> |
| <div class="line"><a name="l02624"></a><span class="lineno"> 2624</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"LoadedNetwork::Execute: Unknown ImportedInputId: {}"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>  }</div> |
| <div class="line"><a name="l02626"></a><span class="lineno"> 2626</span> }</div> |
| <div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>  </div> |
| <div class="line"><a name="l02628"></a><span class="lineno"> 2628</span> <a class="code" href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> LoadedNetwork::ValidateImportedOutputID(<a class="code" href="namespacearmnn.html#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span>)</div> |
| <div class="line"><a name="l02629"></a><span class="lineno"> 2629</span> {</div> |
| <div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>  <span class="keywordflow">try</span></div> |
| <div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>  {</div> |
| <div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& importedTensorHandlePin = m_PreImportedOutputHandles.at(<span class="keywordtype">id</span>);</div> |
| <div class="line"><a name="l02633"></a><span class="lineno"> 2633</span>  <span class="keywordflow">if</span> (!importedTensorHandlePin.m_TensorHandle)</div> |
| <div class="line"><a name="l02634"></a><span class="lineno"> 2634</span>  {</div> |
| <div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div> |
| <div class="line"><a name="l02636"></a><span class="lineno"> 2636</span>  <span class="stringliteral">"PreImportedOutput: {} has been deleted"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l02637"></a><span class="lineno"> 2637</span>  }</div> |
| <div class="line"><a name="l02638"></a><span class="lineno"> 2638</span>  <span class="keywordflow">return</span> importedTensorHandlePin.m_LayerBindingId;</div> |
| <div class="line"><a name="l02639"></a><span class="lineno"> 2639</span>  }</div> |
| <div class="line"><a name="l02640"></a><span class="lineno"> 2640</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::out_of_range&)</div> |
| <div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>  {</div> |
| <div class="line"><a name="l02642"></a><span class="lineno"> 2642</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"LoadedNetwork::Execute: Unknown ImportedOutputId: {}"</span>, <span class="keywordtype">id</span>));</div> |
| <div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>  }</div> |
| <div class="line"><a name="l02644"></a><span class="lineno"> 2644</span> }</div> |
| <div class="line"><a name="l02645"></a><span class="lineno"> 2645</span>  </div> |
| <div class="line"><a name="l02646"></a><span class="lineno"> 2646</span> }</div> |
| </div><!-- fragment --></div><!-- contents --> |
| </div><!-- doc-content --> |
| <div class="ttc" id="aclassarmnn_1_1_bindable_layer_html"><div class="ttname"><a href="classarmnn_1_1_bindable_layer.html">armnn::BindableLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00470">Layer.hpp:470</a></div></div> |
| <div class="ttc" id="a_backend_helper_8hpp_html"><div class="ttname"><a href="_backend_helper_8hpp.html">BackendHelper.hpp</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a1c5ec805688cb558465a82a8d9f56a90"><div class="ttname"><a href="namespacearmnn.html#a1c5ec805688cb558465a82a8d9f56a90">armnn::ImportedInputId</a></div><div class="ttdeci">unsigned int ImportedInputId</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00310">Types.hpp:310</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_ac3b4675f7a50a0f242880fb044aa8dec"><div class="ttname"><a href="classarmnn_1_1_graph.html#ac3b4675f7a50a0f242880fb044aa8dec">armnn::Graph::SetLayersOutOfOrder</a></div><div class="ttdeci">void SetLayersOutOfOrder()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.html#l00738">Graph.cpp:738</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div><div class="ttdeci">@ Undefined</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_tensor_html"><div class="ttname"><a href="classarmnn_1_1_tensor.html">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00321">Tensor.hpp:321</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html_ad3ab02a7f6310b35c59ca78b509905ca"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html#ad3ab02a7f6310b35c59ca78b509905ca">armnn::INetworkProperties::m_AsyncEnabled</a></div><div class="ttdeci">const bool m_AsyncEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00059">IRuntime.hpp:59</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_base_tensor_html_aa81f67ac64f0c249e26499600c45d996"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#aa81f67ac64f0c249e26499600c45d996">armnn::BaseTensor::GetMemoryArea</a></div><div class="ttdeci">MemoryType GetMemoryArea() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00307">Tensor.hpp:307</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_graph_1_1_output_layers_accessor_html_a660efe3cd8761bd55b70ae83a7ea4334"><div class="ttname"><a href="structarmnn_1_1_graph_1_1_output_layers_accessor.html#a660efe3cd8761bd55b70ae83a7ea4334">armnn::Graph::OutputLayersAccessor::begin</a></div><div class="ttdeci">ConstIteratorOutputs begin() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00084">Graph.hpp:84</a></div></div> |
| <div class="ttc" id="anamespacearm_1_1pipe_html"><div class="ttname"><a href="namespacearm_1_1pipe.html">arm::pipe</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8hpp_source.html#l00017">BackendRegistry.hpp:17</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a2b6b57945bc68f659e08d28c8a015e91"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a2b6b57945bc68f659e08d28c8a015e91">armnn::LoadedNetwork::GetOutputTensorInfo</a></div><div class="ttdeci">TensorInfo GetOutputTensorInfo(LayerBindingId layerId) const</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00733">LoadedNetwork.cpp:733</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html_a53d95b257e52b0fd292ba6d40d3c5dc3"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html#a53d95b257e52b0fd292ba6d40d3c5dc3">armnn::INetworkProperties::m_InputSource</a></div><div class="ttdeci">const MemorySource m_InputSource</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00065">IRuntime.hpp:65</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_profiler_manager_html_a7b1e3e5bf386004541be2b5b22443208"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.html#a7b1e3e5bf386004541be2b5b22443208">armnn::ProfilerManager::RegisterProfiler</a></div><div class="ttdeci">void RegisterProfiler(IProfiler *profiler)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.html#l00609">Profiling.cpp:609</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_ab522849a917e9095c462e5e5980316be"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab522849a917e9095c462e5e5980316be">armnn::experimental::WorkingMemHandle::GetExecutionDataAt</a></div><div class="ttdeci">std::pair< BackendId, ExecutionData > & GetExecutionDataAt(unsigned int id) override</div><div class="ttdoc">Get the ExecutionData at an index.</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00092">WorkingMemHandle.hpp:92</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00100">Layer.cpp:100</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00394">Tensor.hpp:394</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a87880cba8611688cc57bec8f913958e8"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a87880cba8611688cc57bec8f913958e8">armnn::LoadedNetwork::EnqueueWorkload</a></div><div class="ttdeci">Status EnqueueWorkload(const InputTensors &inputTensors, const OutputTensors &outputTensors, std::vector< ImportedInputId > preImportedInputIds={}, std::vector< ImportedOutputId > preImportedOutputIds={})</div><div class="ttdoc">Single thread execution of the loaded network.</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00872">LoadedNetwork.cpp:872</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a091ea8d2d804c8902f3120fdf2a36512"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a091ea8d2d804c8902f3120fdf2a36512">armnn::LoadedNetwork::RegisterDebugCallback</a></div><div class="ttdeci">void RegisterDebugCallback(const DebugCallbackFunction &func)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l02296">LoadedNetwork.cpp:2296</a></div></div> |
| <div class="ttc" id="a_execution_data_8hpp_html"><div class="ttname"><a href="_execution_data_8hpp.html">ExecutionData.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_tensor_handle_factory_registry_html_a69ca23561f4f8a887f19c6580cbd34c8"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.html#a69ca23561f4f8a887f19c6580cbd34c8">armnn::TensorHandleFactoryRegistry::ReleaseMemory</a></div><div class="ttdeci">void ReleaseMemory()</div><div class="ttdoc">Release memory required for inference.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8cpp_source.html#l00086">TensorHandleFactoryRegistry.cpp:86</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a52928589effc0b9cbb170a93ea792d47"><div class="ttname"><a href="namespacearmnn.html#a52928589effc0b9cbb170a93ea792d47">armnn::ValidateSourcesMatchOptimizedNetwork</a></div><div class="ttdeci">void ValidateSourcesMatchOptimizedNetwork(std::vector< BackendOptions > optimizedOptions, const INetworkProperties &networkProperties)</div><div class="ttdoc">This function performs a sanity check to ensure that the combination of input and output memory sourc...</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00101">LoadedNetwork.cpp:101</a></div></div> |
| <div class="ttc" id="a_loaded_network_8hpp_html"><div class="ttname"><a href="_loaded_network_8hpp.html">LoadedNetwork.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_slot_html"><div class="ttname"><a href="classarmnn_1_1_output_slot.html">armnn::OutputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00100">Layer.hpp:100</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_tensor_handle_factory_registry_html_ae5ecc42140a12c855554a4a621fc8456"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.html#ae5ecc42140a12c855554a4a621fc8456">armnn::TensorHandleFactoryRegistry::GetFactory</a></div><div class="ttdeci">ITensorHandleFactory * GetFactory(ITensorHandleFactory::FactoryId id) const</div><div class="ttdoc">Find a TensorHandleFactory by Id Returns nullptr if not found.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8cpp_source.html#l00039">TensorHandleFactoryRegistry.cpp:39</a></div></div> |
| <div class="ttc" id="aclassarmnn_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#l00152">Tensor.hpp:152</a></div></div> |
| <div class="ttc" id="a_mem_sync_workload_8hpp_html"><div class="ttname"><a href="_mem_sync_workload_8hpp.html">MemSyncWorkload.hpp</a></div></div> |
| <div class="ttc" id="a_graph_8hpp_html"><div class="ttname"><a href="_graph_8hpp.html">Graph.hpp</a></div></div> |
| <div class="ttc" id="a_exceptions_8hpp_html_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00203">Exceptions.hpp:203</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a5b05f3b7208ec7cea3338e30057c0bac"><div class="ttname"><a href="namespacearmnn.html#a5b05f3b7208ec7cea3338e30057c0bac">armnn::MemorySourceFlags</a></div><div class="ttdeci">unsigned int MemorySourceFlags</div><div class="ttdef"><b>Definition:</b> <a href="_memory_sources_8hpp_source.html#l00015">MemorySources.hpp:15</a></div></div> |
| <div class="ttc" id="a_profiling_8hpp_html"><div class="ttname"><a href="_profiling_8hpp.html">Profiling.hpp</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html_a7e26a8e7f1878d82bef452ef3531eaeb"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html#a7e26a8e7f1878d82bef452ef3531eaeb">armnn::INetworkProperties::m_ProfilingEnabled</a></div><div class="ttdeci">const bool m_ProfilingEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00061">IRuntime.hpp:61</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html">armnn::LoadedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8hpp_source.html#l00042">LoadedNetwork.hpp:42</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html">armnn::ITensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_8hpp_source.html#l00016">ITensorHandle.hpp:16</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_backend_options_1_1_backend_option_html"><div class="ttname"><a href="structarmnn_1_1_backend_options_1_1_backend_option.html">armnn::BackendOptions::BackendOption</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.html#l00215">BackendOptions.hpp:215</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_a39754dbf5b5cb692d3ba97f23b23962f"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a39754dbf5b5cb692d3ba97f23b23962f">armnn::experimental::WorkingMemHandle::GetOutputConnection</a></div><div class="ttdeci">const std::vector< std::vector< ITensorHandle * >::iterator > & GetOutputConnection(LayerBindingId layerBindingId) const</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00112">WorkingMemHandle.hpp:112</a></div></div> |
| <div class="ttc" id="a_deprecated_8hpp_html_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.html#l00033">Deprecated.hpp:33</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_a1a573373f4505385578f830caebf6adb"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a1a573373f4505385578f830caebf6adb">armnn::experimental::WorkingMemHandle::IsAllocated</a></div><div class="ttdeci">bool IsAllocated() override</div><div class="ttdoc">IsAllocated returns true if the backing memory is currently allocated.</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00077">WorkingMemHandle.hpp:77</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a55cddc2dbb32d680cd85b635ba370e48"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a55cddc2dbb32d680cd85b635ba370e48">armnn::ITensorHandle::GetImportFlags</a></div><div class="ttdeci">virtual unsigned int GetImportFlags() const</div><div class="ttdoc">Get flags describing supported import sources.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_8hpp_source.html#l00070">ITensorHandle.hpp:70</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_ae41171032a9c106c1fd4b5991045eb0b"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#ae41171032a9c106c1fd4b5991045eb0b">armnn::LoadedNetwork::SendNetworkStructure</a></div><div class="ttdeci">void SendNetworkStructure(arm::pipe::IProfilingService &profilingService)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00672">LoadedNetwork.cpp:672</a></div></div> |
| <div class="ttc" id="a_backend_registry_8hpp_html"><div class="ttname"><a href="_backend_registry_8hpp.html">BackendRegistry.hpp</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_handle_1_1_output_mem_descriptor_coords_html"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_handle_1_1_output_mem_descriptor_coords.html">armnn::experimental::WorkingMemHandle::OutputMemDescriptorCoords</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00040">WorkingMemHandle.hpp:40</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00395">Tensor.hpp:395</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_af5f530544d09a44d726f24702b67b35b"><div class="ttname"><a href="classarmnn_1_1_layer.html#af5f530544d09a44d726f24702b67b35b">armnn::Layer::GetInputSlots</a></div><div class="ttdeci">const std::vector< InputSlot > & GetInputSlots() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00258">Layer.hpp:258</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_graph_1_1_input_layers_accessor_html_a39ebf520b6f30ab8776bdcb99ee38b93"><div class="ttname"><a href="structarmnn_1_1_graph_1_1_input_layers_accessor.html#a39ebf520b6f30ab8776bdcb99ee38b93">armnn::Graph::InputLayersAccessor::end</a></div><div class="ttdeci">ConstIteratorInputs end() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00070">Graph.hpp:70</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_i_working_mem_handle_html"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_i_working_mem_handle.html">armnn::experimental::IWorkingMemHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_working_mem_handle_8hpp_source.html#l00020">IWorkingMemHandle.hpp:20</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::BoostLogSeverityMapping::error</a></div><div class="ttdeci">@ error</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a48fe2df41d914c38c913160956acc706"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a48fe2df41d914c38c913160956acc706">armnn::LoadedNetwork::WorkloadQueue</a></div><div class="ttdeci">std::vector< std::unique_ptr< IWorkload > > WorkloadQueue</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8hpp_source.html#l00045">LoadedNetwork.hpp:45</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_registry_html_a8a7a14a6f1f1078e1b9d31c60d09e007"><div class="ttname"><a href="classarmnn_1_1_backend_registry.html#a8a7a14a6f1f1078e1b9d31c60d09e007">armnn::BackendRegistry::GetMemoryOptimizerStrategies</a></div><div class="ttdeci">MemoryOptimizerStrategiesMapRef GetMemoryOptimizerStrategies()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.html#l00150">BackendRegistry.cpp:150</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a704bd570f39deda992bccdc639640dc7"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a704bd570f39deda992bccdc639640dc7">armnn::LoadedNetwork::ImportInputs</a></div><div class="ttdeci">std::vector< ImportedInputId > ImportInputs(const InputTensors &inputTensors, MemorySource forceImportMemorySource=MemorySource::Undefined)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01486">LoadedNetwork.cpp:1486</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_handler_html_afe3429ac30b180c11f01ea0f9f546f0e"><div class="ttname"><a href="classarmnn_1_1_output_handler.html#afe3429ac30b180c11f01ea0f9f546f0e">armnn::OutputHandler::GetData</a></div><div class="ttdeci">ITensorHandle * GetData() const</div><div class="ttdoc">Gets the allocated tensor memory.</div><div class="ttdef"><b>Definition:</b> <a href="_output_handler_8hpp_source.html#l00046">OutputHandler.hpp:46</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00332">Layer.hpp:332</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_factory_html_a9c95f90eb40e31f629e0e2947b8bc6f9"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.html#a9c95f90eb40e31f629e0e2947b8bc6f9">armnn::ITensorHandleFactory::LegacyFactoryId</a></div><div class="ttdeci">static const FactoryId LegacyFactoryId</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_factory_8hpp_source.html#l00050">ITensorHandleFactory.hpp:50</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_exception_html_abf843cbb29dec939d0731e491bab6f70"><div class="ttname"><a href="classarmnn_1_1_exception.html#abf843cbb29dec939d0731e491bab6f70">armnn::Exception::what</a></div><div class="ttdeci">virtual const char * what() const noexcept override</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8cpp_source.html#l00032">Exceptions.cpp:32</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00230">Layer.hpp:230</a></div></div> |
| <div class="ttc" id="a_logging_8hpp_html_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.html#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.html#l00212">Logging.hpp:212</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_input_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::InputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdoc">Gets the TensorInfo for this InputSlot.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00614">Layer.cpp:614</a></div></div> |
| <div class="ttc" id="a_assert_8hpp_html"><div class="ttname"><a href="_assert_8hpp.html">Assert.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a82d949cbbc7667d9f13e3f2a474cad36"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a82d949cbbc7667d9f13e3f2a474cad36">armnn::ITensorHandle::DecorateTensorHandle</a></div><div class="ttdeci">virtual std::shared_ptr< ITensorHandle > DecorateTensorHandle(const TensorInfo &tensorInfo)</div><div class="ttdoc">Returns a decorated version of this TensorHandle allowing us to override the TensorInfo for it.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_8hpp_source.html#l00098">ITensorHandle.hpp:98</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a4f81a9eff30c9b9fe76f5b83af470ba7"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a4f81a9eff30c9b9fe76f5b83af470ba7">armnn::ITensorHandle::Import</a></div><div class="ttdeci">virtual bool Import(void *memory, MemorySource source)</div><div class="ttdoc">Import externally allocated memory.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_8hpp_source.html#l00076">ITensorHandle.hpp:76</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_abdfaf46d2e4cd003c0f13cdb1f1e6a20"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#abdfaf46d2e4cd003c0f13cdb1f1e6a20">armnn::experimental::WorkingMemHandle::GetBindingIdVector</a></div><div class="ttdeci">std::vector< LayerBindingId > & GetBindingIdVector()</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00119">WorkingMemHandle.hpp:119</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html_abbc76b61436b870aed2c8592690e9a70"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html#abbc76b61436b870aed2c8592690e9a70">armnn::INetworkProperties::m_OutputNetworkDetailsMethod</a></div><div class="ttdeci">const ProfilingDetailsMethod m_OutputNetworkDetailsMethod</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00063">IRuntime.hpp:63</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a0d8160388a127c1a23b37bc88dc6e2ec"><div class="ttname"><a href="namespacearmnn.html#a0d8160388a127c1a23b37bc88dc6e2ec">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00035">IRuntime.hpp:35</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a37a1a6b381ccc76df203fee023234996"><div class="ttname"><a href="namespacearmnn.html#a37a1a6b381ccc76df203fee023234996">armnn::OutputQueueDescriptor</a></div><div class="ttdeci">MemCopyQueueDescriptor OutputQueueDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00092">WorkloadData.hpp:92</a></div></div> |
| <div class="ttc" id="a_logging_8hpp_html"><div class="ttname"><a href="_logging_8hpp.html">Logging.hpp</a></div></div> |
| <div class="ttc" id="a_profiling_8hpp_html_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.html#l00220">Profiling.hpp:220</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277aec0fc0100c4fc1ce4eea230c3dc10360">armnn::MemorySource::Undefined</a></div><div class="ttdeci">@ Undefined</div></div> |
| <div class="ttc" id="astructarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer.</div><div class="ttdef"><b>Definition:</b> <a href="_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_ab0ba2e3d5e666b99e28a485d117ddfc3"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab0ba2e3d5e666b99e28a485d117ddfc3">armnn::experimental::WorkingMemHandle::GetInputHandle</a></div><div class="ttdeci">ITensorHandle * GetInputHandle(LayerBindingId layerBindingId) const</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00097">WorkingMemHandle.hpp:97</a></div></div> |
| <div class="ttc" id="a_i_backend_internal_8hpp_html"><div class="ttname"><a href="_i_backend_internal_8hpp.html">IBackendInternal.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_ac88d932e6e015a59551322b25796b11a"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#ac88d932e6e015a59551322b25796b11a">armnn::LoadedNetwork::ImportOutputs</a></div><div class="ttdeci">std::vector< ImportedOutputId > ImportOutputs(const OutputTensors &outputTensors, MemorySource forceImportMemorySource=MemorySource::Undefined)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01632">LoadedNetwork.cpp:1632</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry & BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.html#l00015">BackendRegistry.cpp:15</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_ae65834ecb69e3bc6a41ca1a57e4b63ab"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ae65834ecb69e3bc6a41ca1a57e4b63ab">armnn::experimental::WorkingMemHandle::GetInputConnections</a></div><div class="ttdeci">const std::vector< std::vector< ITensorHandle * >::iterator > & GetInputConnections(LayerBindingId layerBindingId) const</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00107">WorkingMemHandle.hpp:107</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_aa311c7fe7e05406c9ff4e4ed3ba09825"><div class="ttname"><a href="classarmnn_1_1_graph.html#aa311c7fe7e05406c9ff4e4ed3ba09825">armnn::Graph::GetOutputLayers</a></div><div class="ttdeci">OutputLayersAccessor GetOutputLayers() const</div><div class="ttdoc">Returns a wrapper object with begin(), end() methods to iterate over the output layers in a range-bas...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00203">Graph.hpp:203</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_workload_factory_html"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.html#l00022">WorkloadFactory.hpp:22</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.html#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs).</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00309">Types.hpp:309</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_id_html_af7445617163d3f07c47b92ae56c6cf8b"><div class="ttname"><a href="classarmnn_1_1_backend_id.html#af7445617163d3f07c47b92ae56c6cf8b">armnn::BackendId::Get</a></div><div class="ttdeci">const std::string & Get() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00138">BackendId.hpp:138</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_a8dc12f0ee5b232d397bd18ced1a72a64"><div class="ttname"><a href="classarmnn_1_1_layer.html#a8dc12f0ee5b232d397bd18ced1a72a64">armnn::Layer::GetGuid</a></div><div class="ttdeci">LayerGuid GetGuid() const final</div><div class="ttdoc">Returns the unique id of the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00343">Layer.hpp:343</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_af2c0edc7ea62a8baaec4d3d9b2b09256"><div class="ttname"><a href="classarmnn_1_1_layer.html#af2c0edc7ea62a8baaec4d3d9b2b09256">armnn::Layer::GetOutputHandler</a></div><div class="ttdeci">const OutputHandler & GetOutputHandler(unsigned int i=0) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00245">Layer.hpp:245</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a5acae80f1d8fd03cdb3878bd356683d7"><div class="ttname"><a href="namespacearmnn.html#a5acae80f1d8fd03cdb3878bd356683d7">armnn::CopyToOutputTensor</a></div><div class="ttdeci">void CopyToOutputTensor(const Tensor &outputTensor, ITensorHandle *outputTensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01444">LoadedNetwork.cpp:1444</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_a1594bddc87d6477df300317658f566bb"><div class="ttname"><a href="classarmnn_1_1_layer.html#a1594bddc87d6477df300317658f566bb">armnn::Layer::GetNumOutputSlots</a></div><div class="ttdeci">unsigned int GetNumOutputSlots() const override</div><div class="ttdoc">Returns the number of connectable output slots.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00335">Layer.hpp:335</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_aa815fde54f6d8e8aa5b4f0301cf4178b"><div class="ttname"><a href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.html#l00033">RefWorkloadUtils.hpp:33</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_afdf8eb85585a798ad0e936bde884d87b"><div class="ttname"><a href="classarmnn_1_1_graph.html#afdf8eb85585a798ad0e936bde884d87b">armnn::Graph::GetNumLayers</a></div><div class="ttdeci">size_t GetNumLayers() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00205">Graph.hpp:205</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_factory_html"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.html">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_factory_8hpp_source.html#l00046">ITensorHandleFactory.hpp:46</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_tensor_handle_factory_registry_html_aeef3a1178e2dfe2ca2461d89cd47fff6"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.html#aeef3a1178e2dfe2ca2461d89cd47fff6">armnn::TensorHandleFactoryRegistry::GetMatchingImportFactoryId</a></div><div class="ttdeci">ITensorHandleFactory::FactoryId GetMatchingImportFactoryId(ITensorHandleFactory::FactoryId copyFactoryId)</div><div class="ttdoc">Get a matching TensorHandleFatory Id for Memory Import given TensorHandleFactory Id for Memory Copy.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8cpp_source.html#l00072">TensorHandleFactoryRegistry.cpp:72</a></div></div> |
| <div class="ttc" id="a_heap_profiling_8hpp_html_aeeb927880fc4ffc2eea754a67d884a53"><div class="ttname"><a href="_heap_profiling_8hpp.html#aeeb927880fc4ffc2eea754a67d884a53">ARMNN_SCOPED_HEAP_PROFILING</a></div><div class="ttdeci">#define ARMNN_SCOPED_HEAP_PROFILING(TAG)</div><div class="ttdef"><b>Definition:</b> <a href="_heap_profiling_8hpp_source.html#l00045">HeapProfiling.hpp:45</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_ac624e40d8096e61c73b246934f18afd0"><div class="ttname"><a href="namespacearmnn.html#ac624e40d8096e61c73b246934f18afd0">armnn::GetOutputTensor</a></div><div class="ttdeci">const armnn::Tensor GetOutputTensor(const LayerBindingId layerId, const OutputTensors &outputTensors)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01473">LoadedNetwork.cpp:1473</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a84f86b4de5adf0b164e811c87051a0ee"><div class="ttname"><a href="namespacearmnn.html#a84f86b4de5adf0b164e811c87051a0ee">armnn::CheckFlag</a></div><div class="ttdeci">bool CheckFlag(MemorySourceFlags flags, MemorySource source)</div><div class="ttdef"><b>Definition:</b> <a href="_memory_sources_8hpp_source.html#l00041">MemorySources.hpp:41</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a></div><div class="ttdeci">@ Success</div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html">armnn::INetworkProperties</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00043">IRuntime.hpp:43</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_a98cdff4e0b45f4c80bfcedaf926e16e0"><div class="ttname"><a href="classarmnn_1_1_layer.html#a98cdff4e0b45f4c80bfcedaf926e16e0">armnn::Layer::GetOutputSlots</a></div><div class="ttdeci">const std::vector< OutputSlot > & GetOutputSlots() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00259">Layer.hpp:259</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_a8d8179a4a0703602a5d7dbb6e92eaf69"><div class="ttname"><a href="classarmnn_1_1_graph.html#a8d8179a4a0703602a5d7dbb6e92eaf69">armnn::Graph::GetNumInputs</a></div><div class="ttdeci">size_t GetNumInputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00194">Graph.hpp:194</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_a7487c3835e842582920969f2663bcc30"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a7487c3835e842582920969f2663bcc30">armnn::experimental::WorkingMemHandle::MemSyncOutputs</a></div><div class="ttdeci">void MemSyncOutputs()</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8cpp_source.html#l00136">WorkingMemHandle.cpp:136</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_exception_html"><div class="ttname"><a href="classarmnn_1_1_exception.html">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those.</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00046">Exceptions.hpp:46</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a563609828050f1b3a7868c23f3365923"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a563609828050f1b3a7868c23f3365923">armnn::ITensorHandle::Unmap</a></div><div class="ttdeci">virtual void Unmap() const =0</div><div class="ttdoc">Unmap the tensor data.</div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html">armnn::experimental::WorkingMemHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00029">WorkingMemHandle.hpp:29</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_runtime_exception_html"><div class="ttname"><a href="classarmnn_1_1_runtime_exception.html">armnn::RuntimeException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00120">Exceptions.hpp:120</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_handle_1_1_input_mem_descriptor_coords_html"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_handle_1_1_input_mem_descriptor_coords.html">armnn::experimental::WorkingMemHandle::InputMemDescriptorCoords</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00033">WorkingMemHandle.hpp:33</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_ad90f4f6c9360c5cb64c164b9ddcb3130"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#ad90f4f6c9360c5cb64c164b9ddcb3130">armnn::LoadedNetwork::GetNetworkGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetNetworkGuid()</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00710">LoadedNetwork.cpp:710</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_base_tensor_html_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo & GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00297">Tensor.hpp:297</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_handler_html"><div class="ttname"><a href="classarmnn_1_1_output_handler.html">armnn::OutputHandler</a></div><div class="ttdef"><b>Definition:</b> <a href="_output_handler_8hpp_source.html#l00028">OutputHandler.hpp:28</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_af616683424cb40d83b5a923db7f06f11"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#af616683424cb40d83b5a923db7f06f11">armnn::LoadedNetwork::GetInputTensorInfo</a></div><div class="ttdeci">TensorInfo GetInputTensorInfo(LayerBindingId layerId) const</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00715">LoadedNetwork.cpp:715</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">armnn::LayerType::MemImport</a></div><div class="ttdeci">@ MemImport</div></div> |
| <div class="ttc" id="anamespacearmnn_html_a92c91193007aa49f4732d6dba5397f8d"><div class="ttname"><a href="namespacearmnn.html#a92c91193007aa49f4732d6dba5397f8d">armnn::CopyTensorContentsGeneric</a></div><div class="ttdeci">void CopyTensorContentsGeneric(const ITensorHandle *srcTensor, ITensorHandle *dstTensor, CopyFunc copy)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8hpp_source.html#l00046">WorkloadUtils.hpp:46</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_a9a97cb6d32661a57fc33bd29b8e41ff4"><div class="ttname"><a href="classarmnn_1_1_layer.html#a9a97cb6d32661a57fc33bd29b8e41ff4">armnn::Layer::GetNameStr</a></div><div class="ttdeci">const std::string & GetNameStr() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00240">Layer.hpp:240</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a2231ac018fe2c465f2d42fef597d67e7"><div class="ttname"><a href="namespacearmnn.html#a2231ac018fe2c465f2d42fef597d67e7">armnn::InputQueueDescriptor</a></div><div class="ttdeci">MemCopyQueueDescriptor InputQueueDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00091">WorkloadData.hpp:91</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_tensor_handle_factory_registry_html_a46d1634d1bfbf6920adc98569ba10a94"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.html#a46d1634d1bfbf6920adc98569ba10a94">armnn::TensorHandleFactoryRegistry::AquireMemory</a></div><div class="ttdeci">void AquireMemory()</div><div class="ttdoc">Aquire memory required for inference.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8cpp_source.html#l00078">TensorHandleFactoryRegistry.cpp:78</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_input_slot_html"><div class="ttname"><a href="classarmnn_1_1_input_slot.html">armnn::InputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00042">Layer.hpp:42</a></div></div> |
| <div class="ttc" id="a_arm_n_n_profiling_8hpp_html"><div class="ttname"><a href="_arm_n_n_profiling_8hpp.html">ArmNNProfiling.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_registry_html_afc0c63ca8db8957b58826f6d7bd231b2"><div class="ttname"><a href="classarmnn_1_1_backend_registry.html#afc0c63ca8db8957b58826f6d7bd231b2">armnn::BackendRegistry::GetFactory</a></div><div class="ttdeci">FactoryFunction GetFactory(const BackendId &id) const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.html#l00057">BackendRegistry.cpp:57</a></div></div> |
| <div class="ttc" id="a_heap_profiling_8hpp_html"><div class="ttname"><a href="_heap_profiling_8hpp.html">HeapProfiling.hpp</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_ac68a434f0e78e33726bfb22a39ec813f"><div class="ttname"><a href="namespacearmnn.html#ac68a434f0e78e33726bfb22a39ec813f">armnn::ImportedOutputId</a></div><div class="ttdeci">unsigned int ImportedOutputId</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00311">Types.hpp:311</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_backend_options_html"><div class="ttname"><a href="structarmnn_1_1_backend_options.html">armnn::BackendOptions</a></div><div class="ttdoc">Struct for the users to pass backend specific options.</div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.html#l00022">BackendOptions.hpp:22</a></div></div> |
| <div class="ttc" id="a_working_mem_handle_8hpp_html"><div class="ttname"><a href="_working_mem_handle_8hpp.html">WorkingMemHandle.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00286">Layer.hpp:286</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_a919fb58873ef3a6549e4490e226f2eae"><div class="ttname"><a href="classarmnn_1_1_graph.html#a919fb58873ef3a6549e4490e226f2eae">armnn::Graph::GetInputLayers</a></div><div class="ttdeci">InputLayersAccessor GetInputLayers() const</div><div class="ttdoc">Returns a wrapper object with begin(), end() methods to iterate over the input layers in a range-base...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00199">Graph.hpp:199</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_graph_1_1_input_layers_accessor_html_af6f3e2b0ee65cd102e20c9f734160b90"><div class="ttname"><a href="structarmnn_1_1_graph_1_1_input_layers_accessor.html#af6f3e2b0ee65cd102e20c9f734160b90">armnn::Graph::InputLayersAccessor::begin</a></div><div class="ttdeci">ConstIteratorInputs begin() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00065">Graph.hpp:65</a></div></div> |
| <div class="ttc" id="a_tensor_handle_8hpp_html"><div class="ttname"><a href="_tensor_handle_8hpp.html">TensorHandle.hpp</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00042">Types.hpp:42</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_factory_html_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.html#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_af75dd30cff3d42ff35ddd2b625b7e9ae"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#af75dd30cff3d42ff35ddd2b625b7e9ae">armnn::LoadedNetwork::MakeLoadedNetwork</a></div><div class="ttdeci">static std::unique_ptr< LoadedNetwork > MakeLoadedNetwork(std::unique_ptr< IOptimizedNetwork > net, std::string &errorMessage, const INetworkProperties &networkProperties, arm::pipe::IProfilingService *profilingService)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l00173">LoadedNetwork.cpp:173</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a16e72675c37a8f251cf02951e222d4ab"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a16e72675c37a8f251cf02951e222d4ab">armnn::LoadedNetwork::CreateWorkingMemHandle</a></div><div class="ttdeci">std::unique_ptr< IWorkingMemHandle > CreateWorkingMemHandle(NetworkId networkId)</div><div class="ttdoc">Create a new unique WorkingMemHandle object.</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l02025">LoadedNetwork.cpp:2025</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_profiler_manager_html_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.html#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.html#l00602">Profiling.cpp:602</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_ad5e03a241b63b19580f8fdd08c3647b7"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ad5e03a241b63b19580f8fdd08c3647b7">armnn::experimental::WorkingMemHandle::GetOutputHandle</a></div><div class="ttdeci">ITensorHandle * GetOutputHandle(LayerBindingId layerBindingId) const</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8hpp_source.html#l00102">WorkingMemHandle.hpp:102</a></div></div> |
| <div class="ttc" id="a_deprecated_8hpp_html_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.html#l00034">Deprecated.hpp:34</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_memory_import_exception_html"><div class="ttname"><a href="classarmnn_1_1_memory_import_exception.html">armnn::MemoryImportException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00125">Exceptions.hpp:125</a></div></div> |
| <div class="ttc" id="anamespacestd_html"><div class="ttname"><a href="namespacestd.html">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00149">BackendId.hpp:149</a></div></div> |
| <div class="ttc" id="a_mem_copy_workload_8hpp_html"><div class="ttname"><a href="_mem_copy_workload_8hpp.html">MemCopyWorkload.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_capability_exception_html"><div class="ttname"><a href="classarmnn_1_1_backend_capability_exception.html">armnn::BackendCapabilityException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00152">Exceptions.hpp:152</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_af497e16cf92179b5e55543741351b8bf"><div class="ttname"><a href="classarmnn_1_1_graph.html#af497e16cf92179b5e55543741351b8bf">armnn::Graph::TopologicalSort</a></div><div class="ttdeci">Graph & TopologicalSort()</div><div class="ttdoc">Sorts layers in topological order and return this.</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00191">Graph.hpp:191</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_a95b1c23f6f296a0c39383bef20fdd46a"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#a95b1c23f6f296a0c39383bef20fdd46a">armnn::LoadedNetwork::Execute</a></div><div class="ttdeci">Status Execute(const InputTensors &inputTensors, const OutputTensors &outputTensors, IWorkingMemHandle &workingMemHandle, std::vector< ImportedInputId > preImportedInputs={}, std::vector< ImportedOutputId > preImportedOutputs={})</div><div class="ttdoc">Thread safe execution of the loaded network.</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01803">LoadedNetwork.cpp:1803</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.html#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.html#l00014">IgnoreUnused.hpp:14</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a15f3ad9b5e4e3d46b0a6dda246a7bc28"><div class="ttname"><a href="namespacearmnn.html#a15f3ad9b5e4e3d46b0a6dda246a7bc28">armnn::DebugCallbackFunction</a></div><div class="ttdeci">std::function< void(LayerGuid guid, unsigned int slotIndex, ITensorHandle *tensorHandle)> DebugCallbackFunction</div><div class="ttdoc">Define the type of callback for the Debug layer to call.</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00398">Types.hpp:398</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a14fcd7f88d11cea0a018269dca5f9277"><div class="ttname"><a href="namespacearmnn.html#a14fcd7f88d11cea0a018269dca5f9277">armnn::MemorySource</a></div><div class="ttdeci">MemorySource</div><div class="ttdoc">Define the Memory Source to reduce copies.</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00244">Types.hpp:244</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_registry_html_a6dea5df9078a3e9b44176175043237f6"><div class="ttname"><a href="classarmnn_1_1_backend_registry.html#a6dea5df9078a3e9b44176175043237f6">armnn::BackendRegistry::GetAllocators</a></div><div class="ttdeci">std::unordered_map< BackendId, std::shared_ptr< ICustomAllocator > > GetAllocators()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.html#l00128">BackendRegistry.cpp:128</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_layer_html_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.html#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00290">Layer.hpp:290</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_backend_id_html"><div class="ttname"><a href="classarmnn_1_1_backend_id.html">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00075">BackendId.hpp:75</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_af06f742ce80985a8fbbbc028c20259b1"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#af06f742ce80985a8fbbbc028c20259b1">armnn::LoadedNetwork::ClearImportedOutputs</a></div><div class="ttdeci">void ClearImportedOutputs(const std::vector< ImportedOutputId > outputIds)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01782">LoadedNetwork.cpp:1782</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_ab35a0f45d4b1bdad5c8e6614c7bf8d18"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#ab35a0f45d4b1bdad5c8e6614c7bf8d18">armnn::experimental::WorkingMemHandle::ValidateBindingIds</a></div><div class="ttdeci">void ValidateBindingIds()</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8cpp_source.html#l00145">WorkingMemHandle.cpp:145</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_slot_html_af303cf872a3f95e29992e45224e4cf8e"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#af303cf872a3f95e29992e45224e4cf8e">armnn::OutputSlot::GetTensorHandleFactoryId</a></div><div class="ttdeci">ITensorHandleFactory::FactoryId GetTensorHandleFactoryId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00218">Layer.cpp:218</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_graph_1_1_output_layers_accessor_html_ad2a661f37e89422e29dc70b3e4cc7185"><div class="ttname"><a href="structarmnn_1_1_graph_1_1_output_layers_accessor.html#ad2a661f37e89422e29dc70b3e4cc7185">armnn::Graph::OutputLayersAccessor::end</a></div><div class="ttdeci">ConstIteratorOutputs end() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00090">Graph.hpp:90</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_input_slot_html_a9effd325a6d512a3f8ff4bd207d53255"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">armnn::InputSlot::GetConnectedOutputSlot</a></div><div class="ttdeci">const OutputSlot * GetConnectedOutputSlot() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00056">Layer.hpp:56</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">armnn::experimental::WorkingMemDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00020">WorkingMemDescriptor.hpp:20</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html">armnn::experimental::WorkingMemDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00018">WorkingMemDescriptor.hpp:18</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_validation_exception_html"><div class="ttname"><a href="classarmnn_1_1_graph_validation_exception.html">armnn::GraphValidationException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00110">Exceptions.hpp:110</a></div></div> |
| <div class="ttc" id="a_layer_8hpp_html"><div class="ttname"><a href="_layer_8hpp.html">Layer.hpp</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_aaf8558a23ae9be6e7ea165989f1fa808"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#aaf8558a23ae9be6e7ea165989f1fa808">armnn::LoadedNetwork::FreeWorkingMemory</a></div><div class="ttdeci">void FreeWorkingMemory()</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01286">LoadedNetwork.cpp:1286</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_mem_sync_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_mem_sync_queue_descriptor.html">armnn::MemSyncQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00099">WorkloadData.hpp:99</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_factory_html_a32f4aa6a7089d877af08928139c2c277"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.html#a32f4aa6a7089d877af08928139c2c277">armnn::ITensorHandleFactory::FactoryId</a></div><div class="ttdeci">std::string FactoryId</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_handle_factory_8hpp_source.html#l00049">ITensorHandleFactory.hpp:49</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">armnn::BoostLogSeverityMapping::warning</a></div><div class="ttdeci">@ warning</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00329">Tensor.hpp:329</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div><div class="ttdeci">@ Input</div></div> |
| <div class="ttc" id="aclassarmnn_1_1experimental_1_1_working_mem_handle_html_a8518772c5d692e334a76617582b10b92"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_working_mem_handle.html#a8518772c5d692e334a76617582b10b92">armnn::experimental::WorkingMemHandle::Allocate</a></div><div class="ttdeci">void Allocate() override</div><div class="ttdoc">Allocate the backing memory required for execution.</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_handle_8cpp_source.html#l00100">WorkingMemHandle.cpp:100</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_output_handler_html_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_output_handler.html#a66e8f43a5b42b500871ed96e15419567">armnn::OutputHandler::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdoc">Gets the matching TensorInfo for the output.</div><div class="ttdef"><b>Definition:</b> <a href="_output_handler_8hpp_source.html#l00042">OutputHandler.hpp:42</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_loaded_network_html_aa792fd8b43401e3d6665110cdb0af27b"><div class="ttname"><a href="classarmnn_1_1_loaded_network.html#aa792fd8b43401e3d6665110cdb0af27b">armnn::LoadedNetwork::ClearImportedInputs</a></div><div class="ttdeci">void ClearImportedInputs(const std::vector< ImportedInputId > inputIds)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01761">LoadedNetwork.cpp:1761</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_backend_internal_html_a72ca1cf423bda4b0a9ffb789627126de"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.html#a72ca1cf423bda4b0a9ffb789627126de">armnn::IBackendInternal::IWorkloadFactoryPtr</a></div><div class="ttdeci">std::unique_ptr< IWorkloadFactory > IWorkloadFactoryPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_backend_internal_8hpp_source.html#l00089">IBackendInternal.hpp:89</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html_a604654b453ec291a503d62a0beb849d3"><div class="ttname"><a href="classarmnn_1_1_graph.html#a604654b453ec291a503d62a0beb849d3">armnn::Graph::GetNumOutputs</a></div><div class="ttdeci">size_t GetNumOutputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00195">Graph.hpp:195</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_null_pointer_exception_html"><div class="ttname"><a href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00146">Exceptions.hpp:146</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdoc">When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00491">Types.hpp:491</a></div></div> |
| <div class="ttc" id="aclassarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00030">Graph.hpp:30</a></div></div> |
| <div class="ttc" id="a_i_memory_manager_8hpp_html"><div class="ttname"><a href="_i_memory_manager_8hpp.html">IMemoryManager.hpp</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_i_network_properties_html_a3266436db920d1ca96b0afaadacf3972"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.html#a3266436db920d1ca96b0afaadacf3972">armnn::INetworkProperties::m_OutputSource</a></div><div class="ttdeci">const MemorySource m_OutputSource</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00066">IRuntime.hpp:66</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086"><div class="ttname"><a href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Status::Failure</a></div><div class="ttdeci">@ Failure</div></div> |
| <div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::experimental::WorkingMemDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00021">WorkingMemDescriptor.hpp:21</a></div></div> |
| <div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#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.html#l00026">WorkloadData.hpp:26</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div><div class="ttdeci">@ Output</div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a></div><div class="ttdeci">@ Constant</div></div> |
| <div class="ttc" id="aclassarmnn_1_1_i_tensor_handle_html_a9afbc055a017adf1bc38ee137bca6e90"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.html#a9afbc055a017adf1bc38ee137bca6e90">armnn::ITensorHandle::Map</a></div><div class="ttdeci">virtual const void * Map(bool blocking=true) const =0</div><div class="ttdoc">Map the tensor data for access.</div></div> |
| <div class="ttc" id="anamespacearmnn_html_a9ef4b4b6c421b5fd4b62274e63d08f11"><div class="ttname"><a href="namespacearmnn.html#a9ef4b4b6c421b5fd4b62274e63d08f11">armnn::GetInputTensor</a></div><div class="ttdeci">const armnn::ConstTensor GetInputTensor(const LayerBindingId layerId, const InputTensors &inputTensors)</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.html#l01460">LoadedNetwork.cpp:1460</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a406399d2a16ead98e4e93cdd57adead4"><div class="ttname"><a href="namespacearmnn.html#a406399d2a16ead98e4e93cdd57adead4">armnn::HasMatchingCapability</a></div><div class="ttdeci">bool HasMatchingCapability(const BackendOptions::BackendOption &capability, const BackendCapabilities &capabilities)</div><div class="ttdoc">Convenience function to check if a given capability matches a capability in a BackendCapabilities str...</div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8cpp_source.html#l00085">BackendHelper.cpp:85</a></div></div> |
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