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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
| commit | d5d43d82c0137e08553e44345c609cdd1a7931c7 (patch) | |
| tree | f1509f7fa94db0373a2c127682dd3d0ccc1915bd /22.05.01/classarmnn_1_1_loaded_network.xhtml | |
| parent | 549b9600a6eaf0727fa084465a75f173edf8f381 (diff) | |
| download | armnn-d5d43d82c0137e08553e44345c609cdd1a7931c7.tar.gz | |
Update Doxygen for 22.05 patch release
* Pooling3D added to tfLite delegate
* Available in tag 22.05.01
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I8d605bba4e87d30baa2c6d7b338c78a4400dc021
Diffstat (limited to '22.05.01/classarmnn_1_1_loaded_network.xhtml')
| -rw-r--r-- | 22.05.01/classarmnn_1_1_loaded_network.xhtml | 781 |
1 files changed, 781 insertions, 0 deletions
diff --git a/22.05.01/classarmnn_1_1_loaded_network.xhtml b/22.05.01/classarmnn_1_1_loaded_network.xhtml new file mode 100644 index 0000000000..f59d8c2541 --- /dev/null +++ b/22.05.01/classarmnn_1_1_loaded_network.xhtml @@ -0,0 +1,781 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: LoadedNetwork Class Reference</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" 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+<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.05.01</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('classarmnn_1_1_loaded_network.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="summary"> +<a href="#nested-classes">Classes</a> | +<a href="#pub-types">Public Types</a> | +<a href="#pub-methods">Public Member Functions</a> | +<a href="#pub-static-methods">Static Public Member Functions</a> | +<a href="classarmnn_1_1_loaded_network-members.xhtml">List of all members</a> </div> + <div class="headertitle"> +<div class="title">LoadedNetwork Class Reference</div> </div> +</div><!--header--> +<div class="contents"> + +<p><code>#include <<a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>></code></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a> +Public Types</h2></td></tr> +<tr class="memitem:a48fe2df41d914c38c913160956acc706"><td class="memItemLeft" align="right" valign="top">using </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a48fe2df41d914c38c913160956acc706">WorkloadQueue</a> = std::vector< std::unique_ptr< <a class="el" href="classarmnn_1_1_i_workload.xhtml">IWorkload</a> > ></td></tr> +<tr class="separator:a48fe2df41d914c38c913160956acc706"><td class="memSeparator" colspan="2"> </td></tr> +</table><table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> +Public Member Functions</h2></td></tr> +<tr class="memitem:a1bf130efa381d53486c78ea417ea4db1"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a1bf130efa381d53486c78ea417ea4db1">~LoadedNetwork</a> ()</td></tr> +<tr class="separator:a1bf130efa381d53486c78ea417ea4db1"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a16e72675c37a8f251cf02951e222d4ab"><td class="memItemLeft" align="right" valign="top">std::unique_ptr< <a class="el" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a16e72675c37a8f251cf02951e222d4ab">CreateWorkingMemHandle</a> (<a class="el" href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">NetworkId</a> networkId)</td></tr> +<tr class="memdesc:a16e72675c37a8f251cf02951e222d4ab"><td class="mdescLeft"> </td><td class="mdescRight">Create a new unique WorkingMemHandle object. <a href="#a16e72675c37a8f251cf02951e222d4ab">More...</a><br /></td></tr> +<tr class="separator:a16e72675c37a8f251cf02951e222d4ab"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af616683424cb40d83b5a923db7f06f11"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#af616683424cb40d83b5a923db7f06f11">GetInputTensorInfo</a> (<a class="el" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId) const</td></tr> +<tr class="separator:af616683424cb40d83b5a923db7f06f11"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a2b6b57945bc68f659e08d28c8a015e91"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a2b6b57945bc68f659e08d28c8a015e91">GetOutputTensorInfo</a> (<a class="el" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId) const</td></tr> +<tr class="separator:a2b6b57945bc68f659e08d28c8a015e91"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a704bd570f39deda992bccdc639640dc7"><td class="memItemLeft" align="right" valign="top">std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a704bd570f39deda992bccdc639640dc7">ImportInputs</a> (const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> &inputTensors, <a class="el" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> forceImportMemorySource=<a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</td></tr> +<tr class="separator:a704bd570f39deda992bccdc639640dc7"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ac88d932e6e015a59551322b25796b11a"><td class="memItemLeft" align="right" valign="top">std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#ac88d932e6e015a59551322b25796b11a">ImportOutputs</a> (const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> &outputTensors, <a class="el" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> forceImportMemorySource=<a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</td></tr> +<tr class="separator:ac88d932e6e015a59551322b25796b11a"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa792fd8b43401e3d6665110cdb0af27b"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#aa792fd8b43401e3d6665110cdb0af27b">ClearImportedInputs</a> (const std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > inputIds)</td></tr> +<tr class="separator:aa792fd8b43401e3d6665110cdb0af27b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af06f742ce80985a8fbbbc028c20259b1"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#af06f742ce80985a8fbbbc028c20259b1">ClearImportedOutputs</a> (const std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > outputIds)</td></tr> +<tr class="separator:af06f742ce80985a8fbbbc028c20259b1"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a87880cba8611688cc57bec8f913958e8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a87880cba8611688cc57bec8f913958e8">EnqueueWorkload</a> (const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> &inputTensors, const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> &outputTensors, std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > preImportedInputIds={}, std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > preImportedOutputIds={})</td></tr> +<tr class="memdesc:a87880cba8611688cc57bec8f913958e8"><td class="mdescLeft"> </td><td class="mdescRight">Single thread execution of the loaded network. <a href="#a87880cba8611688cc57bec8f913958e8">More...</a><br /></td></tr> +<tr class="separator:a87880cba8611688cc57bec8f913958e8"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a95b1c23f6f296a0c39383bef20fdd46a"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a95b1c23f6f296a0c39383bef20fdd46a">Execute</a> (const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> &inputTensors, const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> &outputTensors, <a class="el" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a> &workingMemHandle, std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > preImportedInputs={}, std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > preImportedOutputs={})</td></tr> +<tr class="memdesc:a95b1c23f6f296a0c39383bef20fdd46a"><td class="mdescLeft"> </td><td class="mdescRight">Thread safe execution of the loaded network. <a href="#a95b1c23f6f296a0c39383bef20fdd46a">More...</a><br /></td></tr> +<tr class="separator:a95b1c23f6f296a0c39383bef20fdd46a"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aee8e1cb09e0d4dcbe64df111c5edd55e"><td class="memItemLeft" align="right" valign="top">const std::shared_ptr< <a class="el" href="classarmnn_1_1_i_profiler.xhtml">IProfiler</a> > & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#aee8e1cb09e0d4dcbe64df111c5edd55e">GetProfiler</a> () const</td></tr> +<tr class="separator:aee8e1cb09e0d4dcbe64df111c5edd55e"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aaf8558a23ae9be6e7ea165989f1fa808"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#aaf8558a23ae9be6e7ea165989f1fa808">FreeWorkingMemory</a> ()</td></tr> +<tr class="separator:aaf8558a23ae9be6e7ea165989f1fa808"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a091ea8d2d804c8902f3120fdf2a36512"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a091ea8d2d804c8902f3120fdf2a36512">RegisterDebugCallback</a> (const <a class="el" href="namespacearmnn.xhtml#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a> &func)</td></tr> +<tr class="separator:a091ea8d2d804c8902f3120fdf2a36512"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ae41171032a9c106c1fd4b5991045eb0b"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#ae41171032a9c106c1fd4b5991045eb0b">SendNetworkStructure</a> (arm::pipe::IProfilingService &profilingService)</td></tr> +<tr class="separator:ae41171032a9c106c1fd4b5991045eb0b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a390c87e27deac4f51af9533053b2ee14"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#a390c87e27deac4f51af9533053b2ee14">IsAsyncEnabled</a> ()</td></tr> +<tr class="separator:a390c87e27deac4f51af9533053b2ee14"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ad90f4f6c9360c5cb64c164b9ddcb3130"><td class="memItemLeft" align="right" valign="top">arm::pipe::ProfilingGuid </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#ad90f4f6c9360c5cb64c164b9ddcb3130">GetNetworkGuid</a> ()</td></tr> +<tr class="separator:ad90f4f6c9360c5cb64c164b9ddcb3130"><td class="memSeparator" colspan="2"> </td></tr> +</table><table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> +Static Public Member Functions</h2></td></tr> +<tr class="memitem:af75dd30cff3d42ff35ddd2b625b7e9ae"><td class="memItemLeft" align="right" valign="top">static std::unique_ptr< <a class="el" href="classarmnn_1_1_loaded_network.xhtml">LoadedNetwork</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_loaded_network.xhtml#af75dd30cff3d42ff35ddd2b625b7e9ae">MakeLoadedNetwork</a> (std::unique_ptr< <a class="el" href="classarmnn_1_1_i_optimized_network.xhtml">IOptimizedNetwork</a> > net, std::string &errorMessage, const <a class="el" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> &networkProperties, arm::pipe::IProfilingService *profilingService)</td></tr> +<tr class="separator:af75dd30cff3d42ff35ddd2b625b7e9ae"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> +<div class="textblock"> +<p class="definition">Definition at line <a class="el" href="_loaded_network_8hpp_source.xhtml#l00042">42</a> of file <a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>.</p> +</div><h2 class="groupheader">Member Typedef Documentation</h2> +<a id="a48fe2df41d914c38c913160956acc706"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a48fe2df41d914c38c913160956acc706">◆ </a></span>WorkloadQueue</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">using <a class="el" href="classarmnn_1_1_loaded_network.xhtml#a48fe2df41d914c38c913160956acc706">WorkloadQueue</a> = std::vector<std::unique_ptr<<a class="el" href="classarmnn_1_1_i_workload.xhtml">IWorkload</a>> ></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8hpp_source.xhtml#l00045">45</a> of file <a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>.</p> + +</div> +</div> +<h2 class="groupheader">Constructor & Destructor Documentation</h2> +<a id="a1bf130efa381d53486c78ea417ea4db1"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a1bf130efa381d53486c78ea417ea4db1">◆ </a></span>~LoadedNetwork()</h2> + +<div class="memitem"> +<div class="memproto"> +<table class="mlabels"> + <tr> + <td class="mlabels-left"> + <table class="memname"> + <tr> + <td class="memname">~<a class="el" href="classarmnn_1_1_loaded_network.xhtml">LoadedNetwork</a> </td> + <td>(</td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> + </td> + <td class="mlabels-right"> +<span class="mlabels"><span class="mlabel">inline</span></span> </td> + </tr> +</table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8hpp_source.xhtml#l00047">47</a> of file <a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>.</p> +<div class="fragment"><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>  <a class="code" href="classarmnn_1_1_loaded_network.xhtml#aaf8558a23ae9be6e7ea165989f1fa808">FreeWorkingMemory</a>();</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  }</div><div class="ttc" id="classarmnn_1_1_loaded_network_xhtml_aaf8558a23ae9be6e7ea165989f1fa808"><div class="ttname"><a href="classarmnn_1_1_loaded_network.xhtml#aaf8558a23ae9be6e7ea165989f1fa808">armnn::LoadedNetwork::FreeWorkingMemory</a></div><div class="ttdeci">void FreeWorkingMemory()</div><div class="ttdef"><b>Definition:</b> <a href="_loaded_network_8cpp_source.xhtml#l01141">LoadedNetwork.cpp:1141</a></div></div> +</div><!-- fragment --> +</div> +</div> +<h2 class="groupheader">Member Function Documentation</h2> +<a id="aa792fd8b43401e3d6665110cdb0af27b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa792fd8b43401e3d6665110cdb0af27b">◆ </a></span>ClearImportedInputs()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void ClearImportedInputs </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > </td> + <td class="paramname"><em>inputIds</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01586">1586</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00621">RuntimeImpl::ClearImportedInputs()</a>.</p> +<div class="fragment"><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span> {</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> <span class="keywordtype">id</span> : inputIds)</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  {</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> > m_PreImportedInputHandles.size())</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>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"ClearImportedInputs::Unknown ImportedInputId: {}"</span>, <span class="keywordtype">id</span>));</div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  }</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="keyword">auto</span>& importedTensorHandle = m_PreImportedInputHandles[id].m_TensorHandle;</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  <span class="keywordflow">if</span> (!importedTensorHandle)</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>  <span class="keywordflow">throw</span> InvalidArgumentException(</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</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="l01600"></a><span class="lineno"> 1600</span>  }</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  <span class="comment">// Call Unimport then destroy the tensorHandle</span></div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  importedTensorHandle->Unimport();</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  importedTensorHandle = {};</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> }</div></div><!-- fragment --> +</div> +</div> +<a id="af06f742ce80985a8fbbbc028c20259b1"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af06f742ce80985a8fbbbc028c20259b1">◆ </a></span>ClearImportedOutputs()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void ClearImportedOutputs </td> + <td>(</td> + <td class="paramtype">const std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > </td> + <td class="paramname"><em>outputIds</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01607">1607</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00625">RuntimeImpl::ClearImportedOutputs()</a>.</p> +<div class="fragment"><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span> {</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> <span class="keywordtype">id</span> : outputIds)</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>  <span class="keywordflow">if</span> (<span class="keywordtype">id</span> > m_PreImportedOutputHandles.size())</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  {</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"ClearImportedOutputs::Unknown ImportedOutputId: {}"</span>, <span class="keywordtype">id</span>));</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> </div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>  <span class="keyword">auto</span>& importedTensorHandle = m_PreImportedOutputHandles[id].m_TensorHandle;</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  <span class="keywordflow">if</span> (!importedTensorHandle)</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  {</div><div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>  <span class="keywordflow">throw</span> InvalidArgumentException(</div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</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="l01621"></a><span class="lineno"> 1621</span>  }</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  <span class="comment">// Call Unimport then destroy the tensorHandle</span></div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  importedTensorHandle->Unimport();</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  importedTensorHandle = {};</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> }</div></div><!-- fragment --> +</div> +</div> +<a id="a16e72675c37a8f251cf02951e222d4ab"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a16e72675c37a8f251cf02951e222d4ab">◆ </a></span>CreateWorkingMemHandle()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">std::unique_ptr< <a class="el" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a> > CreateWorkingMemHandle </td> + <td>(</td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">NetworkId</a> </td> + <td class="paramname"><em>networkId</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p>Create a new unique WorkingMemHandle object. </p> +<p>Create multiple handles if you wish to have overlapped Execution by calling this function from different threads. </p> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01850">1850</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00014">ARMNN_ASSERT</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00033">ARMNN_NO_DEPRECATE_WARN_BEGIN</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00034">ARMNN_NO_DEPRECATE_WARN_END</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00275">Layer::GetBackendId()</a>, and <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00046">ITensorHandleFactory::LegacyFactoryId</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00721">RuntimeImpl::CreateWorkingMemHandle()</a>.</p> +<div class="fragment"><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>  Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</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="comment">// Tensors that will need to be allocated internally within armnn</span></div><div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  std::vector<std::unique_ptr<ITensorHandle>> managedTensorHandles;</div><div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>  <span class="comment">// Tensors that will be allocated externally by the user</span></div><div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>  std::vector<std::unique_ptr<ITensorHandle>> unmanagedTensorHandles;</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>  std::vector<WorkingMemDescriptor> workingMemDescriptors;</div><div class="line"><a name="l01860"></a><span class="lineno"> 1860</span>  std::unordered_map<LayerGuid, WorkingMemDescriptor> workingMemDescriptorMap;</div><div class="line"><a name="l01861"></a><span class="lineno"> 1861</span> </div><div class="line"><a name="l01862"></a><span class="lineno"> 1862</span>  <span class="keyword">auto</span> GetTensorHandle = [&](<a class="code" href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">Layer</a>* layer, <span class="keyword">const</span> OutputSlot& outputSlot)</div><div class="line"><a name="l01863"></a><span class="lineno"> 1863</span>  {</div><div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = outputSlot.GetTensorHandleFactoryId();</div><div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>  <span class="keyword">const</span> TensorInfo& tensorInfo = outputSlot.GetTensorInfo();</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="keywordflow">if</span> (factoryId == <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>)</div><div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>  {</div><div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>  BackendId <span class="keywordtype">id</span> = layer->GetBackendId();</div><div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</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="l01872"></a><span class="lineno"> 1872</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></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>  <span class="keywordflow">else</span></div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  {</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>  ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div><div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(handleFactory);</div><div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>  <span class="keywordflow">return</span> handleFactory->CreateTensorHandle(tensorInfo, <span class="keyword">false</span>);</div><div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>  }</div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>  };</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="keyword">struct </span>HandleInfo</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>  ITensorHandle* m_TensorHandle;</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>  <span class="keywordtype">bool</span> m_IsInputLayerHandle = <span class="keyword">false</span>;</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>  <span class="keywordtype">bool</span> m_IsOutputLayerHandle = <span class="keyword">false</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>  WorkingMemHandle::InputMemDescriptorCoords m_InputMemDescriptorCoords;</div><div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>  WorkingMemHandle::OutputMemDescriptorCoords m_OutputMemDescriptorCoords;</div><div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>  };</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span> </div><div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>  std::unordered_map<const OutputSlot*, HandleInfo> outputToHandleInfoMap;</div><div class="line"><a name="l01894"></a><span class="lineno"> 1894</span> </div><div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex = 0;</div><div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div><div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>  {</div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>  <span class="comment">// Constant layers execution and management is handled during loaded network construction</span></div><div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div><div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>  {</div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>  <span class="keywordflow">continue</span>;</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>  WorkingMemDescriptor workingMemDescriptor;</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="keywordtype">bool</span> isMemoryManaged = <span class="keyword">true</span>;</div><div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>  <span class="keywordtype">bool</span> isInputLayer = <span class="keyword">false</span>;</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>  <span class="keywordtype">bool</span> isOutputLayer = <span class="keyword">false</span>;</div><div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>  <span class="keywordtype">bool</span> isConnectedToOutputLayer = <span class="keyword">false</span>;</div><div class="line"><a name="l01910"></a><span class="lineno"> 1910</span> </div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> || layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">LayerType::MemImport</a>)</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="comment">// Input layers/workloads will not be executed so the descriptor is not added to workingMemDescriptors</span></div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>  <span class="comment">// However we will still need to manage the tensorHandle</span></div><div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>  isInputLayer = <span class="keyword">true</span>;</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>  isMemoryManaged = !m_NetworkProperties.m_ImportEnabled;</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>  {</div><div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>  isOutputLayer = <span class="keyword">true</span>;</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> </div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex = 0;</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>  <span class="comment">// Create a tensor handle for each output slot of a layer</span></div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>  <span class="comment">// Once we create it, we start managing its lifetime</span></div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& slot : layer->GetOutputSlots())</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="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="l01929"></a><span class="lineno"> 1929</span>  {</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>  <span class="keywordflow">if</span> ((slot.GetConnection(i)->GetOwningLayer().GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>))</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="keywordflow">if</span> (!isConnectedToOutputLayer)</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>  {</div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>  isConnectedToOutputLayer = <span class="keyword">true</span>;</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</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="l01936"></a><span class="lineno"> 1936</span>  isMemoryManaged = !m_NetworkProperties.m_ExportEnabled;</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>  <span class="keywordflow">else</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>  <span class="comment">// Importing in this case would likely cause unexpected behaviour, so we disallow it.</span></div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) <<</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</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="l01943"></a><span class="lineno"> 1943</span>  <span class="stringliteral">"This will prevent importing on the connected OutputLayers."</span>,</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  layer->GetName(), layer->GetGuid());</div><div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>  isMemoryManaged = <span class="keyword">true</span>;</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> </div><div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>  ITensorHandle* tensorHandle;</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>  <span class="keywordflow">if</span> (isMemoryManaged)</div><div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>  {</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>  managedTensorHandles.emplace_back(GetTensorHandle(layer, slot));</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>  tensorHandle = managedTensorHandles.back().get();</div><div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>  }</div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>  <span class="keywordflow">else</span></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>  unmanagedTensorHandles.emplace_back(GetTensorHandle(layer, slot));</div><div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>  tensorHandle = unmanagedTensorHandles.back().get();</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>  workingMemDescriptor.m_Outputs.push_back(tensorHandle);</div><div class="line"><a name="l01963"></a><span class="lineno"> 1963</span> </div><div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>  HandleInfo& handleInfo = outputToHandleInfoMap[&slot];</div><div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>  handleInfo.m_TensorHandle = tensorHandle;</div><div class="line"><a name="l01966"></a><span class="lineno"> 1966</span> </div><div class="line"><a name="l01967"></a><span class="lineno"> 1967</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="l01968"></a><span class="lineno"> 1968</span>  <span class="keywordflow">if</span> (isConnectedToOutputLayer)</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>  handleInfo.m_IsOutputLayerHandle = <span class="keyword">true</span>;</div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>  handleInfo.m_OutputMemDescriptorCoords.m_OutputSlotCoords = {layerIndex, slotIndex};</div><div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>  }</div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  <span class="comment">// Store the LayerBindingId of the InputLayer</span></div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  <span class="keywordflow">if</span> (isInputLayer)</div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>  {</div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  handleInfo.m_IsInputLayerHandle = <span class="keyword">true</span>;</div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span>BindableLayer*<span class="keyword">></span>(layer)->GetBindingId();</div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>  handleInfo.m_InputMemDescriptorCoords.m_LayerBindingId = bindingId;</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>  slotIndex++;</div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>  }</div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</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="l01983"></a><span class="lineno"> 1983</span>  <span class="comment">// to each tensor handle we encounter.</span></div><div class="line"><a name="l01984"></a><span class="lineno"> 1984</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="l01985"></a><span class="lineno"> 1985</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="l01986"></a><span class="lineno"> 1986</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& slot : layer->GetInputSlots())</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>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(slot.GetConnection());</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>  <span class="keyword">auto</span> outputSlot = slot.GetConnectedOutputSlot();</div><div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>  <span class="keyword">auto</span> key = outputSlot->GetOwningLayer().GetGuid();</div><div class="line"><a name="l01991"></a><span class="lineno"> 1991</span> </div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>  <span class="comment">// Constant layers execution and management is handled during loaded network construction</span></div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  <span class="keyword">auto</span> found = m_ConstantTensorHandles.find(key);</div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>  <span class="keywordflow">if</span> (found != m_ConstantTensorHandles.end())</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>  ITensorHandle* tensorHandle = found->second;</div><div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>  workingMemDescriptor.m_Inputs.push_back(tensorHandle);</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="comment">// Odd case where a constant layer is connected to an output layer</span></div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>  <span class="comment">// We will need to create a HandleInfo to track it</span></div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>  <span class="keywordflow">if</span> (isOutputLayer)</div><div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>  {</div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span>BindableLayer*<span class="keyword">></span>(layer)->GetBindingId();</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>  HandleInfo& handleInfo = outputToHandleInfoMap[outputSlot];</div><div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>  handleInfo.m_TensorHandle = tensorHandle;</div><div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>  handleInfo.m_IsOutputLayerHandle = <span class="keyword">true</span>;</div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>  handleInfo.m_OutputMemDescriptorCoords.m_LayerBindingIds.push_back(bindingId);</div><div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, 0});</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>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</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>  HandleInfo& handleInfo = outputToHandleInfoMap.at(outputSlot);</div><div class="line"><a name="l02015"></a><span class="lineno"> 2015</span> </div><div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>  ITensorHandle* inputTensorHandle = handleInfo.m_TensorHandle;</div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>  workingMemDescriptor.m_Inputs.push_back(inputTensorHandle);</div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span> </div><div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>  <span class="comment">// Store the LayerBindingId of the OutputLayer</span></div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>  <span class="keywordflow">if</span> (isOutputLayer)</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>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <span class="keyword">static_cast<</span>BindableLayer*<span class="keyword">></span>(layer)->GetBindingId();</div><div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>  handleInfo.m_OutputMemDescriptorCoords.m_LayerBindingIds.push_back(bindingId);</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, 0});</div><div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>  }</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</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="l02027"></a><span class="lineno"> 2027</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="l02028"></a><span class="lineno"> 2028</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (handleInfo.m_IsOutputLayerHandle)</div><div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  {</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>  handleInfo.m_OutputMemDescriptorCoords.m_InputSlotCoords.push_back({layerIndex, slot.GetSlotIndex()});</div><div class="line"><a name="l02031"></a><span class="lineno"> 2031</span>  }</div><div class="line"><a name="l02032"></a><span class="lineno"> 2032</span> </div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>  <span class="comment">// Store the coordinates of the InputSlots connected to the InputLayer</span></div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</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="l02035"></a><span class="lineno"> 2035</span>  <span class="keywordflow">if</span> (handleInfo.m_IsInputLayerHandle)</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>  std::pair<LayerGuid, unsigned int> connectionLocation{layerIndex, slot.GetSlotIndex()};</div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>  handleInfo.m_InputMemDescriptorCoords.m_InputSlotCoords.emplace_back(connectionLocation);</div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>  }</div><div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>  }</div><div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>  workingMemDescriptorMap.insert({layer->GetGuid(), workingMemDescriptor});</div><div class="line"><a name="l02042"></a><span class="lineno"> 2042</span> </div><div class="line"><a name="l02043"></a><span class="lineno"> 2043</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="l02044"></a><span class="lineno"> 2044</span>  <span class="comment">// However we will still need to manage the tensorHandle</span></div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>  <span class="keywordflow">if</span> (!isInputLayer)</div><div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>  {</div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>  workingMemDescriptors.push_back(workingMemDescriptor);</div><div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>  layerIndex++;</div><div class="line"><a name="l02049"></a><span class="lineno"> 2049</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> </div><div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>  std::vector<std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>> tensorMemory;</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="keyword">auto</span> externalMemoryManager = CreateExternalMemoryManger(tensorMemory);</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="comment">// Sort m_TensorMemory, so it's order matches the outputSlot order</span></div><div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>  std::sort(tensorMemory.begin(), tensorMemory.end(),</div><div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>  [](<span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& lhs,</div><div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>  <span class="keyword">const</span> std::pair<std::shared_ptr<TensorMemory>, <a class="code" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a>>& rhs)</div><div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>  {</div><div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>  <span class="keywordflow">return</span> lhs.first->m_OutputSlotId < rhs.first->m_OutputSlotId;</div><div class="line"><a name="l02062"></a><span class="lineno"> 2062</span>  });</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>  std::vector<WorkingMemHandle::InputMemDescriptorCoords> inputConnectionsInfo;</div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>  std::vector<WorkingMemHandle::OutputMemDescriptorCoords> outputConnectionsInfo;</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>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& handleInfo: outputToHandleInfoMap)</div><div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>  {</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>  <span class="keywordflow">if</span> (handleInfo.second.m_IsOutputLayerHandle)</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>  outputConnectionsInfo.emplace_back(handleInfo.second.m_OutputMemDescriptorCoords);</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> </div><div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>  <span class="keywordflow">if</span> (handleInfo.second.m_IsInputLayerHandle)</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>  inputConnectionsInfo.emplace_back(handleInfo.second.m_InputMemDescriptorCoords);</div><div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>  }</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> </div><div class="line"><a name="l02080"></a><span class="lineno"> 2080</span>  <span class="keywordflow">return</span> std::make_unique<WorkingMemHandle>(networkId,</div><div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>  inputConnectionsInfo,</div><div class="line"><a name="l02082"></a><span class="lineno"> 2082</span>  outputConnectionsInfo,</div><div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>  workingMemDescriptors,</div><div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>  workingMemDescriptorMap,</div><div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>  std::move(externalMemoryManager),</div><div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  std::move(tensorMemory),</div><div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  std::move(managedTensorHandles),</div><div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>  std::move(unmanagedTensorHandles));</div><div class="line"><a name="l02089"></a><span class="lineno"> 2089</span> }</div><div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#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.xhtml#l00033">Deprecated.hpp:33</a></div></div> +<div class="ttc" id="namespacearmnn_serializer_xhtml_a9a8118be7780e95363d631cbca7e7800"><div class="ttname"><a href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">armnnSerializer::Layer</a></div><div class="ttdeci">Layer</div><div class="ttdef"><b>Definition:</b> <a href="_armnn_schema__generated_8h_source.xhtml#l01249">ArmnnSchema_generated.h:1249</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00205">Logging.hpp:205</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00290">Types.hpp:290</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#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.xhtml#l00034">Deprecated.hpp:34</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">armnn::BoostLogSeverityMapping::warning</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">armnn::LayerType::MemImport</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a14fcd7f88d11cea0a018269dca5f9277"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00230">Types.hpp:230</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml_ae5ecc42140a12c855554a4a621fc8456"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#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.xhtml#l00039">TensorHandleFactoryRegistry.cpp:39</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a32f4aa6a7089d877af08928139c2c277"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">armnn::ITensorHandleFactory::FactoryId</a></div><div class="ttdeci">std::string FactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00045">ITensorHandleFactory.hpp:45</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::PaddingMode::Constant</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a9c95f90eb40e31f629e0e2947b8bc6f9"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">armnn::ITensorHandleFactory::LegacyFactoryId</a></div><div class="ttdeci">static const FactoryId LegacyFactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00046">ITensorHandleFactory.hpp:46</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a87880cba8611688cc57bec8f913958e8"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a87880cba8611688cc57bec8f913958e8">◆ </a></span>EnqueueWorkload()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> EnqueueWorkload </td> + <td>(</td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> & </td> + <td class="paramname"><em>inputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> & </td> + <td class="paramname"><em>outputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > </td> + <td class="paramname"><em>preImportedInputIds</em> = <code>{}</code>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > </td> + <td class="paramname"><em>preImportedOutputIds</em> = <code>{}</code> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p>Single thread execution of the loaded network. </p> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00755">755</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00015">ARMNN_ASSERT_MSG</a>, <a class="el" href="_logging_8hpp_source.xhtml#l00205">ARMNN_LOG</a>, <a class="el" href="_profiling_8hpp_source.xhtml#l00220">ARMNN_SCOPED_PROFILING_EVENT</a>, <a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Failure</a>, <a class="el" href="_output_handler_8hpp_source.xhtml#l00046">OutputHandler::GetData()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00192">Graph::GetInputLayers()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00187">Graph::GetNumInputs()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00198">Graph::GetNumLayers()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00188">Graph::GetNumOutputs()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00196">Graph::GetOutputLayers()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00026">QueueDescriptor::m_Inputs</a>, <a class="el" href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00018">WorkloadInfo::m_InputTensorInfos</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>, and <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">armnn::warning</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00630">RuntimeImpl::EnqueueWorkload()</a>.</p> +<div class="fragment"><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">const</span> Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span> </div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  <span class="comment">// Walk graph to determine the order of execution.</span></div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keywordflow">if</span> (graph.GetNumLayers() < 2)</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  {</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) << <span class="stringliteral">"IRuntime::EnqueueWorkload()::Less than two nodes in graph"</span>;</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</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>  <span class="comment">// Data that must be kept alive for the entire execution of the workload.</span></div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  WorkloadData workloadData(inputTensors, outputTensors);</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keywordflow">if</span> (graph.GetNumInputs() != inputTensors.size())</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  {</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"Number of inputs provided does not match network."</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> </div><div class="line"><a name="l00777"></a><span class="lineno"> 777</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="l00778"></a><span class="lineno"> 778</span>  {</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareInputs"</span>);</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  m_InputQueue.clear();</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  m_InputQueue.reserve(graph.GetNumInputs());</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span> </div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <span class="keywordflow">if</span> (preImportedInputIds.size() > graph.GetNumInputs())</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  {</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"Invalid number of preImportedInputIds"</span>);</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  }</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span> </div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0;</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> importedInputIdIndex = 0;</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  std::sort(preImportedInputIds.begin(), preImportedInputIds.end());</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* inputLayer : graph.GetInputLayers())</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  {</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <span class="keywordflow">if</span> (importedInputIdIndex < preImportedInputIds.size() &&</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  inputIndex == preImportedInputIds[importedInputIdIndex])</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="comment">// Only replace tensorhandles if they have not already been replaced</span></div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <span class="keywordflow">if</span> (!m_IsInputImported[inputIndex])</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  {</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <span class="keyword">auto</span> outputTensorHandle = m_PreImportedInputHandles[inputIndex].m_TensorHandle.get();</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>  <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="l00802"></a><span class="lineno"> 802</span>  {</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keyword">auto</span> workload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  workload->ReplaceInputTensorHandle(outputTensorHandle, workloadInfo.m_SlotIndex);</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>  m_IsInputImported[inputIndex] = <span class="keyword">true</span>;</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  }</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  importedInputIdIndex++;</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  }</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keywordflow">else</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> (m_IsInputImported[inputIndex])</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>  OutputHandler& handler = <span class="keyword">const_cast<</span>OutputHandler&<span class="keyword">></span>(inputLayer->GetOutputHandler(0));</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">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: m_InputWorkloadSlotPairs[inputLayer->GetBindingId()])</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="keyword">auto</span> workload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  workload->ReplaceInputTensorHandle(handler.GetData(), workloadInfo.m_SlotIndex);</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>  m_IsInputImported[inputIndex] = <span class="keyword">false</span>;</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  }</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="comment">// InputTensorHandle is not imported yet, process to enqueue input</span></div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <span class="keyword">const</span> TensorPin& pin = workloadData.GetInputTensorPin(inputLayer->GetBindingId());</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  EnqueueInput(*inputLayer, pin.GetTensorHandle(), pin.GetTensorInfo());</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  }</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  inputIndex++;</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>  }</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</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="l00833"></a><span class="lineno"> 833</span>  {</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareOutputs"</span>);</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  m_OutputQueue.clear();</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  m_OutputQueue.reserve(graph.GetNumOutputs());</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span> </div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keywordflow">if</span> (preImportedOutputIds.size() > graph.GetNumOutputs())</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  {</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"Invalid number of preImportedOutputIds"</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> </div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> importedOutputIdIndex = 0;</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  std::sort(preImportedOutputIds.begin(), preImportedOutputIds.end());</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* outputLayer : graph.GetOutputLayers())</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  {</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <span class="keywordflow">if</span> (importedOutputIdIndex < preImportedOutputIds.size() &&</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  outputIndex == preImportedOutputIds[importedOutputIdIndex])</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  {</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="comment">// Only replace tensorhandles if they have not already been replaced</span></div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  ITensorHandle* inputTensorHandle = m_PreImportedOutputHandles[outputIndex].m_TensorHandle.get();</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="keywordflow">if</span> (!m_IsOutputImported[outputIndex])</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  {</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = outputLayer->GetBindingId();</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& indices = m_OutputWorkloadSlotPairs[bindingId];</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">auto</span> outputWorkload = m_WorkloadQueue[indices.m_OutputSlotIndices.m_WorkloadIndex].get();</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span> </div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  outputWorkload->ReplaceOutputTensorHandle(inputTensorHandle,</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  indices.m_OutputSlotIndices.m_SlotIndex);</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="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& workloadInfo: indices.m_InputSlotIndices)</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>  <span class="keyword">auto</span> inputWorkload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  inputWorkload->ReplaceInputTensorHandle(inputTensorHandle, workloadInfo.m_SlotIndex);</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>  m_IsOutputImported[outputIndex] = <span class="keyword">true</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"> 872</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(inputTensorHandle != <span class="keyword">nullptr</span>, <span class="stringliteral">"Data should have been allocated."</span>);</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  MemSyncQueueDescriptor syncDesc;</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  syncDesc.m_Inputs.push_back(inputTensorHandle);</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  WorkloadInfo <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  info.m_InputTensorInfos.push_back(</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  outputLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo());</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  <span class="keyword">auto</span> syncWorkload = std::make_unique<SyncMemGenericWorkload>(syncDesc, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(syncWorkload, <span class="stringliteral">"No sync workload created"</span>);</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  m_OutputQueue.push_back(move(syncWorkload));</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  importedOutputIdIndex++;</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  }</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keywordflow">else</span></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>  <span class="keywordflow">if</span> (m_IsOutputImported[outputIndex])</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  {</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keyword">const</span> <span class="keyword">auto</span> bindingId = outputLayer->GetBindingId();</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& indices = m_OutputWorkloadSlotPairs[bindingId];</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span> </div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="keyword">auto</span> outputWorkload = m_WorkloadQueue[indices.m_OutputSlotIndices.m_WorkloadIndex].get();</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <span class="keyword">const</span> OutputHandler& outputHandler =</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  outputLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetOutputHandler();</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span> </div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  outputWorkload->ReplaceOutputTensorHandle(</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  outputHandler.GetData(), indices.m_OutputSlotIndices.m_SlotIndex);</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span> </div><div class="line"><a name="l00897"></a><span class="lineno"> 897</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="l00898"></a><span class="lineno"> 898</span>  {</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  <span class="keyword">auto</span> inputWorkload = m_WorkloadQueue[workloadInfo.m_WorkloadIndex].get();</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  inputWorkload->ReplaceInputTensorHandle(outputHandler.GetData(), workloadInfo.m_SlotIndex);</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>  m_IsOutputImported[outputIndex] = <span class="keyword">false</span>;</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  }</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span> </div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keyword">const</span> TensorPin& pin = workloadData.GetOutputTensorPin(outputLayer->GetBindingId());</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <span class="comment">// OutputTensorHandle is not imported yet, process to enqueue Output</span></div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  EnqueueOutput(*outputLayer, pin.GetTensorHandle(), pin.GetTensorInfo());</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  }</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  outputIndex++;</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  }</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  }</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>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  ProfilingGuid inferenceGuid = m_ProfilingService->GetNextGuid();</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <span class="keywordflow">if</span> (timelineUtils)</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  {</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <span class="comment">// Add inference timeline trace if profiling is enabled.</span></div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  timelineUtils->CreateTypedEntity(inferenceGuid, LabelsAndEventClasses::INFERENCE_GUID);</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  timelineUtils->CreateRelationship(ProfilingRelationshipType::RetentionLink,</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  networkGuid,</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  inferenceGuid,</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  LabelsAndEventClasses::EXECUTION_OF_GUID);</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  timelineUtils->RecordEvent(inferenceGuid, LabelsAndEventClasses::ARMNN_PROFILING_SOL_EVENT_CLASS);</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  }</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>  <span class="keywordtype">bool</span> executionSucceeded = <span class="keyword">true</span>;</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>  {</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keywordflow">if</span> (m_ProfilingService->IsProfilingEnabled())</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  {</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  m_ProfilingService->IncrementCounterValue(INFERENCES_RUN);</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>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"Execute"</span>);</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <a class="code" href="_heap_profiling_8hpp.xhtml#aeeb927880fc4ffc2eea754a67d884a53">ARMNN_SCOPED_HEAP_PROFILING</a>(<span class="stringliteral">"Executing"</span>);</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  executionSucceeded = <a class="code" href="classarmnn_1_1_loaded_network.xhtml#a95b1c23f6f296a0c39383bef20fdd46a">Execute</a>(timelineUtils, inferenceGuid);</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> </div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keywordflow">if</span> (timelineUtils)</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  {</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="comment">// Add end of life of the inference timeline if profiling is enabled.</span></div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  timelineUtils->RecordEvent(inferenceGuid, LabelsAndEventClasses::ARMNN_PROFILING_EOL_EVENT_CLASS);</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  timelineUtils->Commit();</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> </div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <span class="keywordflow">return</span> executionSucceeded ? <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a> : <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</a>;</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span> }</div><div class="ttc" id="classarmnn_1_1_loaded_network_xhtml_a95b1c23f6f296a0c39383bef20fdd46a"><div class="ttname"><a href="classarmnn_1_1_loaded_network.xhtml#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.xhtml#l01628">LoadedNetwork.cpp:1628</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00205">Logging.hpp:205</a></div></div> +<div class="ttc" id="_profiling_8hpp_xhtml_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.xhtml#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.xhtml#l00220">Profiling.hpp:220</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">armnn::BoostLogSeverityMapping::warning</a></div></div> +<div class="ttc" id="_heap_profiling_8hpp_xhtml_aeeb927880fc4ffc2eea754a67d884a53"><div class="ttname"><a href="_heap_profiling_8hpp.xhtml#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.xhtml#l00045">HeapProfiling.hpp:45</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Status::Failure</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a95b1c23f6f296a0c39383bef20fdd46a"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a95b1c23f6f296a0c39383bef20fdd46a">◆ </a></span>Execute()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> Execute </td> + <td>(</td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> & </td> + <td class="paramname"><em>inputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> & </td> + <td class="paramname"><em>outputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a> & </td> + <td class="paramname"><em>workingMemHandle</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > </td> + <td class="paramname"><em>preImportedInputs</em> = <code>{}</code>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > </td> + <td class="paramname"><em>preImportedOutputs</em> = <code>{}</code> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p>Thread safe execution of the loaded network. </p> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01628">1628</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_working_mem_handle_8cpp_source.xhtml#l00098">WorkingMemHandle::Allocate()</a>, <a class="el" href="_logging_8hpp_source.xhtml#l00205">ARMNN_LOG</a>, <a class="el" href="_profiling_8hpp_source.xhtml#l00220">ARMNN_SCOPED_PROFILING_EVENT</a>, <a class="el" href="_loaded_network_8cpp_source.xhtml#l01294">armnn::CopyToOutputTensor()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::error</a>, <a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Failure</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00115">WorkingMemHandle::GetBindingIdVector()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00103">WorkingMemHandle::GetInputConnections()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00093">WorkingMemHandle::GetInputHandle()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00187">Graph::GetNumInputs()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00188">Graph::GetNumOutputs()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00108">WorkingMemHandle::GetOutputConnection()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00098">WorkingMemHandle::GetOutputHandle()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00088">WorkingMemHandle::GetWorkingMemDescriptorAt()</a>, <a class="el" href="_working_mem_handle_8hpp_source.xhtml#l00073">WorkingMemHandle::IsAllocated()</a>, <a class="el" href="_working_mem_handle_8cpp_source.xhtml#l00125">WorkingMemHandle::MemSyncOutputs()</a>, <a class="el" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Success</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>, and <a class="el" href="_working_mem_handle_8cpp_source.xhtml#l00134">WorkingMemHandle::ValidateBindingIds()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00682">RuntimeImpl::Execute()</a>, and <a class="el" href="_loaded_network_8cpp_source.xhtml#l01141">LoadedNetwork::FreeWorkingMemory()</a>.</p> +<div class="fragment"><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span> {</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>  <span class="keyword">const</span> Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span> </div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>  <span class="keywordflow">if</span> (inputTensors.size() + preImportedInputs.size() != graph.GetNumInputs())</div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  {</div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  <span class="keywordflow">if</span> (preImportedInputs.empty())</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> InvalidArgumentException(<span class="stringliteral">"LoadedNetwork::Execute: Number of inputs provided does not match network."</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="keywordflow">else</span></div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  {</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  <span class="stringliteral">"Number of inputs + preImportedInputs provided does not match network."</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>  }</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span> </div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  <span class="keywordflow">if</span> (outputTensors.size() + preImportedOutputs.size() != graph.GetNumOutputs())</div><div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  {</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  <span class="keywordflow">if</span> (preImportedOutputs.empty())</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="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  <span class="stringliteral">"Number of outputs provided does not match network."</span>);</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>  {</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"LoadedNetwork::Execute: "</span></div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  <span class="stringliteral">"Number of outputs + preImportedOutputs provided does not match network."</span>);</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  }</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>  }</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>  WorkingMemHandle& workingMemHandle = <span class="keyword">dynamic_cast<</span>WorkingMemHandle&<span class="keyword">></span>(iWorkingMemHandle);</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  <span class="comment">// Collect all the given LayerBindingIds and check them for duplicates and unknowns.</span></div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  std::vector<LayerBindingId>& bindingIds = workingMemHandle.GetBindingIdVector();</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = 0;</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair : inputTensors)</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  {</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  bindingIds[index++] = pair.first;</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>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span> : preImportedInputs)</div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>  {</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>  bindingIds[index++] = ValidateImportedInputID(<span class="keywordtype">id</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="keywordflow">for</span> (<span class="keyword">auto</span> pair : outputTensors)</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  {</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>  bindingIds[index++] = pair.first;</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>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span> : preImportedOutputs)</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>  bindingIds[index++] = ValidateImportedOutputID(<span class="keywordtype">id</span>);</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>  }</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>  workingMemHandle.ValidateBindingIds();</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span> </div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>  <span class="keyword">auto</span> resetMemHandle = [&]()</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>  {</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span>: preImportedInputs)</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>  {</div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedInputHandles[id].m_LayerBindingId;</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>  <span class="keyword">auto</span> inputHandle = workingMemHandle.GetInputHandle(layerBindingId);</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>  <span class="keyword">auto</span> inputConnections = workingMemHandle.GetInputConnections(layerBindingId);</div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : inputConnections)</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  {</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>  *it = inputHandle;</div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  }</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>  }</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>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span>: preImportedOutputs)</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>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedOutputHandles[id].m_LayerBindingId;</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span> </div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>  <span class="keyword">auto</span> outputHandle = workingMemHandle.GetOutputHandle(layerBindingId);</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>  <span class="keyword">auto</span> outputConnections = workingMemHandle.GetOutputConnection(layerBindingId);</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span> </div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : outputConnections)</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>  *it = outputHandle;</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  }</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>  };</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>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>  TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService);</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  ProfilingGuid inferenceGuid = m_ProfilingService->GetNextGuid();</div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  <span class="keywordflow">if</span> (timelineUtils)</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>  <span class="comment">// Add inference timeline trace if profiling is enabled.</span></div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  timelineUtils->CreateTypedEntity(inferenceGuid,LabelsAndEventClasses::INFERENCE_GUID);</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>  timelineUtils->CreateRelationship(ProfilingRelationshipType::RetentionLink,</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>  networkGuid,</div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  inferenceGuid,</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  LabelsAndEventClasses::EXECUTION_OF_GUID);</div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  timelineUtils->RecordEvent(inferenceGuid,LabelsAndEventClasses::ARMNN_PROFILING_SOL_EVENT_CLASS);</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> </div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  <span class="keywordtype">bool</span> executionSucceeded = <span class="keyword">true</span>;</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">if</span> (timelineUtils)</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>  <span class="comment">// Add end of life of the inference timeline if profiling is enabled.</span></div><div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  timelineUtils->RecordEvent(inferenceGuid,LabelsAndEventClasses::ARMNN_PROFILING_EOL_EVENT_CLASS);</div><div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>  timelineUtils->Commit();</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> </div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  <span class="keywordflow">if</span> (!workingMemHandle.IsAllocated())</div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  {</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>  workingMemHandle.Allocate();</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  }</div><div class="line"><a name="l01742"></a><span class="lineno"> 1742</span> </div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>  {</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareInputs"</span>);</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair : inputTensors)</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  {</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  EnqueueInput(pair.second, workingMemHandle.GetInputHandle(pair.first));</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>  }</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="comment">// Swap in the pre-imported inputs if any</span></div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> <span class="keywordtype">id</span> : preImportedInputs)</div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  {</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>  <span class="keyword">const</span> ImportedTensorHandlePin& importedInputPin = m_PreImportedInputHandles[id];</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedInputHandles[id].m_LayerBindingId;</div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& preimportedHandle = importedInputPin.m_TensorHandle;</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>  <span class="keyword">auto</span> inputConnections = workingMemHandle.GetInputConnections(layerBindingId);</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : inputConnections)</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>  *it = preimportedHandle.get();</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  }</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>  }</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>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"PrepareOutputs"</span>);</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>  <span class="keywordflow">if</span> (m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a042fb9a87ffa70730766d19505d80490">m_ExportEnabled</a>)</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  {</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair: outputTensors)</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>  ImportOutputTensor(pair.second, workingMemHandle.GetOutputHandle(pair.first));</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>  }</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> </div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> <span class="keywordtype">id</span> : preImportedOutputs)</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="keyword">const</span> ImportedTensorHandlePin& importedOutputPin = m_PreImportedOutputHandles[id];</div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerBindingId = m_PreImportedOutputHandles[id].m_LayerBindingId;</div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& preimportedHandle = importedOutputPin.m_TensorHandle;</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>  <span class="keyword">auto</span> outputConnections = workingMemHandle.GetOutputConnection(layerBindingId);</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span> </div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : outputConnections)</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>  *it = preimportedHandle.get();</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>  }</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> </div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  <span class="keyword">auto</span> Fail = [&](<span class="keyword">const</span> std::exception& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</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>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << <span class="stringliteral">"An error occurred attempting to execute a workload: "</span> << <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>.what();</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  executionSucceeded = <span class="keyword">false</span>;</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>  ProfilingDynamicGuid workloadInferenceID(0);</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span> </div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>  {</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</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="l01799"></a><span class="lineno"> 1799</span>  {</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>  <span class="keyword">auto</span>& workload = m_WorkloadQueue[i];</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>  <span class="keywordflow">if</span> (timelineUtils)</div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  {</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>  workloadInferenceID = timelineUtils->RecordWorkloadInferenceAndStartOfLifeEvent(workload->GetGuid(),</div><div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  inferenceGuid);</div><div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  }</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>  workload->ExecuteAsync(workingMemHandle.GetWorkingMemDescriptorAt(i));</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span> </div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>  <span class="keywordflow">if</span> (timelineUtils)</div><div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>  {</div><div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>  timelineUtils->RecordEndOfLifeEvent(workloadInferenceID);</div><div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>  }</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>  }</div><div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> RuntimeException& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div><div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>  {</div><div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>  resetMemHandle();</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>  Fail(error);</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">catch</span> (<span class="keyword">const</span> std::runtime_error& error)</div><div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>  {</div><div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>  resetMemHandle();</div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>  Fail(error);</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">catch</span> (...)</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>  resetMemHandle();</div><div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  <span class="keywordflow">throw</span>;</div><div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  }</div><div class="line"><a name="l01829"></a><span class="lineno"> 1829</span> </div><div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>  <span class="keywordflow">if</span> (!m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a042fb9a87ffa70730766d19505d80490">m_ExportEnabled</a>)</div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>  {</div><div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> pair: outputTensors)</div><div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>  {</div><div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>  <a class="code" href="namespacearmnn.xhtml#a5acae80f1d8fd03cdb3878bd356683d7">CopyToOutputTensor</a>(pair.second, workingMemHandle.GetOutputHandle(pair.first));</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>  {</div><div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"SyncMemGeneric_Execute"</span>);</div><div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>  workingMemHandle.MemSyncOutputs();</div><div class="line"><a name="l01841"></a><span class="lineno"> 1841</span>  }</div><div class="line"><a name="l01842"></a><span class="lineno"> 1842</span> </div><div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>  resetMemHandle();</div><div class="line"><a name="l01844"></a><span class="lineno"> 1844</span> </div><div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>  <span class="keywordflow">return</span> executionSucceeded ? <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a> : <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">Status::Failure</a>;</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span> }</div><div class="ttc" id="namespacearmnn_xhtml_ac68a434f0e78e33726bfb22a39ec813f"><div class="ttname"><a href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">armnn::ImportedOutputId</a></div><div class="ttdeci">unsigned int ImportedOutputId</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00292">Types.hpp:292</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00205">Logging.hpp:205</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a5acae80f1d8fd03cdb3878bd356683d7"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l01294">LoadedNetwork.cpp:1294</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::BoostLogSeverityMapping::error</a></div></div> +<div class="ttc" id="_profiling_8hpp_xhtml_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.xhtml#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.xhtml#l00220">Profiling.hpp:220</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00290">Types.hpp:290</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_a042fb9a87ffa70730766d19505d80490"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#a042fb9a87ffa70730766d19505d80490">armnn::INetworkProperties::m_ExportEnabled</a></div><div class="ttdeci">const bool m_ExportEnabled</div><div class="ttdoc">Deprecated and will be removed in future release. </div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00056">IRuntime.hpp:56</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1c5ec805688cb558465a82a8d9f56a90"><div class="ttname"><a href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">armnn::ImportedInputId</a></div><div class="ttdeci">unsigned int ImportedInputId</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00291">Types.hpp:291</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70bae139a585510a502bbf1841cf589f5086">armnn::Status::Failure</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aaf8558a23ae9be6e7ea165989f1fa808"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aaf8558a23ae9be6e7ea165989f1fa808">◆ </a></span>FreeWorkingMemory()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void FreeWorkingMemory </td> + <td>(</td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01141">1141</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00015">ARMNN_ASSERT_MSG</a>, <a class="el" href="_logging_8hpp_source.xhtml#l00205">ARMNN_LOG</a>, <a class="el" href="_memory_sources_8hpp_source.xhtml#l00041">armnn::CheckFlag()</a>, <a class="el" href="_workload_utils_8hpp_source.xhtml#l00046">armnn::CopyTensorContentsGeneric()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::error</a>, <a class="el" href="_loaded_network_8cpp_source.xhtml#l01628">LoadedNetwork::Execute()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00069">ITensorHandle::GetImportFlags()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00295">BaseTensor< MemoryType >::GetInfo()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00305">BaseTensor< MemoryType >::GetMemoryArea()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00075">ITensorHandle::Import()</a>, and <a class="el" href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">ITensorHandle::Map()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00721">RuntimeImpl::CreateWorkingMemHandle()</a>, and <a class="el" href="_runtime_8cpp_source.xhtml#l00630">RuntimeImpl::EnqueueWorkload()</a>.</p> +<div class="fragment"><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> <span class="preprocessor">#if !defined(ARMNN_DISABLE_THREADS)</span></div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  std::lock_guard<std::mutex> lockGuard(m_WorkingMemMutex);</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> <span class="preprocessor">#endif</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>  <span class="keywordflow">if</span> (!m_IsWorkingMemAllocated)</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  {</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  }</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">if</span> (m_ExternalMemoryManager)</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>  m_ExternalMemoryManager->Deallocate();</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</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="comment">// Informs the memory managers to release memory in its respective memory group</span></div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& memoryManager : m_BackendMemoryMangers)</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>  <span class="keywordflow">if</span> (memoryManager)</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  {</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  memoryManager->Release();</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  }</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  }</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#a69ca23561f4f8a887f19c6580cbd34c8">ReleaseMemory</a>();</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  m_IsWorkingMemAllocated = <span class="keyword">false</span>;</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml_a69ca23561f4f8a887f19c6580cbd34c8"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#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.xhtml#l00086">TensorHandleFactoryRegistry.cpp:86</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af616683424cb40d83b5a923db7f06f11"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af616683424cb40d83b5a923db7f06f11">◆ </a></span>GetInputTensorInfo()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> GetInputTensorInfo </td> + <td>(</td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> </td> + <td class="paramname"><em>layerId</em></td><td>)</td> + <td> const</td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00606">606</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00015">ARMNN_ASSERT_MSG</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00599">RuntimeImpl::GetInputTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00607"></a><span class="lineno"> 607</span> {</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& inputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetInputLayers())</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  {</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(inputLayer->GetNumOutputSlots() == 1, <span class="stringliteral">"Input layer should have exactly 1 output slot"</span>);</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordflow">if</span> (inputLayer->GetBindingId() == layerId)</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">return</span> inputLayer->GetOutputSlot(0).GetTensorInfo();</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>  }</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>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"No input layer is associated with id {}"</span>, layerId));</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> }</div><div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ad90f4f6c9360c5cb64c164b9ddcb3130"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ad90f4f6c9360c5cb64c164b9ddcb3130">◆ </a></span>GetNetworkGuid()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">ProfilingGuid GetNetworkGuid </td> + <td>(</td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00601">601</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> +<div class="fragment"><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>  <span class="keywordflow">return</span> m_OptimizedNetwork->GetGuid();</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a2b6b57945bc68f659e08d28c8a015e91"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a2b6b57945bc68f659e08d28c8a015e91">◆ </a></span>GetOutputTensorInfo()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> GetOutputTensorInfo </td> + <td>(</td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> </td> + <td class="paramname"><em>layerId</em></td><td>)</td> + <td> const</td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00620">620</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00015">ARMNN_ASSERT_MSG</a>, <a class="el" href="_exceptions_8hpp_source.xhtml#l00203">CHECK_LOCATION</a>, <a class="el" href="_backend_id_8hpp_source.xhtml#l00138">BackendId::Get()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00275">Layer::GetBackendId()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00225">Layer::GetNameStr()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, and <a class="el" href="_workload_factory_8cpp_source.xhtml#l01516">IWorkloadFactory::IsLayerSupported()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00604">RuntimeImpl::GetOutputTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00621"></a><span class="lineno"> 621</span> {</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& outputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetOutputLayers())</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  {</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(outputLayer->GetNumInputSlots() == 1, <span class="stringliteral">"Output layer should have exactly 1 input slot"</span>);</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(outputLayer->GetInputSlot(0).GetConnection(), <span class="stringliteral">"Input slot on Output layer must be connected"</span>);</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <span class="keywordflow">if</span> (outputLayer->GetBindingId() == layerId)</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="keywordflow">return</span> outputLayer->GetInputSlot(0).GetConnection()->GetTensorInfo();</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>  }</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span> </div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <span class="keywordflow">throw</span> InvalidArgumentException(fmt::format(<span class="stringliteral">"No output layer is associated with id {}"</span>, layerId));</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span> }</div><div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aee8e1cb09e0d4dcbe64df111c5edd55e"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aee8e1cb09e0d4dcbe64df111c5edd55e">◆ </a></span>GetProfiler()</h2> + +<div class="memitem"> +<div class="memproto"> +<table class="mlabels"> + <tr> + <td class="mlabels-left"> + <table class="memname"> + <tr> + <td class="memname">const std::shared_ptr<<a class="el" href="classarmnn_1_1_i_profiler.xhtml">IProfiler</a>>& GetProfiler </td> + <td>(</td> + <td class="paramname"></td><td>)</td> + <td> const</td> + </tr> + </table> + </td> + <td class="mlabels-right"> +<span class="mlabels"><span class="mlabel">inline</span></span> </td> + </tr> +</table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8hpp_source.xhtml#l00087">87</a> of file <a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00721">RuntimeImpl::CreateWorkingMemHandle()</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00630">RuntimeImpl::EnqueueWorkload()</a>, and <a class="el" href="_runtime_8cpp_source.xhtml#l00682">RuntimeImpl::Execute()</a>.</p> +<div class="fragment"><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> { <span class="keywordflow">return</span> m_OptimizedNetwork->GetProfiler(); }</div></div><!-- fragment --> +</div> +</div> +<a id="a704bd570f39deda992bccdc639640dc7"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a704bd570f39deda992bccdc639640dc7">◆ </a></span>ImportInputs()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">std::vector< <a class="el" href="namespacearmnn.xhtml#a1c5ec805688cb558465a82a8d9f56a90">ImportedInputId</a> > ImportInputs </td> + <td>(</td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> & </td> + <td class="paramname"><em>inputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> </td> + <td class="paramname"><em>forceImportMemorySource</em> = <code><a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a></code> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01335">1335</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00014">ARMNN_ASSERT</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00065">Graph::InputLayersAccessor::begin()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00085">ITensorHandle::CanBeImported()</a>, <a class="el" href="_memory_sources_8hpp_source.xhtml#l00041">armnn::CheckFlag()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00070">Graph::InputLayersAccessor::end()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00275">Layer::GetBackendId()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00463">BindableLayer::GetBindingId()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00069">ITensorHandle::GetImportFlags()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00295">BaseTensor< MemoryType >::GetInfo()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00192">Graph::GetInputLayers()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00305">BaseTensor< MemoryType >::GetMemoryArea()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00244">Layer::GetOutputSlots()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00205">OutputSlot::GetTensorHandleFactoryId()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00092">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00271">Layer::GetType()</a>, <a class="el" href="_backend_helper_8cpp_source.xhtml#l00058">armnn::HasCapability()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00075">ITensorHandle::Import()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::Input</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00184">Graph::TopologicalSort()</a>, and <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00609">RuntimeImpl::ImportInputs()</a>.</p> +<div class="fragment"><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span> {</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  <span class="keywordflow">if</span> (!m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  {</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  <span class="comment">// Cannot import if import is not enabled and forceImportMemorySource is undefined</span></div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  <span class="keywordflow">if</span> (forceImportMemorySource == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  {</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportInputs: Memory Import failed, NetworkProperties.m_ImportEnabled"</span>);</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  }</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  <span class="keywordflow">if</span> (inputTensors.size() != m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetNumInputs())</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>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportInputs: Force Import failed, incorrect number of tensors"</span>);</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>  std::vector<ImportedInputId> importedInputs;</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0;</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* inputLayer : graph.GetInputLayers())</div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  {</div><div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  <span class="keyword">auto</span> outputTensorHandle = m_PreImportedInputHandles[inputIndex].m_TensorHandle.get();</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</span> </div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  <span class="keywordflow">if</span> (!outputTensorHandle)</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  {</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  inputIndex++;</div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <span class="keywordflow">continue</span>;</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> </div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  <span class="keyword">auto</span> layerBindingId = inputLayer->GetBindingId();</div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</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="l01365"></a><span class="lineno"> 1365</span>  {</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>  <span class="keywordflow">return</span> inputTensor.first == layerBindingId;</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> </div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  <span class="keywordflow">if</span> (it == inputTensors.end())</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  {</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  inputIndex++;</div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  }</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>  <span class="keyword">const</span> <span class="keyword">auto</span>& inputTensor = *it;</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  std::unique_ptr<ITensorHandle> passThroughTensorHandle =</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.second.GetInfo(),</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  inputTensor.second.GetMemoryArea());</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> (outputTensorHandle->CanBeImported(passThroughTensorHandle->Map(), forceImportMemorySource)</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>  && (outputTensorHandle->Import(passThroughTensorHandle->Map(), forceImportMemorySource)))</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  {</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  importedInputs.push_back(inputIndex);</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>  passThroughTensorHandle->Unmap();</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span> </div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  inputIndex++;</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</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">return</span> importedInputs;</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  {</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  <span class="comment">// Import when the import of network properties is enabled</span></div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  std::vector<ImportedInputId> importedInputs;</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span> </div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputTensor : inputTensors)</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  {</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  <span class="keyword">auto</span> layerBindingId = inputTensor.first;</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <span class="keyword">auto</span> it = std::find_if(graph.GetInputLayers().begin(), graph.GetInputLayers().end(), [=](<span class="keyword">auto</span>* layer)</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>  <span class="keywordflow">return</span> layer->GetBindingId() == layerBindingId;</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  });</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>  <span class="keywordflow">if</span> (it == graph.GetInputLayers().end())</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="keywordflow">throw</span> MemoryImportException(fmt::format(</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  <span class="stringliteral">"ImportInputs: Memory Import failed, unknown LayerBindingId: {}"</span>, layerBindingId));</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  }</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span> </div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">Layer</a>* layer = *it;</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  <span class="keywordflow">if</span> (layer->GetType() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  {</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"ImportInputs: given layer not an InputLayer"</span>);</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  }</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="keyword">auto</span>& backend = m_Backends.at(layer->GetBackendId());</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.xhtml#abd839f0f103c1ae19a4b38d59b869108">HasCapability</a>(BackendOptions::BackendOption{<span class="stringliteral">"PreImportIOTensors"</span>, <span class="keyword">true</span>}, backend->GetCapabilities()))</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>  std::string er = backend->GetId();</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  er += <span class="stringliteral">" does not have PreImportIOTensors capability"</span>;</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>  <span class="keywordflow">throw</span> BackendCapabilityException(er);</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  }</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span> </div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  <span class="keyword">const</span> OutputSlot& outputSlot = layer->GetOutputSlots()[0];</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>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = outputSlot.GetTensorHandleFactoryId();</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  <span class="keyword">const</span> TensorInfo& tensorInfo = outputSlot.GetTensorInfo();</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span> </div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(handleFactory);</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>  ImportedTensorHandlePin importedTensorHandlePin{layerBindingId,</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  handleFactory->CreateTensorHandle(tensorInfo, <span class="keyword">false</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>  ITensorHandle* tensorHandle = importedTensorHandlePin.m_TensorHandle.get();</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">if</span> (!<a class="code" href="namespacearmnn.xhtml#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(tensorHandle->GetImportFlags(), m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>))</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>  <span class="keywordflow">throw</span> MemoryImportException(</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>  fmt::format(<span class="stringliteral">"ImportInputs: Memory Import failed, backend: "</span></div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  <span class="stringliteral">"{} does not support importing from source {}"</span></div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  , factoryId, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>));</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> </div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  std::unique_ptr<ITensorHandle> passThroughTensorHandle =</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  std::make_unique<ConstPassthroughTensorHandle>(inputTensor.second.GetInfo(),</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  inputTensor.second.GetMemoryArea());</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>  <span class="keywordflow">if</span> (tensorHandle->Import(passThroughTensorHandle->Map(), m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a53d95b257e52b0fd292ba6d40d3c5dc3">m_InputSource</a>))</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  {</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  importedInputs.push_back(m_CurImportedInputId++);</div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  passThroughTensorHandle->Unmap();</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>  <span class="keywordflow">else</span></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>  passThroughTensorHandle->Unmap();</div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportInputs: Memory Import failed"</span>);</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  }</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>  m_PreImportedInputHandles.push_back(std::move(importedTensorHandlePin));</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>  <span class="keywordflow">return</span> importedInputs;</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>  }</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span> }</div><div class="ttc" id="namespacearmnn_xhtml_abd839f0f103c1ae19a4b38d59b869108"><div class="ttname"><a href="namespacearmnn.xhtml#abd839f0f103c1ae19a4b38d59b869108">armnn::HasCapability</a></div><div class="ttdeci">bool HasCapability(const std::string &name, const BackendCapabilities &capabilities)</div><div class="ttdoc">Convenience function to check if a capability exists in a BackendCapabilites struct. </div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8cpp_source.xhtml#l00058">BackendHelper.cpp:58</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_a53d95b257e52b0fd292ba6d40d3c5dc3"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#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.xhtml#l00064">IRuntime.hpp:64</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_ad3ab02a7f6310b35c59ca78b509905ca"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#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.xhtml#l00058">IRuntime.hpp:58</a></div></div> +<div class="ttc" id="namespacearmnn_serializer_xhtml_a9a8118be7780e95363d631cbca7e7800"><div class="ttname"><a href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">armnnSerializer::Layer</a></div><div class="ttdeci">Layer</div><div class="ttdef"><b>Definition:</b> <a href="_armnn_schema__generated_8h_source.xhtml#l01249">ArmnnSchema_generated.h:1249</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml_ae5ecc42140a12c855554a4a621fc8456"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#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.xhtml#l00039">TensorHandleFactoryRegistry.cpp:39</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a32f4aa6a7089d877af08928139c2c277"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">armnn::ITensorHandleFactory::FactoryId</a></div><div class="ttdeci">std::string FactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00045">ITensorHandleFactory.hpp:45</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a84f86b4de5adf0b164e811c87051a0ee"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00041">MemorySources.hpp:41</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ac88d932e6e015a59551322b25796b11a"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ac88d932e6e015a59551322b25796b11a">◆ </a></span>ImportOutputs()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">std::vector< <a class="el" href="namespacearmnn.xhtml#ac68a434f0e78e33726bfb22a39ec813f">ImportedOutputId</a> > ImportOutputs </td> + <td>(</td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> & </td> + <td class="paramname"><em>outputTensors</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="namespacearmnn.xhtml#a14fcd7f88d11cea0a018269dca5f9277">MemorySource</a> </td> + <td class="paramname"><em>forceImportMemorySource</em> = <code><a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a></code> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l01468">1468</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00014">ARMNN_ASSERT</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00084">Graph::OutputLayersAccessor::begin()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00085">ITensorHandle::CanBeImported()</a>, <a class="el" href="_memory_sources_8hpp_source.xhtml#l00041">armnn::CheckFlag()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00090">Graph::OutputLayersAccessor::end()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00275">Layer::GetBackendId()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00463">BindableLayer::GetBindingId()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00056">InputSlot::GetConnectedOutputSlot()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00069">ITensorHandle::GetImportFlags()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00243">Layer::GetInputSlots()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00305">BaseTensor< MemoryType >::GetMemoryArea()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00196">Graph::GetOutputLayers()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00205">OutputSlot::GetTensorHandleFactoryId()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00092">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00271">Layer::GetType()</a>, <a class="el" href="_backend_helper_8cpp_source.xhtml#l00058">armnn::HasCapability()</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00075">ITensorHandle::Import()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::Output</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00184">Graph::TopologicalSort()</a>, and <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00615">RuntimeImpl::ImportOutputs()</a>.</p> +<div class="fragment"><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span> {</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>  <span class="keywordflow">if</span> (!m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>)</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  {</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  <span class="comment">// Cannot import if import is not enabled and forceImportMemorySource is undefined</span></div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>  <span class="keywordflow">if</span> (forceImportMemorySource == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>)</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  {</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportOutputs: Memory Import failed, NetworkProperties.m_ImportEnabled"</span>);</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  }</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  <span class="comment">// If forceImportMemorySource is defined, try import if memory is aligned</span></div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  <span class="keywordflow">if</span> (outputTensors.size() != m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetNumOutputs())</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  {</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportOutputs: Force Import failed, incorrect number of tensors"</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>  std::vector<ImportedOutputId> importedOutputs;</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>  Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span> </div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> BindableLayer* <span class="keyword">const</span> outputLayer : graph.GetOutputLayers())</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="keyword">auto</span> inputTensorHandle = m_PreImportedOutputHandles[outputIndex].m_TensorHandle.get();</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="keywordflow">if</span> (!inputTensorHandle)</div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  {</div><div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>  outputIndex++;</div><div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <span class="keywordflow">continue</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> </div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  <span class="keyword">auto</span> layerBindingId = outputLayer->GetBindingId();</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</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="l01499"></a><span class="lineno"> 1499</span>  {</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  <span class="keywordflow">return</span> outputTensor.first == layerBindingId;</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> </div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  <span class="keywordflow">if</span> (it == outputTensors.end())</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  {</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  outputIndex++;</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  }</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="keyword">const</span> <span class="keyword">auto</span> outputTensor = *it;</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  <span class="comment">// Check if the output memory can be imported</span></div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  <span class="keywordflow">if</span> (inputTensorHandle->CanBeImported(outputTensor.second.GetMemoryArea(), forceImportMemorySource)</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  && inputTensorHandle->Import(outputTensor.second.GetMemoryArea(), forceImportMemorySource))</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>  importedOutputs.push_back(outputIndex);</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  }</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  outputIndex++;</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>  <span class="keywordflow">return</span> importedOutputs;</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>  std::vector<ImportedOutputId> importedOutputs;</div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  Graph& graph = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span> </div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& outputTensor : outputTensors)</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>  <span class="keyword">auto</span> layerBindingId = outputTensor.first;</div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  <span class="keyword">auto</span> it = std::find_if(graph.GetOutputLayers().begin(), graph.GetOutputLayers().end(), [=](<span class="keyword">auto</span>* layer)</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  {</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  <span class="keywordflow">return</span> layer->GetBindingId() == layerBindingId;</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  });</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">if</span> (it == graph.GetOutputLayers().end())</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">throw</span> MemoryImportException(fmt::format(<span class="stringliteral">"ImportOutputs: Memory Import failed, unknown LayerBindingId: {}"</span>,</div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  layerBindingId));</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> </div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">Layer</a>* layer = *it;</div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  <span class="keywordflow">if</span> (layer->GetType() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</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">throw</span> InvalidArgumentException(<span class="stringliteral">"ImportOutputs: given layer not an OutputLayer"</span>);</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> </div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  <span class="keyword">auto</span>& backend = m_Backends.at(layer->GetBackendId());</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.xhtml#abd839f0f103c1ae19a4b38d59b869108">HasCapability</a>(BackendOptions::BackendOption{<span class="stringliteral">"PreImportIOTensors"</span>, <span class="keyword">true</span>}, backend->GetCapabilities()))</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>  std::string er = backend->GetId();</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  er += <span class="stringliteral">" does not have PreImportIOTensors capability"</span>;</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  <span class="keywordflow">throw</span> BackendCapabilityException(er);</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  }</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="keyword">const</span> InputSlot& inputSlot = layer->GetInputSlots()[0];</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> factoryId = inputSlot.GetConnectedOutputSlot()->GetTensorHandleFactoryId();</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  <span class="keyword">const</span> TensorInfo& tensorInfo = inputSlot.GetConnectedOutputSlot()->GetTensorInfo();</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span> </div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(factoryId);</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(handleFactory);</div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span> </div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  ImportedTensorHandlePin importedTensorHandlePin{layerBindingId,</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  handleFactory->CreateTensorHandle(tensorInfo, <span class="keyword">false</span>)};</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span> </div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  ITensorHandle* tensorHandle = importedTensorHandlePin.m_TensorHandle.get();</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span> </div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.xhtml#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(tensorHandle->GetImportFlags(), m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>))</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">throw</span> MemoryImportException(fmt::format(<span class="stringliteral">"ImportInputs: Memory Import failed, backend: "</span></div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  <span class="stringliteral">"{} does not support importing from source {}"</span></div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  , factoryId, m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>));</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  }</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>  <span class="keywordflow">if</span> (tensorHandle->Import(outputTensor.second.GetMemoryArea(), m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#a3266436db920d1ca96b0afaadacf3972">m_OutputSource</a>))</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  {</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  importedOutputs.push_back(m_CurImportedOutputId++);</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">else</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>  <span class="keywordflow">throw</span> MemoryImportException(<span class="stringliteral">"ImportInputs: Memory Import failed"</span>);</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  }</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span> </div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  m_PreImportedOutputHandles.push_back(std::move(importedTensorHandlePin));</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> </div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  <span class="keywordflow">return</span> importedOutputs;</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span> }</div><div class="ttc" id="namespacearmnn_xhtml_abd839f0f103c1ae19a4b38d59b869108"><div class="ttname"><a href="namespacearmnn.xhtml#abd839f0f103c1ae19a4b38d59b869108">armnn::HasCapability</a></div><div class="ttdeci">bool HasCapability(const std::string &name, const BackendCapabilities &capabilities)</div><div class="ttdoc">Convenience function to check if a capability exists in a BackendCapabilites struct. </div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8cpp_source.xhtml#l00058">BackendHelper.cpp:58</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_ad3ab02a7f6310b35c59ca78b509905ca"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#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.xhtml#l00058">IRuntime.hpp:58</a></div></div> +<div class="ttc" id="namespacearmnn_serializer_xhtml_a9a8118be7780e95363d631cbca7e7800"><div class="ttname"><a href="namespacearmnn_serializer.xhtml#a9a8118be7780e95363d631cbca7e7800">armnnSerializer::Layer</a></div><div class="ttdeci">Layer</div><div class="ttdef"><b>Definition:</b> <a href="_armnn_schema__generated_8h_source.xhtml#l01249">ArmnnSchema_generated.h:1249</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml_ae5ecc42140a12c855554a4a621fc8456"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#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.xhtml#l00039">TensorHandleFactoryRegistry.cpp:39</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a32f4aa6a7089d877af08928139c2c277"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">armnn::ITensorHandleFactory::FactoryId</a></div><div class="ttdeci">std::string FactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00045">ITensorHandleFactory.hpp:45</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_a3266436db920d1ca96b0afaadacf3972"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#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.xhtml#l00065">IRuntime.hpp:65</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a84f86b4de5adf0b164e811c87051a0ee"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00041">MemorySources.hpp:41</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a390c87e27deac4f51af9533053b2ee14"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a390c87e27deac4f51af9533053b2ee14">◆ </a></span>IsAsyncEnabled()</h2> + +<div class="memitem"> +<div class="memproto"> +<table class="mlabels"> + <tr> + <td class="mlabels-left"> + <table class="memname"> + <tr> + <td class="memname">bool IsAsyncEnabled </td> + <td>(</td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> + </td> + <td class="mlabels-right"> +<span class="mlabels"><span class="mlabel">inline</span></span> </td> + </tr> +</table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8hpp_source.xhtml#l00095">95</a> of file <a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00721">RuntimeImpl::CreateWorkingMemHandle()</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00630">RuntimeImpl::EnqueueWorkload()</a>, and <a class="el" href="_runtime_8cpp_source.xhtml#l00682">RuntimeImpl::Execute()</a>.</p> +<div class="fragment"><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">return</span> m_NetworkProperties.<a class="code" href="structarmnn_1_1_i_network_properties.xhtml#ad3ab02a7f6310b35c59ca78b509905ca">m_AsyncEnabled</a>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div><div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml_ad3ab02a7f6310b35c59ca78b509905ca"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml#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.xhtml#l00058">IRuntime.hpp:58</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af75dd30cff3d42ff35ddd2b625b7e9ae"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af75dd30cff3d42ff35ddd2b625b7e9ae">◆ </a></span>MakeLoadedNetwork()</h2> + +<div class="memitem"> +<div class="memproto"> +<table class="mlabels"> + <tr> + <td class="mlabels-left"> + <table class="memname"> + <tr> + <td class="memname">std::unique_ptr< <a class="el" href="classarmnn_1_1_loaded_network.xhtml">LoadedNetwork</a> > MakeLoadedNetwork </td> + <td>(</td> + <td class="paramtype">std::unique_ptr< <a class="el" href="classarmnn_1_1_i_optimized_network.xhtml">IOptimizedNetwork</a> > </td> + <td class="paramname"><em>net</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::string & </td> + <td class="paramname"><em>errorMessage</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> & </td> + <td class="paramname"><em>networkProperties</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">arm::pipe::IProfilingService * </td> + <td class="paramname"><em>profilingService</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> + </td> + <td class="mlabels-right"> +<span class="mlabels"><span class="mlabel">static</span></span> </td> + </tr> +</table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00087">87</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="classarmnn_1_1_i_tensor_handle.xhtml#a5cceed8b707a09bf27eb61f17acf8a88">ITensorHandle::Allocate()</a>, <a class="el" href="_assert_8hpp_source.xhtml#l00014">ARMNN_ASSERT</a>, <a class="el" href="_logging_8hpp_source.xhtml#l00205">ARMNN_LOG</a>, <a class="el" href="_profiling_8hpp_source.xhtml#l00220">ARMNN_SCOPED_PROFILING_EVENT</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00015">armnn::BackendRegistryInstance()</a>, <a class="el" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::Constant</a>, <a class="el" href="_i_backend_internal_8cpp_source.xhtml#l00012">IBackendInternal::CreateMemoryManager()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#afd5a5e90515b31c0174f76ec8897e9b1">IBackendInternal::CreateWorkloadFactory()</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::error</a>, <a class="el" href="_i_backend_internal_8hpp_source.xhtml#l00170">IBackendInternal::GetCapabilities()</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00057">BackendRegistry::GetFactory()</a>, <a class="el" href="classarmnn_1_1_i_backend.xhtml#aa9fc23b7155bd678232eeb351059b748">IBackend::GetId()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00572">ProfilerManager::GetInstance()</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00150">BackendRegistry::GetMemoryOptimizerStrategies()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00187">Graph::GetNumInputs()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00188">Graph::GetNumOutputs()</a>, <a class="el" href="_backend_helper_8cpp_source.xhtml#l00058">armnn::HasCapability()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::Input</a>, <a class="el" href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00046">ITensorHandleFactory::LegacyFactoryId</a>, <a class="el" href="_i_runtime_8hpp_source.xhtml#l00058">INetworkProperties::m_AsyncEnabled</a>, <a class="el" href="_i_runtime_8hpp_source.xhtml#l00062">INetworkProperties::m_OutputNetworkDetailsMethod</a>, <a class="el" href="_working_mem_descriptor_8hpp_source.xhtml#l00021">WorkingMemDescriptor::m_Outputs</a>, <a class="el" href="_i_runtime_8hpp_source.xhtml#l00060">INetworkProperties::m_ProfilingEnabled</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">armnn::MemImport</a>, <a class="el" href="_numeric_cast_8hpp_source.xhtml#l00035">armnn::numeric_cast()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::Output</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00579">ProfilerManager::RegisterProfiler()</a>, <a class="el" href="_i_backend_internal_8cpp_source.xhtml#l00119">IBackendInternal::SupportsTensorAllocatorAPI()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00184">Graph::TopologicalSort()</a>, and <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00178">RuntimeImpl::LoadNetwork()</a>.</p> +<div class="fragment"><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> {</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  std::unique_ptr<LoadedNetwork> loadedNetwork;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keyword">auto</span> Fail = [&](<span class="keyword">const</span> std::exception& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) -> std::unique_ptr<LoadedNetwork></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  errorMessage = ToErrorMessage(<span class="stringliteral">"An error occurred when preparing the network workloads: "</span>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>) << errorMessage;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">return</span> std::unique_ptr<LoadedNetwork>();</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  };</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">try</span></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>  loadedNetwork.reset(<span class="keyword">new</span> LoadedNetwork(std::move(net), networkProperties, profilingService));</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_runtime_exception.xhtml">armnn::RuntimeException</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">error</a>)</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">return</span> Fail(error);</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>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>& error)</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">return</span> Fail(error);</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>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::runtime_error& error)</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>  <span class="keywordflow">return</span> Fail(error);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">return</span> loadedNetwork;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> }</div><div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00205">Logging.hpp:205</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acb5e100e5a9a3e7f6d1fd97512215282">armnn::BoostLogSeverityMapping::error</a></div></div> +<div class="ttc" id="classarmnn_1_1_runtime_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_runtime_exception.xhtml">armnn::RuntimeException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00120">Exceptions.hpp:120</a></div></div> +<div class="ttc" id="classarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">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.xhtml#l00046">Exceptions.hpp:46</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a091ea8d2d804c8902f3120fdf2a36512"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a091ea8d2d804c8902f3120fdf2a36512">◆ </a></span>RegisterDebugCallback()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void RegisterDebugCallback </td> + <td>(</td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a> & </td> + <td class="paramname"><em>func</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l02091">2091</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_backend_registry_8cpp_source.xhtml#l00015">armnn::BackendRegistryInstance()</a>, <a class="el" href="namespacearmnn.xhtml#a14d24d90ab4ba2956e92e27890ba4c91acb17869fe51048b5a5c4c6106551a255">armnn::Constant</a>, <a class="el" href="_backend_registry_8cpp_source.xhtml#l00128">BackendRegistry::GetAllocators()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00275">Layer::GetBackendId()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00056">InputSlot::GetConnectedOutputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00322">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00243">Layer::GetInputSlots()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00143">OutputSlot::GetNumConnections()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00244">Layer::GetOutputSlots()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle.xhtml#a437893b8dcf58a0b68b70e1ad7933be6">ITensorHandle::GetParent()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00271">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::Input</a>, <a class="el" href="_memory_manager_8hpp_source.xhtml#l00034">BufferStorage::m_BufferSize</a>, <a class="el" href="_memory_manager_8hpp_source.xhtml#l00022">TensorMemory::m_Offset</a>, <a class="el" href="_memory_manager_8hpp_source.xhtml#l00032">BufferStorage::m_TensorMemoryVector</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::Output</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00184">Graph::TopologicalSort()</a>, and <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_runtime_8cpp_source.xhtml#l00752">RuntimeImpl::RegisterDebugCallback()</a>.</p> +<div class="fragment"><div class="line"><a name="l02092"></a><span class="lineno"> 2092</span> {</div><div class="line"><a name="l02093"></a><span class="lineno"> 2093</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& workloadPtr: m_WorkloadQueue)</div><div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>  {</div><div class="line"><a name="l02095"></a><span class="lineno"> 2095</span>  workloadPtr.get()->RegisterDebugCallback(func);</div><div class="line"><a name="l02096"></a><span class="lineno"> 2096</span>  }</div><div class="line"><a name="l02097"></a><span class="lineno"> 2097</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ae41171032a9c106c1fd4b5991045eb0b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ae41171032a9c106c1fd4b5991045eb0b">◆ </a></span>SendNetworkStructure()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">void SendNetworkStructure </td> + <td>(</td> + <td class="paramtype">arm::pipe::IProfilingService & </td> + <td class="paramname"><em>profilingService</em></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_loaded_network_8cpp_source.xhtml#l00563">563</a> of file <a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_profiling_8hpp_source.xhtml#l00220">ARMNN_SCOPED_PROFILING_EVENT</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::Input</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::Output</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00184">Graph::TopologicalSort()</a>, and <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Undefined</a>.</p> +<div class="fragment"><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> {</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">"LoadNetwork_SendNetworkStructure"</span>);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  ProfilingGuid networkGuid = m_OptimizedNetwork->GetGuid();</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>  std::unique_ptr<TimelineUtilityMethods> timelineUtils =</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  TimelineUtilityMethods::GetTimelineUtils(profilingService);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  timelineUtils->CreateTypedEntity(networkGuid, LabelsAndEventClasses::NETWORK_GUID);</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span> </div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : order)</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  {</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="comment">// Add layer to the post-optimisation network structure</span></div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  AddLayerStructure(timelineUtils, *layer, networkGuid);</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keywordflow">switch</span> (layer->GetType())</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  {</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  {</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="comment">// Inputs and outputs are treated in a special way - see EnqueueInput() and EnqueueOutput().</span></div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">default</span>:</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>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& workload : m_WorkloadQueue)</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>  <span class="comment">// Add workload to the post-optimisation network structure</span></div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  AddWorkloadStructure(timelineUtils, workload, *layer);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  }</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">break</span>;</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>  }</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">// Commit to send the post-optimisation network structure</span></div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  timelineUtils->Commit();</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span> }</div><div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div> +<div class="ttc" id="_profiling_8hpp_xhtml_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.xhtml#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.xhtml#l00220">Profiling.hpp:220</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div> +</div><!-- fragment --> +</div> +</div> +<hr/>The documentation for this class was generated from the following files:<ul> +<li>src/armnn/<a class="el" href="_loaded_network_8hpp_source.xhtml">LoadedNetwork.hpp</a></li> +<li>src/armnn/<a class="el" href="_loaded_network_8cpp_source.xhtml">LoadedNetwork.cpp</a></li> +</ul> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- 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