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<div class="title">CreateWorkloadClNeon.hpp</div> </div>
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<a href="_create_workload_cl_neon_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_create_workload_8hpp.xhtml">test/CreateWorkload.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_mem_copy_workload_8hpp.xhtml">backendsCommon/MemCopyWorkload.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_ref_workload_factory_8hpp.xhtml">reference/RefWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_ref_tensor_handle_8hpp.xhtml">reference/RefTensorHandle.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#if defined(ARMCOMPUTECL_ENABLED)</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_cl_tensor_handle_8hpp.xhtml">cl/ClTensorHandle.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#if defined(ARMCOMPUTENEON_ENABLED)</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_neon_tensor_handle_8hpp.xhtml">neon/NeonTensorHandle.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> {</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="keyword">using namespace </span><a class="code" href="namespacestd.xhtml">std</a>;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">template</span><<span class="keyword">typename</span> IComputeTensorHandle></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> boost::test_tools::predicate_result CompareTensorHandleShape(IComputeTensorHandle* tensorHandle,</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  std::initializer_list<unsigned int> expectedDimensions)</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  arm_compute::ITensorInfo* <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = tensorHandle->GetTensor().info();</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">auto</span> infoNumDims = info->num_dimensions();</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">auto</span> numExpectedDims = expectedDimensions.size();</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">if</span> (infoNumDims != numExpectedDims)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  boost::test_tools::predicate_result res(<span class="keyword">false</span>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  res.message() << <span class="stringliteral">"Different number of dimensions ["</span> << info->num_dimensions()</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  << <span class="stringliteral">"!="</span> << expectedDimensions.size() << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">return</span> res;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  }</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">size_t</span> i = info->num_dimensions() - 1;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> expectedDimension : expectedDimensions)</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">if</span> (info->dimension(i) != expectedDimension)</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  {</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  boost::test_tools::predicate_result res(<span class="keyword">false</span>);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  res.message() << <span class="stringliteral">"For dimension "</span> << i <<</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="stringliteral">" expected size "</span> << expectedDimension <<</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="stringliteral">" got "</span> << info->dimension(i);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">return</span> res;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  i--;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> }</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="keyword">template</span><<span class="keyword">typename</span> IComputeTensorHandle></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="keywordtype">void</span> CreateMemCopyWorkloads(<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">IWorkloadFactory</a>& factory)</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a> registry;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> refFactory;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="comment">// Creates the layers we're testing.</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> layer1 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_mem_copy_layer.xhtml">MemCopyLayer</a>>(<span class="stringliteral">"layer1"</span>);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> layer2 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_mem_copy_layer.xhtml">MemCopyLayer</a>>(<span class="stringliteral">"layer2"</span>);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// Creates extra layers.</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// Connects up.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> tensorInfo({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer1, tensorInfo);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer1, layer2, tensorInfo);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer2, output, tensorInfo);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  input->CreateTensorHandles(registry, refFactory);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  layer1-><a class="code" href="classarmnn_1_1_layer.xhtml#a3ff62126ec713a2708e5fbaa6146a7de">CreateTensorHandles</a>(registry, factory);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  layer2->CreateTensorHandles(registry, refFactory);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  output->CreateTensorHandles(registry, refFactory);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// make the workloads and check them</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">auto</span> workload1 = MakeAndCheckWorkload<CopyMemGenericWorkload>(*layer1, factory);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keyword">auto</span> workload2 = MakeAndCheckWorkload<CopyMemGenericWorkload>(*layer2, refFactory);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">MemCopyQueueDescriptor</a> queueDescriptor1 = workload1->GetData();</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  BOOST_TEST(queueDescriptor1.m_Inputs.size() == 1);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  BOOST_TEST(queueDescriptor1.m_Outputs.size() == 1);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keyword">auto</span> inputHandle1 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor1.m_Inputs[0]);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">auto</span> outputHandle1 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor1.m_Outputs[0]);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  BOOST_TEST((inputHandle1->GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(outputHandle1, {2, 3}));</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>  <a class="code" href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">MemCopyQueueDescriptor</a> queueDescriptor2 = workload2->GetData();</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  BOOST_TEST(queueDescriptor2.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>.size() == 1);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  BOOST_TEST(queueDescriptor2.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>.size() == 1);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keyword">auto</span> inputHandle2 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor2.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">auto</span> outputHandle2 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor2.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(inputHandle2, {2, 3}));</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  BOOST_TEST((outputHandle2->GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</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> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> } <span class="comment">//namespace</span></div><div class="ttc" id="_mem_copy_workload_8hpp_xhtml"><div class="ttname"><a href="_mem_copy_workload_8hpp.xhtml">MemCopyWorkload.hpp</a></div></div>
<div class="ttc" id="_ref_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_factory_8hpp.xhtml">RefWorkloadFactory.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00397">Graph.hpp:397</a></div></div>
<div class="ttc" id="_neon_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_neon_tensor_handle_8hpp.xhtml">NeonTensorHandle.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="_create_workload_8hpp_xhtml"><div class="ttname"><a href="_create_workload_8hpp.xhtml">CreateWorkload.hpp</a></div></div>
<div class="ttc" id="namespacestd_xhtml"><div class="ttname"><a href="namespacestd.xhtml">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00147">BackendId.hpp:147</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.xhtml#l00013">OutputLayer.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_ref_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_workload_factory.xhtml">armnn::RefWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_factory_8hpp_source.xhtml#l00030">RefWorkloadFactory.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_mem_copy_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_mem_copy_layer.xhtml">armnn::MemCopyLayer</a></div><div class="ttdoc">This layer represents a memory copy operation. </div><div class="ttdef"><b>Definition:</b> <a href="_mem_copy_layer_8hpp_source.xhtml#l00013">MemCopyLayer.hpp:13</a></div></div>
<div class="ttc" id="_ref_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_ref_tensor_handle_8hpp.xhtml">RefTensorHandle.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">armnn::TensorHandleFactoryRegistry</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8hpp_source.xhtml#l00020">TensorHandleFactoryRegistry.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_mem_copy_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">armnn::MemCopyQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00058">WorkloadData.hpp:58</a></div></div>
<div class="ttc" id="_cl_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cl_tensor_handle_8hpp.xhtml">ClTensorHandle.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00031">WorkloadData.hpp:31</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a3ff62126ec713a2708e5fbaa6146a7de"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a3ff62126ec713a2708e5fbaa6146a7de">armnn::Layer::CreateTensorHandles</a></div><div class="ttdeci">virtual void CreateTensorHandles(const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00240">Layer.cpp:240</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div>
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