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<div class="textblock"><code>#include "<a class="el" href="_graph_utils_8hpp_source.xhtml">../GraphUtils.hpp</a>"</code><br />
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<p class="definition">Definition at line <a class="el" href="_add_broadcast_reshape_layer_tests_8cpp_source.xhtml#l00015">15</a> of file <a class="el" href="_add_broadcast_reshape_layer_tests_8cpp_source.xhtml">AddBroadcastReshapeLayerTests.cpp</a>.</p>
<p class="reference">References <a class="el" href="_graph_8hpp_source.xhtml#l00417">Graph::AddLayer()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00175">Graph::cbegin()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00177">Graph::cend()</a>, <a class="el" href="_test_utils_8hpp_source.xhtml#l00021">CheckSequence()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00083">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00316">Layer::GetInputSlot()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00195">TensorInfo::GetNumDimensions()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00318">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00063">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_optimizer_8hpp_source.xhtml#l00043">armnn::MakeOptimizations()</a>, <a class="el" href="_optimizer_8cpp_source.xhtml#l00016">Optimizer::Pass()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, and <a class="el" href="_layer_8cpp_source.xhtml#l00058">OutputSlot::SetTensorInfo()</a>.</p>
<div class="fragment"><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="keyword">using namespace </span>optimizations;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keywordtype">void</span> AddBroadcastReshapeLayerOptimizerTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info0,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info1,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">const</span> std::string& reshapeLayerName,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& expectedReshapeShape,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> expectedDataType)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</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">auto</span> input0 = 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">"input0"</span>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">auto</span> input1 = 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>>(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">auto</span> add = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>>(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">auto</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="l00032"></a><span class="lineno"> 32</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  add-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  input0->GetOutputSlot().Connect(add-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(add-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  add-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  &IsLayerOfType<OutputLayer>));</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="comment">// Run optimizer</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// Broadcast reshape layer has been added to the graph correctly</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  &IsLayerOfType<OutputLayer>));</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>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, reshapeLayerName);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  CHECK(reshapeLayer);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">auto</span> addedReshapeTensorInfo = reshapeLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// Tensorshape and the data type are correct</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  CHECK((addedReshapeTensorInfo.GetShape() == expectedReshapeShape));</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  CHECK((addedReshapeTensorInfo.GetDataType() == expectedDataType));</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> }</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayerSimpleTest"</span>)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 1 }, DataType::Float32);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  AddBroadcastReshapeLayerOptimizerTest(info0, info1, info0, <span class="stringliteral">"Reshape_for:add-1"</span>,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 1, 1 }),</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  DataType::Float32);</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> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayer1DTest"</span>)</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> {</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 5 }, DataType::Float32);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 1, 1, 5 }, DataType::Float32);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  AddBroadcastReshapeLayerOptimizerTest(info0, info1, outputInfo, <span class="stringliteral">"Reshape_for:add-1"</span>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 1, 5 }),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  DataType::Float32);</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> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayer2DTest"</span>)</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  AddBroadcastReshapeLayerOptimizerTest(info0, info1, outputInfo, <span class="stringliteral">"Reshape_for:add-1"</span>,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 3, 5 }),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  DataType::Float32);</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> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayer3DTest"</span>)</div><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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 2, 1, 1, 1 }, DataType::Float32);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 3, 4, 5 }, DataType::Float32);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 2, 3, 4, 5 }, DataType::Float32);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  AddBroadcastReshapeLayerOptimizerTest(info0, info1, outputInfo, <span class="stringliteral">"Reshape_for:add-1"</span>,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 3, 4, 5 }),</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  DataType::Float32);</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> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayer3DMergedTest"</span>)</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> {</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 2, 3, 1, 1 }, DataType::Float32);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 3, 4, 5 }, DataType::Float32);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 2, 3, 4, 5 }, DataType::Float32);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  AddBroadcastReshapeLayerOptimizerTest(info0, info1, outputInfo, <span class="stringliteral">"Reshape_for:add-1"</span>,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 3, 4, 5 }),</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  DataType::Float32);</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> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayerSubtractionTest"</span>)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 5 }, DataType::Float32);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 3, 5 }, DataType::Float32);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">auto</span> input0 = 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">"input0"</span>);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">auto</span> input1 = 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>>(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">auto</span> sub = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>>(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">auto</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="l00126"></a><span class="lineno"> 126</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  sub-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  input0->GetOutputSlot().Connect(sub-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(sub-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  sub-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  &IsLayerOfType<SubtractionLayer>,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// Broadcast reshape layer has been added to the graph correctly</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  &IsLayerOfType<SubtractionLayer>,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:sub-0"</span>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  CHECK(reshapeLayer);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">auto</span> addedReshapeTensorInfo = reshapeLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// Tensorshape and the data type are correct</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  CHECK((addedReshapeTensorInfo.GetShape() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 1, 5 })));</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  CHECK((addedReshapeTensorInfo.GetDataType() == DataType::Float32));</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayerDivisionTest"</span>)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 4, 5 }, DataType::QAsymmS8);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 1, 2, 4, 5 }, DataType::QAsymmS8);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 4, 5 }, DataType::QAsymmS8);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keyword">auto</span> input0 = 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">"input0"</span>);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keyword">auto</span> input1 = 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>>(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">auto</span> div = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>>(<span class="stringliteral">"div"</span>);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keyword">auto</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="l00171"></a><span class="lineno"> 171</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  div-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  input0->GetOutputSlot().Connect(div-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(div-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  div-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  &IsLayerOfType<DivisionLayer>,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// Broadcast reshape layer has been added to the graph correctly</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  &IsLayerOfType<DivisionLayer>,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:div-0"</span>);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  CHECK(reshapeLayer);</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">auto</span> addedReshapeTensorInfo = reshapeLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// Tensorshape and the data type are correct</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  CHECK((addedReshapeTensorInfo.GetShape() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 4, 5 })));</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  CHECK((addedReshapeTensorInfo.GetDataType() == DataType::QAsymmS8));</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> }</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> TEST_CASE(<span class="stringliteral">"AddBroadcastReshapeLayerMultiplicationTest"</span>)</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keyword">auto</span> input0 = 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">"input0"</span>);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keyword">auto</span> input1 = 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>>(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keyword">auto</span> mul = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>>(<span class="stringliteral">"mul"</span>);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keyword">auto</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="l00216"></a><span class="lineno"> 216</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  input0->GetOutputSlot().Connect(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="comment">// Broadcast reshape layer has been added to the graph correctly</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:mul-0"</span>);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  CHECK(reshapeLayer);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keyword">auto</span> addedReshapeTensorInfo = reshapeLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="comment">// Tensorshape and the data type are correct</span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  CHECK((addedReshapeTensorInfo.GetShape() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({ 1, 1, 3, 5 })));</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  CHECK((addedReshapeTensorInfo.GetDataType() == DataType::QAsymmU8));</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> }</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> TEST_CASE(<span class="stringliteral">"AddNoBroadcastReshapeLayerTest"</span>)</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> {</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 1, 1, 1 }, DataType::QAsymmU8);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> </div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">auto</span> input0 = 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">"input0"</span>);</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keyword">auto</span> input1 = 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>>(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keyword">auto</span> mul = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>>(<span class="stringliteral">"mul"</span>);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keyword">auto</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="l00261"></a><span class="lineno"> 261</span>  input0-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  input0->GetOutputSlot().Connect(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  input1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="comment">// Broadcast reshape layer has not been added to the graph</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> </div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:mul-0"</span>);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  CHECK(!reshapeLayer);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> }</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> TEST_CASE(<span class="stringliteral">"ReshapeParentConstLayerTest"</span>)</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> {</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info0({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> info1({ 5 }, DataType::QAsymmU8, 0.0f, 0, <span class="keyword">true</span>);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 3, 5 }, DataType::QAsymmU8);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keyword">auto</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="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">auto</span> constant = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(<span class="stringliteral">"constant"</span>);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keyword">auto</span> mul = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>>(<span class="stringliteral">"mul"</span>);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keyword">auto</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="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  uint8_t tensor[] = { 1, 1, 1, 1, 1 };</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(info1, &tensor));</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info0);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  constant-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info1);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  input->GetOutputSlot().Connect(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  constant-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(mul-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  mul-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  &IsLayerOfType<ConstantLayer>,</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="comment">// Broadcast reshape layer has not been added to the graph</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  &IsLayerOfType<ConstantLayer>,</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  &IsLayerOfType<MultiplicationLayer>,</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> </div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> expectedShape = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ 1, 1, 1, 5 };</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  CHECK(constant->m_LayerOutput.get()->GetTensorInfo().GetShape() == expectedShape);</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  CHECK(constant->m_LayerOutput.get()->GetTensorInfo().GetNumDimensions() == info0.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:mul-0"</span>);</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  CHECK(!reshapeLayer);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> }</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> TEST_CASE(<span class="stringliteral">"ReshapeParentConstAddLayerMultipleConnectionsTest"</span>)</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="comment">// In this test case we recreate the situation where an Addition layer has</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="comment">// a constant second term, e.g. [1,512] + [1]. The AddBroadcastReshapeLayer</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="comment">// should modify the constant tensor info to match the number of dimensions.</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="comment">// However, if this constant term is being reused elsewhere then we shouldn't</span></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// modify it. Instead we insert a resize layer.</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// What we'll do is have two sequential add layers both using the same const tensor.</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo({ 1, 512 }, DataType::Float32);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> constantTermInfo({ 1 }, DataType::Float32, 0.0f, 0, <span class="keyword">true</span>);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 512 }, DataType::Float32);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keyword">auto</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="l00353"></a><span class="lineno"> 353</span>  <span class="keyword">auto</span> constant = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(<span class="stringliteral">"constant"</span>);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keyword">auto</span> add1 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>>(<span class="stringliteral">"add1"</span>);</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keyword">auto</span> add2 = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>>(<span class="stringliteral">"add2"</span>);</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keyword">auto</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="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  constant-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(constantTermInfo);</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordtype">float</span> tensor[] = { 2.0f };</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(constantTermInfo, &tensor));</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  add1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  input->GetOutputSlot().Connect(add1-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  constant-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(add1-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  add1-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(add2-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  add2-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="comment">// This second connection should prevent the modification of the const output tensor.</span></div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  constant-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(add2-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1));</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  &IsLayerOfType<ConstantLayer>,</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="comment">// Run optimizer</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="comment">// Broadcast reshape should have been added before each addition layer.</span></div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  CHECK(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(),</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  &IsLayerOfType<ConstantLayer>,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  &IsLayerOfType<ReshapeLayer>,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  &IsLayerOfType<AdditionLayer>,</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="comment">// Ensure the output shape of the constant hasn't changed.</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  CHECK(constant->m_LayerOutput.get()->GetTensorInfo().GetShape() == constantTermInfo.GetShape());</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="comment">// There should be two extra reshape layers with appropriate names.</span></div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:add1-1"</span>);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> reshapeLayer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"Reshape_for:add2-1"</span>);</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  CHECK(reshapeLayer1);</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  CHECK(reshapeLayer2);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> }</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> </div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> }</div><div class="ttc" id="classarmnn_1_1_constant_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_constant_layer.xhtml">armnn::ConstantLayer</a></div><div class="ttdoc">A layer that the constant data can be bound to. </div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.xhtml#l00015">ConstantLayer.hpp:15</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &&... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00043">Optimizer.hpp:43</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</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#l00152">Tensor.hpp:152</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#l00417">Graph.hpp:417</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a98b1109a9006f8cc7d4566146a3bd737"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">armnn::Graph::cbegin</a></div><div class="ttdeci">ConstIterator cbegin() const</div><div class="ttdoc">Returns const iterator pointing to the beginning of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00175">Graph.hpp:175</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00083">Layer.cpp:83</a></div></div>
<div class="ttc" id="classarmnn_1_1_optimizer_xhtml_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a></div><div class="ttdeci">static void Pass(Graph &graph, const Optimizations &optimizations)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8cpp_source.xhtml#l00016">Optimizer.cpp:16</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00316">Layer.hpp:316</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00035">Types.hpp:35</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</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#l00030">Graph.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_addition_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_addition_layer.xhtml">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.xhtml#l00013">AdditionLayer.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_subtraction_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_subtraction_layer.xhtml">armnn::SubtractionLayer</a></div><div class="ttdoc">This layer represents a subtraction operation. </div><div class="ttdef"><b>Definition:</b> <a href="_subtraction_layer_8hpp_source.xhtml#l00014">SubtractionLayer.hpp:14</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="_test_utils_8hpp_xhtml_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.xhtml#l00021">TestUtils.hpp:21</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div>
<div class="ttc" id="classarmnn_1_1_division_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_division_layer.xhtml">armnn::DivisionLayer</a></div><div class="ttdoc">This layer represents a division operation. </div><div class="ttdef"><b>Definition:</b> <a href="_division_layer_8hpp_source.xhtml#l00014">DivisionLayer.hpp:14</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00318">Layer.hpp:318</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a02fd29b6dc3e21fbe4484362d85893bc"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">armnn::Graph::cend</a></div><div class="ttdeci">ConstIterator cend() const</div><div class="ttdoc">Returns const iterator pointing to the end of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00177">Graph.hpp:177</a></div></div>
<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a4fc55afb4885278ad1510b2c4307af76"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">armnn::optimizations::AddBroadcastReshapeLayer</a></div><div class="ttdeci">OptimizeForType< Layer, AddBroadcastReshapeLayerImpl > AddBroadcastReshapeLayer</div><div class="ttdef"><b>Definition:</b> <a href="_add_broadcast_reshape_layer_8hpp_source.xhtml#l00094">AddBroadcastReshapeLayer.hpp:94</a></div></div>
<div class="ttc" id="classarmnn_1_1_multiplication_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_multiplication_layer.xhtml">armnn::MultiplicationLayer</a></div><div class="ttdoc">This layer represents a multiplication operation. </div><div class="ttdef"><b>Definition:</b> <a href="_multiplication_layer_8hpp_source.xhtml#l00014">MultiplicationLayer.hpp:14</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00063">Layer.cpp:63</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</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#l00210">Layer.hpp:210</a></div></div>
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