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95 <div class="headertitle">
96<div class="title">WorkloadFactory.cpp</div> </div>
97</div><!--header-->
98<div class="contents">
99<a href="_workload_factory_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div>
100<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.</span></div>
101<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
102<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
103<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
104<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_layer_8hpp.html">Layer.hpp</a>&gt;</span></div>
105<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_layers_fwd_8hpp.html">LayersFwd.hpp</a>&gt;</span></div>
106<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160; </div>
107<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_types_8hpp.html">armnn/Types.hpp</a>&gt;</span></div>
108<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_backend_internal_8hpp.html">armnn/backends/IBackendInternal.hpp</a>&gt;</span></div>
109<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_layer_support_8hpp.html">armnn/backends/ILayerSupport.hpp</a>&gt;</span></div>
110<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_backend_helper_8hpp.html">armnn/BackendHelper.hpp</a>&gt;</span></div>
111<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_backend_registry_8hpp.html">armnn/BackendRegistry.hpp</a>&gt;</span></div>
112<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_polymorphic_downcast_8hpp.html">armnn/utility/PolymorphicDowncast.hpp</a>&gt;</span></div>
113<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_transform_iterator_8hpp.html">armnn/utility/TransformIterator.hpp</a>&gt;</span></div>
114<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; </div>
115<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_factory_8hpp.html">armnn/backends/WorkloadFactory.hpp</a>&gt;</span></div>
116<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; </div>
117<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="preprocessor">#include &lt;sstream&gt;</span></div>
118<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; </div>
119<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
120<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;{</div>
121<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; </div>
122<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="keyword">namespace</span></div>
123<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;{</div>
124<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="keyword">using</span> LayerList = std::list&lt;Layer*&gt;;</div>
125<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="keyword">using</span> Iterator = LayerList::const_iterator; <span class="comment">// Const so pointers in the list can&#39;t be modified externally.</span></div>
126<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; </div>
127<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="keyword">const</span> TensorInfo OverrideDataType(<span class="keyword">const</span> TensorInfo&amp; info, Optional&lt;DataType&gt; type)</div>
128<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;{</div>
129<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordflow">if</span> (!type)</div>
130<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; {</div>
131<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div>
132<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; }</div>
133<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; </div>
134<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keywordflow">return</span> TensorInfo(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetShape(),</div>
135<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; type.value(),</div>
136<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetQuantizationScale(),</div>
137<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetQuantizationOffset(),</div>
138<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.IsConstant());</div>
139<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;}</div>
140<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; </div>
141<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;} <span class="comment">// anonymous namespace</span></div>
142<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; </div>
143<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;<span class="keyword">inline</span> <a class="code" href="classarmnn_1_1_optional.html">armnn::Optional&lt;armnn::DataType&gt;</a> <a class="code" href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(<a class="code" href="classarmnn_1_1_optional.html">armnn::Optional&lt;armnn::DataType&gt;</a> weightsType)</div>
144<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;{</div>
145<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keywordflow">if</span> (!weightsType)</div>
146<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; {</div>
147<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keywordflow">return</span> weightsType;</div>
148<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; }</div>
149<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; </div>
150<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keywordflow">switch</span>(weightsType.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>())</div>
151<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; {</div>
152<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>:</div>
153<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>:</div>
154<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>:</div>
155<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keywordflow">return</span> weightsType;</div>
156<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>:</div>
157<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>:</div>
158<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a>:</div>
159<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>:</div>
160<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>;</div>
161<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">default</span>:</div>
162<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">&quot;GetBiasTypeFromWeightsType(): Unsupported data type.&quot;</span>);</div>
163<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; }</div>
164<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keywordflow">return</span> <a class="code" href="structarmnn_1_1_empty_optional.html">armnn::EmptyOptional</a>();</div>
165<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;}</div>
166<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; </div>
167<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; </div>
168<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;<span class="keywordtype">bool</span> IWorkloadFactory::IsLayerConfigurationSupported(<span class="keyword">const</span> BackendId&amp; backendId,</div>
169<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">const</span> IConnectableLayer&amp; connectableLayer,</div>
170<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; Optional&lt;DataType&gt; dataType,</div>
171<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; std::string&amp; outReasonIfUnsupported,</div>
172<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>&amp; modelOptions)</div>
173<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;{</div>
174<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; Optional&lt;std::string&amp;&gt; reason = outReasonIfUnsupported;</div>
175<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordtype">bool</span> result;</div>
176<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keyword">const</span> Layer&amp; layer = *(PolymorphicDowncast&lt;const Layer*&gt;(&amp;connectableLayer));</div>
177<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; </div>
178<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keyword">auto</span> <span class="keyword">const</span>&amp; backendRegistry = <a class="code" href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>();</div>
179<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keywordflow">if</span> (!backendRegistry.IsBackendRegistered(backendId))</div>
180<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; {</div>
181<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; std::stringstream ss;</div>
182<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; ss &lt;&lt; connectableLayer.GetName() &lt;&lt; <span class="stringliteral">&quot; is not supported on &quot;</span> &lt;&lt; backendId</div>
183<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; &lt;&lt; <span class="stringliteral">&quot; because this backend is not registered.&quot;</span>;</div>
184<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; </div>
185<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; outReasonIfUnsupported = ss.str();</div>
186<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
187<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; }</div>
188<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; </div>
189<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keyword">auto</span> backendFactory = backendRegistry.GetFactory(backendId);</div>
190<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keyword">auto</span> backendObject = backendFactory();</div>
191<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keyword">auto</span> layerSupport = backendObject-&gt;GetLayerSupport(modelOptions);</div>
192<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keyword">auto</span> layerSupportObject = LayerSupportHandle(layerSupport, backendId);</div>
193<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; </div>
194<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keywordflow">switch</span>(layer.GetType())</div>
195<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; {</div>
196<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36">LayerType::Activation</a>:</div>
197<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; {</div>
198<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ActivationLayer*&gt;(&amp;layer);</div>
199<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
200<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
201<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; result = layerSupportObject.IsActivationSupported(</div>
202<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; OverrideDataType(input, dataType),</div>
203<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; OverrideDataType(output, dataType),</div>
204<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; cLayer-&gt;GetParameters(),</div>
205<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; reason);</div>
206<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keywordflow">break</span>;</div>
207<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; }</div>
208<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">LayerType::Addition</a>:</div>
209<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; {</div>
210<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
211<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
212<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
213<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
214<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; result = layerSupportObject.IsAdditionSupported(</div>
215<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; OverrideDataType(input0, dataType),</div>
216<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; OverrideDataType(input1, dataType),</div>
217<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; OverrideDataType(output, dataType),</div>
218<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; reason);</div>
219<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
220<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="keywordflow">break</span>;</div>
221<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; }</div>
222<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c">LayerType::ArgMinMax</a>:</div>
223<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; {</div>
224<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ArgMinMaxLayer*&gt;(&amp;layer);</div>
225<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keyword">const</span> ArgMinMaxDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
226<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; </div>
227<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
228<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
229<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; result = layerSupportObject.IsArgMinMaxSupported(</div>
230<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; OverrideDataType(input, dataType),</div>
231<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; OverrideDataType(output, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>),</div>
232<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; descriptor,</div>
233<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; reason);</div>
234<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <span class="keywordflow">break</span>;</div>
235<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; }</div>
236<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9882ff3cfed27d6161c20a305e7a3484">LayerType::BatchMatMul</a>:</div>
237<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; {</div>
238<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const BatchMatMulLayer*&gt;(&amp;layer);</div>
239<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keyword">const</span> BatchMatMulDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
240<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; </div>
241<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
242<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
243<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
244<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; result = layerSupportObject.IsBatchMatMulSupported(</div>
245<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; OverrideDataType(input0, dataType),</div>
246<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; OverrideDataType(input1, dataType),</div>
247<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; OverrideDataType(output, dataType),</div>
248<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; descriptor,</div>
249<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; reason);</div>
250<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="keywordflow">break</span>;</div>
251<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; }</div>
252<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">LayerType::BatchNormalization</a>:</div>
253<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; {</div>
254<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const BatchNormalizationLayer*&gt;(&amp;layer);</div>
255<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
256<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
257<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keyword">const</span> TensorInfo&amp; mean = cLayer-&gt;m_Mean-&gt;GetTensorInfo();</div>
258<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keyword">const</span> TensorInfo&amp; var = cLayer-&gt;m_Variance-&gt;GetTensorInfo();</div>
259<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keyword">const</span> TensorInfo&amp; beta = cLayer-&gt;m_Beta-&gt;GetTensorInfo();</div>
260<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <span class="keyword">const</span> TensorInfo&amp; gamma = cLayer-&gt;m_Gamma-&gt;GetTensorInfo();</div>
261<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; result = layerSupportObject.IsBatchNormalizationSupported(</div>
262<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; OverrideDataType(input, dataType),</div>
263<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; OverrideDataType(output, dataType),</div>
264<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; OverrideDataType(mean, dataType),</div>
265<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; OverrideDataType(var, dataType),</div>
266<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; OverrideDataType(beta, dataType),</div>
267<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; OverrideDataType(gamma, dataType),</div>
268<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; cLayer-&gt;GetParameters(),</div>
269<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; reason);</div>
270<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <span class="keywordflow">break</span>;</div>
271<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; }</div>
272<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">LayerType::BatchToSpaceNd</a>:</div>
273<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; {</div>
274<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
275<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
276<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const BatchToSpaceNdLayer*&gt;(&amp;layer);</div>
277<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; </div>
278<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; result = layerSupportObject.IsBatchToSpaceNdSupported(OverrideDataType(input, dataType),</div>
279<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; OverrideDataType(output, dataType),</div>
280<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; cLayer-&gt;GetParameters(),</div>
281<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; reason);</div>
282<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <span class="keywordflow">break</span>;</div>
283<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; }</div>
284<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6f7ce1d0822dea293ac2edc111e54ed">LayerType::BroadcastTo</a>:</div>
285<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; {</div>
286<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const BroadcastToLayer*&gt;(&amp;layer);</div>
287<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetConnection()-&gt;GetTensorInfo();</div>
288<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
289<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; </div>
290<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; result = layerSupportObject.IsBroadcastToSupported(OverrideDataType(input, dataType),</div>
291<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; OverrideDataType(output, dataType),</div>
292<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; cLayer-&gt;GetParameters(),</div>
293<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; reason);</div>
294<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; <span class="keywordflow">break</span>;</div>
295<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; }</div>
296<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a4cd9f3996d60790cd11c04f842ebc43c">LayerType::Cast</a>:</div>
297<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; {</div>
298<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
299<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
300<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; </div>
301<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; result = layerSupportObject.IsCastSupported(OverrideDataType(input, dataType),</div>
302<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; OverrideDataType(output, dataType),</div>
303<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; reason);</div>
304<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <span class="keywordflow">break</span>;</div>
305<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; }</div>
306<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0ca5f33c1d35fd4105d3a26a2823f9dd">LayerType::ChannelShuffle</a>:</div>
307<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; {</div>
308<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ChannelShuffleLayer*&gt;(&amp;layer);</div>
309<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; </div>
310<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
311<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetInputSlot(0).GetTensorInfo();</div>
312<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; </div>
313<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="keyword">const</span> ChannelShuffleDescriptor descriptor = cLayer-&gt;GetParameters();</div>
314<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; </div>
315<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; result = layerSupportObject.IsChannelShuffleSupported(OverrideDataType(input, dataType),</div>
316<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; OverrideDataType(output, dataType),</div>
317<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; descriptor,</div>
318<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; reason);</div>
319<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="keywordflow">break</span>;</div>
320<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; }</div>
321<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">LayerType::Comparison</a>:</div>
322<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; {</div>
323<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ComparisonLayer*&gt;(&amp;layer);</div>
324<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; </div>
325<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
326<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
327<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
328<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; </div>
329<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; result = layerSupportObject.IsComparisonSupported(OverrideDataType(input0, dataType),</div>
330<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; OverrideDataType(input1, dataType),</div>
331<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; OverrideDataType(output, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">DataType::Boolean</a>),</div>
332<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; cLayer-&gt;GetParameters(),</div>
333<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; reason);</div>
334<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; <span class="keywordflow">break</span>;</div>
335<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; }</div>
336<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>:</div>
337<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; {</div>
338<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
339<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; result = layerSupportObject.IsConstantSupported(OverrideDataType(output, dataType), reason);</div>
340<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="keywordflow">break</span>;</div>
341<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; }</div>
342<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">LayerType::ConvertFp16ToFp32</a>:</div>
343<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; {</div>
344<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
345<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
346<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; result = layerSupportObject.IsConvertFp16ToFp32Supported(input, output, reason);</div>
347<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="keywordflow">break</span>;</div>
348<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; }</div>
349<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">LayerType::ConvertFp32ToFp16</a>:</div>
350<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; {</div>
351<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
352<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
353<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; result = layerSupportObject.IsConvertFp32ToFp16Supported(input, output, reason);</div>
354<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="keywordflow">break</span>;</div>
355<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; }</div>
356<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">LayerType::Convolution2d</a>:</div>
357<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; {</div>
358<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const Convolution2dLayer*&gt;(&amp;layer);</div>
359<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; </div>
360<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="keyword">const</span> TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
361<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; dataType);</div>
362<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keyword">const</span> TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
363<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; </div>
364<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>(layer.GetInputSlot(1).GetConnection(),</div>
365<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="stringliteral">&quot;Convolution2dLayer: Weights should be connected as a Constant Layer.&quot;</span>);</div>
366<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keyword">const</span> TensorInfo weights = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(),</div>
367<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; dataType);</div>
368<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; </div>
369<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; <span class="keyword">const</span> Convolution2dDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
370<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; </div>
371<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; <span class="comment">// Construct optional biases object based on the value of m_BiasEnabled</span></div>
372<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; Optional&lt;TensorInfo&gt; biases;</div>
373<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div>
374<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; {</div>
375<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>(layer.GetInputSlot(2).GetConnection(),</div>
376<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; <span class="stringliteral">&quot;Convolution2dLayer:Bias should be connected as a Constant Layer.&quot;</span>);</div>
377<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; biases = OverrideDataType(layer.GetInputSlot(2).GetTensorInfo(),</div>
378<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <a class="code" href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(dataType));</div>
379<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; }</div>
380<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; </div>
381<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; result = layerSupportObject.IsConvolution2dSupported(</div>
382<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; input,</div>
383<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; output,</div>
384<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; descriptor,</div>
385<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; weights,</div>
386<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; biases,</div>
387<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; reason);</div>
388<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; <span class="keywordflow">break</span>;</div>
389<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; }</div>
390<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a583550d0f265fd3756f7de0e42c51953">LayerType::Convolution3d</a>:</div>
391<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; {</div>
392<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const Convolution3dLayer*&gt;(&amp;layer);</div>
393<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; </div>
394<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; <span class="keyword">const</span> TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
395<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; dataType);</div>
396<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; <span class="keyword">const</span> TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
397<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; </div>
398<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>(layer.GetInputSlot(1).GetConnection(),</div>
399<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="stringliteral">&quot;Convolution3dLayer: Weights should be connected as a Constant Layer.&quot;</span>);</div>
400<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="keyword">const</span> TensorInfo weights = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(),</div>
401<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; dataType);</div>
402<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; </div>
403<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; <span class="keyword">const</span> Convolution3dDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
404<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; </div>
405<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; <span class="comment">// Construct optional biases object based on the value of m_BiasEnabled</span></div>
406<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; Optional&lt;TensorInfo&gt; biases;</div>
407<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div>
408<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; {</div>
409<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; biases = OverrideDataType(layer.GetInputSlot(2).GetTensorInfo(),</div>
410<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; <a class="code" href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(dataType));</div>
411<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; }</div>
412<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; </div>
413<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; result = layerSupportObject.IsConvolution3dSupported(</div>
414<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; input,</div>
415<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; output,</div>
416<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; descriptor,</div>
417<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; weights,</div>
418<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; biases,</div>
419<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; reason);</div>
420<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; <span class="keywordflow">break</span>;</div>
421<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; }</div>
422<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba">LayerType::Debug</a>:</div>
423<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; {</div>
424<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
425<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
426<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; </div>
427<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; result = layerSupportObject.IsDebugSupported(OverrideDataType(input, dataType),</div>
428<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; OverrideDataType(output, dataType),</div>
429<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; reason);</div>
430<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; <span class="keywordflow">break</span>;</div>
431<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; }</div>
432<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d">LayerType::DepthToSpace</a>:</div>
433<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; {</div>
434<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const DepthToSpaceLayer*&gt;(&amp;layer);</div>
435<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; </div>
436<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
437<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
438<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; </div>
439<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; result = layerSupportObject.IsDepthToSpaceSupported(OverrideDataType(input, dataType),</div>
440<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; OverrideDataType(output, dataType),</div>
441<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; cLayer-&gt;GetParameters(),</div>
442<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; reason);</div>
443<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <span class="keywordflow">break</span>;</div>
444<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; }</div>
445<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">LayerType::DepthwiseConvolution2d</a>:</div>
446<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; {</div>
447<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const DepthwiseConvolution2dLayer*&gt;(&amp;layer);</div>
448<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
449<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; dataType);</div>
450<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
451<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160; <span class="keyword">const</span> TensorInfo&amp; weights = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(),</div>
452<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160; dataType);</div>
453<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160; </div>
454<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160; <span class="keyword">const</span> DepthwiseConvolution2dDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
455<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; </div>
456<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <span class="comment">// Construct optional biases object based on the value of m_BiasEnabled</span></div>
457<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; Optional&lt;TensorInfo&gt; biases;</div>
458<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div>
459<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; {</div>
460<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; biases = OverrideDataType(cLayer-&gt;GetInputSlot(2).GetTensorInfo(),</div>
461<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; <a class="code" href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(dataType));</div>
462<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; }</div>
463<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; </div>
464<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; result = layerSupportObject.IsDepthwiseConvolutionSupported(input,</div>
465<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; output,</div>
466<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; descriptor,</div>
467<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160; weights,</div>
468<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; biases,</div>
469<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; reason);</div>
470<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; <span class="keywordflow">break</span>;</div>
471<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160; }</div>
472<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d">LayerType::Dequantize</a>:</div>
473<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; {</div>
474<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
475<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
476<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; </div>
477<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; result = layerSupportObject.IsDequantizeSupported(input,</div>
478<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; OverrideDataType(output, dataType),</div>
479<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; reason);</div>
480<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160; <span class="keywordflow">break</span>;</div>
481<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; }</div>
482<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">LayerType::DetectionPostProcess</a>:</div>
483<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160; {</div>
484<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const DetectionPostProcessLayer*&gt;(&amp;layer);</div>
485<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160; <span class="keyword">const</span> TensorInfo&amp; boxEncodings = layer.GetInputSlot(0).GetTensorInfo();</div>
486<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160; <span class="keyword">const</span> TensorInfo&amp; scores = layer.GetInputSlot(1).GetTensorInfo();</div>
487<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>&#160; <span class="keyword">const</span> TensorInfo&amp; anchors = cLayer-&gt;m_Anchors-&gt;GetTensorInfo();</div>
488<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>&#160; </div>
489<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>&#160; <span class="keyword">const</span> TensorInfo&amp; detectionBoxes = layer.GetOutputSlot(0).GetTensorInfo();</div>
490<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>&#160; <span class="keyword">const</span> TensorInfo&amp; detectionClasses = layer.GetOutputSlot(1).GetTensorInfo();</div>
491<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>&#160; <span class="keyword">const</span> TensorInfo&amp; detectionScores = layer.GetOutputSlot(2).GetTensorInfo();</div>
492<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>&#160; <span class="keyword">const</span> TensorInfo&amp; numDetections = layer.GetOutputSlot(3).GetTensorInfo();</div>
493<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>&#160; </div>
494<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160; <span class="keyword">const</span> DetectionPostProcessDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
495<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; result = layerSupportObject.IsDetectionPostProcessSupported(boxEncodings,</div>
496<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; scores,</div>
497<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; anchors,</div>
498<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; detectionBoxes,</div>
499<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; detectionClasses,</div>
500<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; detectionScores,</div>
501<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; numDetections,</div>
502<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; descriptor,</div>
503<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160; reason);</div>
504<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; <span class="keywordflow">break</span>;</div>
505<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; }</div>
506<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">LayerType::ElementwiseBinary</a>:</div>
507<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; {</div>
508<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ElementwiseBinaryLayer*&gt;(&amp;layer);</div>
509<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160; </div>
510<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
511<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
512<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
513<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160; std::vector&lt;TensorInfo&gt; infos = { OverrideDataType(input0, dataType),</div>
514<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; OverrideDataType(input1, dataType),</div>
515<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; OverrideDataType(output, dataType) };</div>
516<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160; result = layerSupport-&gt;IsLayerSupported(<a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">LayerType::ElementwiseBinary</a>,</div>
517<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; infos,</div>
518<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160; cLayer-&gt;GetParameters(),</div>
519<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; EmptyOptional(),</div>
520<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; EmptyOptional(),</div>
521<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160; reason);</div>
522<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160; <span class="keywordflow">break</span>;</div>
523<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>&#160; }</div>
524<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7">LayerType::ElementwiseUnary</a>:</div>
525<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160; {</div>
526<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ElementwiseUnaryLayer*&gt;(&amp;layer);</div>
527<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>&#160; </div>
528<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
529<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
530<div class="line"><a name="l00432"></a><span class="lineno"> 432</span>&#160; </div>
531<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>&#160; result = layerSupportObject.IsElementwiseUnarySupported(OverrideDataType(input, dataType),</div>
532<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>&#160; OverrideDataType(output, dataType),</div>
533<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>&#160; cLayer-&gt;GetParameters(),</div>
534<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>&#160; reason);</div>
535<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>&#160; <span class="keywordflow">break</span>;</div>
536<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>&#160; }</div>
537<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb3e3f51c9107e26c9bccf9a188ce2ed">LayerType::Fill</a>:</div>
538<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160; {</div>
539<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const FillLayer*&gt;(&amp;layer);</div>
540<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
541<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
542<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; <span class="keyword">const</span> FillDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
543<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>&#160; </div>
544<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160; result = layerSupportObject.IsFillSupported(</div>
545<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; OverrideDataType(input, dataType),</div>
546<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; OverrideDataType(output, dataType),</div>
547<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160; descriptor,</div>
548<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; reason);</div>
549<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160; <span class="keywordflow">break</span>;</div>
550<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160; }</div>
551<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">LayerType::FakeQuantization</a>:</div>
552<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>&#160; {</div>
553<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const FakeQuantizationLayer*&gt;(&amp;layer);</div>
554<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
555<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; result = layerSupportObject.IsFakeQuantizationSupported(OverrideDataType(input, dataType),</div>
556<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; cLayer-&gt;GetParameters(),</div>
557<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; reason);</div>
558<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; <span class="keywordflow">break</span>;</div>
559<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; }</div>
560<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af3f6d0343d56ce88ce7958170ed05cb3">LayerType::Floor</a>:</div>
561<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; {</div>
562<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
563<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
564<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160; result = layerSupportObject.IsFloorSupported(OverrideDataType(input, dataType),</div>
565<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160; OverrideDataType(output, dataType),</div>
566<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>&#160; reason);</div>
567<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>&#160; <span class="keywordflow">break</span>;</div>
568<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>&#160; }</div>
569<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">LayerType::FullyConnected</a>:</div>
570<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>&#160; {</div>
571<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const FullyConnectedLayer*&gt;(&amp;layer);</div>
572<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
573<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
574<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>&#160; </div>
575<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160; <span class="keyword">const</span> FullyConnectedDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
576<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>&#160; TensorInfo weightsInfo;</div>
577<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; <span class="keyword">const</span> TensorInfo* weightsInfoPtr = <span class="keyword">nullptr</span>;</div>
578<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; </div>
579<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; weightsInfo = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(), dataType);</div>
580<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160; weightsInfoPtr = &amp;weightsInfo;</div>
581<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; </div>
582<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; TensorInfo biasInfo;</div>
583<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; <span class="keyword">const</span> TensorInfo* biasInfoPtr = <span class="keyword">nullptr</span>;</div>
584<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; <span class="keyword">static</span> <span class="keyword">const</span> TensorInfo dummyBFloat16Bias(TensorShape({1,1,1,1}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>);</div>
585<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; <span class="keyword">static</span> <span class="keyword">const</span> TensorInfo dummyFloat16Bias(TensorShape({1,1,1,1}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div>
586<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160; <span class="keyword">static</span> <span class="keyword">const</span> TensorInfo dummyFloat32Bias(TensorShape({1,1,1,1}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div>
587<div class="line"><a name="l00489"></a><span class="lineno"> 489</span>&#160; <span class="keyword">static</span> <span class="keyword">const</span> TensorInfo dummyQA8Bias(TensorShape({1,1,1,1}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>);</div>
588<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>&#160; </div>
589<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div>
590<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>&#160; {</div>
591<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>&#160; biasInfo = OverrideDataType(layer.GetInputSlot(2).GetTensorInfo(), dataType);</div>
592<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>&#160; biasInfoPtr = &amp;biasInfo;</div>
593<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>&#160; }</div>
594<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>&#160; <span class="keywordflow">else</span></div>
595<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>&#160; {</div>
596<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>&#160; <span class="comment">// If biases are not enabled pass a dummy tensorinfo for the validation</span></div>
597<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>&#160; <span class="keywordflow">switch</span>(input.GetDataType())</div>
598<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>&#160; {</div>
599<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>:</div>
600<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>&#160; {</div>
601<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>&#160; biasInfoPtr = &amp;dummyBFloat16Bias;</div>
602<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>&#160; <span class="keywordflow">break</span>;</div>
603<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>&#160; }</div>
604<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div>
605<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>&#160; {</div>
606<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>&#160; biasInfoPtr = &amp;dummyFloat16Bias;</div>
607<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>&#160; <span class="keywordflow">break</span>;</div>
608<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>&#160; }</div>
609<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</div>
610<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>&#160; {</div>
611<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>&#160; biasInfoPtr = &amp;dummyFloat32Bias;</div>
612<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>&#160; <span class="keywordflow">break</span>;</div>
613<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>&#160; }</div>
614<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div>
615<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div>
616<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div>
617<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div>
618<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>&#160; {</div>
619<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>&#160; biasInfoPtr = &amp;dummyQA8Bias;</div>
620<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>&#160; <span class="keywordflow">break</span>;</div>
621<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>&#160; }</div>
622<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>&#160; <span class="keywordflow">default</span>:</div>
623<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>&#160; {</div>
624<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>&#160; <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">&quot;Unexpected bias type&quot;</span>);</div>
625<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>&#160; }</div>
626<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>&#160; }</div>
627<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>&#160; }</div>
628<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>&#160; result = layerSupportObject.IsFullyConnectedSupported(</div>
629<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>&#160; OverrideDataType(input, dataType),</div>
630<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>&#160; OverrideDataType(output, dataType),</div>
631<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>&#160; *weightsInfoPtr,</div>
632<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>&#160; *biasInfoPtr,</div>
633<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>&#160; descriptor,</div>
634<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>&#160; reason);</div>
635<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>&#160; <span class="keywordflow">break</span>;</div>
636<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>&#160; }</div>
637<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af617f46b788e11a564cb16c9f5d59fea">LayerType::Fused</a>:</div>
638<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>&#160; {</div>
639<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const FusedLayer*&gt;(&amp;layer);</div>
640<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>&#160; </div>
641<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>&#160; <span class="comment">// Get vector of all outputs.</span></div>
642<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>&#160; <span class="keyword">auto</span> getOutTensorInfo = [&amp;dataType](<span class="keyword">const</span> OutputSlot&amp; slot)</div>
643<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>&#160; {</div>
644<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetTensorInfo(), dataType);</div>
645<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>&#160; };</div>
646<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>&#160; <span class="keyword">auto</span> beginOutputs = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().begin(), getOutTensorInfo);</div>
647<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>&#160; <span class="keyword">auto</span> endOutputs = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().end(), getOutTensorInfo);</div>
648<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>&#160; std::vector&lt;TensorInfo&gt; outputs(beginOutputs, endOutputs);</div>
649<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>&#160; <span class="keyword">const</span> std::vector&lt;std::reference_wrapper&lt;TensorInfo&gt;&gt; outputPtrs(outputs.begin(), outputs.end());</div>
650<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>&#160; </div>
651<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>&#160; <span class="comment">// Get vector of all inputs.</span></div>
652<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>&#160; <span class="keyword">auto</span> getInputTensorInfo = [&amp;dataType](<span class="keyword">const</span> InputSlot&amp; slot)</div>
653<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>&#160; {</div>
654<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetTensorInfo(), dataType);</div>
655<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>&#160; };</div>
656<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>&#160; <span class="keyword">auto</span> beginInputs = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().begin(), getInputTensorInfo);</div>
657<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>&#160; <span class="keyword">auto</span> endInputs = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().end(), getInputTensorInfo);</div>
658<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>&#160; std::vector&lt;TensorInfo&gt; inputs(beginInputs, endInputs);</div>
659<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>&#160; <span class="keyword">const</span> std::vector&lt;std::reference_wrapper&lt;TensorInfo&gt;&gt; inputPtrs(inputs.begin(), inputs.end());</div>
660<div class="line"><a name="l00562"></a><span class="lineno"> 562</span>&#160; </div>
661<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>&#160; result = layerSupportObject.IsFusedSupported(inputPtrs,</div>
662<div class="line"><a name="l00564"></a><span class="lineno"> 564</span>&#160; outputPtrs,</div>
663<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>&#160; cLayer-&gt;GetParameters(),</div>
664<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>&#160; reason);</div>
665<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>&#160; <span class="keywordflow">break</span>;</div>
666<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>&#160; }</div>
667<div class="line"><a name="l00569"></a><span class="lineno"> 569</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53">LayerType::Gather</a>:</div>
668<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>&#160; {</div>
669<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
670<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
671<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
672<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const GatherLayer*&gt;(&amp;layer);</div>
673<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>&#160; <span class="keyword">const</span> GatherDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
674<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>&#160; result = layerSupportObject.IsGatherSupported(OverrideDataType(input0, dataType),</div>
675<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>&#160; input1,</div>
676<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>&#160; OverrideDataType(output, dataType),</div>
677<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>&#160; descriptor,</div>
678<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>&#160; reason);</div>
679<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>&#160; <span class="keywordflow">break</span>;</div>
680<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>&#160; }</div>
681<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3028cc42e40f9a1f4f8b35556d9715a4">LayerType::GatherNd</a>:</div>
682<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>&#160; {</div>
683<div class="line"><a name="l00585"></a><span class="lineno"> 585</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
684<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
685<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
686<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>&#160; result = layerSupportObject.IsGatherNdSupported(OverrideDataType(input0, dataType),</div>
687<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>&#160; input1,</div>
688<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>&#160; OverrideDataType(output, dataType),</div>
689<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>&#160; reason);</div>
690<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>&#160; <span class="keywordflow">break</span>;</div>
691<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>&#160; }</div>
692<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div>
693<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>&#160; {</div>
694<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetOutputSlot(0).GetTensorInfo();</div>
695<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>&#160; result = layerSupportObject.IsInputSupported(OverrideDataType(input, dataType), reason);</div>
696<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>&#160; <span class="keywordflow">break</span>;</div>
697<div class="line"><a name="l00599"></a><span class="lineno"> 599</span>&#160; }</div>
698<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4">LayerType::InstanceNormalization</a>:</div>
699<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>&#160; {</div>
700<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const InstanceNormalizationLayer*&gt;(&amp;layer);</div>
701<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>&#160; <span class="keyword">const</span> InstanceNormalizationDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
702<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>&#160; </div>
703<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
704<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
705<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>&#160; </div>
706<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>&#160; result = layerSupportObject.IsInstanceNormalizationSupported(</div>
707<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>&#160; OverrideDataType(input, dataType),</div>
708<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>&#160; OverrideDataType(output, dataType),</div>
709<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>&#160; descriptor,</div>
710<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>&#160; reason);</div>
711<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>&#160; <span class="keywordflow">break</span>;</div>
712<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>&#160; }</div>
713<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2">LayerType::L2Normalization</a>:</div>
714<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>&#160; {</div>
715<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const L2NormalizationLayer*&gt;(&amp;layer);</div>
716<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>&#160; <span class="keyword">const</span> L2NormalizationDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
717<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>&#160; </div>
718<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
719<div class="line"><a name="l00621"></a><span class="lineno"> 621</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
720<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>&#160; </div>
721<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>&#160; result = layerSupportObject.IsL2NormalizationSupported(</div>
722<div class="line"><a name="l00624"></a><span class="lineno"> 624</span>&#160; OverrideDataType(input, dataType),</div>
723<div class="line"><a name="l00625"></a><span class="lineno"> 625</span>&#160; OverrideDataType(output, dataType),</div>
724<div class="line"><a name="l00626"></a><span class="lineno"> 626</span>&#160; descriptor,</div>
725<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>&#160; reason);</div>
726<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>&#160; <span class="keywordflow">break</span>;</div>
727<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>&#160; }</div>
728<div class="line"><a name="l00630"></a><span class="lineno"> 630</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30">LayerType::LogicalBinary</a>:</div>
729<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>&#160; {</div>
730<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const LogicalBinaryLayer*&gt;(&amp;layer);</div>
731<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>&#160; </div>
732<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
733<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
734<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
735<div class="line"><a name="l00637"></a><span class="lineno"> 637</span>&#160; </div>
736<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>&#160; result = layerSupportObject.IsLogicalBinarySupported(input0,</div>
737<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>&#160; input1,</div>
738<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>&#160; output,</div>
739<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>&#160; cLayer-&gt;GetParameters(),</div>
740<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>&#160; reason);</div>
741<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>&#160; <span class="keywordflow">break</span>;</div>
742<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>&#160; }</div>
743<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488">LayerType::LogSoftmax</a>:</div>
744<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>&#160; {</div>
745<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const LogSoftmaxLayer*&gt;(&amp;layer);</div>
746<div class="line"><a name="l00648"></a><span class="lineno"> 648</span>&#160; </div>
747<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
748<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
749<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>&#160; </div>
750<div class="line"><a name="l00652"></a><span class="lineno"> 652</span>&#160; result = layerSupportObject.IsLogSoftmaxSupported(OverrideDataType(input, dataType),</div>
751<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>&#160; OverrideDataType(output, dataType),</div>
752<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>&#160; cLayer-&gt;GetParameters(),</div>
753<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>&#160; reason);</div>
754<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>&#160; <span class="keywordflow">break</span>;</div>
755<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>&#160; }</div>
756<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925">LayerType::Lstm</a>:</div>
757<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>&#160; {</div>
758<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const LstmLayer*&gt;(&amp;layer);</div>
759<div class="line"><a name="l00661"></a><span class="lineno"> 661</span>&#160; <span class="keyword">const</span> LstmDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
760<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>&#160; </div>
761<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>&#160; <span class="comment">// All inputs.</span></div>
762<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
763<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>&#160; dataType);</div>
764<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputStateIn = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(),</div>
765<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>&#160; dataType);</div>
766<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateIn = OverrideDataType(layer.GetInputSlot(2).GetTensorInfo(),</div>
767<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>&#160; dataType);</div>
768<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>&#160; <span class="comment">// All outputs</span></div>
769<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>&#160; <span class="keyword">const</span> TensorInfo&amp; scratchBuffer = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
770<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputStateOut = OverrideDataType(layer.GetOutputSlot(1).GetTensorInfo(), dataType);</div>
771<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateOut = OverrideDataType(layer.GetOutputSlot(2).GetTensorInfo(), dataType);</div>
772<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = OverrideDataType(layer.GetOutputSlot(3).GetTensorInfo(), dataType);</div>
773<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>&#160; </div>
774<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>&#160; <span class="comment">// Basic parameters</span></div>
775<div class="line"><a name="l00677"></a><span class="lineno"> 677</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToForgetWeights</div>
776<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
777<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToCellWeights</div>
778<div class="line"><a name="l00680"></a><span class="lineno"> 680</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToCellWeights-&gt;GetTensorInfo(), dataType);</div>
779<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToOutputWeights</div>
780<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
781<div class="line"><a name="l00683"></a><span class="lineno"> 683</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToForgetWeights</div>
782<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
783<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToCellWeights</div>
784<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToCellWeights-&gt;GetTensorInfo(), dataType);</div>
785<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToOutputWeights</div>
786<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
787<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>&#160; <span class="keyword">const</span> TensorInfo&amp; forgetGateBias</div>
788<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_ForgetGateBias-&gt;GetTensorInfo(), dataType);</div>
789<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellBias</div>
790<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_CellBias-&gt;GetTensorInfo(), dataType);</div>
791<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputGateBias</div>
792<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_OutputGateBias-&gt;GetTensorInfo(), dataType);</div>
793<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>&#160; </div>
794<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>&#160; LstmInputParamsInfo paramsInfo;</div>
795<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>&#160; </div>
796<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>&#160; paramsInfo.m_InputToForgetWeights = &amp;inputToForgetWeights;</div>
797<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>&#160; paramsInfo.m_InputToCellWeights = &amp;inputToCellWeights;</div>
798<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>&#160; paramsInfo.m_InputToOutputWeights = &amp;inputToOutputWeights;</div>
799<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>&#160; paramsInfo.m_RecurrentToForgetWeights = &amp;recurrentToForgetWeights;</div>
800<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>&#160; paramsInfo.m_RecurrentToCellWeights = &amp;recurrentToCellWeights;</div>
801<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>&#160; paramsInfo.m_RecurrentToOutputWeights = &amp;recurrentToOutputWeights;</div>
802<div class="line"><a name="l00704"></a><span class="lineno"> 704</span>&#160; paramsInfo.m_ForgetGateBias = &amp;forgetGateBias;</div>
803<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>&#160; paramsInfo.m_CellBias = &amp;cellBias;</div>
804<div class="line"><a name="l00706"></a><span class="lineno"> 706</span>&#160; paramsInfo.m_OutputGateBias = &amp;outputGateBias;</div>
805<div class="line"><a name="l00707"></a><span class="lineno"> 707</span>&#160; </div>
806<div class="line"><a name="l00708"></a><span class="lineno"> 708</span>&#160; </div>
807<div class="line"><a name="l00709"></a><span class="lineno"> 709</span>&#160; <span class="comment">// Optional parameters</span></div>
808<div class="line"><a name="l00710"></a><span class="lineno"> 710</span>&#160; TensorInfo optInputToInputWeights;</div>
809<div class="line"><a name="l00711"></a><span class="lineno"> 711</span>&#160; TensorInfo optRecurrentToInputWeights;</div>
810<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>&#160; TensorInfo optCellToInputWeights;</div>
811<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>&#160; TensorInfo optInputGateBias;</div>
812<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>&#160; TensorInfo optProjectionWeights;</div>
813<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>&#160; TensorInfo optProjectionBias;</div>
814<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>&#160; TensorInfo optCellToForgetWeights;</div>
815<div class="line"><a name="l00717"></a><span class="lineno"> 717</span>&#160; TensorInfo optCellToOutputWeights;</div>
816<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>&#160; TensorInfo optInputLayerNormWeights;</div>
817<div class="line"><a name="l00719"></a><span class="lineno"> 719</span>&#160; TensorInfo optForgetLayerNormWeights;</div>
818<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>&#160; TensorInfo optCellLayerNormWeights;</div>
819<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>&#160; TensorInfo optOutputLayerNormWeights;</div>
820<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>&#160; </div>
821<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>&#160; <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div>
822<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>&#160; {</div>
823<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>&#160; optInputToInputWeights =</div>
824<div class="line"><a name="l00726"></a><span class="lineno"> 726</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_InputToInputWeights-&gt;GetTensorInfo(), dataType);</div>
825<div class="line"><a name="l00727"></a><span class="lineno"> 727</span>&#160; paramsInfo.m_InputToInputWeights = &amp;optInputToInputWeights;</div>
826<div class="line"><a name="l00728"></a><span class="lineno"> 728</span>&#160; </div>
827<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>&#160; optRecurrentToInputWeights =</div>
828<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_RecurrentToInputWeights-&gt;GetTensorInfo(), dataType);</div>
829<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>&#160; paramsInfo.m_RecurrentToInputWeights = &amp;optRecurrentToInputWeights;</div>
830<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>&#160; optInputGateBias =</div>
831<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_InputGateBias-&gt;GetTensorInfo(), dataType);</div>
832<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>&#160; paramsInfo.m_InputGateBias = &amp;optInputGateBias;</div>
833<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>&#160; }</div>
834<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>&#160; </div>
835<div class="line"><a name="l00737"></a><span class="lineno"> 737</span>&#160; <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div>
836<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>&#160; {</div>
837<div class="line"><a name="l00739"></a><span class="lineno"> 739</span>&#160; optProjectionWeights =</div>
838<div class="line"><a name="l00740"></a><span class="lineno"> 740</span>&#160; OverrideDataType(cLayer-&gt;m_ProjectionParameters.m_ProjectionWeights-&gt;GetTensorInfo(), dataType);</div>
839<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>&#160; paramsInfo.m_ProjectionWeights = &amp;optProjectionWeights;</div>
840<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>&#160; <span class="keywordflow">if</span> (cLayer-&gt;m_ProjectionParameters.m_ProjectionBias != <span class="keyword">nullptr</span>)</div>
841<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>&#160; {</div>
842<div class="line"><a name="l00744"></a><span class="lineno"> 744</span>&#160; optProjectionBias =</div>
843<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>&#160; OverrideDataType(cLayer-&gt;m_ProjectionParameters.m_ProjectionBias-&gt;GetTensorInfo(), dataType);</div>
844<div class="line"><a name="l00746"></a><span class="lineno"> 746</span>&#160; paramsInfo.m_ProjectionBias = &amp;optProjectionBias;</div>
845<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>&#160; }</div>
846<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>&#160; }</div>
847<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>&#160; </div>
848<div class="line"><a name="l00750"></a><span class="lineno"> 750</span>&#160; <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div>
849<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>&#160; {</div>
850<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>&#160; <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div>
851<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>&#160; {</div>
852<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>&#160; optCellToInputWeights =</div>
853<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToInputWeights-&gt;GetTensorInfo(),</div>
854<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>&#160; dataType);</div>
855<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>&#160; paramsInfo.m_CellToInputWeights = &amp;optCellToInputWeights;</div>
856<div class="line"><a name="l00758"></a><span class="lineno"> 758</span>&#160; }</div>
857<div class="line"><a name="l00759"></a><span class="lineno"> 759</span>&#160; optCellToForgetWeights =</div>
858<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
859<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>&#160; paramsInfo.m_CellToForgetWeights = &amp;optCellToForgetWeights;</div>
860<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>&#160; optCellToOutputWeights =</div>
861<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
862<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>&#160; paramsInfo.m_CellToOutputWeights = &amp;optCellToOutputWeights;</div>
863<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>&#160; }</div>
864<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>&#160; </div>
865<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>&#160; <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</div>
866<div class="line"><a name="l00768"></a><span class="lineno"> 768</span>&#160; {</div>
867<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>&#160; <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div>
868<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>&#160; {</div>
869<div class="line"><a name="l00771"></a><span class="lineno"> 771</span>&#160; optInputLayerNormWeights = OverrideDataType(</div>
870<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>&#160; cLayer-&gt;m_LayerNormParameters.m_InputLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
871<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>&#160; paramsInfo.m_InputLayerNormWeights = &amp;optInputLayerNormWeights;</div>
872<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>&#160; }</div>
873<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>&#160; </div>
874<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>&#160; optForgetLayerNormWeights = OverrideDataType(</div>
875<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>&#160; cLayer-&gt;m_LayerNormParameters.m_ForgetLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
876<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>&#160; paramsInfo.m_ForgetLayerNormWeights = &amp;optForgetLayerNormWeights;</div>
877<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>&#160; </div>
878<div class="line"><a name="l00780"></a><span class="lineno"> 780</span>&#160; optCellLayerNormWeights = OverrideDataType(</div>
879<div class="line"><a name="l00781"></a><span class="lineno"> 781</span>&#160; cLayer-&gt;m_LayerNormParameters.m_CellLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
880<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>&#160; paramsInfo.m_CellLayerNormWeights = &amp;optCellLayerNormWeights;</div>
881<div class="line"><a name="l00783"></a><span class="lineno"> 783</span>&#160; </div>
882<div class="line"><a name="l00784"></a><span class="lineno"> 784</span>&#160; optOutputLayerNormWeights = OverrideDataType(</div>
883<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>&#160; cLayer-&gt;m_LayerNormParameters.m_OutputLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
884<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>&#160; paramsInfo.m_OutputLayerNormWeights = &amp;optOutputLayerNormWeights;</div>
885<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>&#160; }</div>
886<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>&#160; </div>
887<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>&#160; result = layerSupportObject.IsLstmSupported(</div>
888<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>&#160; input,</div>
889<div class="line"><a name="l00791"></a><span class="lineno"> 791</span>&#160; outputStateIn,</div>
890<div class="line"><a name="l00792"></a><span class="lineno"> 792</span>&#160; cellStateIn,</div>
891<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>&#160; scratchBuffer,</div>
892<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>&#160; outputStateOut,</div>
893<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>&#160; cellStateOut,</div>
894<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>&#160; output,</div>
895<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>&#160; descriptor,</div>
896<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>&#160; paramsInfo,</div>
897<div class="line"><a name="l00799"></a><span class="lineno"> 799</span>&#160; reason);</div>
898<div class="line"><a name="l00800"></a><span class="lineno"> 800</span>&#160; <span class="keywordflow">break</span>;</div>
899<div class="line"><a name="l00801"></a><span class="lineno"> 801</span>&#160; }</div>
900<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">LayerType::Maximum</a>:</div>
901<div class="line"><a name="l00803"></a><span class="lineno"> 803</span>&#160; {</div>
902<div class="line"><a name="l00804"></a><span class="lineno"> 804</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
903<div class="line"><a name="l00805"></a><span class="lineno"> 805</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
904<div class="line"><a name="l00806"></a><span class="lineno"> 806</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
905<div class="line"><a name="l00807"></a><span class="lineno"> 807</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
906<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>&#160; </div>
907<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>&#160; result = layerSupportObject.IsMaximumSupported(OverrideDataType(input0, dataType),</div>
908<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>&#160; OverrideDataType(input1, dataType),</div>
909<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>&#160; OverrideDataType(output, dataType),</div>
910<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>&#160; reason);</div>
911<div class="line"><a name="l00813"></a><span class="lineno"> 813</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
912<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>&#160; <span class="keywordflow">break</span>;</div>
913<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>&#160; }</div>
914<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>:</div>
915<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>&#160; {</div>
916<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
917<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
918<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>&#160; </div>
919<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>&#160; result = layerSupportObject.IsMemCopySupported(OverrideDataType(input, dataType),</div>
920<div class="line"><a name="l00822"></a><span class="lineno"> 822</span>&#160; OverrideDataType(output, dataType),</div>
921<div class="line"><a name="l00823"></a><span class="lineno"> 823</span>&#160; reason);</div>
922<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>&#160; <span class="keywordflow">break</span>;</div>
923<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>&#160; }</div>
924<div class="line"><a name="l00826"></a><span class="lineno"> 826</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">LayerType::MemImport</a>:</div>
925<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>&#160; {</div>
926<div class="line"><a name="l00828"></a><span class="lineno"> 828</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
927<div class="line"><a name="l00829"></a><span class="lineno"> 829</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
928<div class="line"><a name="l00830"></a><span class="lineno"> 830</span>&#160; </div>
929<div class="line"><a name="l00831"></a><span class="lineno"> 831</span>&#160; result = layerSupportObject.IsMemImportSupported(OverrideDataType(input, dataType),</div>
930<div class="line"><a name="l00832"></a><span class="lineno"> 832</span>&#160; OverrideDataType(output, dataType),</div>
931<div class="line"><a name="l00833"></a><span class="lineno"> 833</span>&#160; reason);</div>
932<div class="line"><a name="l00834"></a><span class="lineno"> 834</span>&#160; <span class="keywordflow">break</span>;</div>
933<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>&#160; }</div>
934<div class="line"><a name="l00836"></a><span class="lineno"> 836</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">LayerType::Merge</a>:</div>
935<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>&#160; {</div>
936<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
937<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
938<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
939<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>&#160; </div>
940<div class="line"><a name="l00842"></a><span class="lineno"> 842</span>&#160; result = layerSupportObject.IsMergeSupported(OverrideDataType(input0, dataType),</div>
941<div class="line"><a name="l00843"></a><span class="lineno"> 843</span>&#160; OverrideDataType(input1, dataType),</div>
942<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>&#160; OverrideDataType(output, dataType),</div>
943<div class="line"><a name="l00845"></a><span class="lineno"> 845</span>&#160; reason);</div>
944<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>&#160; <span class="keywordflow">break</span>;</div>
945<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>&#160; }</div>
946<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">LayerType::Concat</a>:</div>
947<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>&#160; {</div>
948<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ConcatLayer*&gt;(&amp;layer);</div>
949<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>&#160; </div>
950<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>&#160; <span class="comment">// Get vector of all inputs.</span></div>
951<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>&#160; <span class="keyword">auto</span> getTensorInfo = [&amp;dataType](<span class="keyword">const</span> InputSlot&amp; slot)</div>
952<div class="line"><a name="l00854"></a><span class="lineno"> 854</span>&#160; {</div>
953<div class="line"><a name="l00855"></a><span class="lineno"> 855</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()-&gt;GetTensorInfo(), dataType);</div>
954<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>&#160; };</div>
955<div class="line"><a name="l00857"></a><span class="lineno"> 857</span>&#160; </div>
956<div class="line"><a name="l00858"></a><span class="lineno"> 858</span>&#160; <span class="keyword">auto</span> beginI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().begin(), getTensorInfo);</div>
957<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>&#160; <span class="keyword">auto</span> endI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().end(), getTensorInfo);</div>
958<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>&#160; std::vector&lt;TensorInfo&gt; inputs(beginI, endI);</div>
959<div class="line"><a name="l00861"></a><span class="lineno"> 861</span>&#160; </div>
960<div class="line"><a name="l00862"></a><span class="lineno"> 862</span>&#160; <span class="keyword">auto</span> getTensorInfoPtr = [](<span class="keyword">const</span> TensorInfo&amp; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
961<div class="line"><a name="l00863"></a><span class="lineno"> 863</span>&#160; {</div>
962<div class="line"><a name="l00864"></a><span class="lineno"> 864</span>&#160; <span class="keywordflow">return</span> &amp;<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div>
963<div class="line"><a name="l00865"></a><span class="lineno"> 865</span>&#160; };</div>
964<div class="line"><a name="l00866"></a><span class="lineno"> 866</span>&#160; </div>
965<div class="line"><a name="l00867"></a><span class="lineno"> 867</span>&#160; <span class="keyword">auto</span> beginPtr = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.begin(), getTensorInfoPtr);</div>
966<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>&#160; <span class="keyword">auto</span> endPtr = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.end(), getTensorInfoPtr);</div>
967<div class="line"><a name="l00869"></a><span class="lineno"> 869</span>&#160; std::vector&lt;const TensorInfo*&gt; inputPtrs(beginPtr, endPtr);</div>
968<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>&#160; </div>
969<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
970<div class="line"><a name="l00872"></a><span class="lineno"> 872</span>&#160; </div>
971<div class="line"><a name="l00873"></a><span class="lineno"> 873</span>&#160; result = layerSupportObject.IsConcatSupported(inputPtrs, output, cLayer-&gt;GetParameters(), reason);</div>
972<div class="line"><a name="l00874"></a><span class="lineno"> 874</span>&#160; </div>
973<div class="line"><a name="l00875"></a><span class="lineno"> 875</span>&#160; </div>
974<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>&#160; <span class="keywordflow">break</span>;</div>
975<div class="line"><a name="l00877"></a><span class="lineno"> 877</span>&#160; }</div>
976<div class="line"><a name="l00878"></a><span class="lineno"> 878</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">LayerType::Multiplication</a>:</div>
977<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>&#160; {</div>
978<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
979<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
980<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
981<div class="line"><a name="l00883"></a><span class="lineno"> 883</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
982<div class="line"><a name="l00884"></a><span class="lineno"> 884</span>&#160; result = layerSupportObject.IsMultiplicationSupported(</div>
983<div class="line"><a name="l00885"></a><span class="lineno"> 885</span>&#160; OverrideDataType(input0, dataType),</div>
984<div class="line"><a name="l00886"></a><span class="lineno"> 886</span>&#160; OverrideDataType(input1, dataType),</div>
985<div class="line"><a name="l00887"></a><span class="lineno"> 887</span>&#160; OverrideDataType(output, dataType),</div>
986<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>&#160; reason);</div>
987<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
988<div class="line"><a name="l00890"></a><span class="lineno"> 890</span>&#160; <span class="keywordflow">break</span>;</div>
989<div class="line"><a name="l00891"></a><span class="lineno"> 891</span>&#160; }</div>
990<div class="line"><a name="l00892"></a><span class="lineno"> 892</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">LayerType::Normalization</a>:</div>
991<div class="line"><a name="l00893"></a><span class="lineno"> 893</span>&#160; {</div>
992<div class="line"><a name="l00894"></a><span class="lineno"> 894</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const NormalizationLayer*&gt;(&amp;layer);</div>
993<div class="line"><a name="l00895"></a><span class="lineno"> 895</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
994<div class="line"><a name="l00896"></a><span class="lineno"> 896</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
995<div class="line"><a name="l00897"></a><span class="lineno"> 897</span>&#160; result = layerSupportObject.IsNormalizationSupported(OverrideDataType(input, dataType),</div>
996<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>&#160; OverrideDataType(output, dataType),</div>
997<div class="line"><a name="l00899"></a><span class="lineno"> 899</span>&#160; cLayer-&gt;GetParameters(),</div>
998<div class="line"><a name="l00900"></a><span class="lineno"> 900</span>&#160; reason);</div>
999<div class="line"><a name="l00901"></a><span class="lineno"> 901</span>&#160; <span class="keywordflow">break</span>;</div>
1000<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>&#160; }</div>
1001<div class="line"><a name="l00903"></a><span class="lineno"> 903</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</div>
1002<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>&#160; {</div>
1003<div class="line"><a name="l00905"></a><span class="lineno"> 905</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetInputSlot(0).GetTensorInfo();</div>
1004<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>&#160; result = layerSupportObject.IsOutputSupported(OverrideDataType(output, dataType), reason);</div>
1005<div class="line"><a name="l00907"></a><span class="lineno"> 907</span>&#160; <span class="keywordflow">break</span>;</div>
1006<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>&#160; }</div>
1007<div class="line"><a name="l00909"></a><span class="lineno"> 909</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">LayerType::Permute</a>:</div>
1008<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>&#160; {</div>
1009<div class="line"><a name="l00911"></a><span class="lineno"> 911</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const PermuteLayer*&gt;(&amp;layer);</div>
1010<div class="line"><a name="l00912"></a><span class="lineno"> 912</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1011<div class="line"><a name="l00913"></a><span class="lineno"> 913</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1012<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>&#160; result = layerSupportObject.IsPermuteSupported(OverrideDataType(input, dataType),</div>
1013<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>&#160; OverrideDataType(output, dataType),</div>
1014<div class="line"><a name="l00916"></a><span class="lineno"> 916</span>&#160; cLayer-&gt;GetParameters(),</div>
1015<div class="line"><a name="l00917"></a><span class="lineno"> 917</span>&#160; reason);</div>
1016<div class="line"><a name="l00918"></a><span class="lineno"> 918</span>&#160; <span class="keywordflow">break</span>;</div>
1017<div class="line"><a name="l00919"></a><span class="lineno"> 919</span>&#160; }</div>
1018<div class="line"><a name="l00920"></a><span class="lineno"> 920</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">LayerType::Pad</a>:</div>
1019<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>&#160; {</div>
1020<div class="line"><a name="l00922"></a><span class="lineno"> 922</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const PadLayer*&gt;(&amp;layer);</div>
1021<div class="line"><a name="l00923"></a><span class="lineno"> 923</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1022<div class="line"><a name="l00924"></a><span class="lineno"> 924</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1023<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>&#160; result = layerSupportObject.IsPadSupported(</div>
1024<div class="line"><a name="l00926"></a><span class="lineno"> 926</span>&#160; OverrideDataType(input, dataType),</div>
1025<div class="line"><a name="l00927"></a><span class="lineno"> 927</span>&#160; OverrideDataType(output, dataType),</div>
1026<div class="line"><a name="l00928"></a><span class="lineno"> 928</span>&#160; cLayer-&gt;GetParameters(),</div>
1027<div class="line"><a name="l00929"></a><span class="lineno"> 929</span>&#160; reason);</div>
1028<div class="line"><a name="l00930"></a><span class="lineno"> 930</span>&#160; <span class="keywordflow">break</span>;</div>
1029<div class="line"><a name="l00931"></a><span class="lineno"> 931</span>&#160; }</div>
1030<div class="line"><a name="l00932"></a><span class="lineno"> 932</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001">LayerType::Pooling2d</a>:</div>
1031<div class="line"><a name="l00933"></a><span class="lineno"> 933</span>&#160; {</div>
1032<div class="line"><a name="l00934"></a><span class="lineno"> 934</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const Pooling2dLayer*&gt;(&amp;layer);</div>
1033<div class="line"><a name="l00935"></a><span class="lineno"> 935</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1034<div class="line"><a name="l00936"></a><span class="lineno"> 936</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1035<div class="line"><a name="l00937"></a><span class="lineno"> 937</span>&#160; result = layerSupportObject.IsPooling2dSupported(OverrideDataType(input, dataType),</div>
1036<div class="line"><a name="l00938"></a><span class="lineno"> 938</span>&#160; OverrideDataType(output, dataType),</div>
1037<div class="line"><a name="l00939"></a><span class="lineno"> 939</span>&#160; cLayer-&gt;GetParameters(),</div>
1038<div class="line"><a name="l00940"></a><span class="lineno"> 940</span>&#160; reason);</div>
1039<div class="line"><a name="l00941"></a><span class="lineno"> 941</span>&#160; <span class="keywordflow">break</span>;</div>
1040<div class="line"><a name="l00942"></a><span class="lineno"> 942</span>&#160; }</div>
1041<div class="line"><a name="l00943"></a><span class="lineno"> 943</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2b3140dc366b9fcd25ed786a79d1817c">LayerType::Pooling3d</a>:</div>
1042<div class="line"><a name="l00944"></a><span class="lineno"> 944</span>&#160; {</div>
1043<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const Pooling3dLayer*&gt;(&amp;layer);</div>
1044<div class="line"><a name="l00946"></a><span class="lineno"> 946</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1045<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1046<div class="line"><a name="l00948"></a><span class="lineno"> 948</span>&#160; result = layerSupportObject.IsPooling3dSupported(OverrideDataType(input, dataType),</div>
1047<div class="line"><a name="l00949"></a><span class="lineno"> 949</span>&#160; OverrideDataType(output, dataType),</div>
1048<div class="line"><a name="l00950"></a><span class="lineno"> 950</span>&#160; cLayer-&gt;GetParameters(),</div>
1049<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>&#160; reason);</div>
1050<div class="line"><a name="l00952"></a><span class="lineno"> 952</span>&#160; <span class="keywordflow">break</span>;</div>
1051<div class="line"><a name="l00953"></a><span class="lineno"> 953</span>&#160; }</div>
1052<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278">LayerType::PreCompiled</a>:</div>
1053<div class="line"><a name="l00955"></a><span class="lineno"> 955</span>&#160; {</div>
1054<div class="line"><a name="l00956"></a><span class="lineno"> 956</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const PreCompiledLayer*&gt;(&amp;layer);</div>
1055<div class="line"><a name="l00957"></a><span class="lineno"> 957</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1056<div class="line"><a name="l00958"></a><span class="lineno"> 958</span>&#160; result = layerSupportObject.IsPreCompiledSupported(OverrideDataType(input, dataType),</div>
1057<div class="line"><a name="l00959"></a><span class="lineno"> 959</span>&#160; cLayer-&gt;GetParameters(),</div>
1058<div class="line"><a name="l00960"></a><span class="lineno"> 960</span>&#160; reason);</div>
1059<div class="line"><a name="l00961"></a><span class="lineno"> 961</span>&#160; <span class="keywordflow">break</span>;</div>
1060<div class="line"><a name="l00962"></a><span class="lineno"> 962</span>&#160; }</div>
1061<div class="line"><a name="l00963"></a><span class="lineno"> 963</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb">LayerType::Quantize</a>:</div>
1062<div class="line"><a name="l00964"></a><span class="lineno"> 964</span>&#160; {</div>
1063<div class="line"><a name="l00965"></a><span class="lineno"> 965</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1064<div class="line"><a name="l00966"></a><span class="lineno"> 966</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1065<div class="line"><a name="l00967"></a><span class="lineno"> 967</span>&#160; result = layerSupportObject.IsQuantizeSupported(input, output, reason);</div>
1066<div class="line"><a name="l00968"></a><span class="lineno"> 968</span>&#160; <span class="keywordflow">break</span>;</div>
1067<div class="line"><a name="l00969"></a><span class="lineno"> 969</span>&#160; }</div>
1068<div class="line"><a name="l00970"></a><span class="lineno"> 970</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a91880b71ea6d007439b7bc7c320b5c25">LayerType::QLstm</a>:</div>
1069<div class="line"><a name="l00971"></a><span class="lineno"> 971</span>&#160; {</div>
1070<div class="line"><a name="l00972"></a><span class="lineno"> 972</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const QLstmLayer*&gt;(&amp;layer);</div>
1071<div class="line"><a name="l00973"></a><span class="lineno"> 973</span>&#160; <span class="keyword">const</span> QLstmDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
1072<div class="line"><a name="l00974"></a><span class="lineno"> 974</span>&#160; </div>
1073<div class="line"><a name="l00975"></a><span class="lineno"> 975</span>&#160; <span class="comment">// Inputs</span></div>
1074<div class="line"><a name="l00976"></a><span class="lineno"> 976</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1075<div class="line"><a name="l00977"></a><span class="lineno"> 977</span>&#160; <span class="keyword">const</span> TensorInfo&amp; previousOutputIn = layer.GetInputSlot(1).GetTensorInfo();</div>
1076<div class="line"><a name="l00978"></a><span class="lineno"> 978</span>&#160; <span class="keyword">const</span> TensorInfo&amp; previousCellStateIn = layer.GetInputSlot(2).GetTensorInfo();</div>
1077<div class="line"><a name="l00979"></a><span class="lineno"> 979</span>&#160; </div>
1078<div class="line"><a name="l00980"></a><span class="lineno"> 980</span>&#160; <span class="comment">// Outputs</span></div>
1079<div class="line"><a name="l00981"></a><span class="lineno"> 981</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputStateOut = layer.GetOutputSlot(0).GetTensorInfo();</div>
1080<div class="line"><a name="l00982"></a><span class="lineno"> 982</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateOut = layer.GetOutputSlot(1).GetTensorInfo();</div>
1081<div class="line"><a name="l00983"></a><span class="lineno"> 983</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(2).GetTensorInfo();</div>
1082<div class="line"><a name="l00984"></a><span class="lineno"> 984</span>&#160; </div>
1083<div class="line"><a name="l00985"></a><span class="lineno"> 985</span>&#160; <span class="comment">// Lstm parameters</span></div>
1084<div class="line"><a name="l00986"></a><span class="lineno"> 986</span>&#160; LstmInputParamsInfo paramsInfo;</div>
1085<div class="line"><a name="l00987"></a><span class="lineno"> 987</span>&#160; </div>
1086<div class="line"><a name="l00988"></a><span class="lineno"> 988</span>&#160; <span class="comment">// Basic parameters</span></div>
1087<div class="line"><a name="l00989"></a><span class="lineno"> 989</span>&#160; paramsInfo.m_InputToForgetWeights = &amp;cLayer-&gt;m_BasicParameters.m_InputToForgetWeights-&gt;GetTensorInfo();</div>
1088<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>&#160; paramsInfo.m_InputToCellWeights = &amp;cLayer-&gt;m_BasicParameters.m_InputToCellWeights-&gt;GetTensorInfo();</div>
1089<div class="line"><a name="l00991"></a><span class="lineno"> 991</span>&#160; paramsInfo.m_InputToOutputWeights = &amp;cLayer-&gt;m_BasicParameters.m_InputToOutputWeights-&gt;GetTensorInfo();</div>
1090<div class="line"><a name="l00992"></a><span class="lineno"> 992</span>&#160; </div>
1091<div class="line"><a name="l00993"></a><span class="lineno"> 993</span>&#160; paramsInfo.m_RecurrentToForgetWeights =</div>
1092<div class="line"><a name="l00994"></a><span class="lineno"> 994</span>&#160; &amp;cLayer-&gt;m_BasicParameters.m_RecurrentToForgetWeights-&gt;GetTensorInfo();</div>
1093<div class="line"><a name="l00995"></a><span class="lineno"> 995</span>&#160; paramsInfo.m_RecurrentToCellWeights =</div>
1094<div class="line"><a name="l00996"></a><span class="lineno"> 996</span>&#160; &amp;cLayer-&gt;m_BasicParameters.m_RecurrentToCellWeights-&gt;GetTensorInfo();</div>
1095<div class="line"><a name="l00997"></a><span class="lineno"> 997</span>&#160; paramsInfo.m_RecurrentToOutputWeights =</div>
1096<div class="line"><a name="l00998"></a><span class="lineno"> 998</span>&#160; &amp;cLayer-&gt;m_BasicParameters.m_RecurrentToOutputWeights-&gt;GetTensorInfo();</div>
1097<div class="line"><a name="l00999"></a><span class="lineno"> 999</span>&#160; </div>
1098<div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160; paramsInfo.m_ForgetGateBias = &amp;cLayer-&gt;m_BasicParameters.m_ForgetGateBias-&gt;GetTensorInfo();</div>
1099<div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160; paramsInfo.m_CellBias = &amp;cLayer-&gt;m_BasicParameters.m_CellBias-&gt;GetTensorInfo();</div>
1100<div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160; paramsInfo.m_OutputGateBias = &amp;cLayer-&gt;m_BasicParameters.m_OutputGateBias-&gt;GetTensorInfo();</div>
1101<div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160; </div>
1102<div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160; <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div>
1103<div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160; {</div>
1104<div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160; paramsInfo.m_InputToInputWeights = &amp;cLayer-&gt;m_CifgParameters.m_InputToInputWeights-&gt;GetTensorInfo();</div>
1105<div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>&#160; paramsInfo.m_RecurrentToInputWeights =</div>
1106<div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>&#160; &amp;cLayer-&gt;m_CifgParameters.m_RecurrentToInputWeights-&gt;GetTensorInfo();</div>
1107<div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>&#160; paramsInfo.m_InputGateBias = &amp;cLayer-&gt;m_CifgParameters.m_InputGateBias-&gt;GetTensorInfo();</div>
1108<div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160; }</div>
1109<div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160; </div>
1110<div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160; <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div>
1111<div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>&#160; {</div>
1112<div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160; paramsInfo.m_ProjectionWeights = &amp;cLayer-&gt;m_ProjectionParameters.m_ProjectionWeights-&gt;GetTensorInfo();</div>
1113<div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>&#160; </div>
1114<div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>&#160; <span class="comment">// Projection bias is optional even if projection is enabled</span></div>
1115<div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>&#160; <span class="keywordflow">if</span> (cLayer-&gt;m_ProjectionParameters.m_ProjectionBias != <span class="keyword">nullptr</span>)</div>
1116<div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>&#160; {</div>
1117<div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160; paramsInfo.m_ProjectionBias = &amp;cLayer-&gt;m_ProjectionParameters.m_ProjectionBias-&gt;GetTensorInfo();</div>
1118<div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160; }</div>
1119<div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160; }</div>
1120<div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160; </div>
1121<div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>&#160; <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div>
1122<div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160; {</div>
1123<div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160; <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div>
1124<div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160; {</div>
1125<div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160; paramsInfo.m_CellToInputWeights =</div>
1126<div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160; &amp;cLayer-&gt;m_PeepholeParameters.m_CellToInputWeights-&gt;GetTensorInfo();</div>
1127<div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160; }</div>
1128<div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160; </div>
1129<div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160; paramsInfo.m_CellToForgetWeights =</div>
1130<div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>&#160; &amp;cLayer-&gt;m_PeepholeParameters.m_CellToForgetWeights-&gt;GetTensorInfo();</div>
1131<div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>&#160; paramsInfo.m_CellToOutputWeights = &amp;cLayer-&gt;m_PeepholeParameters.m_CellToOutputWeights-&gt;GetTensorInfo();</div>
1132<div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160; }</div>
1133<div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160; </div>
1134<div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160; <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</div>
1135<div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160; {</div>
1136<div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160; <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div>
1137<div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160; {</div>
1138<div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160; paramsInfo.m_InputLayerNormWeights =</div>
1139<div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160; &amp;cLayer-&gt;m_LayerNormParameters.m_InputLayerNormWeights-&gt;GetTensorInfo();</div>
1140<div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160; }</div>
1141<div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160; </div>
1142<div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160; paramsInfo.m_ForgetLayerNormWeights =</div>
1143<div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160; &amp;cLayer-&gt;m_LayerNormParameters.m_ForgetLayerNormWeights-&gt;GetTensorInfo();</div>
1144<div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160; paramsInfo.m_CellLayerNormWeights =</div>
1145<div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160; &amp;cLayer-&gt;m_LayerNormParameters.m_CellLayerNormWeights-&gt;GetTensorInfo();</div>
1146<div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160; paramsInfo.m_OutputLayerNormWeights =</div>
1147<div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160; &amp;cLayer-&gt;m_LayerNormParameters.m_OutputLayerNormWeights-&gt;GetTensorInfo();</div>
1148<div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160; }</div>
1149<div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160; </div>
1150<div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160; result = layerSupportObject.IsQLstmSupported(input,</div>
1151<div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160; previousOutputIn,</div>
1152<div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160; previousCellStateIn,</div>
1153<div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160; outputStateOut,</div>
1154<div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160; cellStateOut,</div>
1155<div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160; output,</div>
1156<div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160; descriptor,</div>
1157<div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>&#160; paramsInfo,</div>
1158<div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160; reason);</div>
1159<div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>&#160; <span class="keywordflow">break</span>;</div>
1160<div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>&#160; }</div>
1161<div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">LayerType::QuantizedLstm</a>:</div>
1162<div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>&#160; {</div>
1163<div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const QuantizedLstmLayer*&gt;(&amp;layer);</div>
1164<div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160; </div>
1165<div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160; <span class="comment">// Inputs</span></div>
1166<div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1167<div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160; <span class="keyword">const</span> TensorInfo&amp; previousCellStateIn = layer.GetInputSlot(1).GetTensorInfo();</div>
1168<div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160; <span class="keyword">const</span> TensorInfo&amp; previousOutputIn = layer.GetInputSlot(2).GetTensorInfo();</div>
1169<div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160; </div>
1170<div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160; <span class="comment">// Outputs</span></div>
1171<div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateOut = layer.GetOutputSlot(0).GetTensorInfo();</div>
1172<div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(1).GetTensorInfo();</div>
1173<div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160; </div>
1174<div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160; <span class="comment">// QuantizedLstm parameters</span></div>
1175<div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160; QuantizedLstmInputParamsInfo paramsInfo;</div>
1176<div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160; </div>
1177<div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160; paramsInfo.m_InputToInputWeights =</div>
1178<div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_InputToInputWeights-&gt;GetTensorInfo();</div>
1179<div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160; paramsInfo.m_InputToForgetWeights =</div>
1180<div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_InputToForgetWeights-&gt;GetTensorInfo();</div>
1181<div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160; paramsInfo.m_InputToCellWeights =</div>
1182<div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_InputToCellWeights-&gt;GetTensorInfo();</div>
1183<div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160; paramsInfo.m_InputToOutputWeights =</div>
1184<div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_InputToOutputWeights-&gt;GetTensorInfo();</div>
1185<div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160; </div>
1186<div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>&#160; paramsInfo.m_RecurrentToInputWeights =</div>
1187<div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_RecurrentToInputWeights-&gt;GetTensorInfo();</div>
1188<div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>&#160; paramsInfo.m_RecurrentToForgetWeights =</div>
1189<div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_RecurrentToForgetWeights-&gt;GetTensorInfo();</div>
1190<div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>&#160; paramsInfo.m_RecurrentToCellWeights =</div>
1191<div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_RecurrentToCellWeights-&gt;GetTensorInfo();</div>
1192<div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160; paramsInfo.m_RecurrentToOutputWeights =</div>
1193<div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_RecurrentToOutputWeights-&gt;GetTensorInfo();</div>
1194<div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160; </div>
1195<div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160; paramsInfo.m_InputGateBias =</div>
1196<div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_InputGateBias-&gt;GetTensorInfo();</div>
1197<div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160; paramsInfo.m_ForgetGateBias =</div>
1198<div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_ForgetGateBias-&gt;GetTensorInfo();</div>
1199<div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160; paramsInfo.m_CellBias =</div>
1200<div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_CellBias-&gt;GetTensorInfo();</div>
1201<div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160; paramsInfo.m_OutputGateBias =</div>
1202<div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>&#160; &amp;cLayer-&gt;m_QuantizedLstmParameters.m_OutputGateBias-&gt;GetTensorInfo();;</div>
1203<div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>&#160; </div>
1204<div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>&#160; result = layerSupportObject.IsQuantizedLstmSupported(input,</div>
1205<div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>&#160; previousCellStateIn,</div>
1206<div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>&#160; previousOutputIn,</div>
1207<div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>&#160; cellStateOut,</div>
1208<div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>&#160; output,</div>
1209<div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>&#160; paramsInfo,</div>
1210<div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>&#160; reason);</div>
1211<div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>&#160; <span class="keywordflow">break</span>;</div>
1212<div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>&#160; }</div>
1213<div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">LayerType::Division</a>:</div>
1214<div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>&#160; {</div>
1215<div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
1216<div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
1217<div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
1218<div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1219<div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>&#160; result = layerSupportObject.IsDivisionSupported(</div>
1220<div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>&#160; OverrideDataType(input0, dataType),</div>
1221<div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>&#160; OverrideDataType(input1, dataType),</div>
1222<div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>&#160; OverrideDataType(output, dataType),</div>
1223<div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>&#160; reason);</div>
1224<div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
1225<div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160; <span class="keywordflow">break</span>;</div>
1226<div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160; }</div>
1227<div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a021da1b20f73dc252361a54d80497ef3">LayerType::Rank</a>:</div>
1228<div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160; {</div>
1229<div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1230<div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1231<div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>&#160; result = layerSupportObject.IsRankSupported(OverrideDataType(input, dataType),</div>
1232<div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>&#160; OverrideDataType(output, dataType),</div>
1233<div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>&#160; reason);</div>
1234<div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>&#160; <span class="keywordflow">break</span>;</div>
1235<div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>&#160; }</div>
1236<div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad">LayerType::Reshape</a>:</div>
1237<div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>&#160; {</div>
1238<div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ReshapeLayer*&gt;(&amp;layer);</div>
1239<div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1240<div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1241<div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>&#160; result = layerSupportObject.IsReshapeSupported(OverrideDataType(input, dataType),</div>
1242<div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>&#160; OverrideDataType(output, dataType),</div>
1243<div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>&#160; cLayer-&gt;GetParameters(),</div>
1244<div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>&#160; reason);</div>
1245<div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>&#160; <span class="keywordflow">break</span>;</div>
1246<div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>&#160; }</div>
1247<div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">LayerType::Resize</a>:</div>
1248<div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>&#160; {</div>
1249<div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ResizeLayer*&gt;(&amp;layer);</div>
1250<div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1251<div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1252<div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>&#160; result = layerSupportObject.IsResizeSupported(OverrideDataType(input, dataType),</div>
1253<div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>&#160; OverrideDataType(output, dataType),</div>
1254<div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>&#160; cLayer-&gt;GetParameters(),</div>
1255<div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>&#160; reason);</div>
1256<div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>&#160; <span class="keywordflow">break</span>;</div>
1257<div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>&#160; }</div>
1258<div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af9a0b6ef62dc10097826358e28b19295">LayerType::ReverseV2</a>:</div>
1259<div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>&#160; {</div>
1260<div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetConnection()-&gt;GetTensorInfo();</div>
1261<div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetConnection()-&gt;GetTensorInfo();</div>
1262<div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1263<div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>&#160; result = layerSupportObject.IsReverseV2Supported(OverrideDataType(input0, dataType),</div>
1264<div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>&#160; OverrideDataType(input1, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>),</div>
1265<div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>&#160; OverrideDataType(output, dataType),</div>
1266<div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>&#160; reason);</div>
1267<div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>&#160; <span class="keywordflow">break</span>;</div>
1268<div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>&#160; }</div>
1269<div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7401e8c502f3f7c3544e3f16bf3f488b">LayerType::ScatterNd</a>:</div>
1270<div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>&#160; {</div>
1271<div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ScatterNdLayer*&gt;(&amp;layer);</div>
1272<div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1273<div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>&#160; <span class="keyword">const</span> TensorInfo&amp; indices = layer.GetInputSlot(1).GetTensorInfo();</div>
1274<div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>&#160; <span class="keyword">const</span> TensorInfo&amp; updates = layer.GetInputSlot(2).GetTensorInfo();</div>
1275<div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1276<div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>&#160; </div>
1277<div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>&#160; result = layerSupportObject.IsScatterNdSupported(OverrideDataType(input, dataType),</div>
1278<div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>&#160; OverrideDataType(indices, dataType),</div>
1279<div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>&#160; OverrideDataType(updates, dataType),</div>
1280<div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>&#160; OverrideDataType(output, dataType),</div>
1281<div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>&#160; cLayer-&gt;GetParameters(),</div>
1282<div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>&#160; reason);</div>
1283<div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>&#160; </div>
1284<div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>&#160; <span class="keywordflow">break</span>;</div>
1285<div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>&#160; }</div>
1286<div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a880c1273b27d27cfc82004c3a4b205c9">LayerType::Shape</a>:</div>
1287<div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>&#160; {</div>
1288<div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1289<div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1290<div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>&#160; </div>
1291<div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>&#160; result = layerSupportObject.IsShapeSupported(OverrideDataType(input, dataType),</div>
1292<div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>&#160; OverrideDataType(output, dataType),</div>
1293<div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>&#160; reason);</div>
1294<div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>&#160; <span class="keywordflow">break</span>;</div>
1295<div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>&#160; }</div>
1296<div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb">LayerType::Slice</a>:</div>
1297<div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>&#160; {</div>
1298<div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const SliceLayer*&gt;(&amp;layer);</div>
1299<div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>&#160; </div>
1300<div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1301<div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1302<div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>&#160; </div>
1303<div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>&#160; result = layerSupportObject.IsSliceSupported(OverrideDataType(input, dataType),</div>
1304<div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>&#160; OverrideDataType(output, dataType),</div>
1305<div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>&#160; cLayer-&gt;GetParameters(),</div>
1306<div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>&#160; reason);</div>
1307<div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>&#160; <span class="keywordflow">break</span>;</div>
1308<div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>&#160; }</div>
1309<div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">LayerType::Softmax</a>:</div>
1310<div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>&#160; {</div>
1311<div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const SoftmaxLayer*&gt;(&amp;layer);</div>
1312<div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1313<div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1314<div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>&#160; result = layerSupportObject.IsSoftmaxSupported(OverrideDataType(input, dataType),</div>
1315<div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>&#160; OverrideDataType(output, dataType),</div>
1316<div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>&#160; cLayer-&gt;GetParameters(),</div>
1317<div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>&#160; reason);</div>
1318<div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>&#160; <span class="keywordflow">break</span>;</div>
1319<div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>&#160; }</div>
1320<div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279">LayerType::SpaceToBatchNd</a>:</div>
1321<div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>&#160; {</div>
1322<div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const SpaceToBatchNdLayer*&gt;(&amp;layer);</div>
1323<div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1324<div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1325<div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>&#160; result = layerSupportObject.IsSpaceToBatchNdSupported(OverrideDataType(input, dataType),</div>
1326<div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>&#160; OverrideDataType(output, dataType),</div>
1327<div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>&#160; cLayer-&gt;GetParameters(),</div>
1328<div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>&#160; reason);</div>
1329<div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>&#160; <span class="keywordflow">break</span>;</div>
1330<div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>&#160; }</div>
1331<div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a">LayerType::SpaceToDepth</a>:</div>
1332<div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>&#160; {</div>
1333<div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const SpaceToDepthLayer*&gt;(&amp;layer);</div>
1334<div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>&#160; </div>
1335<div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1336<div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1337<div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>&#160; </div>
1338<div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>&#160; result = layerSupportObject.IsSpaceToDepthSupported(OverrideDataType(input, dataType),</div>
1339<div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>&#160; OverrideDataType(output, dataType),</div>
1340<div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>&#160; cLayer-&gt;GetParameters(),</div>
1341<div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>&#160; reason);</div>
1342<div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>&#160; <span class="keywordflow">break</span>;</div>
1343<div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>&#160; }</div>
1344<div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf">LayerType::Splitter</a>:</div>
1345<div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>&#160; {</div>
1346<div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const SplitterLayer*&gt;(&amp;layer);</div>
1347<div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1348<div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>&#160; </div>
1349<div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>&#160; <span class="comment">// Get vector of all outputs.</span></div>
1350<div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>&#160; <span class="keyword">auto</span> getTensorInfo = [&amp;dataType](<span class="keyword">const</span> OutputSlot&amp; slot)</div>
1351<div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>&#160; {</div>
1352<div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetTensorInfo(), dataType);</div>
1353<div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>&#160; };</div>
1354<div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>&#160; <span class="keyword">auto</span> beginI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().begin(), getTensorInfo);</div>
1355<div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>&#160; <span class="keyword">auto</span> endI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().end(), getTensorInfo);</div>
1356<div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>&#160; std::vector&lt;TensorInfo&gt; outputs(beginI, endI);</div>
1357<div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>&#160; </div>
1358<div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>&#160; <span class="keyword">const</span> std::vector&lt;std::reference_wrapper&lt;TensorInfo&gt;&gt; outputPtrs(outputs.begin(), outputs.end());</div>
1359<div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>&#160; </div>
1360<div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>&#160; result = layerSupportObject.IsSplitterSupported(OverrideDataType(input, dataType),</div>
1361<div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>&#160; outputPtrs,</div>
1362<div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>&#160; cLayer-&gt;GetParameters(),</div>
1363<div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>&#160; reason);</div>
1364<div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>&#160; <span class="keywordflow">break</span>;</div>
1365<div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>&#160; }</div>
1366<div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca">LayerType::Stack</a>:</div>
1367<div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>&#160; {</div>
1368<div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const StackLayer*&gt;(&amp;layer);</div>
1369<div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>&#160; </div>
1370<div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>&#160; <span class="comment">// Get vector of all inputs.</span></div>
1371<div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>&#160; <span class="keyword">auto</span> getTensorInfo = [&amp;dataType](<span class="keyword">const</span> InputSlot&amp; slot)</div>
1372<div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>&#160; {</div>
1373<div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()-&gt;GetTensorInfo(), dataType);</div>
1374<div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>&#160; };</div>
1375<div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>&#160; <span class="keyword">auto</span> beginI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().begin(), getTensorInfo);</div>
1376<div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>&#160; <span class="keyword">auto</span> endI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().end(), getTensorInfo);</div>
1377<div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>&#160; std::vector&lt;TensorInfo&gt; inputs(beginI, endI);</div>
1378<div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>&#160; </div>
1379<div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>&#160; <span class="keyword">auto</span> getTensorInfoPtr = [](<span class="keyword">const</span> TensorInfo&amp; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
1380<div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>&#160; {</div>
1381<div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>&#160; <span class="keywordflow">return</span> &amp;<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div>
1382<div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>&#160; };</div>
1383<div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>&#160; <span class="keyword">auto</span> beginPtr = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.begin(), getTensorInfoPtr);</div>
1384<div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>&#160; <span class="keyword">auto</span> endPtr = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.end(), getTensorInfoPtr);</div>
1385<div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>&#160; std::vector&lt;const TensorInfo*&gt; inputPtrs(beginPtr, endPtr);</div>
1386<div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>&#160; </div>
1387<div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1388<div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>&#160; </div>
1389<div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>&#160; result = layerSupportObject.IsStackSupported(inputPtrs, output, cLayer-&gt;GetParameters(), reason);</div>
1390<div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>&#160; </div>
1391<div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>&#160; <span class="keywordflow">break</span>;</div>
1392<div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>&#160; }</div>
1393<div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">LayerType::StandIn</a>:</div>
1394<div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>&#160; {</div>
1395<div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const StandInLayer*&gt;(&amp;layer);</div>
1396<div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>&#160; </div>
1397<div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>&#160; <span class="comment">// Get vector of all inputs.</span></div>
1398<div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>&#160; <span class="keyword">auto</span> getTensorInfoIn = [&amp;dataType](<span class="keyword">const</span> InputSlot&amp; slot)</div>
1399<div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>&#160; {</div>
1400<div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()-&gt;GetTensorInfo(), dataType);</div>
1401<div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>&#160; };</div>
1402<div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>&#160; <span class="keyword">auto</span> getTensorInfoOut = [&amp;dataType](<span class="keyword">const</span> OutputSlot&amp; slot)</div>
1403<div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>&#160; {</div>
1404<div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>&#160; <span class="keywordflow">return</span> OverrideDataType(slot.GetTensorInfo(), dataType);</div>
1405<div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>&#160; };</div>
1406<div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>&#160; <span class="keyword">auto</span> beginI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().begin(), getTensorInfoIn);</div>
1407<div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>&#160; <span class="keyword">auto</span> endI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetInputSlots().end(), getTensorInfoIn);</div>
1408<div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>&#160; std::vector&lt;TensorInfo&gt; inputs(beginI, endI);</div>
1409<div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>&#160; </div>
1410<div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>&#160; <span class="keyword">auto</span> beginO = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().begin(), getTensorInfoOut);</div>
1411<div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>&#160; <span class="keyword">auto</span> endO = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(layer.GetOutputSlots().end(), getTensorInfoOut);</div>
1412<div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>&#160; std::vector&lt;TensorInfo&gt; outputs(beginO, endO);</div>
1413<div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>&#160; </div>
1414<div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>&#160; </div>
1415<div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>&#160; <span class="keyword">auto</span> getTensorInfoPtr = [](<span class="keyword">const</span> TensorInfo&amp; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
1416<div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>&#160; {</div>
1417<div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>&#160; <span class="keywordflow">return</span> &amp;<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div>
1418<div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>&#160; };</div>
1419<div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>&#160; <span class="keyword">auto</span> beginPtrI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.begin(), getTensorInfoPtr);</div>
1420<div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>&#160; <span class="keyword">auto</span> endPtrI = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(inputs.end(), getTensorInfoPtr);</div>
1421<div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>&#160; std::vector&lt;const TensorInfo*&gt; inputPtrs(beginPtrI, endPtrI);</div>
1422<div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>&#160; </div>
1423<div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>&#160; <span class="keyword">auto</span> beginPtrO = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(outputs.begin(), getTensorInfoPtr);</div>
1424<div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>&#160; <span class="keyword">auto</span> endPtrO = <a class="code" href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">MakeTransformIterator</a>(outputs.end(), getTensorInfoPtr);</div>
1425<div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>&#160; std::vector&lt;const TensorInfo*&gt; outputPtrs(beginPtrO, endPtrO);</div>
1426<div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>&#160; </div>
1427<div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>&#160; </div>
1428<div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>&#160; result = layerSupportObject.IsStandInSupported(inputPtrs,</div>
1429<div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>&#160; outputPtrs,</div>
1430<div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>&#160; cLayer-&gt;GetParameters(),</div>
1431<div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>&#160; reason);</div>
1432<div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>&#160; <span class="keywordflow">break</span>;</div>
1433<div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>&#160; }</div>
1434<div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d">LayerType::StridedSlice</a>:</div>
1435<div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>&#160; {</div>
1436<div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const StridedSliceLayer*&gt;(&amp;layer);</div>
1437<div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1438<div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1439<div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>&#160; result = layerSupportObject.IsStridedSliceSupported(OverrideDataType(input, dataType),</div>
1440<div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>&#160; OverrideDataType(output, dataType),</div>
1441<div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>&#160; cLayer-&gt;GetParameters(),</div>
1442<div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>&#160; reason);</div>
1443<div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>&#160; <span class="keywordflow">break</span>;</div>
1444<div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>&#160; }</div>
1445<div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">LayerType::Subtraction</a>:</div>
1446<div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>&#160; {</div>
1447<div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
1448<div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
1449<div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
1450<div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1451<div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>&#160; result = layerSupportObject.IsSubtractionSupported(</div>
1452<div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>&#160; OverrideDataType(input0, dataType),</div>
1453<div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>&#160; OverrideDataType(input1, dataType),</div>
1454<div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>&#160; OverrideDataType(output, dataType),</div>
1455<div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>&#160; reason);</div>
1456<div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
1457<div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>&#160; <span class="keywordflow">break</span>;</div>
1458<div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>&#160; }</div>
1459<div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">LayerType::Switch</a>:</div>
1460<div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>&#160; {</div>
1461<div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
1462<div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
1463<div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output0 = layer.GetOutputSlot(0).GetTensorInfo();</div>
1464<div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output1 = layer.GetOutputSlot(1).GetTensorInfo();</div>
1465<div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>&#160; result = layerSupportObject.IsSwitchSupported(OverrideDataType(input0, dataType),</div>
1466<div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>&#160; OverrideDataType(input1, dataType),</div>
1467<div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>&#160; OverrideDataType(output0, dataType),</div>
1468<div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>&#160; OverrideDataType(output1, dataType),</div>
1469<div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160; reason);</div>
1470<div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>&#160; <span class="keywordflow">break</span>;</div>
1471<div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>&#160; }</div>
1472<div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d">LayerType::Mean</a>:</div>
1473<div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>&#160; {</div>
1474<div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const MeanLayer*&gt;(&amp;layer);</div>
1475<div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1476<div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1477<div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>&#160; result = layerSupportObject.IsMeanSupported(</div>
1478<div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>&#160; OverrideDataType(input, dataType),</div>
1479<div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>&#160; OverrideDataType(output, dataType),</div>
1480<div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>&#160; cLayer-&gt;GetParameters(),</div>
1481<div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>&#160; reason);</div>
1482<div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160; <span class="keywordflow">break</span>;</div>
1483<div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>&#160; }</div>
1484<div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">LayerType::Minimum</a>:</div>
1485<div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160; {</div>
1486<div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>&#160; <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div>
1487<div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input0 = layer.GetInputSlot(0).GetTensorInfo();</div>
1488<div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input1 = layer.GetInputSlot(1).GetTensorInfo();</div>
1489<div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1490<div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160; result = layerSupportObject.IsMinimumSupported(OverrideDataType(input0, dataType),</div>
1491<div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160; OverrideDataType(input1, dataType),</div>
1492<div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160; OverrideDataType(output, dataType),</div>
1493<div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160; reason);</div>
1494<div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160; <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div>
1495<div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160; <span class="keywordflow">break</span>;</div>
1496<div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>&#160; }</div>
1497<div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">LayerType::Prelu</a>:</div>
1498<div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>&#160; {</div>
1499<div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1500<div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>&#160; <span class="keyword">const</span> TensorInfo&amp; alpha = layer.GetInputSlot(1).GetTensorInfo();</div>
1501<div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1502<div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>&#160; result = layerSupportObject.IsPreluSupported(OverrideDataType(input, dataType),</div>
1503<div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>&#160; OverrideDataType(alpha, dataType),</div>
1504<div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160; OverrideDataType(output, dataType),</div>
1505<div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>&#160; reason);</div>
1506<div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>&#160; <span class="keywordflow">break</span>;</div>
1507<div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>&#160; }</div>
1508<div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ac5457c5f3cfb4da8638ce7190f8e5152">LayerType::Tile</a>:</div>
1509<div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>&#160; {</div>
1510<div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const TileLayer*&gt;(&amp;layer);</div>
1511<div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1512<div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1513<div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160; </div>
1514<div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>&#160; result = layerSupportObject.IsTileSupported(OverrideDataType(input, dataType),</div>
1515<div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>&#160; OverrideDataType(output, dataType),</div>
1516<div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160; cLayer-&gt;GetParameters(),</div>
1517<div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160; reason);</div>
1518<div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160; </div>
1519<div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160; <span class="keywordflow">break</span>;</div>
1520<div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160; }</div>
1521<div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54">LayerType::Transpose</a>:</div>
1522<div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160; {</div>
1523<div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const TransposeLayer*&gt;(&amp;layer);</div>
1524<div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1525<div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1526<div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160; result = layerSupportObject.IsTransposeSupported(OverrideDataType(input, dataType),</div>
1527<div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>&#160; OverrideDataType(output, dataType),</div>
1528<div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160; cLayer-&gt;GetParameters(),</div>
1529<div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160; reason);</div>
1530<div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>&#160; <span class="keywordflow">break</span>;</div>
1531<div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>&#160; }</div>
1532<div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a">LayerType::TransposeConvolution2d</a>:</div>
1533<div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160; {</div>
1534<div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const TransposeConvolution2dLayer*&gt;(&amp;layer);</div>
1535<div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>&#160; </div>
1536<div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>&#160; <span class="keyword">const</span> TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
1537<div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>&#160; dataType);</div>
1538<div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>&#160; <span class="keyword">const</span> TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
1539<div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>&#160; </div>
1540<div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>&#160; <span class="keyword">const</span> TransposeConvolution2dDescriptor&amp; descriptor = cLayer-&gt;GetParameters();</div>
1541<div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>&#160; </div>
1542<div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>&#160; Optional&lt;TensorInfo&gt; biases;</div>
1543<div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div>
1544<div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>&#160; {</div>
1545<div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>(</div>
1546<div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>&#160; cLayer-&gt;m_Bias.get() != <span class="keyword">nullptr</span>,</div>
1547<div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>&#160; <span class="stringliteral">&quot;TransposeConvolution2d: Bias was enabled in the descriptor but no value was supplied.&quot;</span>);</div>
1548<div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>&#160; biases = OverrideDataType(cLayer-&gt;m_Bias-&gt;GetTensorInfo(),</div>
1549<div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>&#160; <a class="code" href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(dataType));</div>
1550<div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>&#160; }</div>
1551<div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>&#160; </div>
1552<div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>(cLayer-&gt;m_Weight.get() != <span class="keyword">nullptr</span>,</div>
1553<div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>&#160; <span class="stringliteral">&quot;TransposeConvolution2d: Weights cannot be null.&quot;</span>);</div>
1554<div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>&#160; <span class="keyword">const</span> TensorInfo weights = OverrideDataType(cLayer-&gt;m_Weight-&gt;GetTensorInfo(), dataType);</div>
1555<div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160; </div>
1556<div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>&#160; result = layerSupportObject.IsTransposeConvolution2dSupported(input,</div>
1557<div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>&#160; output,</div>
1558<div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>&#160; descriptor,</div>
1559<div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160; weights,</div>
1560<div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>&#160; biases,</div>
1561<div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>&#160; reason);</div>
1562<div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>&#160; </div>
1563<div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160; <span class="keywordflow">break</span>;</div>
1564<div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160; }</div>
1565<div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aec4875f03ff0bb0b26cf76ac7f41e3c8">LayerType::Reduce</a>:</div>
1566<div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>&#160; {</div>
1567<div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const ReduceLayer*&gt;(&amp;layer);</div>
1568<div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = layer.GetInputSlot(0).GetTensorInfo();</div>
1569<div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = layer.GetOutputSlot(0).GetTensorInfo();</div>
1570<div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160; </div>
1571<div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160; result = layerSupportObject.IsReduceSupported(OverrideDataType(input, dataType),</div>
1572<div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160; OverrideDataType(output, dataType),</div>
1573<div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160; cLayer-&gt;GetParameters(),</div>
1574<div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>&#160; reason);</div>
1575<div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>&#160; <span class="keywordflow">break</span>;</div>
1576<div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>&#160; }</div>
1577<div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">LayerType::UnidirectionalSequenceLstm</a>:</div>
1578<div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>&#160; {</div>
1579<div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>&#160; <span class="keyword">auto</span> cLayer = PolymorphicDowncast&lt;const UnidirectionalSequenceLstmLayer*&gt;(&amp;layer);</div>
1580<div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ae6c5f1b51bd32133c4dcc632045d6b58">UnidirectionalSequenceLstmDescriptor</a>&amp; descriptor = cLayer-&gt;GetParameters();</div>
1581<div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160; </div>
1582<div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>&#160; <span class="comment">// All inputs.</span></div>
1583<div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160; <span class="keyword">const</span> TensorInfo&amp; input = OverrideDataType(layer.GetInputSlot(0).GetTensorInfo(),</div>
1584<div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>&#160; dataType);</div>
1585<div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputStateIn = OverrideDataType(layer.GetInputSlot(1).GetTensorInfo(),</div>
1586<div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160; dataType);</div>
1587<div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateIn = OverrideDataType(layer.GetInputSlot(2).GetTensorInfo(),</div>
1588<div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>&#160; dataType);</div>
1589<div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>&#160; <span class="comment">// Outputs</span></div>
1590<div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputStateOut = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType);</div>
1591<div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellStateOut = OverrideDataType(layer.GetOutputSlot(1).GetTensorInfo(), dataType);</div>
1592<div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>&#160; <span class="keyword">const</span> TensorInfo&amp; output = OverrideDataType(layer.GetOutputSlot(2).GetTensorInfo(), dataType);</div>
1593<div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>&#160; </div>
1594<div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>&#160; <span class="comment">// Basic parameters</span></div>
1595<div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToForgetWeights</div>
1596<div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
1597<div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToCellWeights</div>
1598<div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToCellWeights-&gt;GetTensorInfo(), dataType);</div>
1599<div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>&#160; <span class="keyword">const</span> TensorInfo&amp; inputToOutputWeights</div>
1600<div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_InputToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
1601<div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToForgetWeights</div>
1602<div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
1603<div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToCellWeights</div>
1604<div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToCellWeights-&gt;GetTensorInfo(), dataType);</div>
1605<div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160; <span class="keyword">const</span> TensorInfo&amp; recurrentToOutputWeights</div>
1606<div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_RecurrentToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
1607<div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>&#160; <span class="keyword">const</span> TensorInfo&amp; forgetGateBias</div>
1608<div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_ForgetGateBias-&gt;GetTensorInfo(), dataType);</div>
1609<div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>&#160; <span class="keyword">const</span> TensorInfo&amp; cellBias</div>
1610<div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_CellBias-&gt;GetTensorInfo(), dataType);</div>
1611<div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outputGateBias</div>
1612<div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>&#160; = OverrideDataType(cLayer-&gt;m_BasicParameters.m_OutputGateBias-&gt;GetTensorInfo(), dataType);</div>
1613<div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>&#160; </div>
1614<div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160; LstmInputParamsInfo paramsInfo;</div>
1615<div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>&#160; </div>
1616<div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>&#160; paramsInfo.m_InputToForgetWeights = &amp;inputToForgetWeights;</div>
1617<div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>&#160; paramsInfo.m_InputToCellWeights = &amp;inputToCellWeights;</div>
1618<div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>&#160; paramsInfo.m_InputToOutputWeights = &amp;inputToOutputWeights;</div>
1619<div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160; paramsInfo.m_RecurrentToForgetWeights = &amp;recurrentToForgetWeights;</div>
1620<div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>&#160; paramsInfo.m_RecurrentToCellWeights = &amp;recurrentToCellWeights;</div>
1621<div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>&#160; paramsInfo.m_RecurrentToOutputWeights = &amp;recurrentToOutputWeights;</div>
1622<div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>&#160; paramsInfo.m_ForgetGateBias = &amp;forgetGateBias;</div>
1623<div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>&#160; paramsInfo.m_CellBias = &amp;cellBias;</div>
1624<div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>&#160; paramsInfo.m_OutputGateBias = &amp;outputGateBias;</div>
1625<div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>&#160; </div>
1626<div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>&#160; <span class="comment">// Optional parameters</span></div>
1627<div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>&#160; TensorInfo optInputToInputWeights;</div>
1628<div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>&#160; TensorInfo optRecurrentToInputWeights;</div>
1629<div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>&#160; TensorInfo optCellToInputWeights;</div>
1630<div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>&#160; TensorInfo optInputGateBias;</div>
1631<div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160; TensorInfo optProjectionWeights;</div>
1632<div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>&#160; TensorInfo optProjectionBias;</div>
1633<div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>&#160; TensorInfo optCellToForgetWeights;</div>
1634<div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>&#160; TensorInfo optCellToOutputWeights;</div>
1635<div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>&#160; TensorInfo optInputLayerNormWeights;</div>
1636<div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>&#160; TensorInfo optForgetLayerNormWeights;</div>
1637<div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>&#160; TensorInfo optCellLayerNormWeights;</div>
1638<div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>&#160; TensorInfo optOutputLayerNormWeights;</div>
1639<div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>&#160; </div>
1640<div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>&#160; <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div>
1641<div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>&#160; {</div>
1642<div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>&#160; optInputToInputWeights =</div>
1643<div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_InputToInputWeights-&gt;GetTensorInfo(), dataType);</div>
1644<div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>&#160; paramsInfo.m_InputToInputWeights = &amp;optInputToInputWeights;</div>
1645<div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160; </div>
1646<div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160; optRecurrentToInputWeights =</div>
1647<div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_RecurrentToInputWeights-&gt;GetTensorInfo(), dataType);</div>
1648<div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>&#160; paramsInfo.m_RecurrentToInputWeights = &amp;optRecurrentToInputWeights;</div>
1649<div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>&#160; optInputGateBias =</div>
1650<div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>&#160; OverrideDataType(cLayer-&gt;m_CifgParameters.m_InputGateBias-&gt;GetTensorInfo(), dataType);</div>
1651<div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>&#160; paramsInfo.m_InputGateBias = &amp;optInputGateBias;</div>
1652<div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>&#160; }</div>
1653<div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>&#160; </div>
1654<div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160; <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div>
1655<div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>&#160; {</div>
1656<div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>&#160; optProjectionWeights =</div>
1657<div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160; OverrideDataType(cLayer-&gt;m_ProjectionParameters.m_ProjectionWeights-&gt;GetTensorInfo(), dataType);</div>
1658<div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160; paramsInfo.m_ProjectionWeights = &amp;optProjectionWeights;</div>
1659<div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>&#160; <span class="keywordflow">if</span> (cLayer-&gt;m_ProjectionParameters.m_ProjectionBias != <span class="keyword">nullptr</span>)</div>
1660<div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160; {</div>
1661<div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>&#160; optProjectionBias =</div>
1662<div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160; OverrideDataType(cLayer-&gt;m_ProjectionParameters.m_ProjectionBias-&gt;GetTensorInfo(), dataType);</div>
1663<div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>&#160; paramsInfo.m_ProjectionBias = &amp;optProjectionBias;</div>
1664<div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>&#160; }</div>
1665<div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>&#160; }</div>
1666<div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160; </div>
1667<div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>&#160; <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div>
1668<div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>&#160; {</div>
1669<div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>&#160; <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div>
1670<div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>&#160; {</div>
1671<div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160; optCellToInputWeights =</div>
1672<div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToInputWeights-&gt;GetTensorInfo(),</div>
1673<div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160; dataType);</div>
1674<div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>&#160; paramsInfo.m_CellToInputWeights = &amp;optCellToInputWeights;</div>
1675<div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160; }</div>
1676<div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160; optCellToForgetWeights =</div>
1677<div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToForgetWeights-&gt;GetTensorInfo(), dataType);</div>
1678<div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>&#160; paramsInfo.m_CellToForgetWeights = &amp;optCellToForgetWeights;</div>
1679<div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160; optCellToOutputWeights =</div>
1680<div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>&#160; OverrideDataType(cLayer-&gt;m_PeepholeParameters.m_CellToOutputWeights-&gt;GetTensorInfo(), dataType);</div>
1681<div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>&#160; paramsInfo.m_CellToOutputWeights = &amp;optCellToOutputWeights;</div>
1682<div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160; }</div>
1683<div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>&#160; </div>
1684<div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>&#160; <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</div>
1685<div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>&#160; {</div>
1686<div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>&#160; <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div>
1687<div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>&#160; {</div>
1688<div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>&#160; optInputLayerNormWeights = OverrideDataType(</div>
1689<div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>&#160; cLayer-&gt;m_LayerNormParameters.m_InputLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
1690<div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>&#160; paramsInfo.m_InputLayerNormWeights = &amp;optInputLayerNormWeights;</div>
1691<div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>&#160; }</div>
1692<div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160; </div>
1693<div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>&#160; optForgetLayerNormWeights = OverrideDataType(</div>
1694<div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>&#160; cLayer-&gt;m_LayerNormParameters.m_ForgetLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
1695<div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>&#160; paramsInfo.m_ForgetLayerNormWeights = &amp;optForgetLayerNormWeights;</div>
1696<div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>&#160; </div>
1697<div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160; optCellLayerNormWeights = OverrideDataType(</div>
1698<div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160; cLayer-&gt;m_LayerNormParameters.m_CellLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
1699<div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160; paramsInfo.m_CellLayerNormWeights = &amp;optCellLayerNormWeights;</div>
1700<div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160; </div>
1701<div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160; optOutputLayerNormWeights = OverrideDataType(</div>
1702<div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160; cLayer-&gt;m_LayerNormParameters.m_OutputLayerNormWeights-&gt;GetTensorInfo(), dataType);</div>
1703<div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>&#160; paramsInfo.m_OutputLayerNormWeights = &amp;optOutputLayerNormWeights;</div>
1704<div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>&#160; }</div>
1705<div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160; </div>
1706<div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160; result = layerSupportObject.IsUnidirectionalSequenceLstmSupported(input,</div>
1707<div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160; outputStateIn,</div>
1708<div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160; cellStateIn,</div>
1709<div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160; outputStateOut,</div>
1710<div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160; cellStateOut,</div>
1711<div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>&#160; output,</div>
1712<div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160; descriptor,</div>
1713<div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>&#160; paramsInfo,</div>
1714<div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>&#160; reason);</div>
1715<div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160; <span class="keywordflow">break</span>;</div>
1716<div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>&#160; }</div>
1717<div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>&#160; <span class="keywordflow">default</span>:</div>
1718<div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>&#160; {</div>
1719<div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>&#160; reason.value() = <span class="stringliteral">&quot;Unrecognised layer type&quot;</span>;</div>
1720<div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>&#160; result = <span class="keyword">false</span>;</div>
1721<div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160; <span class="keywordflow">break</span>;</div>
1722<div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>&#160; }</div>
1723<div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160; }</div>
1724<div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160; <span class="keywordflow">return</span> result;</div>
1725<div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;}</div>
1726<div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160; </div>
1727<div class="line"><a name="l01629"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87"> 1629</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_backend_id.html">BackendId</a>&amp; backendId,</div>
1728<div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>&amp; connectableLayer,</div>
1729<div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160; <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;DataType&gt;</a> dataType,</div>
1730<div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160; std::string&amp; outReasonIfUnsupported)</div>
1731<div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160;{</div>
1732<div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160; <span class="keywordflow">return</span> IsLayerConfigurationSupported(backendId, connectableLayer, dataType, outReasonIfUnsupported);</div>
1733<div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;}</div>
1734<div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>&#160; </div>
1735<div class="line"><a name="l01637"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.html#a7d94ea841143b76fe08ccb308839bfd7"> 1637</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>&amp; connectableLayer,</div>
1736<div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>&#160; <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;DataType&gt;</a> dataType,</div>
1737<div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>&#160; std::string&amp; outReasonIfUnsupported)</div>
1738<div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160;{</div>
1739<div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>&#160; <span class="keyword">auto</span> layer = PolymorphicDowncast&lt;const Layer*&gt;(&amp;connectableLayer);</div>
1740<div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>&#160; <span class="keywordflow">return</span> IsLayerConfigurationSupported(layer-&gt;GetBackendId(), connectableLayer, dataType, outReasonIfUnsupported);</div>
1741<div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>&#160;}</div>
1742<div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160; </div>
1743<div class="line"><a name="l01645"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.html#aeaff50773427132e1066a7de56a53db1"> 1645</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>&amp; connectableLayer,</div>
1744<div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>&#160; <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;DataType&gt;</a> dataType,</div>
1745<div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>&#160; std::string&amp; outReasonIfUnsupported,</div>
1746<div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>&amp; modelOptions)</div>
1747<div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>&#160;{</div>
1748<div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>&#160; <span class="keyword">auto</span> layer = PolymorphicDowncast&lt;const Layer*&gt;(&amp;connectableLayer);</div>
1749<div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>&#160; <span class="keywordflow">return</span> IsLayerConfigurationSupported(layer-&gt;GetBackendId(),</div>
1750<div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>&#160; connectableLayer,</div>
1751<div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>&#160; dataType,</div>
1752<div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>&#160; outReasonIfUnsupported,</div>
1753<div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>&#160; modelOptions);</div>
1754<div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>&#160;}</div>
1755<div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>&#160; </div>
1756<div class="line"><a name="l01658"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.html#a52ba8d60c6582a847ef7bc914116d394"> 1658</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_backend_id.html">BackendId</a>&amp; backendId,</div>
1757<div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>&amp; connectableLayer,</div>
1758<div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>&#160; <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;DataType&gt;</a> dataType,</div>
1759<div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>&#160; std::string&amp; outReasonIfUnsupported,</div>
1760<div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>&amp; modelOptions)</div>
1761<div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>&#160;{</div>
1762<div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>&#160; <span class="keywordflow">return</span> IsLayerConfigurationSupported(backendId,</div>
1763<div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>&#160; connectableLayer,</div>
1764<div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>&#160; dataType,</div>
1765<div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>&#160; outReasonIfUnsupported,</div>
1766<div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>&#160; modelOptions);</div>
1767<div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>&#160;}</div>
1768<div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>&#160; </div>
1769<div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>&#160;} <span class="comment">// namepsace armnn</span></div>
1770</div><!-- fragment --></div><!-- contents -->
1771</div><!-- doc-content -->
1772<div class="ttc" id="a_backend_helper_8hpp_html"><div class="ttname"><a href="_backend_helper_8hpp.html">BackendHelper.hpp</a></div></div>
1773<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a">armnn::LayerType::SpaceToDepth</a></div><div class="ttdeci">@ SpaceToDepth</div></div>
1774<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div><div class="ttdeci">@ Boolean</div></div>
1775<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</a></div><div class="ttdeci">@ Permute</div></div>
1776<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf">armnn::LayerType::Splitter</a></div><div class="ttdeci">@ Splitter</div></div>
1777<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::LayerType::BatchNormalization</a></div><div class="ttdeci">@ BatchNormalization</div></div>
1778<div class="ttc" id="aclassarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00270">Optional.hpp:270</a></div></div>
1779<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4">armnn::LayerType::InstanceNormalization</a></div><div class="ttdeci">@ InstanceNormalization</div></div>
1780<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::LayerType::ConvertFp16ToFp32</a></div><div class="ttdeci">@ ConvertFp16ToFp32</div></div>
1781<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af3f6d0343d56ce88ce7958170ed05cb3">armnn::LayerType::Floor</a></div><div class="ttdeci">@ Floor</div></div>
1782<div class="ttc" id="anamespacearmnn_html_ae6c5f1b51bd32133c4dcc632045d6b58"><div class="ttname"><a href="namespacearmnn.html#ae6c5f1b51bd32133c4dcc632045d6b58">armnn::UnidirectionalSequenceLstmDescriptor</a></div><div class="ttdeci">LstmDescriptor UnidirectionalSequenceLstmDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01169">Descriptors.hpp:1169</a></div></div>
1783<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54">armnn::LayerType::Transpose</a></div><div class="ttdeci">@ Transpose</div></div>
1784<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">armnn::LayerType::Comparison</a></div><div class="ttdeci">@ Comparison</div></div>
1785<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d">armnn::LayerType::StridedSlice</a></div><div class="ttdeci">@ StridedSlice</div></div>
1786<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div><div class="ttdeci">@ Float32</div></div>
1787<div class="ttc" id="anamespacearmnn_html_ada0fb4f79f3673b4ebd94a42175bf78d"><div class="ttname"><a href="namespacearmnn.html#ada0fb4f79f3673b4ebd94a42175bf78d">armnn::GetBiasTypeFromWeightsType</a></div><div class="ttdeci">armnn::Optional&lt; armnn::DataType &gt; GetBiasTypeFromWeightsType(armnn::Optional&lt; armnn::DataType &gt; weightsType)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_support_rules_8hpp_source.html#l00013">LayerSupportRules.hpp:13</a></div></div>
1788<div class="ttc" id="a_deprecated_8hpp_html_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.html#l00033">Deprecated.hpp:33</a></div></div>
1789<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ac5457c5f3cfb4da8638ce7190f8e5152"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ac5457c5f3cfb4da8638ce7190f8e5152">armnn::LayerType::Tile</a></div><div class="ttdeci">@ Tile</div></div>
1790<div class="ttc" id="anamespacearmnn_html_a2cf1ea7140f419eba6d60d01dd0a795a"><div class="ttname"><a href="namespacearmnn.html#a2cf1ea7140f419eba6d60d01dd0a795a">armnn::MakeTransformIterator</a></div><div class="ttdeci">constexpr TransformIterator&lt; Function, Iterator &gt; MakeTransformIterator(Iterator i, Function f)</div><div class="ttdef"><b>Definition:</b> <a href="_transform_iterator_8hpp_source.html#l00090">TransformIterator.hpp:90</a></div></div>
1791<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div><div class="ttdeci">@ QAsymmU8</div></div>
1792<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca">armnn::LayerType::Stack</a></div><div class="ttdeci">@ Stack</div></div>
1793<div class="ttc" id="a_backend_registry_8hpp_html"><div class="ttname"><a href="_backend_registry_8hpp.html">BackendRegistry.hpp</a></div></div>
1794<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div><div class="ttdeci">@ QSymmS8</div></div>
1795<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a></div><div class="ttdeci">@ Normalization</div></div>
1796<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">armnn::LayerType::QuantizedLstm</a></div><div class="ttdeci">@ QuantizedLstm</div></div>
1797<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aec4875f03ff0bb0b26cf76ac7f41e3c8"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aec4875f03ff0bb0b26cf76ac7f41e3c8">armnn::LayerType::Reduce</a></div><div class="ttdeci">@ Reduce</div></div>
1798<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7">armnn::LayerType::ElementwiseUnary</a></div><div class="ttdeci">@ ElementwiseUnary</div></div>
1799<div class="ttc" id="a_i_layer_support_8hpp_html"><div class="ttname"><a href="_i_layer_support_8hpp.html">ILayerSupport.hpp</a></div></div>
1800<div class="ttc" id="a_transform_iterator_8hpp_html"><div class="ttname"><a href="_transform_iterator_8hpp.html">TransformIterator.hpp</a></div></div>
1801<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div><div class="ttdeci">@ QSymmS16</div></div>
1802<div class="ttc" id="a_workload_factory_8hpp_html"><div class="ttname"><a href="_workload_factory_8hpp.html">WorkloadFactory.hpp</a></div></div>
1803<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a3028cc42e40f9a1f4f8b35556d9715a4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3028cc42e40f9a1f4f8b35556d9715a4">armnn::LayerType::GatherNd</a></div><div class="ttdeci">@ GatherNd</div></div>
1804<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">armnn::LayerType::ElementwiseBinary</a></div><div class="ttdeci">@ ElementwiseBinary</div></div>
1805<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div><div class="ttdeci">@ BFloat16</div></div>
1806<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::LayerType::ConvertFp32ToFp16</a></div><div class="ttdeci">@ ConvertFp32ToFp16</div></div>
1807<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb">armnn::LayerType::Slice</a></div><div class="ttdeci">@ Slice</div></div>
1808<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div><div class="ttdeci">@ Float16</div></div>
1809<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a0ca5f33c1d35fd4105d3a26a2823f9dd"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0ca5f33c1d35fd4105d3a26a2823f9dd">armnn::LayerType::ChannelShuffle</a></div><div class="ttdeci">@ ChannelShuffle</div></div>
1810<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">armnn::LayerType::Subtraction</a></div><div class="ttdeci">@ Subtraction</div></div>
1811<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">armnn::LayerType::Prelu</a></div><div class="ttdeci">@ Prelu</div></div>
1812<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a7401e8c502f3f7c3544e3f16bf3f488b"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7401e8c502f3f7c3544e3f16bf3f488b">armnn::LayerType::ScatterNd</a></div><div class="ttdeci">@ ScatterNd</div></div>
1813<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30">armnn::LayerType::LogicalBinary</a></div><div class="ttdeci">@ LogicalBinary</div></div>
1814<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">armnn::LayerType::Concat</a></div><div class="ttdeci">@ Concat</div></div>
1815<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a">armnn::LayerType::TransposeConvolution2d</a></div><div class="ttdeci">@ TransposeConvolution2d</div></div>
1816<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">armnn::LayerType::Merge</a></div><div class="ttdeci">@ Merge</div></div>
1817<div class="ttc" id="a_polymorphic_downcast_8hpp_html"><div class="ttname"><a href="_polymorphic_downcast_8hpp.html">PolymorphicDowncast.hpp</a></div></div>
1818<div class="ttc" id="astructarmnn_1_1_empty_optional_html"><div class="ttname"><a href="structarmnn_1_1_empty_optional.html">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00032">Optional.hpp:32</a></div></div>
1819<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">armnn::LayerType::StandIn</a></div><div class="ttdeci">@ StandIn</div></div>
1820<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba">armnn::LayerType::Debug</a></div><div class="ttdeci">@ Debug</div></div>
1821<div class="ttc" id="a_i_backend_internal_8hpp_html"><div class="ttname"><a href="_i_backend_internal_8hpp.html">IBackendInternal.hpp</a></div></div>
1822<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">armnn::LayerType::Softmax</a></div><div class="ttdeci">@ Softmax</div></div>
1823<div class="ttc" id="a_layers_fwd_8hpp_html"><div class="ttname"><a href="_layers_fwd_8hpp.html">LayersFwd.hpp</a></div></div>
1824<div class="ttc" id="anamespacearmnn_html_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.html#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry &amp; BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.html#l00015">BackendRegistry.cpp:15</a></div></div>
1825<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb">armnn::LayerType::Quantize</a></div><div class="ttdeci">@ Quantize</div></div>
1826<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">armnn::LayerType::Multiplication</a></div><div class="ttdeci">@ Multiplication</div></div>
1827<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</a></div><div class="ttdeci">@ Addition</div></div>
1828<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d">armnn::LayerType::DepthToSpace</a></div><div class="ttdeci">@ DepthToSpace</div></div>
1829<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af6f7ce1d0822dea293ac2edc111e54ed"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6f7ce1d0822dea293ac2edc111e54ed">armnn::LayerType::BroadcastTo</a></div><div class="ttdeci">@ BroadcastTo</div></div>
1830<div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
1831<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">armnn::LayerType::DetectionPostProcess</a></div><div class="ttdeci">@ DetectionPostProcess</div></div>
1832<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">armnn::LayerType::MemImport</a></div><div class="ttdeci">@ MemImport</div></div>
1833<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001">armnn::LayerType::Pooling2d</a></div><div class="ttdeci">@ Pooling2d</div></div>
1834<div class="ttc" id="aclassarmnn_1_1_i_workload_factory_html_a74dc9ec1a223eab8b072368b2dacee87"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a74dc9ec1a223eab8b072368b2dacee87">armnn::IWorkloadFactory::IsLayerSupported</a></div><div class="ttdeci">static bool IsLayerSupported(const BackendId &amp;backendId, const IConnectableLayer &amp;layer, Optional&lt; DataType &gt; dataType, std::string &amp;outReasonIfUnsupported)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01629">WorkloadFactory.cpp:1629</a></div></div>
1835<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">armnn::LayerType::Division</a></div><div class="ttdeci">@ Division</div></div>
1836<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div><div class="ttdeci">@ Signed32</div></div>
1837<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a880c1273b27d27cfc82004c3a4b205c9"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a880c1273b27d27cfc82004c3a4b205c9">armnn::LayerType::Shape</a></div><div class="ttdeci">@ Shape</div></div>
1838<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div><div class="ttdeci">@ QAsymmS8</div></div>
1839<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::LayerType::FullyConnected</a></div><div class="ttdeci">@ FullyConnected</div></div>
1840<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53">armnn::LayerType::Gather</a></div><div class="ttdeci">@ Gather</div></div>
1841<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a2b3140dc366b9fcd25ed786a79d1817c"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2b3140dc366b9fcd25ed786a79d1817c">armnn::LayerType::Pooling3d</a></div><div class="ttdeci">@ Pooling3d</div></div>
1842<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488">armnn::LayerType::LogSoftmax</a></div><div class="ttdeci">@ LogSoftmax</div></div>
1843<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a9882ff3cfed27d6161c20a305e7a3484"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9882ff3cfed27d6161c20a305e7a3484">armnn::LayerType::BatchMatMul</a></div><div class="ttdeci">@ BatchMatMul</div></div>
1844<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">armnn::LayerType::DepthwiseConvolution2d</a></div><div class="ttdeci">@ DepthwiseConvolution2d</div></div>
1845<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a4cd9f3996d60790cd11c04f842ebc43c"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a4cd9f3996d60790cd11c04f842ebc43c">armnn::LayerType::Cast</a></div><div class="ttdeci">@ Cast</div></div>
1846<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">armnn::LayerType::BatchToSpaceNd</a></div><div class="ttdeci">@ BatchToSpaceNd</div></div>
1847<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">armnn::LayerType::Switch</a></div><div class="ttdeci">@ Switch</div></div>
1848<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad">armnn::LayerType::Reshape</a></div><div class="ttdeci">@ Reshape</div></div>
1849<div class="ttc" id="a_deprecated_8hpp_html_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.html#l00034">Deprecated.hpp:34</a></div></div>
1850<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279">armnn::LayerType::SpaceToBatchNd</a></div><div class="ttdeci">@ SpaceToBatchNd</div></div>
1851<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4adb3e3f51c9107e26c9bccf9a188ce2ed"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb3e3f51c9107e26c9bccf9a188ce2ed">armnn::LayerType::Fill</a></div><div class="ttdeci">@ Fill</div></div>
1852<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2">armnn::LayerType::L2Normalization</a></div><div class="ttdeci">@ L2Normalization</div></div>
1853<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af617f46b788e11a564cb16c9f5d59fea"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af617f46b788e11a564cb16c9f5d59fea">armnn::LayerType::Fused</a></div><div class="ttdeci">@ Fused</div></div>
1854<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::LayerType::Minimum</a></div><div class="ttdeci">@ Minimum</div></div>
1855<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278">armnn::LayerType::PreCompiled</a></div><div class="ttdeci">@ PreCompiled</div></div>
1856<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div><div class="ttdeci">@ UnidirectionalSequenceLstm</div></div>
1857<div class="ttc" id="aclassarmnn_1_1_backend_id_html"><div class="ttname"><a href="classarmnn_1_1_backend_id.html">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00075">BackendId.hpp:75</a></div></div>
1858<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af9a0b6ef62dc10097826358e28b19295"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af9a0b6ef62dc10097826358e28b19295">armnn::LayerType::ReverseV2</a></div><div class="ttdeci">@ ReverseV2</div></div>
1859<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div><div class="ttdeci">@ MemCopy</div></div>
1860<div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div>
1861<div class="ttc" id="a_types_8hpp_html"><div class="ttname"><a href="_types_8hpp.html">Types.hpp</a></div></div>
1862<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c">armnn::LayerType::ArgMinMax</a></div><div class="ttdeci">@ ArgMinMax</div></div>
1863<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">armnn::LayerType::Pad</a></div><div class="ttdeci">@ Pad</div></div>
1864<div class="ttc" id="a_layer_8hpp_html"><div class="ttname"><a href="_layer_8hpp.html">Layer.hpp</a></div></div>
1865<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a021da1b20f73dc252361a54d80497ef3"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a021da1b20f73dc252361a54d80497ef3">armnn::LayerType::Rank</a></div><div class="ttdeci">@ Rank</div></div>
1866<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d">armnn::LayerType::Mean</a></div><div class="ttdeci">@ Mean</div></div>
1867<div class="ttc" id="aclassarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00080">INetwork.hpp:80</a></div></div>
1868<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div><div class="ttdeci">@ Input</div></div>
1869<div class="ttc" id="anamespacearmnn_html_a5b6893cda5b69359a4244c06054da18f"><div class="ttname"><a href="namespacearmnn.html#a5b6893cda5b69359a4244c06054da18f">armnn::ModelOptions</a></div><div class="ttdeci">std::vector&lt; BackendOptions &gt; ModelOptions</div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.html#l00018">BackendOptions.hpp:18</a></div></div>
1870<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">armnn::LayerType::Resize</a></div><div class="ttdeci">@ Resize</div></div>
1871<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a></div><div class="ttdeci">@ Convolution2d</div></div>
1872<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">armnn::LayerType::FakeQuantization</a></div><div class="ttdeci">@ FakeQuantization</div></div>
1873<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">armnn::LayerType::Maximum</a></div><div class="ttdeci">@ Maximum</div></div>
1874<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36">armnn::LayerType::Activation</a></div><div class="ttdeci">@ Activation</div></div>
1875<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925">armnn::LayerType::Lstm</a></div><div class="ttdeci">@ Lstm</div></div>
1876<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d">armnn::LayerType::Dequantize</a></div><div class="ttdeci">@ Dequantize</div></div>
1877<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a583550d0f265fd3756f7de0e42c51953"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a583550d0f265fd3756f7de0e42c51953">armnn::LayerType::Convolution3d</a></div><div class="ttdeci">@ Convolution3d</div></div>
1878<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a91880b71ea6d007439b7bc7c320b5c25"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a91880b71ea6d007439b7bc7c320b5c25">armnn::LayerType::QLstm</a></div><div class="ttdeci">@ QLstm</div></div>
1879<div class="ttc" id="aclassarmnn_1_1_optional_reference_switch_html_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch&lt; std::is_reference&lt; T &gt;::value, T &gt;::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00146">Optional.hpp:146</a></div></div>
1880<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div><div class="ttdeci">@ Output</div></div>
1881<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a></div><div class="ttdeci">@ Constant</div></div>
1882<div class="ttc" id="a_exceptions_8hpp_html_a5b0cd1f24b12298894d6367f186ea6dc"><div class="ttname"><a href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a></div><div class="ttdeci">#define ARMNN_THROW_INVALIDARG_MSG_IF_FALSE(_cond, _str)</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00210">Exceptions.hpp:210</a></div></div>
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1886 <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.html">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.html">backendsCommon</a></li><li class="navelem"><a class="el" href="_workload_factory_8cpp.html">WorkloadFactory.cpp</a></li>
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