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<div class="title">ConvertFp32NetworkToFp16.hpp</div> </div>
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<a href="_convert_fp32_network_to_fp16_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_optimization_8hpp.xhtml">Optimization.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_network_utils_8hpp.xhtml">NetworkUtils.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> {</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="keyword">namespace </span>optimizations</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> {</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml"> 15</a></span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml">ConvertFp32NetworkToFp16Impl</a></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#aaa2a4663cec52a8aa89a93c7c8317183"> 18</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#aaa2a4663cec52a8aa89a93c7c8317183">Run</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph, <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer)<span class="keyword"> const</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keywordflow">if</span>(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="comment">// if the outputs of this layer are DataType::Float32</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="comment">// add a ConvertFloat32ToFloat16 layer after each of the outputs</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, layer);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  }</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  }</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="comment">// For DetectionPostProcess Layer output is always Float32 regardless of input type</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>()[0].GetConnectedOutputSlot()->GetOwningLayer();</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordflow">if</span> (connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">LayerType::DetectionPostProcess</a>)</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="comment">// if the inputs of this layer are DataType::Float32</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// add a ConvertFloat16ToFloat32 layer before each of the inputs</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// NOTE: We need to call InsertConvertFp16ToFp32LayersBefore with expectCorrectInputType = false</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// here, otherwise it will expect the inputs to be DataType::Float16</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, layer, <span class="keyword">false</span>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  }</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">LayerType::ConvertFp32ToFp16</a> && layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">LayerType::ConvertFp16ToFp32</a>)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">// if the inputs/outputs of this layer are DataType::Float32</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="comment">// change the data type for all inputs and outputs to DataType::Float16</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af6cb8de21ef0da269ec9b67755ae92a0">BeginInputSlots</a>(); input != layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a9752e12d6b79e18da1a25f76159d2a72">EndInputSlots</a>(); ++input)</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// if it is connected to OutputSlot of the InputLayer do not change the DataType of connection</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="comment">// InputSlots of the current layer will be updated when conversion layer is inserted after InputLayer</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& base = input->GetConnectedOutputSlot()->GetOwningLayer();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">if</span> (base.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  {</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> convertInfo = input->GetConnection()->GetTensorInfo();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">if</span> (convertInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  {</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  convertInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">SetDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  input->GetConnection()->SetTensorInfo(convertInfo);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  }</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  }</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// For DetectionPostProcess Layer output is always Float32 regardless of input type</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">LayerType::DetectionPostProcess</a>)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// change outputs to DataType::Float16</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a817d4be6dd88f532d36f51748ec14185">BeginOutputSlots</a>(); output != layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a55f76d98fcd2f5cdac3e2b14536cb7ab">EndOutputSlots</a>(); ++output)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> convertInfo = output->GetTensorInfo();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">if</span> (convertInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  convertInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">SetDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  output->SetTensorInfo(convertInfo);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  }</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  }</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  }</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="keyword">protected</span>:</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#a8c54552a0f174237e8c7edeb7daf2684">ConvertFp32NetworkToFp16Impl</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#a2b3e400ddbdb7b3f846b47bb535dfd97">~ConvertFp32NetworkToFp16Impl</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> };</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1optimizations.xhtml#a86d19da62b6cfed3928f6fe7026f22fa"> 87</a></span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_optimize_for_type.xhtml">Fp32NetworkToFp16Converter</a> = <a class="code" href="classarmnn_1_1_optimize_for_type.xhtml">OptimizeForType<Layer, ConvertFp32NetworkToFp16Impl></a>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> } <span class="comment">// namespace optimizations</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_layer_xhtml_a9752e12d6b79e18da1a25f76159d2a72"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a9752e12d6b79e18da1a25f76159d2a72">armnn::Layer::EndInputSlots</a></div><div class="ttdeci">std::vector< InputSlot >::iterator EndInputSlots()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00242">Layer.hpp:242</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_abf625e50a5eaeafce5b39580dc95a9d3"><div class="ttname"><a href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">armnn::InsertConvertFp32ToFp16LayersAfter</a></div><div class="ttdeci">std::vector< ConvertFp32ToFp16Layer * > InsertConvertFp32ToFp16LayersAfter(Graph &graph, Layer &layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00201">NetworkUtils.cpp:201</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad31c56533e4f9f9f51719599fbfcf7bb"><div class="ttname"><a href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">armnn::InsertConvertFp16ToFp32LayersBefore</a></div><div class="ttdeci">std::vector< ConvertFp16ToFp32Layer * > InsertConvertFp16ToFp32LayersBefore(Graph &graph, Layer &layer, bool expectCorrectInputType)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00129">NetworkUtils.cpp:129</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div>
<div class="ttc" id="classarmnn_1_1_optimize_for_type_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimize_for_type.xhtml">armnn::OptimizeForType</a></div><div class="ttdef"><b>Definition:</b> <a href="_optimization_8hpp_source.xhtml#l00067">Optimization.hpp:67</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::LayerType::ConvertFp32ToFp16</a></div></div>
<div class="ttc" id="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl_xhtml_a8c54552a0f174237e8c7edeb7daf2684"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#a8c54552a0f174237e8c7edeb7daf2684">armnn::optimizations::ConvertFp32NetworkToFp16Impl::ConvertFp32NetworkToFp16Impl</a></div><div class="ttdeci">ConvertFp32NetworkToFp16Impl()=default</div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_af5f530544d09a44d726f24702b67b35b"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">armnn::Layer::GetInputSlots</a></div><div class="ttdeci">const std::vector< InputSlot > & GetInputSlots() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00237">Layer.hpp:237</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_af6cb8de21ef0da269ec9b67755ae92a0"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#af6cb8de21ef0da269ec9b67755ae92a0">armnn::Layer::BeginInputSlots</a></div><div class="ttdeci">std::vector< InputSlot >::iterator BeginInputSlots()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00241">Layer.hpp:241</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::LayerType::ConvertFp16ToFp32</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">armnn::LayerType::DetectionPostProcess</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00194">Tensor.hpp:194</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="_network_utils_8hpp_xhtml"><div class="ttname"><a href="_network_utils_8hpp.xhtml">NetworkUtils.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div>
<div class="ttc" id="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl_xhtml_aaa2a4663cec52a8aa89a93c7c8317183"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#aaa2a4663cec52a8aa89a93c7c8317183">armnn::optimizations::ConvertFp32NetworkToFp16Impl::Run</a></div><div class="ttdeci">void Run(Graph &graph, Layer &layer) const</div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_network_to_fp16_8hpp_source.xhtml#l00018">ConvertFp32NetworkToFp16.hpp:18</a></div></div>
<div class="ttc" id="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl_xhtml_a2b3e400ddbdb7b3f846b47bb535dfd97"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml#a2b3e400ddbdb7b3f846b47bb535dfd97">armnn::optimizations::ConvertFp32NetworkToFp16Impl::~ConvertFp32NetworkToFp16Impl</a></div><div class="ttdeci">~ConvertFp32NetworkToFp16Impl()=default</div></div>
<div class="ttc" id="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl_xhtml"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_convert_fp32_network_to_fp16_impl.xhtml">armnn::optimizations::ConvertFp32NetworkToFp16Impl</a></div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_network_to_fp16_8hpp_source.xhtml#l00015">ConvertFp32NetworkToFp16.hpp:15</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a71975fcec1464d639f1a78f73164d1bd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a71975fcec1464d639f1a78f73164d1bd">armnn::TensorInfo::SetDataType</a></div><div class="ttdeci">void SetDataType(DataType type)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a817d4be6dd88f532d36f51748ec14185"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a817d4be6dd88f532d36f51748ec14185">armnn::Layer::BeginOutputSlots</a></div><div class="ttdeci">std::vector< OutputSlot >::iterator BeginOutputSlots()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00245">Layer.hpp:245</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a55f76d98fcd2f5cdac3e2b14536cb7ab"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a55f76d98fcd2f5cdac3e2b14536cb7ab">armnn::Layer::EndOutputSlots</a></div><div class="ttdeci">std::vector< OutputSlot >::iterator EndOutputSlots()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00246">Layer.hpp:246</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#aea909c7327109228ef618d459015def3">armnn::Layer::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00283">Layer.cpp:283</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="_optimization_8hpp_xhtml"><div class="ttname"><a href="_optimization_8hpp.xhtml">Optimization.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
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