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| <a href="_g_c_functions_factory_8cpp.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 (c) 2018-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="_g_c_function_factory_8h.xhtml">arm_compute/graph/backends/GLES/GCFunctionFactory.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="_cast_8h.xhtml">arm_compute/core/utils/misc/Cast.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="graph_2_graph_8h.xhtml">arm_compute/graph/Graph.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_function_helpers_8h.xhtml">arm_compute/graph/backends/FunctionHelpers.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_g_c_functions_8h.xhtml">arm_compute/runtime/GLES_COMPUTE/GCFunctions.h</a>"</span></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="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1utils_1_1cast.xhtml">arm_compute::utils::cast</a>;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</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="keyword">namespace </span>graph</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">namespace </span>backends</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="keyword">struct </span>GCTargetInfo</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keyword">using</span> TensorType = <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">arm_compute::IGCTensor</a>;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keyword">static</span> <a class="code" href="namespacearm__compute_1_1graph.xhtml#a31488d29805a596498c0234ae392d35d">Target</a> TargetType;</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> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <a class="code" href="namespacearm__compute_1_1graph.xhtml#a31488d29805a596498c0234ae392d35d">Target</a> GCTargetInfo::TargetType = Target::GC;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">struct </span>GCConvolutionLayerFunctions</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="keyword">using</span> GenericConvolutionLayer = GCConvolutionLayer;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">using</span> GEMMConvolutionLayer = GCConvolutionLayer;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">using</span> DirectConvolutionLayer = GCDirectConvolutionLayer;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> };</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">struct </span>GCDepthwiseConvolutionLayerFunctions</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>  <span class="keyword">using</span> DepthwiseConvolutionLayer3x3 = GCDepthwiseConvolutionLayer3x3;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> };</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="keyword">struct </span>GCEltwiseFunctions</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="keyword">using</span> Addition = GCArithmeticAddition;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">using</span> Multiplication = GCPixelWiseMultiplication;</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> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="keyword">namespace </span>detail</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> <span class="keyword">template</span> <></div><div class="line"><a name="l00072"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a5c80e4e51582453953cc94742f25438c"> 72</a></span> std::unique_ptr<IFunction> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a5c80e4e51582453953cc94742f25438c">create_convolution_layer<GCConvolutionLayerFunctions, GCTargetInfo></a>(<a class="code" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml">ConvolutionLayerNode</a> &node, <a class="code" href="classarm__compute_1_1graph_1_1_graph_context.xhtml">GraphContext</a> &ctx)</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>  validate_node<GCTargetInfo>(node, 3 <span class="comment">/* expected inputs */</span>, 1 <span class="comment">/* expected outputs */</span>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Extract IO and info</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *input = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(0));</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a> = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(1));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *biases = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(2));</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *output = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a27369471d9b2ba47746e1e923f585b9f">output</a>(0));</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="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()))</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  biases-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a9ebcdce876b4cd07736afa47d50154de">set_data_type</a>(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>);</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"> 87</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a> = node.<a class="code" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#ad087f1f9aa1e444236911adf6c57df04">convolution_info</a>();</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute_1_1graph.xhtml#a683661ae75dcb7aef16b9c9bde31517d">ConvolutionMethod</a> conv_algorithm = node.<a class="code" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#a16b2c6652c4cee5b566daf018f768a42">convolution_method</a>();</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> fused_act = node.<a class="code" href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#a32186582e0a6e02ed7ac3944f60b9c62">fused_activation</a>();</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// Create and configure function (we assume that functions have been validated before creation)</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  std::shared_ptr<IMemoryManager> mm = <a class="code" href="namespacearm__compute_1_1graph_1_1backends.xhtml#a8919c520c1cb9086dd1116de509bd481">get_memory_manager</a>(ctx, GCTargetInfo::TargetType);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  std::unique_ptr<IFunction> func;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::string func_name;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordflow">if</span>(conv_algorithm == ConvolutionMethod::Direct)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  {</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  std::tie(func, func_name) = create_named_function<GCConvolutionLayerFunctions::DirectConvolutionLayer>(</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  std::string(<span class="stringliteral">"DirectConvolutionLayer"</span>),</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, fused_act);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  }</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  std::tie(func, func_name) = create_named_memory_managed_function<GCConvolutionLayerFunctions::GenericConvolutionLayer>(</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  std::string(<span class="stringliteral">"ConvolutionLayer"</span>), mm,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a>(), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">U</a>, 1<a class="code" href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">U</a>), fused_act);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// Log info</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="graph_2_logger_8h.xhtml#ab2d8baa35618bdad1d2814942355311e">ARM_COMPUTE_LOG_GRAPH_INFO</a>(<span class="stringliteral">"Instantiated "</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  << node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a1d89c28bd42ba9a52da008bb69367171">name</a>()</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  << <span class="stringliteral">" Type: "</span> << func_name</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  << <span class="stringliteral">" Data Type: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  << <span class="stringliteral">" Input QuantInfo: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>()</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  << <span class="stringliteral">" Weights QuantInfo: "</span> << <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>()</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  << <span class="stringliteral">" Input shape: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  << <span class="stringliteral">" Weights shape: "</span> << <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>()</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  << <span class="stringliteral">" Output shape: "</span> << output->info()->tensor_shape()</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  << (fused_act.<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#af5a8385102f8f8dd6c5957eac08b04c2">enabled</a>() ? <span class="stringliteral">" "</span> + <a class="code" href="namespacearm__compute.xhtml#ab75d8ff29ba9b398d5740b3efd156e71">to_string</a>(fused_act.<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a9e0fb1d1462557f28966ae19988532c2">activation</a>()) : <span class="stringliteral">""</span>)</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  << std::endl);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">return</span> func;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> }</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a08ab53b1d15e738a39f29d778a91a512"> 125</a></span> std::unique_ptr<IFunction> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a08ab53b1d15e738a39f29d778a91a512">create_depthwise_convolution_layer<GCDepthwiseConvolutionLayerFunctions, GCTargetInfo></a>(<a class="code" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml">DepthwiseConvolutionLayerNode</a> &node)</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> {</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  validate_node<GCTargetInfo>(node, 3 <span class="comment">/* expected inputs */</span>, 1 <span class="comment">/* expected outputs */</span>);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Extract IO and info</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *input = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(0));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a> = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(1));</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *biases = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(2));</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *output = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a27369471d9b2ba47746e1e923f585b9f">output</a>(0));</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()))</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  biases-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a9ebcdce876b4cd07736afa47d50154de">set_data_type</a>(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a> = node.<a class="code" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#ad087f1f9aa1e444236911adf6c57df04">convolution_info</a>();</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute_1_1graph.xhtml#a75ce9b1baad4303a53124d6f0795821f">DepthwiseConvolutionMethod</a> dwc_algorithm = node.<a class="code" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a8cefd89d2de49691e778c8d5a08ac92f">depthwise_convolution_method</a>();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> fused_act = node.<a class="code" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a32186582e0a6e02ed7ac3944f60b9c62">fused_activation</a>();</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth_multiplier = node.<a class="code" href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a88e38a50a2e964b19521fe8f2e9a144f">depth_multiplier</a>();</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">// Create and configure function (we assume that functions have been validated before creation)</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::unique_ptr<IFunction> func;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::string func_name;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">if</span>(dwc_algorithm == DepthwiseConvolutionMethod::Optimized3x3)</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  {</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::tie(func, func_name) = create_named_function<GCDepthwiseConvolutionLayerFunctions::DepthwiseConvolutionLayer3x3>(</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  std::string(<span class="stringliteral">"DepthwiseConvolutionLayer3x3"</span>),</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, depth_multiplier, fused_act);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  }</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Generic DepthwiseConvolutionLayer is not supported in GLES backend"</span>);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// Log info</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="graph_2_logger_8h.xhtml#ab2d8baa35618bdad1d2814942355311e">ARM_COMPUTE_LOG_GRAPH_INFO</a>(<span class="stringliteral">"Instantiated "</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  << node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a1d89c28bd42ba9a52da008bb69367171">name</a>()</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  << <span class="stringliteral">" Type: "</span> << func_name</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  << <span class="stringliteral">" Target "</span> << GCTargetInfo::TargetType</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  << <span class="stringliteral">" Data Type: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  << <span class="stringliteral">" Input QuantInfo: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>()</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  << <span class="stringliteral">" Weights QuantInfo: "</span> << <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>()</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  << <span class="stringliteral">" Input shape: "</span> << input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  << <span class="stringliteral">" Weights shape: "</span> << <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>()</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  << <span class="stringliteral">" Output shape: "</span> << output->info()->tensor_shape()</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  << <span class="stringliteral">" Depth multiplier: "</span> << depth_multiplier</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  << (fused_act.<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#af5a8385102f8f8dd6c5957eac08b04c2">enabled</a>() ? <span class="stringliteral">" "</span> + <a class="code" href="namespacearm__compute.xhtml#ab75d8ff29ba9b398d5740b3efd156e71">to_string</a>(fused_act.<a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml#a9e0fb1d1462557f28966ae19988532c2">activation</a>()) : <span class="stringliteral">""</span>)</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  << std::endl);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">return</span> func;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> }</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00177"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a863bcac2c361e883edf7f9abb4abd9a7"> 177</a></span> std::unique_ptr<IFunction> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a863bcac2c361e883edf7f9abb4abd9a7">create_eltwise_layer<GCEltwiseFunctions, GCTargetInfo></a>(<a class="code" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml">EltwiseLayerNode</a> &node)</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> {</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="graph_2_logger_8h.xhtml#a300d153929a99c7b571d4cda3f7987a5">ARM_COMPUTE_LOG_GRAPH_VERBOSE</a>(</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="stringliteral">"Creating GC EltwiseLayer node with ID : "</span> << node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a5ea90a25ef8059df2d2e51b82991ebf3">id</a>() << <span class="stringliteral">" and Name: "</span> << node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a1d89c28bd42ba9a52da008bb69367171">name</a>() << std::endl);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#abe0cb3e4411a1c289e3e40e3f9d79fec">num_inputs</a>() != 2);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a75d7c8bdf0059bb235880f8ef8d190bc">num_outputs</a>() != 1);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="comment">// Extract IO and info</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *input1 = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(0));</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *input2 = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">input</a>(1));</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="classarm__compute_1_1_i_g_c_tensor.xhtml">GCTargetInfo::TensorType</a> *output = get_backing_tensor<GCTargetInfo>(node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a27369471d9b2ba47746e1e923f585b9f">output</a>(0));</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute_1_1graph.xhtml#aa12973876c037bddff8e9ece94aca0e4">EltwiseOperation</a> eltwise_op = node.<a class="code" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#acda6687f669fe87581d7bff8fcd82ebc">eltwise_operation</a>();</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5d58c32bff63e4c34b3234f884a4da58">convert_policy</a> = node.<a class="code" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#aa7b3781f10fc0ac73a9a4f748e22d3d4">convert_policy</a>();</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(input1 == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(input2 == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(output == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  std::unique_ptr<IFunction> func = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  std::string func_name;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordflow">if</span>(eltwise_op == EltwiseOperation::Add)</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  std::tie(func, func_name) = create_named_function<GCEltwiseFunctions::Addition>(</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  std::string(<span class="stringliteral">"GCArithmeticAddition"</span>),</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  input1, input2, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5d58c32bff63e4c34b3234f884a4da58">convert_policy</a>);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  }</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(eltwise_op == EltwiseOperation::Sub)</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  {</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Arithmetic subtraction is not supported in GLES backend"</span>);</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(eltwise_op == EltwiseOperation::Mul)</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  {</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  std::tie(func, func_name) = create_named_function<GCEltwiseFunctions::Multiplication>(</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  std::string(<span class="stringliteral">"PixelWiseMultiplication"</span>),</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  input1, input2, output, 1.f);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Unsupported element-wise operation!"</span>);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="comment">// Log info</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <a class="code" href="graph_2_logger_8h.xhtml#ab2d8baa35618bdad1d2814942355311e">ARM_COMPUTE_LOG_GRAPH_INFO</a>(<span class="stringliteral">"Instantiated "</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  << node.<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a1d89c28bd42ba9a52da008bb69367171">name</a>()</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  << <span class="stringliteral">" Type: "</span> << node.<a class="code" href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#a65d13dc93e2df5e8ab725263cf9f4ac5">type</a>()</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  << <span class="stringliteral">" Target: "</span> << GCTargetInfo::TargetType</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  << <span class="stringliteral">" Operation: "</span> << func_name</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  << <span class="stringliteral">" Data Type: "</span> << input1->info()->data_type()</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  << <span class="stringliteral">" Shape: "</span> << input1->info()->tensor_shape()</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  << std::endl);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">return</span> func;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> }</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> } <span class="comment">//namespace detail</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div><div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph_1_1backends_1_1_g_c_function_factory.xhtml#aa7ac6bf065e64181f3c92fee4b3b5c79"> 231</a></span> std::unique_ptr<IFunction> GCFunctionFactory::create(<a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml">INode</a> *node, <a class="code" href="classarm__compute_1_1graph_1_1_graph_context.xhtml">GraphContext</a> &ctx)</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keywordflow">if</span>(node == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  {</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  }</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="namespacearm__compute_1_1graph.xhtml#acac9cbaeea226ed297804c012dc12b16">NodeType</a> type = node-><a class="code" href="classarm__compute_1_1graph_1_1_i_node.xhtml#a6b2d83e561886647467f86c20ce39bec">type</a>();</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">switch</span>(type)</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">case</span> NodeType::ActivationLayer:</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">return</span> detail::create_activation_layer<GCActivationLayer, GCTargetInfo>(*polymorphic_downcast<ActivationLayerNode *>(node));</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keywordflow">case</span> NodeType::BatchNormalizationLayer:</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="keywordflow">return</span> detail::create_batch_normalization_layer<GCBatchNormalizationLayer, GCTargetInfo>(*polymorphic_downcast<BatchNormalizationLayerNode *>(node));</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordflow">case</span> NodeType::ConvolutionLayer:</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a5c80e4e51582453953cc94742f25438c">detail::create_convolution_layer<GCConvolutionLayerFunctions, GCTargetInfo></a>(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx);</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keywordflow">case</span> NodeType::ConcatenateLayer:</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">return</span> detail::create_concatenate_layer<GCConcatenateLayer, GCTargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node));</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">case</span> NodeType::DepthwiseConvolutionLayer:</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a08ab53b1d15e738a39f29d778a91a512">detail::create_depthwise_convolution_layer<GCDepthwiseConvolutionLayerFunctions, GCTargetInfo></a>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">case</span> NodeType::EltwiseLayer:</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a863bcac2c361e883edf7f9abb4abd9a7">detail::create_eltwise_layer<GCEltwiseFunctions, GCTargetInfo></a>(*polymorphic_downcast<EltwiseLayerNode *>(node));</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keywordflow">case</span> NodeType::FullyConnectedLayer:</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">return</span> detail::create_fully_connected_layer<GCFullyConnectedLayer, GCTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">case</span> NodeType::NormalizationLayer:</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">return</span> detail::create_normalization_layer<GCNormalizationLayer, GCTargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">case</span> NodeType::NormalizePlanarYUVLayer:</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">return</span> detail::create_normalize_planar_yuv_layer<GCNormalizePlanarYUVLayer, GCTargetInfo>(*polymorphic_downcast<NormalizePlanarYUVLayerNode *>(node));</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">case</span> NodeType::PoolingLayer:</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">return</span> detail::create_pooling_layer<GCPoolingLayer, GCTargetInfo>(*polymorphic_downcast<PoolingLayerNode *>(node));</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">case</span> NodeType::ResizeLayer:</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">return</span> detail::create_resize_layer<GCScale, GCTargetInfo>(*polymorphic_downcast<ResizeLayerNode *>(node));</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keywordflow">case</span> NodeType::SoftmaxLayer:</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> detail::create_softmax_layer<GCSoftmaxLayer, GCTargetInfo>(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  }</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> }</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> } <span class="comment">// namespace backends</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> } <span class="comment">// namespace graph</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_a1d89c28bd42ba9a52da008bb69367171"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#a1d89c28bd42ba9a52da008bb69367171">arm_compute::graph::INode::name</a></div><div class="ttdeci">std::string name() const</div><div class="ttdoc">Returns node's name.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00107">INode.cpp:107</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00261">Error.h:261</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab75d8ff29ba9b398d5740b3efd156e71"><div class="ttname"><a href="namespacearm__compute.xhtml#ab75d8ff29ba9b398d5740b3efd156e71">arm_compute::to_string</a></div><div class="ttdeci">std::string to_string(const arm_compute::GradientDimension &type)</div><div class="ttdoc">Formatted output of the GradientDimension type.</div><div class="ttdef"><b>Definition:</b> <a href="tests_2_type_printer_8h_source.xhtml#l00064">TypePrinter.h:64</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_eltwise_layer_node_xhtml_a65d13dc93e2df5e8ab725263cf9f4ac5"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#a65d13dc93e2df5e8ab725263cf9f4ac5">arm_compute::graph::EltwiseLayerNode::type</a></div><div class="ttdeci">NodeType type() const override</div><div class="ttdoc">Returns node's type.</div><div class="ttdef"><b>Definition:</b> <a href="_eltwise_layer_node_8cpp_source.xhtml#l00077">EltwiseLayerNode.cpp:77</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_eltwise_layer_node_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml">arm_compute::graph::EltwiseLayerNode</a></div><div class="ttdoc">Eltwise Layer node.</div><div class="ttdef"><b>Definition:</b> <a href="_eltwise_layer_node_8h_source.xhtml#l00034">EltwiseLayerNode.h:34</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_aa12973876c037bddff8e9ece94aca0e4"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#aa12973876c037bddff8e9ece94aca0e4">arm_compute::graph::EltwiseOperation</a></div><div class="ttdeci">EltwiseOperation</div><div class="ttdoc">Supported Element-wise operations.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00098">Types.h:98</a></div></div> |
| <div class="ttc" id="_function_helpers_8h_xhtml"><div class="ttname"><a href="_function_helpers_8h.xhtml">FunctionHelpers.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor.cpp:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml_af5a8385102f8f8dd6c5957eac08b04c2"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml#af5a8385102f8f8dd6c5957eac08b04c2">arm_compute::ActivationLayerInfo::enabled</a></div><div class="ttdeci">bool enabled() const</div><div class="ttdoc">Check if initialised.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01565">Types.h:1565</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node_xhtml_a32186582e0a6e02ed7ac3944f60b9c62"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a32186582e0a6e02ed7ac3944f60b9c62">arm_compute::graph::DepthwiseConvolutionLayerNode::fused_activation</a></div><div class="ttdeci">ActivationLayerInfo fused_activation() const</div><div class="ttdoc">Returns fused activation.</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution_layer_node_8cpp_source.xhtml#l00063">DepthwiseConvolutionLayerNode.cpp:63</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node_xhtml_a88e38a50a2e964b19521fe8f2e9a144f"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a88e38a50a2e964b19521fe8f2e9a144f">arm_compute::graph::DepthwiseConvolutionLayerNode::depth_multiplier</a></div><div class="ttdeci">int depth_multiplier() const</div><div class="ttdoc">Depth multiplier accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution_layer_node_8cpp_source.xhtml#l00043">DepthwiseConvolutionLayerNode.cpp:43</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1utils_1_1cast_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1utils_1_1cast.xhtml">arm_compute::utils::cast</a></div><div class="ttdef"><b>Definition:</b> <a href="_cast_8h_source.xhtml#l00033">Cast.h:33</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_a75d7c8bdf0059bb235880f8ef8d190bc"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#a75d7c8bdf0059bb235880f8ef8d190bc">arm_compute::graph::INode::num_outputs</a></div><div class="ttdeci">size_t num_outputs() const</div><div class="ttdoc">Returns number of outputs of the node.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00183">INode.cpp:183</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::TensorInfo::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00293">TensorInfo.h:293</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_convolution_layer_node_xhtml_a32186582e0a6e02ed7ac3944f60b9c62"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#a32186582e0a6e02ed7ac3944f60b9c62">arm_compute::graph::ConvolutionLayerNode::fused_activation</a></div><div class="ttdeci">ActivationLayerInfo fused_activation() const</div><div class="ttdoc">Returns fused activation.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_layer_node_8cpp_source.xhtml#l00076">ConvolutionLayerNode.cpp:76</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5d58c32bff63e4c34b3234f884a4da58"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5d58c32bff63e4c34b3234f884a4da58">arm_compute::test::validation::convert_policy</a></div><div class="ttdeci">convert_policy</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_pixel_wise_multiplication_8cpp_source.xhtml#l00317">PixelWiseMultiplication.cpp:317</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_g_c_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_g_c_tensor.xhtml">arm_compute::IGCTensor</a></div><div class="ttdoc">Interface for GLES Compute tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_g_c_tensor_8h_source.xhtml#l00035">IGCTensor.h:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node_xhtml_a8cefd89d2de49691e778c8d5a08ac92f"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#a8cefd89d2de49691e778c8d5a08ac92f">arm_compute::graph::DepthwiseConvolutionLayerNode::depthwise_convolution_method</a></div><div class="ttdeci">DepthwiseConvolutionMethod depthwise_convolution_method() const</div><div class="ttdoc">Depthwise convolution layer method accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution_layer_node_8cpp_source.xhtml#l00053">DepthwiseConvolutionLayerNode.cpp:53</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_eltwise_layer_node_xhtml_acda6687f669fe87581d7bff8fcd82ebc"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#acda6687f669fe87581d7bff8fcd82ebc">arm_compute::graph::EltwiseLayerNode::eltwise_operation</a></div><div class="ttdeci">EltwiseOperation eltwise_operation() const</div><div class="ttdoc">Eltwise operation accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_eltwise_layer_node_8cpp_source.xhtml#l00040">EltwiseLayerNode.cpp:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_graph_context_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_graph_context.xhtml">arm_compute::graph::GraphContext</a></div><div class="ttdoc">Graph context.</div><div class="ttdef"><b>Definition:</b> <a href="_graph_context_8h_source.xhtml#l00049">GraphContext.h:49</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml">arm_compute::ActivationLayerInfo</a></div><div class="ttdoc">Activation Layer Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01517">Types.h:1517</a></div></div> |
| <div class="ttc" id="graph_2_logger_8h_xhtml_ab2d8baa35618bdad1d2814942355311e"><div class="ttname"><a href="graph_2_logger_8h.xhtml#ab2d8baa35618bdad1d2814942355311e">ARM_COMPUTE_LOG_GRAPH_INFO</a></div><div class="ttdeci">#define ARM_COMPUTE_LOG_GRAPH_INFO(x)</div><div class="ttdef"><b>Definition:</b> <a href="graph_2_logger_8h_source.xhtml#l00054">Logger.h:54</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2018 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="_cast_8h_xhtml"><div class="ttname"><a href="_cast_8h.xhtml">Cast.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_weights_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_weights_info.xhtml">arm_compute::WeightsInfo</a></div><div class="ttdoc">Convolution Layer Weights Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01658">Types.h:1658</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_convolution_layer_node_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml">arm_compute::graph::ConvolutionLayerNode</a></div><div class="ttdoc">Convolution Layer node.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_layer_node_8h_source.xhtml#l00034">ConvolutionLayerNode.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml">arm_compute::graph::INode</a></div><div class="ttdoc">Node interface.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8h_source.xhtml#l00045">INode.h:45</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape & tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_a27369471d9b2ba47746e1e923f585b9f"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#a27369471d9b2ba47746e1e923f585b9f">arm_compute::graph::INode::output</a></div><div class="ttdeci">Tensor * output(size_t idx) const</div><div class="ttdoc">Returns the tensor of a given output of the node.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00158">INode.cpp:158</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_a75ce9b1baad4303a53124d6f0795821f"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#a75ce9b1baad4303a53124d6f0795821f">arm_compute::graph::DepthwiseConvolutionMethod</a></div><div class="ttdeci">DepthwiseConvolutionMethod</div><div class="ttdoc">Supported Depthwise Convolution layer methods.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00115">Types.h:115</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1utils_1_1cast_xhtml_a2ea3d1fc01a3a442900249ca182ffa5e"><div class="ttname"><a href="namespacearm__compute_1_1utils_1_1cast.xhtml#a2ea3d1fc01a3a442900249ca182ffa5e">arm_compute::utils::cast::U</a></div><div class="ttdeci">U</div><div class="ttdef"><b>Definition:</b> <a href="_saturate_cast_8h_source.xhtml#l00057">SaturateCast.h:57</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node_xhtml_ad087f1f9aa1e444236911adf6c57df04"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml#ad087f1f9aa1e444236911adf6c57df04">arm_compute::graph::DepthwiseConvolutionLayerNode::convolution_info</a></div><div class="ttdeci">PadStrideInfo convolution_info() const</div><div class="ttdoc">Convolution metadata accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution_layer_node_8cpp_source.xhtml#l00058">DepthwiseConvolutionLayerNode.cpp:58</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_a5ea90a25ef8059df2d2e51b82991ebf3"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#a5ea90a25ef8059df2d2e51b82991ebf3">arm_compute::graph::INode::id</a></div><div class="ttdeci">NodeID id() const</div><div class="ttdoc">Returns node's ID.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00102">INode.cpp:102</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_acac9cbaeea226ed297804c012dc12b16"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#acac9cbaeea226ed297804c012dc12b16">arm_compute::graph::NodeType</a></div><div class="ttdeci">NodeType</div><div class="ttdoc">Supported nodes.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00130">Types.h:130</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_convolution_layer_node_xhtml_ad087f1f9aa1e444236911adf6c57df04"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#ad087f1f9aa1e444236911adf6c57df04">arm_compute::graph::ConvolutionLayerNode::convolution_info</a></div><div class="ttdeci">PadStrideInfo convolution_info() const</div><div class="ttdoc">Convolution metadata accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_layer_node_8cpp_source.xhtml#l00066">ConvolutionLayerNode.cpp:66</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00676">Types.h:676</a></div></div> |
| <div class="ttc" id="_g_c_function_factory_8h_xhtml"><div class="ttname"><a href="_g_c_function_factory_8h.xhtml">GCFunctionFactory.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_1_1backends_1_1detail_xhtml_a08ab53b1d15e738a39f29d778a91a512"><div class="ttname"><a href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a08ab53b1d15e738a39f29d778a91a512">arm_compute::graph::backends::detail::create_depthwise_convolution_layer< GCDepthwiseConvolutionLayerFunctions, GCTargetInfo ></a></div><div class="ttdeci">std::unique_ptr< IFunction > create_depthwise_convolution_layer< GCDepthwiseConvolutionLayerFunctions, GCTargetInfo >(DepthwiseConvolutionLayerNode &node)</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_functions_factory_8cpp_source.xhtml#l00125">GCFunctionsFactory.cpp:125</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a9ebcdce876b4cd07736afa47d50154de"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a9ebcdce876b4cd07736afa47d50154de">arm_compute::ITensorInfo::set_data_type</a></div><div class="ttdeci">virtual ITensorInfo & set_data_type(DataType data_type)=0</div><div class="ttdoc">Set the data type to the specified value.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_a31488d29805a596498c0234ae392d35d"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#a31488d29805a596498c0234ae392d35d">arm_compute::graph::Target</a></div><div class="ttdeci">Target</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00089">Types.h:89</a></div></div> |
| <div class="ttc" id="_g_c_functions_8h_xhtml"><div class="ttname"><a href="_g_c_functions_8h.xhtml">GCFunctions.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_convolution_layer_node_xhtml_a16b2c6652c4cee5b566daf018f768a42"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_convolution_layer_node.xhtml#a16b2c6652c4cee5b566daf018f768a42">arm_compute::graph::ConvolutionLayerNode::convolution_method</a></div><div class="ttdeci">ConvolutionMethod convolution_method() const</div><div class="ttdoc">Convolution layer method accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution_layer_node_8cpp_source.xhtml#l00051">ConvolutionLayerNode.cpp:51</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_1_1backends_xhtml_a8919c520c1cb9086dd1116de509bd481"><div class="ttname"><a href="namespacearm__compute_1_1graph_1_1backends.xhtml#a8919c520c1cb9086dd1116de509bd481">arm_compute::graph::backends::get_memory_manager</a></div><div class="ttdeci">std::shared_ptr< IMemoryManager > get_memory_manager(GraphContext &ctx, Target target)</div><div class="ttdoc">Returns the memory manager for a given target.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2backends_2_utils_8h_source.xhtml#l00088">Utils.h:88</a></div></div> |
| <div class="ttc" id="graph_2_logger_8h_xhtml_a300d153929a99c7b571d4cda3f7987a5"><div class="ttname"><a href="graph_2_logger_8h.xhtml#a300d153929a99c7b571d4cda3f7987a5">ARM_COMPUTE_LOG_GRAPH_VERBOSE</a></div><div class="ttdeci">#define ARM_COMPUTE_LOG_GRAPH_VERBOSE(x)</div><div class="ttdef"><b>Definition:</b> <a href="graph_2_logger_8h_source.xhtml#l00050">Logger.h:50</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_xhtml_a683661ae75dcb7aef16b9c9bde31517d"><div class="ttname"><a href="namespacearm__compute_1_1graph.xhtml#a683661ae75dcb7aef16b9c9bde31517d">arm_compute::graph::ConvolutionMethod</a></div><div class="ttdeci">ConvolutionMethod</div><div class="ttdoc">Supported Convolution layer methods.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2graph_2_types_8h_source.xhtml#l00106">Types.h:106</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_abe0cb3e4411a1c289e3e40e3f9d79fec"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#abe0cb3e4411a1c289e3e40e3f9d79fec">arm_compute::graph::INode::num_inputs</a></div><div class="ttdeci">size_t num_inputs() const</div><div class="ttdoc">Returns number of inputs of the node.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00178">INode.cpp:178</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_eltwise_layer_node_xhtml_aa7b3781f10fc0ac73a9a4f748e22d3d4"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_eltwise_layer_node.xhtml#aa7b3781f10fc0ac73a9a4f748e22d3d4">arm_compute::graph::EltwiseLayerNode::convert_policy</a></div><div class="ttdeci">ConvertPolicy convert_policy() const</div><div class="ttdoc">Convert policy accessor.</div><div class="ttdef"><b>Definition:</b> <a href="_eltwise_layer_node_8cpp_source.xhtml#l00045">EltwiseLayerNode.cpp:45</a></div></div> |
| <div class="ttc" id="graph_2_graph_8h_xhtml"><div class="ttname"><a href="graph_2_graph_8h.xhtml">Graph.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_1_1backends_1_1detail_xhtml_a863bcac2c361e883edf7f9abb4abd9a7"><div class="ttname"><a href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a863bcac2c361e883edf7f9abb4abd9a7">arm_compute::graph::backends::detail::create_eltwise_layer< GCEltwiseFunctions, GCTargetInfo ></a></div><div class="ttdeci">std::unique_ptr< IFunction > create_eltwise_layer< GCEltwiseFunctions, GCTargetInfo >(EltwiseLayerNode &node)</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_functions_factory_8cpp_source.xhtml#l00177">GCFunctionsFactory.cpp:177</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node_xhtml"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_depthwise_convolution_layer_node.xhtml">arm_compute::graph::DepthwiseConvolutionLayerNode</a></div><div class="ttdoc">Depthwise Convolution Layer node.</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution_layer_node_8h_source.xhtml#l00034">DepthwiseConvolutionLayerNode.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml_a9e0fb1d1462557f28966ae19988532c2"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml#a9e0fb1d1462557f28966ae19988532c2">arm_compute::ActivationLayerInfo::activation</a></div><div class="ttdeci">ActivationFunction activation() const</div><div class="ttdoc">Get the type of activation function.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01550">Types.h:1550</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_a6b2d83e561886647467f86c20ce39bec"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#a6b2d83e561886647467f86c20ce39bec">arm_compute::graph::INode::type</a></div><div class="ttdeci">virtual NodeType type() const =0</div><div class="ttdoc">Returns node's type.</div></div> |
| <div class="ttc" id="classarm__compute_1_1graph_1_1_i_node_xhtml_ad7c09b0faaf3c808b0489012204852a9"><div class="ttname"><a href="classarm__compute_1_1graph_1_1_i_node.xhtml#ad7c09b0faaf3c808b0489012204852a9">arm_compute::graph::INode::input</a></div><div class="ttdeci">Tensor * input(size_t idx) const</div><div class="ttdoc">Returns the tensor of a given input of the node.</div><div class="ttdef"><b>Definition:</b> <a href="_i_node_8cpp_source.xhtml#l00150">INode.cpp:150</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a269b19ce3f357ac65f41f9951906e38e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">arm_compute::TensorInfo::tensor_shape</a></div><div class="ttdeci">const TensorShape & tensor_shape() const override</div><div class="ttdoc">Size for each dimension of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00252">TensorInfo.h:252</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a82b8ac759c804bc1fb4e2d21e178fb6f"><div class="ttname"><a href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">arm_compute::ConvertPolicy</a></div><div class="ttdeci">ConvertPolicy</div><div class="ttdoc">Policy to handle overflow.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00349">Types.h:349</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1graph_1_1backends_1_1detail_xhtml_a5c80e4e51582453953cc94742f25438c"><div class="ttname"><a href="namespacearm__compute_1_1graph_1_1backends_1_1detail.xhtml#a5c80e4e51582453953cc94742f25438c">arm_compute::graph::backends::detail::create_convolution_layer< GCConvolutionLayerFunctions, GCTargetInfo ></a></div><div class="ttdeci">std::unique_ptr< IFunction > create_convolution_layer< GCConvolutionLayerFunctions, GCTargetInfo >(ConvolutionLayerNode &node, GraphContext &ctx)</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_functions_factory_8cpp_source.xhtml#l00072">GCFunctionsFactory.cpp:72</a></div></div> |
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