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<div class="title">ArmComputeUtils.hpp</div> </div>
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<a href="_arm_compute_utils_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;</div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_descriptors_8hpp.html">armnn/Descriptors.hpp</a>&gt;</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_8hpp.html">armnn/Tensor.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;arm_compute/core/Types.h&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;boost/assert.hpp&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;{</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="keyword">inline</span> arm_compute::NormalizationLayerInfo</div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a5e783a951642781b9e7b55db06a514b7"> 18</a></span>&#160;<a class="code" href="namespacearmnn.html#a5e783a951642781b9e7b55db06a514b7">CreateAclNormalizationLayerInfoForL2Normalization</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; tensorInfo,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;{</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthDimension = dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> ? 1 : 3;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth = tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[depthDimension];</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <span class="comment">// At the time of writing, {CL|Neon}L2Normalization performs the reduction only along dimension 0. This version of</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="comment">// L2 Normalization always performs the reduction along the depth axis, though. Thus, we repurpose</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="comment">// {CL|Neon}NormalizationLayers to act as depthwise L2 normalizations by carefully chosing the normalization</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="comment">// parameters.</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="comment">//</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="comment">// Please refer to both the reference implementation of the normalization layer and the implementation of</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="comment">// {CL|Neon}NormalizationLayer when checking the derivations for the parameter values below.</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="comment">// Make sure normalization covers the entire depth range. ACL requires the normalization size to be odd.</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="comment">// CL: This does not result in extra kernel threads not doing any work: See usage of the RADIUS parameter in</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="comment">// ACL&#39;s normalization_layer_cross_map() CL function.</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">const</span> uint32_t normSize = depth * 2u + 1u;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="comment">// See ACL&#39;s NormalizationLayerInfo::scale_coeff() definition.</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="comment">// For the reference implementation, to make alpha_ become 1, we&#39;d have to use alpha = normSize instead.</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> alpha = 1.0f;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// Don&#39;t offset the reduction.</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> kappa = 0.0f;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="comment">// pow(reduction, -0.5) = 1 / sqrt(reduction)</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 0.5f;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keywordflow">return</span> arm_compute::NormalizationLayerInfo(arm_compute::NormType::CROSS_MAP, normSize, alpha, beta, kappa, <span class="keyword">false</span>);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;}</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;<span class="keyword">inline</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">arm_compute::ActivationLayerInfo::ActivationFunction</a></div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="namespacearmnn.html#afdba36f125621d775d471f0daf613df2"> 51</a></span>&#160;<a class="code" href="namespacearmnn.html#afdba36f125621d775d471f0daf613df2">ConvertActivationFunctionToAclActivationFunction</a>(<a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">ActivationFunction</a> armnnFunction)</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;{</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keyword">using</span> AclActivationFunction = <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">arm_compute::ActivationLayerInfo::ActivationFunction</a>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="keywordflow">switch</span> (armnnFunction)</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">ActivationFunction::Linear</a>: <span class="keywordflow">return</span> AclActivationFunction::LINEAR;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="comment">// Arm compute&#39;s &#39;logistic&#39; function is non-parameterized, so it is exactly a sigmoid function.</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">ActivationFunction::Sigmoid</a>: <span class="keywordflow">return</span> AclActivationFunction::LOGISTIC;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">ActivationFunction::ReLu</a>: <span class="keywordflow">return</span> AclActivationFunction::RELU;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">ActivationFunction::BoundedReLu</a>: <span class="keywordflow">return</span> AclActivationFunction::LU_BOUNDED_RELU;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa6bba7052636d1740303b1b2ef3b53fef">ActivationFunction::SoftReLu</a>: <span class="keywordflow">return</span> AclActivationFunction::SOFT_RELU;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">ActivationFunction::LeakyReLu</a>: <span class="keywordflow">return</span> AclActivationFunction::LEAKY_RELU;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">ActivationFunction::Abs</a>: <span class="keywordflow">return</span> AclActivationFunction::ABS;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">ActivationFunction::Sqrt</a>: <span class="keywordflow">return</span> AclActivationFunction::SQRT;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">ActivationFunction::Square</a>: <span class="keywordflow">return</span> AclActivationFunction::SQUARE;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">ActivationFunction::TanH</a>: <span class="keywordflow">return</span> AclActivationFunction::TANH;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported activation function&quot;</span>);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; }</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;}</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;<span class="keyword">inline</span> arm_compute::ActivationLayerInfo</div><div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ad701d0d29baa4266ab4d33b090aa661c"> 73</a></span>&#160;<a class="code" href="namespacearmnn.html#ad701d0d29baa4266ab4d33b090aa661c">ConvertActivationDescriptorToAclActivationLayerInfo</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.html">ActivationDescriptor</a>&amp; actDesc)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;{</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordflow">return</span> arm_compute::ActivationLayerInfo(<a class="code" href="namespacearmnn.html#afdba36f125621d775d471f0daf613df2">ConvertActivationFunctionToAclActivationFunction</a>(actDesc.<a class="code" href="structarmnn_1_1_activation_descriptor.html#af10fa7883e3579950f477bee92a64844">m_Function</a>),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; actDesc.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a017b2990003a014234f13e999dc7c689">m_A</a>, actDesc.<a class="code" href="structarmnn_1_1_activation_descriptor.html#a28c4c9cb15f6be3499abbc46b356060b">m_B</a>);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;}</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ad256fcf8c7f4d5a240fa47f0b56d50af"> 79</a></span>&#160;<span class="keyword">inline</span> arm_compute::PoolingType <a class="code" href="namespacearmnn.html#ad256fcf8c7f4d5a240fa47f0b56d50af">ConvertPoolingAlgorithmToAclPoolingType</a>(<a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">PoolingAlgorithm</a> poolingAlgorithm)</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;{</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keyword">using</span> arm_compute::PoolingType;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">switch</span> (poolingAlgorithm)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">PoolingAlgorithm::Max</a>: <span class="keywordflow">return</span> PoolingType::MAX;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">PoolingAlgorithm::Average</a>: <span class="keywordflow">return</span> PoolingType::AVG;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">PoolingAlgorithm::L2</a>: <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">PoolingType::L2</a>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported pooling algorithm&quot;</span>);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;}</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a8f3bfacadfd6d2146d6ccd299dabc7aa"> 92</a></span>&#160;<span class="keyword">inline</span> arm_compute::DimensionRoundingType <a class="code" href="namespacearmnn.html#a8f3bfacadfd6d2146d6ccd299dabc7aa">ConvertOutputShapeRoundingToAclDimensionRoundingType</a>(<a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754e">OutputShapeRounding</a></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; rounding)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;{</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keyword">using</span> arm_compute::DimensionRoundingType;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordflow">switch</span> (rounding)</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">OutputShapeRounding::Ceiling</a>: <span class="keywordflow">return</span> DimensionRoundingType::CEIL;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">OutputShapeRounding::Floor</a>: <span class="keywordflow">return</span> DimensionRoundingType::FLOOR;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported Output Shape Rounding type&quot;</span>);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160;}</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;<span class="keyword">inline</span> arm_compute::NormType</div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="namespacearmnn.html#aa5baabb8e3a4aa6cbdcab419d743e747"> 106</a></span>&#160;<a class="code" href="namespacearmnn.html#aa5baabb8e3a4aa6cbdcab419d743e747">ConvertNormalizationAlgorithmChannelToAclNormType</a>(<a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437">NormalizationAlgorithmChannel</a> channelType)</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;{</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keyword">using</span> arm_compute::NormType;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keywordflow">switch</span> (channelType)</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">NormalizationAlgorithmChannel::Across</a>: <span class="keywordflow">return</span> NormType::CROSS_MAP;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b">NormalizationAlgorithmChannel::Within</a>: <span class="keywordflow">return</span> NormType::IN_MAP_2D;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keywordflow">default</span>: <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported normalization algorithm channel type&quot;</span>);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;}</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160;<span class="keyword">inline</span> arm_compute::FullyConnectedLayerInfo</div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="namespacearmnn.html#abccab9266ab13dbd806445af31ddbba7"> 118</a></span>&#160;<a class="code" href="namespacearmnn.html#abccab9266ab13dbd806445af31ddbba7">ConvertFullyConnectedDescriptorToAclFullyConnectedLayerInfo</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.html">FullyConnectedDescriptor</a>&amp; fullyConnectedDesc)</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;{</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; arm_compute::FullyConnectedLayerInfo fc_info;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; fc_info.transpose_weights = fullyConnectedDesc.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a>;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="keywordflow">return</span> fc_info;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;}</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ae9bdcb8ac91731109dc423d6ed476204"> 125</a></span>&#160;<span class="keyword">inline</span> arm_compute::InterpolationPolicy <a class="code" href="namespacearmnn.html#ae9bdcb8ac91731109dc423d6ed476204">ConvertResizeMethodToAclInterpolationPolicy</a>(<a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">ResizeMethod</a> resizeMethod)</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;{</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">switch</span> (resizeMethod)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">ResizeMethod::Bilinear</a>:</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keywordflow">return</span> arm_compute::InterpolationPolicy::BILINEAR;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">ResizeMethod::NearestNeighbor</a>:</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keywordflow">return</span> arm_compute::InterpolationPolicy::NEAREST_NEIGHBOR;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported resize method&quot;</span>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160;}</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="namespacearmnn.html#aa70ebe7b7898fe69ce24db803caa373e"> 138</a></span>&#160;<span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn.html#aa70ebe7b7898fe69ce24db803caa373e">ComputeSoftmaxAclAxis</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_softmax_descriptor.html">SoftmaxDescriptor</a>&amp; softmaxDesc, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; tensor)</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;{</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="comment">// Detect the Android default value of -1 and return the ACL default value of 1.</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keywordflow">if</span> (softmaxDesc.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> == -1)</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; {</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; }</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim = tensor.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; BOOST_ASSERT(dim != 0);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// Currently ArmNN support axis 1.</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordflow">return</span> dim - 1;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;}</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;</div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a8cbabc875597b3bed0ccdc0adb289fde"> 154</a></span>&#160;<span class="keyword">inline</span> std::set&lt;unsigned int&gt; <a class="code" href="namespacearmnn.html#a8cbabc875597b3bed0ccdc0adb289fde">ComputeSplitAxis</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_views_descriptor.html">armnn::SplitterDescriptor</a>&amp; desc, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; input)</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160;{</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numSplit = desc.<a class="code" href="structarmnn_1_1_views_descriptor.html#a35546e7b56e6e972a495b48748478ede">GetNumViews</a>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = desc.<a class="code" href="structarmnn_1_1_views_descriptor.html#a78e8266be865fdd92cadd04d6e25ae1f">GetNumDimensions</a>();</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; std::set&lt;unsigned int&gt; splitAxis;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; numSplit; ++i)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimIdx = 0; dimIdx &lt; numDimensions; ++dimIdx)</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; {</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="keywordflow">if</span> (desc.<a class="code" href="structarmnn_1_1_views_descriptor.html#a3c1ab47a0a319413b3a4b5757ed5b80b">GetViewSizes</a>(i)[dimIdx] != input[dimIdx])</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; splitAxis.insert(dimIdx);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; }</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; }</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; }</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="keywordflow">return</span> splitAxis;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;}</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="structarmnn_1_1_activation_descriptor_html_a017b2990003a014234f13e999dc7c689"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html#a017b2990003a014234f13e999dc7c689">armnn::ActivationDescriptor::m_A</a></div><div class="ttdeci">float m_A</div><div class="ttdoc">Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00037">Descriptors.hpp:37</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a9a2af2f8c4af4f9efa8e79417d505ac4"><div class="ttname"><a href="namespacearmnn.html#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a></div><div class="ttdeci">ResizeMethod</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00100">Types.hpp:100</a></div></div>
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<div class="ttc" id="namespacearmnn_html_ad701d0d29baa4266ab4d33b090aa661c"><div class="ttname"><a href="namespacearmnn.html#ad701d0d29baa4266ab4d33b090aa661c">armnn::ConvertActivationDescriptorToAclActivationLayerInfo</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo ConvertActivationDescriptorToAclActivationLayerInfo(const ActivationDescriptor &amp;actDesc)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00073">ArmComputeUtils.hpp:73</a></div></div>
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<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
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<div class="ttc" id="structarmnn_1_1_activation_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00020">Descriptors.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_html_afdba36f125621d775d471f0daf613df2"><div class="ttname"><a href="namespacearmnn.html#afdba36f125621d775d471f0daf613df2">armnn::ConvertActivationFunctionToAclActivationFunction</a></div><div class="ttdeci">arm_compute::ActivationLayerInfo::ActivationFunction ConvertActivationFunctionToAclActivationFunction(ActivationFunction armnnFunction)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00051">ArmComputeUtils.hpp:51</a></div></div>
<div class="ttc" id="namespacearmnn_html_a56297e0f7b215eea46c818cb7528d9ea"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a></div><div class="ttdeci">ActivationFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00054">Types.hpp:54</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a5e783a951642781b9e7b55db06a514b7"><div class="ttname"><a href="namespacearmnn.html#a5e783a951642781b9e7b55db06a514b7">armnn::CreateAclNormalizationLayerInfoForL2Normalization</a></div><div class="ttdeci">arm_compute::NormalizationLayerInfo CreateAclNormalizationLayerInfoForL2Normalization(const armnn::TensorInfo &amp;tensorInfo, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00018">ArmComputeUtils.hpp:18</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.html">armnn::ViewsDescriptor</a></div><div class="ttdoc">A ViewsDescriptor for the SplitterLayer. Descriptor to configure the splitting process. Number of Views must be equal to the number of outputs, and their order must match - e.g. first view corresponds to the first output, second view to the second output, etc. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00190">Descriptors.hpp:190</a></div></div>
<div class="ttc" id="namespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718">armnn::PoolingAlgorithm</a></div><div class="ttdeci">PoolingAlgorithm</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00093">Types.hpp:93</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_html_a78e8266be865fdd92cadd04d6e25ae1f"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.html#a78e8266be865fdd92cadd04d6e25ae1f">armnn::ViewsDescriptor::GetNumDimensions</a></div><div class="ttdeci">uint32_t GetNumDimensions() const</div><div class="ttdoc">Get the number of dimensions. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00292">Descriptors.cpp:292</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_html_a28c4c9cb15f6be3499abbc46b356060b"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html#a28c4c9cb15f6be3499abbc46b356060b">armnn::ActivationDescriptor::m_B</a></div><div class="ttdeci">float m_B</div><div class="ttdoc">Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00039">Descriptors.hpp:39</a></div></div>
<div class="ttc" id="_descriptors_8hpp_html"><div class="ttname"><a href="_descriptors_8hpp.html">Descriptors.hpp</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a8f3bfacadfd6d2146d6ccd299dabc7aa"><div class="ttname"><a href="namespacearmnn.html#a8f3bfacadfd6d2146d6ccd299dabc7aa">armnn::ConvertOutputShapeRoundingToAclDimensionRoundingType</a></div><div class="ttdeci">arm_compute::DimensionRoundingType ConvertOutputShapeRoundingToAclDimensionRoundingType(OutputShapeRounding rounding)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00092">ArmComputeUtils.hpp:92</a></div></div>
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<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_html_a3c1ab47a0a319413b3a4b5757ed5b80b"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.html#a3c1ab47a0a319413b3a4b5757ed5b80b">armnn::ViewsDescriptor::GetViewSizes</a></div><div class="ttdeci">const uint32_t * GetViewSizes(uint32_t idx) const</div><div class="ttdoc">Get the view sizes at the int value idx. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00332">Descriptors.cpp:332</a></div></div>
<div class="ttc" id="namespacearmnn_html_abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc"><div class="ttname"><a href="namespacearmnn.html#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a></div></div>
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<div class="ttc" id="structarmnn_1_1_softmax_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a></div><div class="ttdoc">A SoftmaxDescriptor for the SoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00123">Descriptors.hpp:123</a></div></div>
<div class="ttc" id="namespacearmnn_html_a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76"><div class="ttname"><a href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a7e6aa2d53f6ee2b1a34b017fa403cb76">armnn::PoolingAlgorithm::L2</a></div></div>
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<div class="ttc" id="namespacearmnn_html_aa70ebe7b7898fe69ce24db803caa373e"><div class="ttname"><a href="namespacearmnn.html#aa70ebe7b7898fe69ce24db803caa373e">armnn::ComputeSoftmaxAclAxis</a></div><div class="ttdeci">unsigned int ComputeSoftmaxAclAxis(const SoftmaxDescriptor &amp;softmaxDesc, const armnn::TensorInfo &amp;tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00138">ArmComputeUtils.hpp:138</a></div></div>
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<div class="ttc" id="namespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a></div><div class="ttdoc">min(a, max(b, input)) </div></div>
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<div class="ttc" id="namespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a></div></div>
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