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<div class="title">Softmax.cpp</div>  </div>
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<a href="backends_2reference_2workloads_2_softmax_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>&#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;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_softmax_8hpp.xhtml">Softmax.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_utils_8hpp.xhtml">armnnUtils/TensorUtils.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;cmath&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;{</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"></span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment">/// Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo.</span></div><div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#aa999ff2585ad75b95954a9323f63c32b">   17</a></span>&#160;<span class="comment"></span><span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#aa999ff2585ad75b95954a9323f63c32b">Softmax</a>(<a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder&lt;float&gt;</a>&amp; in, <a class="code" href="classarmnn_1_1_encoder.xhtml">Encoder&lt;float&gt;</a>&amp; out, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; inputTensorInfo, <span class="keywordtype">float</span> beta, <span class="keywordtype">int</span> axis)</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;{</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;    <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(axis &lt; static_cast&lt;int&gt;(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()),</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;                     <span class="stringliteral">&quot;Required axis index greater than number of dimensions.&quot;</span>);</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;    <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(axis &gt;= -static_cast&lt;int&gt;(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()),</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;                     <span class="stringliteral">&quot;Required axis index lower than negative of the number of dimensions&quot;</span>);</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> uAxis = axis &lt; 0  ?</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;                         inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(<a class="code" href="structarmnn_1_1abs.xhtml">abs</a>(axis))</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;                         : static_cast&lt;unsigned int&gt;(axis);</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; inputShape = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outerSize  = <a class="code" href="namespacearmnn_utils.xhtml#af57864f5e03358d14c2988edae912b8b">armnnUtils::GetNumElementsBetween</a>(inputShape, 0, uAxis);</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axisSize   = inputShape[uAxis];</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> innerSize  = <a class="code" href="namespacearmnn_utils.xhtml#af57864f5e03358d14c2988edae912b8b">armnnUtils::GetNumElementsBetween</a>(inputShape,</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;                                                                      uAxis + 1,</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;                                                                      inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outer = 0; outer &lt; outerSize; ++outer)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBeginIdx  = outer * axisSize * innerSize;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputEndIdx    = inputBeginIdx + axisSize * innerSize;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBeginIdx = outer * axisSize * innerSize;</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inner = 0; inner &lt; innerSize; ++inner, ++inputBeginIdx, ++inputEndIdx, ++outputBeginIdx)</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        {</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;            <span class="comment">// Find max</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;            <span class="keywordtype">float</span> maxValue = std::numeric_limits&lt;float&gt;::lowest();</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> iter = inputBeginIdx; iter &lt; inputEndIdx; iter += innerSize)</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;                in[iter];</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;                maxValue = std::max(maxValue, in.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>());</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;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;            <span class="comment">// Compute sum</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;            <span class="keywordtype">float</span> sum = 0.0f;</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> iter = inputBeginIdx; iter &lt; inputEndIdx; iter += innerSize)</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;                in[iter];</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;                sum += std::exp((in.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>() - maxValue) * beta);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;            }</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            <span class="comment">// Compute result</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIter = outputBeginIdx;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;            out[outputIter];</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> iter = inputBeginIdx; iter &lt; inputEndIdx; iter += innerSize, outputIter += innerSize)</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;            {</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;                out[outputIter];</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;                in[iter];</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;                out.<a class="code" href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">Set</a>(std::exp((in.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>() - maxValue) * beta) / sum);</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;            }</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;        }</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="comment">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00187">Tensor.hpp:187</a></div></div>
<div class="ttc" id="structarmnn_1_1abs_xhtml"><div class="ttname"><a href="structarmnn_1_1abs.xhtml">armnn::abs</a></div><div class="ttdef"><b>Definition:</b> <a href="_abs_8hpp_source.xhtml#l00013">Abs.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_af57864f5e03358d14c2988edae912b8b"><div class="ttname"><a href="namespacearmnn_utils.xhtml#af57864f5e03358d14c2988edae912b8b">armnnUtils::GetNumElementsBetween</a></div><div class="ttdeci">unsigned int GetNumElementsBetween(const armnn::TensorShape &amp;shape, unsigned int firstAxisInclusive, unsigned int lastAxisExclusive)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.xhtml#l00113">TensorUtils.cpp:113</a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_xhtml_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
<div class="ttc" id="classarmnn_1_1_encoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml">armnn::Encoder&lt; float &gt;</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_xhtml_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div>
<div class="ttc" id="_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_utils_8hpp.xhtml">TensorUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="_softmax_8hpp_xhtml"><div class="ttname"><a href="_softmax_8hpp.xhtml">Softmax.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa999ff2585ad75b95954a9323f63c32b"><div class="ttname"><a href="namespacearmnn.xhtml#aa999ff2585ad75b95954a9323f63c32b">armnn::Softmax</a></div><div class="ttdeci">void Softmax(Decoder&lt; float &gt; &amp;in, Encoder&lt; float &gt; &amp;out, const TensorInfo &amp;inputTensorInfo, float beta, int axis)</div><div class="ttdoc">Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo...</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_softmax_8cpp_source.xhtml#l00017">Softmax.cpp:17</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml">armnn::Decoder&lt; float &gt;</a></div></div>
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