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+<a href="backends_2reference_2workloads_2_fully_connected_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><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="_fully_connected_8hpp.html">FullyConnected.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 &quot;<a class="code" href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a>&quot;</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;boost/assert.hpp&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="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></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;</div><div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ad34d1d5b1ca8f52dc296ecf52ba20c8a">   15</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#ad34d1d5b1ca8f52dc296ecf52ba20c8a">FullyConnected</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; rInputShape,</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;                    <a class="code" href="classarmnn_1_1_decoder.html">Decoder&lt;float&gt;</a>&amp; rInputDecoder,</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;                    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; rOutputShape,</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;                    <a class="code" href="classarmnn_1_1_encoder.html">Encoder&lt;float&gt;</a>&amp; rOutputEncoder,</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;                    <a class="code" href="classarmnn_1_1_decoder.html">Decoder&lt;float&gt;</a>&amp; rWeightDecoder,</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;                    <a class="code" href="classarmnn_1_1_decoder.html">Decoder&lt;float&gt;</a>&amp; rBiasDecoder,</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;                    <span class="keyword">const</span> <span class="keywordtype">bool</span> biasEnabled,</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> K,</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;                    <span class="keyword">const</span> <span class="keywordtype">bool</span> transposeWeights)</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;{</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    <span class="comment">// Perform FullyConnected implementation</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = rOutputShape[1];</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n &lt; rInputShape[0]; n++)</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    {</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelOutput = 0; channelOutput &lt; outputSize; channelOutput++)</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="keywordtype">float</span> outval = 0.f;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelInput = 0; channelInput &lt; K; channelInput++)</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;            {</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;                <span class="keywordtype">float</span> weight;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;                <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;                {</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;                    rWeightDecoder[channelOutput * K + channelInput];</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;                    weight = rWeightDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;                }</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;                <span class="keywordflow">else</span></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;                    rWeightDecoder[channelInput * outputSize + channelOutput];</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;                    weight = rWeightDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</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;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;                rInputDecoder[n * K + channelInput];</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;                outval += weight * rInputDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</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;</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;            <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;            {</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                rBiasDecoder[channelOutput];</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;                outval += rBiasDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</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;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            rOutputEncoder[n * outputSize + channelOutput];</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            rOutputEncoder.<a class="code" href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">Set</a>(outval);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;        }</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    }</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;}</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;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_decoder_html"><div class="ttname"><a href="classarmnn_1_1_decoder.html">armnn::Decoder&lt; float &gt;</a></div></div>
+<div class="ttc" id="_fully_connected_8hpp_html"><div class="ttname"><a href="_fully_connected_8hpp.html">FullyConnected.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_html"><div class="ttname"><a href="classarmnn_1_1_encoder.html">armnn::Encoder&lt; float &gt;</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad34d1d5b1ca8f52dc296ecf52ba20c8a"><div class="ttname"><a href="namespacearmnn.html#ad34d1d5b1ca8f52dc296ecf52ba20c8a">armnn::FullyConnected</a></div><div class="ttdeci">void FullyConnected(const TensorShape &amp;rInputShape, Decoder&lt; float &gt; &amp;rInputDecoder, const TensorShape &amp;rOutputShape, Encoder&lt; float &gt; &amp;rOutputEncoder, Decoder&lt; float &gt; &amp;rWeightDecoder, Decoder&lt; float &gt; &amp;rBiasDecoder, const bool biasEnabled, const unsigned int K, const bool transposeWeights)</div><div class="ttdoc">Performs a matrix multiplication and optionally adds a bias. </div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_fully_connected_8cpp_source.html#l00015">FullyConnected.cpp:15</a></div></div>
+<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="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="classarmnn_1_1_decoder_html_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_html_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
+<div class="ttc" id="_ref_workload_utils_8hpp_html"><div class="ttname"><a href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a></div></div>
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