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<a href="#pub-methods">Public Member Functions</a> </div>
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<div class="title">GCFullyConnectedLayer Class Reference</div> </div>
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<p>Basic function to compute a Fully Connected layer on OpenGL ES.
<a href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_g_c_fully_connected_layer_8h_source.xhtml">GCFullyConnectedLayer.h</a>&gt;</code></p>
<div class="dynheader">
Collaboration diagram for GCFullyConnectedLayer:</div>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a72b2bdf0cae7f6e47b0d5f957de6d304"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml#a72b2bdf0cae7f6e47b0d5f957de6d304">GCFullyConnectedLayer</a> ()</td></tr>
<tr class="memdesc:a72b2bdf0cae7f6e47b0d5f957de6d304"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#a72b2bdf0cae7f6e47b0d5f957de6d304">More...</a><br /></td></tr>
<tr class="separator:a72b2bdf0cae7f6e47b0d5f957de6d304"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a68a5db52b1ed7f7ca1d619ac1263ab38"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml#a68a5db52b1ed7f7ca1d619ac1263ab38">configure</a> (const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *weights, const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *biases, <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *output, bool transpose_weights=true, bool are_weights_reshaped=false)</td></tr>
<tr class="memdesc:a68a5db52b1ed7f7ca1d619ac1263ab38"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the input and output tensors. <a href="#a68a5db52b1ed7f7ca1d619ac1263ab38">More...</a><br /></td></tr>
<tr class="separator:a68a5db52b1ed7f7ca1d619ac1263ab38"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
<tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr>
<tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr>
<tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr>
<tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <a href="#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr>
<tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Basic function to compute a Fully Connected layer on OpenGL ES. </p>
<p>This function calls the following OpenGL ES kernels:</p>
<ol type="1">
<li><a class="el" href="classarm__compute_1_1_g_c_im2_col_kernel.xhtml">GCIm2ColKernel</a> (called when the input comes from a convolutional layer)</li>
<li><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer_reshape_weights.xhtml">GCFullyConnectedLayerReshapeWeights</a> (if <code>are_weights_reshaped</code> is set to false and transpose_weights is set to true ) (called once)</li>
<li><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_multiply_kernel.xhtml">GCGEMMMatrixMultiplyKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_g_c_g_e_m_m_matrix_accumulate_biases_kernel.xhtml">GCGEMMMatrixAccumulateBiasesKernel</a> (if <code>biases</code> is not equal to nullptr)</li>
</ol>
<dl class="section note"><dt>Note</dt><dd>The fully connected layer accepts "weights" tensors only with 2 dimensions. </dd></dl>
<p>Definition at line <a class="el" href="_g_c_fully_connected_layer_8h_source.xhtml#l00062">62</a> of file <a class="el" href="_g_c_fully_connected_layer_8h_source.xhtml">GCFullyConnectedLayer.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a class="anchor" id="a72b2bdf0cae7f6e47b0d5f957de6d304"></a>
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<td class="memname"><a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml">GCFullyConnectedLayer</a> </td>
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<p>Constructor. </p>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a class="anchor" id="a68a5db52b1ed7f7ca1d619ac1263ab38"></a>
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<td class="memname">void configure </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *&#160;</td>
<td class="paramname"><em>input</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *&#160;</td>
<td class="paramname"><em>weights</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *&#160;</td>
<td class="paramname"><em>biases</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *&#160;</td>
<td class="paramname"><em>output</em>, </td>
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<td class="paramtype">bool&#160;</td>
<td class="paramname"><em>transpose_weights</em> = <code>true</code>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">bool&#160;</td>
<td class="paramname"><em>are_weights_reshaped</em> = <code>false</code>&#160;</td>
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<td></td>
<td>)</td>
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</div><div class="memdoc">
<p>Set the input and output tensors. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. Data type supported: F16/F32. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. The weights must be 2 dimensional. Data type supported: Same as <code>input</code> </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Bias tensor. It can be nullptr. Data type supported:Same as <code>input</code>. </td></tr>
<tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: Same as <code>input</code>. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">transpose_weights</td><td>(Optional) Transpose weights if true. Defaults to true. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">are_weights_reshaped</td><td>(Optional) Reshape the weights tensor if false. Defaults to false. </td></tr>
</table>
</dd>
</dl>
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<td class="memname">void run </td>
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<td class="paramname"></td><td>)</td>
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<span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td>
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<p>Run the kernels contained in the function. </p>
<p>For NEON kernels:</p><ul>
<li>Multi-threading is used for the kernels which are parallelisable.</li>
<li>By default std::thread::hardware_concurrency() threads are used.</li>
</ul>
<dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl>
<p>For OpenCL kernels:</p><ul>
<li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue. ">CLScheduler</a>.</li>
<li>The queue is then flushed.</li>
</ul>
<dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd></dl>
<p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>arm_compute/runtime/GLES_COMPUTE/functions/<a class="el" href="_g_c_fully_connected_layer_8h_source.xhtml">GCFullyConnectedLayer.h</a></li>
</ul>
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