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-<a href="#pub-methods">Public Member Functions</a> </div>
+<a href="#pub-methods">Public Member Functions</a> |
+<a href="#pub-static-methods">Static Public Member Functions</a> </div>
<div class="headertitle">
<div class="title">CLBatchNormalizationLayer Class Reference</div> </div>
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Collaboration diagram for CLBatchNormalizationLayer:</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:aa75c9e345235e7031d6489425e53645a"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml#aa75c9e345235e7031d6489425e53645a">CLBatchNormalizationLayer</a> ()</td></tr>
-<tr class="memdesc:aa75c9e345235e7031d6489425e53645a"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#aa75c9e345235e7031d6489425e53645a">More...</a><br/></td></tr>
+<tr class="memdesc:aa75c9e345235e7031d6489425e53645a"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#aa75c9e345235e7031d6489425e53645a">More...</a><br /></td></tr>
<tr class="separator:aa75c9e345235e7031d6489425e53645a"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:a088b702f0c5f0c0326be2f4b5c2006ed"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml#a088b702f0c5f0c0326be2f4b5c2006ed">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *mean, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *var, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *beta, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *gamma, float epsilon)</td></tr>
-<tr class="memdesc:a088b702f0c5f0c0326be2f4b5c2006ed"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#a088b702f0c5f0c0326be2f4b5c2006ed">More...</a><br/></td></tr>
-<tr class="separator:a088b702f0c5f0c0326be2f4b5c2006ed"><td class="memSeparator" colspan="2"> </td></tr>
+<tr class="memitem:a2b8fc7ef9b53c8a4e6b13995109ebf18"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml#a2b8fc7ef9b53c8a4e6b13995109ebf18">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *mean, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *var, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *beta=nullptr, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *gamma=nullptr, float epsilon=0.001f, ActivationLayerInfo act_info=ActivationLayerInfo())</td></tr>
+<tr class="memdesc:a2b8fc7ef9b53c8a4e6b13995109ebf18"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#a2b8fc7ef9b53c8a4e6b13995109ebf18">More...</a><br /></td></tr>
+<tr class="separator:a2b8fc7ef9b53c8a4e6b13995109ebf18"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
-<tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br/></td></tr>
+<tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </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"> </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="-"/> 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 </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"> </td><td class="mdescRight">Destructor. <a href="#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br/></td></tr>
+<tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </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"> </td></tr>
+<tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">prepare</a> ()</td></tr>
+<tr class="memdesc:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Prepare the function for executing. <a href="#a820f7291c24155a2980512fae45aac26">More...</a><br /></td></tr>
+<tr class="separator:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr>
+</table><table class="memberdecls">
+<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
+Static Public Member Functions</h2></td></tr>
+<tr class="memitem:af5f30ebbb928758897f5dcd17fc50181"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml#af5f30ebbb928758897f5dcd17fc50181">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *mean, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *var, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *beta=nullptr, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *gamma=nullptr, float epsilon=0.001f, ActivationLayerInfo act_info=ActivationLayerInfo())</td></tr>
+<tr class="memdesc:af5f30ebbb928758897f5dcd17fc50181"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml">CLBatchNormalizationLayer</a>. <a href="#af5f30ebbb928758897f5dcd17fc50181">More...</a><br /></td></tr>
+<tr class="separator:af5f30ebbb928758897f5dcd17fc50181"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Basic function to run <a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml">CLNormalizationLayerKernel</a> and simulate a batch normalization layer. </p>
-<p>Batch normalization is calculated by: </p>
-<p class="formulaDsp">
+<p>Batch normalization is calculated by: </p><p class="formulaDsp">
\[ out_i = \gamma * (\frac{in_i - \mu_{B}}{\sqrt{\sigma^2_{B} + \epsilon}}) + \beta \equiv BN_{\gamma,\beta}(in_i) \]
</p>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
-<a class="anchor" id="a088b702f0c5f0c0326be2f4b5c2006ed"></a>
+<a class="anchor" id="a2b8fc7ef9b53c8a4e6b13995109ebf18"></a>
<div class="memitem">
<div class="memproto">
<table class="memname">
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td>
- <td class="paramname"><em>beta</em>, </td>
+ <td class="paramname"><em>beta</em> = <code>nullptr</code>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td>
- <td class="paramname"><em>gamma</em>, </td>
+ <td class="paramname"><em>gamma</em> = <code>nullptr</code>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">float </td>
- <td class="paramname"><em>epsilon</em> </td>
+ <td class="paramname"><em>epsilon</em> = <code>0.001f</code>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype"><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> </td>
+ <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code> </td>
</tr>
<tr>
<td></td>
</div><div class="memdoc">
<p>Set the input and output tensors. </p>
-<dl class="section note"><dt>Note</dt><dd>If the output tensor is a nullptr, the batch normalization function will be performed in-place</dd></dl>
+<dl class="section note"><dt>Note</dt><dd>If the output tensor is a nullptr or is equal to the input, the batch normalization function will be performed in-place</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">input</td><td>Source tensor. In case of <code>output</code> tensor = nullptr, this tensor will store the result. 3 lower dimensions represent a single input with dimensions [width, height, FM]. The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. </td></tr>
+ <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as <code>input</code> </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">mean</td><td>Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">var</td><td>Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
- <tr><td class="paramdir">[in]</td><td class="paramname">gamma</td><td>Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
- <tr><td class="paramdir">[in]</td><td class="paramname">beta</td><td>Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
- <tr><td class="paramdir">[in]</td><td class="paramname">epsilon</td><td>Small value to avoid division with zero. </td></tr>
- <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">beta</td><td>(Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">gamma</td><td>(Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">epsilon</td><td>(Optional) Small value to avoid division with zero. Default value is 0.001f. </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. </td></tr>
</table>
</dd>
</dl>
</div><div class="memdoc">
<p>Run the kernels contained in the function. </p>
-<p>For NEON kernels:</p>
-<ul>
+<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>
+<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>
+<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>
+<dd>
+Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing. ">prepare()</a> on first run if hasn't been done </dd></dl>
<p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>
</div>
</div>
+<a class="anchor" id="af5f30ebbb928758897f5dcd17fc50181"></a>
+<div class="memitem">
+<div class="memproto">
+<table class="mlabels">
+ <tr>
+ <td class="mlabels-left">
+ <table class="memname">
+ <tr>
+ <td class="memname">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td>
+ <td>(</td>
+ <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </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_tensor_info.xhtml">ITensorInfo</a> * </td>
+ <td class="paramname"><em>output</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td>
+ <td class="paramname"><em>mean</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td>
+ <td class="paramname"><em>var</em>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td>
+ <td class="paramname"><em>beta</em> = <code>nullptr</code>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td>
+ <td class="paramname"><em>gamma</em> = <code>nullptr</code>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype">float </td>
+ <td class="paramname"><em>epsilon</em> = <code>0.001f</code>, </td>
+ </tr>
+ <tr>
+ <td class="paramkey"></td>
+ <td></td>
+ <td class="paramtype"><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> </td>
+ <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code> </td>
+ </tr>
+ <tr>
+ <td></td>
+ <td>)</td>
+ <td></td><td></td>
+ </tr>
+ </table>
+ </td>
+ <td class="mlabels-right">
+<span class="mlabels"><span class="mlabel">static</span></span> </td>
+ </tr>
+</table>
+</div><div class="memdoc">
+
+<p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml">CLBatchNormalizationLayer</a>. </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 info. In case of <code>output</code> tensor info = nullptr, this tensor will store the result. 3 lower dimensions represent a single input with dimensions [width, height, FM]. The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32. </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">mean</td><td>Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">var</td><td>Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">beta</td><td>(Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">gamma</td><td>(Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as <code>input</code> </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">epsilon</td><td>(Optional) Small value to avoid division with zero. Default value is 0.001f. </td></tr>
+ <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.</td></tr>
+ </table>
+ </dd>
+</dl>
+<dl class="section return"><dt>Returns</dt><dd>a status </dd></dl>
+
+<p>Referenced by <a class="el" href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00102">arm_compute::test::validation::DATA_TEST_CASE()</a>.</p>
+
+</div>
+</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_batch_normalization_layer_8h_source.xhtml">CLBatchNormalizationLayer.h</a></li>
</ul>
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<li class="navelem"><a class="el" href="namespacearm__compute.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml">CLBatchNormalizationLayer</a></li>
- <li class="footer">Generated on Thu Sep 28 2017 14:37:57 for Compute Library by
+ <li class="footer">Generated on Wed May 23 2018 11:36:40 for Compute Library by
<a href="http://www.doxygen.org/index.html">
- <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 </li>
+ <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
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