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| <li class="navelem"><a class="el" href="namespacesinga.html">singa</a></li><li class="navelem"><a class="el" href="classsinga_1_1Optimizer.html">Optimizer</a></li> </ul> |
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| |
| <p>The base class for gradient descent algorithms used to update the model parameters in order to optimize the objective (loss) function. |
| <a href="classsinga_1_1Optimizer.html#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="optimizer_8h_source.html">optimizer.h</a>></code></p> |
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| Inheritance diagram for singa::Optimizer:</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:ad0940567e5f2ac6ec99132f2c013c94a"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#ad0940567e5f2ac6ec99132f2c013c94a">Setup</a> (const string &str)</td></tr> |
| <tr class="memdesc:ad0940567e5f2ac6ec99132f2c013c94a"><td class="mdescLeft"> </td><td class="mdescRight">Setup the optimzier using configurations from serialized string (for binding languages). <a href="#ad0940567e5f2ac6ec99132f2c013c94a">More...</a><br /></td></tr> |
| <tr class="separator:ad0940567e5f2ac6ec99132f2c013c94a"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa51db156a64d285d04f575398bb79d1c"><td class="memItemLeft" align="right" valign="top"><a id="aa51db156a64d285d04f575398bb79d1c"></a> |
| virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#aa51db156a64d285d04f575398bb79d1c">Setup</a> (const OptimizerConf &conf)</td></tr> |
| <tr class="memdesc:aa51db156a64d285d04f575398bb79d1c"><td class="mdescLeft"> </td><td class="mdescRight">Setup the meta fields of the optimizer. <br /></td></tr> |
| <tr class="separator:aa51db156a64d285d04f575398bb79d1c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a6385d176ba3b2bf744221f8801291f3e"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#a6385d176ba3b2bf744221f8801291f3e">Register</a> (const string &name, const ParamSpec &specs)</td></tr> |
| <tr class="memdesc:a6385d176ba3b2bf744221f8801291f3e"><td class="mdescLeft"> </td><td class="mdescRight">Register the parameter, e.g., create <a class="el" href="classsinga_1_1Constraint.html" title="Apply constraints for parameters (gradient). ">Constraint</a> and Regularizers. <a href="#a6385d176ba3b2bf744221f8801291f3e">More...</a><br /></td></tr> |
| <tr class="separator:a6385d176ba3b2bf744221f8801291f3e"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a497c98c50be398534651afb9c47ad896"><td class="memItemLeft" align="right" valign="top"><a id="a497c98c50be398534651afb9c47ad896"></a> |
| virtual void </td><td class="memItemRight" valign="bottom"><b>ApplyRegularizerConstraint</b> (int epoch, const string &name, const <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &value, <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &grad, int step=-1)</td></tr> |
| <tr class="separator:a497c98c50be398534651afb9c47ad896"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a98c129ff433c9faff924f17618126539"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#a98c129ff433c9faff924f17618126539">Apply</a> (int epoch, float lr, const string &name, <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &grad, <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &value, int step=-1)=0</td></tr> |
| <tr class="memdesc:a98c129ff433c9faff924f17618126539"><td class="mdescLeft"> </td><td class="mdescRight">Apply the updating algorithm if the gradient is not empty. <a href="#a98c129ff433c9faff924f17618126539">More...</a><br /></td></tr> |
| <tr class="separator:a98c129ff433c9faff924f17618126539"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a23eb982f713174589788369a0316e81d"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#a23eb982f713174589788369a0316e81d">Apply</a> (int epoch, const string &name, <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &grad, <a class="el" href="classsinga_1_1Tensor.html">Tensor</a> &value, int step=-1)</td></tr> |
| <tr class="memdesc:a23eb982f713174589788369a0316e81d"><td class="mdescLeft"> </td><td class="mdescRight">Apply the updating algorithm if the gradient is not empty. <a href="#a23eb982f713174589788369a0316e81d">More...</a><br /></td></tr> |
| <tr class="separator:a23eb982f713174589788369a0316e81d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a2f3ba1fe776cdf373565b0cf208bf540"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classsinga_1_1Optimizer.html#a2f3ba1fe776cdf373565b0cf208bf540">SetLearningRateGenerator</a> (function< float(int)> func)</td></tr> |
| <tr class="memdesc:a2f3ba1fe776cdf373565b0cf208bf540"><td class="mdescLeft"> </td><td class="mdescRight">The argument is a function that returns the learning rate given the current step (i.e., curren running iteration). <a href="#a2f3ba1fe776cdf373565b0cf208bf540">More...</a><br /></td></tr> |
| <tr class="separator:a2f3ba1fe776cdf373565b0cf208bf540"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a4fddc84ed373777a3bff864793312895"><td class="memItemLeft" align="right" valign="top"><a id="a4fddc84ed373777a3bff864793312895"></a> |
| float </td><td class="memItemRight" valign="bottom"><b>GetLearningRate</b> (int step)</td></tr> |
| <tr class="separator:a4fddc84ed373777a3bff864793312895"><td class="memSeparator" colspan="2"> </td></tr> |
| </table><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a> |
| Protected Attributes</h2></td></tr> |
| <tr class="memitem:a08ff43c3cf2dd1a84d2dbcab2b9825eb"><td class="memItemLeft" align="right" valign="top"><a id="a08ff43c3cf2dd1a84d2dbcab2b9825eb"></a> |
| function< float(int)> </td><td class="memItemRight" valign="bottom"><b>learning_rate_generator_</b></td></tr> |
| <tr class="separator:a08ff43c3cf2dd1a84d2dbcab2b9825eb"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a303ef1680d83a7dba74a8de5e412eba7"><td class="memItemLeft" align="right" valign="top"><a id="a303ef1680d83a7dba74a8de5e412eba7"></a> |
| std::unordered_map< std::string, float > </td><td class="memItemRight" valign="bottom"><b>learning_rate_multplier_</b></td></tr> |
| <tr class="separator:a303ef1680d83a7dba74a8de5e412eba7"><td class="memSeparator" colspan="2"> </td></tr> |
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| std::unordered_map< std::string, <a class="el" href="classsinga_1_1Constraint.html">Constraint</a> * > </td><td class="memItemRight" valign="bottom"><b>constraints_</b></td></tr> |
| <tr class="separator:a398deb004c050bd6aed1c41f66554e0a"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ac55e2668b8ddd0fe2d3b98d363836484"><td class="memItemLeft" align="right" valign="top"><a id="ac55e2668b8ddd0fe2d3b98d363836484"></a> |
| std::unordered_map< std::string, <a class="el" href="classsinga_1_1Regularizer.html">Regularizer</a> * > </td><td class="memItemRight" valign="bottom"><b>regularizers_</b></td></tr> |
| <tr class="separator:ac55e2668b8ddd0fe2d3b98d363836484"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a91a5e476ac69c0da15cfbfce6351fec4"><td class="memItemLeft" align="right" valign="top"><a id="a91a5e476ac69c0da15cfbfce6351fec4"></a> |
| <a class="el" href="classsinga_1_1Constraint.html">Constraint</a> * </td><td class="memItemRight" valign="bottom"><b>constraint_</b> = nullptr</td></tr> |
| <tr class="separator:a91a5e476ac69c0da15cfbfce6351fec4"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:accec73a0f0dafbe4617106f6151bcccf"><td class="memItemLeft" align="right" valign="top"><a id="accec73a0f0dafbe4617106f6151bcccf"></a> |
| <a class="el" href="classsinga_1_1Regularizer.html">Regularizer</a> * </td><td class="memItemRight" valign="bottom"><b>regularizer_</b> = nullptr</td></tr> |
| <tr class="separator:accec73a0f0dafbe4617106f6151bcccf"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a71b4defd74f44648cbfd523311258f41"><td class="memItemLeft" align="right" valign="top"><a id="a71b4defd74f44648cbfd523311258f41"></a> |
| OptimizerConf </td><td class="memItemRight" valign="bottom"><b>conf_</b></td></tr> |
| <tr class="separator:a71b4defd74f44648cbfd523311258f41"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>The base class for gradient descent algorithms used to update the model parameters in order to optimize the objective (loss) function. </p> |
| <p>It updates parameters based on the gradients of the loss w.r.t each parameter. Most sub-classes uses first order gradients. An overview of gradient descent algorithms, <a href="http://sebastianruder.com/optimizing-gradient-descent/">http://sebastianruder.com/optimizing-gradient-descent/</a> </p> |
| </div><h2 class="groupheader">Member Function Documentation</h2> |
| <a id="a98c129ff433c9faff924f17618126539"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a98c129ff433c9faff924f17618126539">◆ </a></span>Apply() <span class="overload">[1/2]</span></h2> |
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| <td class="memname">virtual void singa::Optimizer::Apply </td> |
| <td>(</td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>epoch</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>lr</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classsinga_1_1Tensor.html">Tensor</a> & </td> |
| <td class="paramname"><em>grad</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classsinga_1_1Tensor.html">Tensor</a> & </td> |
| <td class="paramname"><em>value</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>step</em> = <code>-1</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">pure virtual</span></span> </td> |
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| </div><div class="memdoc"> |
| |
| <p>Apply the updating algorithm if the gradient is not empty. </p> |
| <p>No learning rate scaling, gradient constraints/regularization will be conducted. It assumes all these operations are done either by users or by Apply(int, const string&, Tensor*, Tensor*). All sub-classes should override this function. </p> |
| |
| <p>Implemented in <a class="el" href="classsinga_1_1RMSProp.html#a2b83ee5006967e91eed435c6adcf782d">singa::RMSProp</a>, <a class="el" href="classsinga_1_1AdaGrad.html#ac9b378fe7ae88f88e45b817f89871f69">singa::AdaGrad</a>, <a class="el" href="classsinga_1_1Nesterov.html#a6551a089c8073dd13b27d59b06ccf2eb">singa::Nesterov</a>, and <a class="el" href="classsinga_1_1SGD.html#ac73356906d1ca127d7d13c376b5edafe">singa::SGD</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a23eb982f713174589788369a0316e81d"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a23eb982f713174589788369a0316e81d">◆ </a></span>Apply() <span class="overload">[2/2]</span></h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void singa::Optimizer::Apply </td> |
| <td>(</td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>epoch</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classsinga_1_1Tensor.html">Tensor</a> & </td> |
| <td class="paramname"><em>grad</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classsinga_1_1Tensor.html">Tensor</a> & </td> |
| <td class="paramname"><em>value</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>step</em> = <code>-1</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Apply the updating algorithm if the gradient is not empty. </p> |
| <p>It will apply regularization and constraint to the parameters if configured during <a class="el" href="classsinga_1_1Optimizer.html#a6385d176ba3b2bf744221f8801291f3e" title="Register the parameter, e.g., create Constraint and Regularizers. ">Register()</a>. If will also scale the learning rate if configured in ParamSpecs (see Register). </p> |
| |
| </div> |
| </div> |
| <a id="a6385d176ba3b2bf744221f8801291f3e"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a6385d176ba3b2bf744221f8801291f3e">◆ </a></span>Register()</h2> |
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| <td class="memname">virtual void singa::Optimizer::Register </td> |
| <td>(</td> |
| <td class="paramtype">const string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const ParamSpec & </td> |
| <td class="paramname"><em>specs</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
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| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">virtual</span></span> </td> |
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| </div><div class="memdoc"> |
| |
| <p>Register the parameter, e.g., create <a class="el" href="classsinga_1_1Constraint.html" title="Apply constraints for parameters (gradient). ">Constraint</a> and Regularizers. </p> |
| <p>If there is no constraint or regularizer, then no need to register the parameter. </p> |
| |
| </div> |
| </div> |
| <a id="a2f3ba1fe776cdf373565b0cf208bf540"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a2f3ba1fe776cdf373565b0cf208bf540">◆ </a></span>SetLearningRateGenerator()</h2> |
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| <td class="memname">void singa::Optimizer::SetLearningRateGenerator </td> |
| <td>(</td> |
| <td class="paramtype">function< float(int)> </td> |
| <td class="paramname"><em>func</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
| </tr> |
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| </div><div class="memdoc"> |
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| <p>The argument is a function that returns the learning rate given the current step (i.e., curren running iteration). </p> |
| |
| </div> |
| </div> |
| <a id="ad0940567e5f2ac6ec99132f2c013c94a"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad0940567e5f2ac6ec99132f2c013c94a">◆ </a></span>Setup()</h2> |
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| <td class="memname">void singa::Optimizer::Setup </td> |
| <td>(</td> |
| <td class="paramtype">const string & </td> |
| <td class="paramname"><em>str</em></td><td>)</td> |
| <td></td> |
| </tr> |
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| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
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| </div><div class="memdoc"> |
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| <p>Setup the optimzier using configurations from serialized string (for binding languages). </p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following file:<ul> |
| <li>/home/moaz/incubator-singa/include/singa/model/<a class="el" href="optimizer_8h_source.html">optimizer.h</a></li> |
| </ul> |
| </div><!-- contents --> |
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| Generated on Mon Apr 22 2019 12:27:05 for Apache Singa by  <a href="http://www.doxygen.org/index.html"> |
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| </a> 1.8.13 |
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