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<html><head><title>dlib C++ Library - lspi_abstract.h</title></head><body bgcolor='white'><pre> |
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<font color='#009900'>// Copyright (C) 2015 Davis E. King ([email protected]) |
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</font><font color='#009900'>// License: Boost Software License See LICENSE.txt for the full license. |
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</font><font color='#0000FF'>#undef</font> DLIB_LSPI_ABSTRACT_Hh_ |
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<font color='#0000FF'>#ifdef</font> DLIB_LSPI_ABSTRACT_Hh_ |
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<font color='#0000FF'>#include</font> "<a style='text-decoration:none' href='approximate_linear_models_abstract.h.html'>approximate_linear_models_abstract.h</a>" |
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<font color='#0000FF'>namespace</font> dlib |
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<b>{</b> |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<font color='#0000FF'>template</font> <font color='#5555FF'><</font> |
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<font color='#0000FF'>typename</font> feature_extractor |
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<font color='#5555FF'>></font> |
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<font color='#0000FF'>class</font> <b><a name='lspi'></a>lspi</b> |
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<b>{</b> |
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<font color='#009900'>/*! |
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REQUIREMENTS ON feature_extractor |
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feature_extractor should implement the example_feature_extractor interface |
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defined at the top of dlib/control/approximate_linear_models_abstract.h |
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WHAT THIS OBJECT REPRESENTS |
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This object is an implementation of the reinforcement learning algorithm |
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described in the following paper: |
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Lagoudakis, Michail G., and Ronald Parr. "Least-squares policy |
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iteration." The Journal of Machine Learning Research 4 (2003): |
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1107-1149. |
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This means that it takes a bunch of training data in the form of |
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process_samples and outputs a policy that hopefully performs well when run |
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on the process that generated those samples. |
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!*/</font> |
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<font color='#0000FF'>public</font>: |
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<font color='#0000FF'>typedef</font> feature_extractor feature_extractor_type; |
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<font color='#0000FF'>typedef</font> <font color='#0000FF'>typename</font> feature_extractor::state_type state_type; |
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<font color='#0000FF'>typedef</font> <font color='#0000FF'>typename</font> feature_extractor::action_type action_type; |
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<font color='#0000FF'>explicit</font> <b><a name='lspi'></a>lspi</b><font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> feature_extractor<font color='#5555FF'>&</font> fe_ |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- #get_feature_extractor() == fe_ |
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- #get_lambda() == 0.01 |
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- #get_discount == 0.8 |
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- #get_epsilon() == 0.01 |
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- is not verbose |
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- #get_max_iterations() == 100 |
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!*/</font> |
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<b><a name='lspi'></a>lspi</b><font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- #get_feature_extractor() == feature_extractor() |
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(i.e. it will have its default value) |
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- #get_lambda() == 0.01 |
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- #get_discount == 0.8 |
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- #get_epsilon() == 0.01 |
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- is not verbose |
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- #get_max_iterations() == 100 |
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!*/</font> |
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<font color='#0000FF'><u>double</u></font> <b><a name='get_discount'></a>get_discount</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font> <font color='#0000FF'>const</font>; |
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<font color='#009900'>/*! |
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ensures |
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- returns the discount applied to the sum of rewards in the Bellman |
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equation. |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='set_discount'></a>set_discount</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'><u>double</u></font> value |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- 0 < value <= 1 |
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ensures |
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- #get_discount() == value |
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!*/</font> |
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<font color='#0000FF'>const</font> feature_extractor<font color='#5555FF'>&</font> <b><a name='get_feature_extractor'></a>get_feature_extractor</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font> <font color='#0000FF'>const</font>; |
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<font color='#009900'>/*! |
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ensures |
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- returns the feature extractor used by this object |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='be_verbose'></a>be_verbose</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- This object will print status messages to standard out so that a |
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user can observe the progress of the algorithm. |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='be_quiet'></a>be_quiet</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- this object will not print anything to standard out |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='set_epsilon'></a>set_epsilon</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'><u>double</u></font> eps |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- eps > 0 |
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ensures |
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- #get_epsilon() == eps |
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!*/</font> |
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<font color='#0000FF'><u>double</u></font> <b><a name='get_epsilon'></a>get_epsilon</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font> <font color='#0000FF'>const</font>; |
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<font color='#009900'>/*! |
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ensures |
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- returns the error epsilon that determines when training should stop. |
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Smaller values may result in a more accurate solution but take longer to |
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train. |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='set_lambda'></a>set_lambda</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'><u>double</u></font> lambda_ |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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requires |
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- lambda >= 0 |
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ensures |
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- #get_lambda() == lambda |
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!*/</font> |
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<font color='#0000FF'><u>double</u></font> <b><a name='get_lambda'></a>get_lambda</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font> <font color='#0000FF'>const</font>; |
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<font color='#009900'>/*! |
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ensures |
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- returns the regularization parameter. It is the parameter that |
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determines the trade off between trying to fit the training data |
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exactly or allowing more errors but hopefully improving the |
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generalization ability of the resulting function. Smaller values |
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encourage exact fitting while larger values of lambda may encourage |
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better generalization. |
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!*/</font> |
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<font color='#0000FF'><u>void</u></font> <b><a name='set_max_iterations'></a>set_max_iterations</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> max_iter |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- #get_max_iterations() == max_iter |
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!*/</font> |
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<font color='#0000FF'><u>unsigned</u></font> <font color='#0000FF'><u>long</u></font> <b><a name='get_max_iterations'></a>get_max_iterations</b> <font face='Lucida Console'>(</font> |
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<font face='Lucida Console'>)</font>; |
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<font color='#009900'>/*! |
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ensures |
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- returns the maximum number of iterations the SVM optimizer is allowed to |
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run before it is required to stop and return a result. |
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!*/</font> |
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<font color='#0000FF'>template</font> <font color='#5555FF'><</font> |
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<font color='#0000FF'>typename</font> vector_type |
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<font color='#5555FF'>></font> |
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policy<font color='#5555FF'><</font>feature_extractor<font color='#5555FF'>></font> <b><a name='train'></a>train</b> <font face='Lucida Console'>(</font> |
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<font color='#0000FF'>const</font> vector_type<font color='#5555FF'>&</font> samples |
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<font face='Lucida Console'>)</font> <font color='#0000FF'>const</font>; |
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<font color='#009900'>/*! |
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requires |
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- samples.size() > 0 |
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- samples is something with an interface that looks like |
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std::vector<process_sample<feature_extractor>>. That is, it should |
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be some kind of array of process_sample objects. |
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ensures |
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- Trains a policy based on the given data and returns the results. The |
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idea is to find a policy that will obtain the largest possible reward |
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when run on the process that generated the samples. In particular, |
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if the returned policy is P then: |
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- P(S) == the best action to take when in state S. |
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- if (feature_extractor::force_last_weight_to_1) then |
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- The last element of P.get_weights() is 1. |
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!*/</font> |
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<b>}</b>; |
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<font color='#009900'>// ---------------------------------------------------------------------------------------- |
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</font> |
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<b>}</b> |
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<font color='#0000FF'>#endif</font> <font color='#009900'>// DLIB_LSPI_ABSTRACT_Hh_ |
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</font> |
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</pre></body></html> |
