/usr/include/shogun/features/streaming/StreamingVwFeatures.h is in libshogun-dev 3.2.0-7.5.
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* Copyright (c) 2009 Yahoo! Inc. All rights reserved. The copyrights
* embodied in the content of this file are licensed under the BSD
* (revised) open source license.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2011 Shashwat Lal Das
* Adaptation of Vowpal Wabbit v5.1.
* Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society.
*/
#ifndef _STREAMING_VWFEATURES__H__
#define _STREAMING_VWFEATURES__H__
#include <shogun/lib/common.h>
#include <shogun/lib/DataType.h>
#include <shogun/mathematics/Math.h>
#include <shogun/io/streaming/InputParser.h>
#include <shogun/io/streaming/StreamingVwFile.h>
#include <shogun/io/streaming/StreamingVwCacheFile.h>
#include <shogun/features/streaming/StreamingDotFeatures.h>
#include <shogun/classifier/vw/vw_common.h>
#include <shogun/classifier/vw/vw_math.h>
namespace shogun
{
/** @brief This class implements streaming features for use with VW.
*
* Each example is stored in a VwExample object, which also
* contains label and other information.
* Features are hashed and are supposed to be used with a weight
* vector of preallocated dimensions.
*/
class CStreamingVwFeatures : public CStreamingDotFeatures
{
public:
/**
* Default constructor.
*
* Sets the reading functions to be
* CStreamingFile::get_*_vector and get_*_vector_and_label
* depending on the type T.
*/
CStreamingVwFeatures();
/**
* Constructor taking args.
* Initializes the parser with the given args.
*
* @param file StreamingFile object, input file.
* @param is_labelled Whether examples are labelled or not.
* @param size Number of example objects to be stored in the parser at a time.
*/
CStreamingVwFeatures(CStreamingVwFile* file,
bool is_labelled, int32_t size);
/**
* Constructor used when initialized
* with a cache file.
*
* @param file StreamingVwCacheFile object
* @param is_labelled Whether examples are labelled or not
* @param size Number of example objects to be stored in the parser at a time
*/
CStreamingVwFeatures(CStreamingVwCacheFile* file,
bool is_labelled, int32_t size);
/**
* Destructor.
*
* Ends the parsing thread. (Waits for pthread_join to complete)
*/
~CStreamingVwFeatures();
/**
* Duplicate this object
*
* @return a copy of this object
*/
CFeatures* duplicate() const;
/**
* Sets the read function (in case the examples are
* unlabelled) to get_*_vector() from CStreamingFile.
*
* The exact function depends on type T.
*
* The parser uses the function set by this while reading
* unlabelled examples.
*/
virtual void set_vector_reader();
/**
* Sets the read function (in case the examples are labelled)
* to get_*_vector_and_label from CStreamingFile.
*
* The exact function depends on type T.
*
* The parser uses the function set by this while reading
* labelled examples.
*/
virtual void set_vector_and_label_reader();
/**
* Starts the parsing thread.
*
* To be called before trying to use any feature vectors from this object.
*/
virtual void start_parser();
/**
* Ends the parsing thread.
*
* Waits for the thread to join.
*/
virtual void end_parser();
/**
* Reset the file back to the first example.
* Only works for cache files.
*/
virtual void reset_stream();
/**
* Get the environment
* @return environment
*/
virtual CVwEnvironment* get_env();
/**
* Set the environment
*
* @param vw_env environment
*/
virtual void set_env(CVwEnvironment* vw_env);
/**
* Instructs the parser to return the next example.
*
* This example is stored as the current_example in this object.
*
* @return True on success, false if there are no more
* examples, or an error occurred.
*/
virtual bool get_next_example();
/**
* Returns the current example.
*
* @return current example as VwExample*
*/
virtual VwExample* get_example();
/**
* Return the label of the current example as a float.
*
* Examples must be labelled, otherwise an error occurs.
*
* @return The label as a float64_t.
*/
virtual float64_t get_label();
/**
* Release the current example, indicating to the parser that
* it has been processed by the learning algorithm.
*
* The parser is then free to throw away that example.
*/
virtual void release_example();
/**
* Expand the vector passed so that it its length is equal to
* the dimensionality of the features. The previous values are
* kept intact through realloc, and the new ones are set to zero.
*
* @param vec float32_t* vector
* @param len length of the vector
*/
virtual void expand_if_required(float32_t*& vec, int32_t& len);
/**
* Expand the vector passed so that it its length is equal to
* the dimensionality of the features. The previous values are
* kept intact through realloc, and the new ones are set to zero.
*
* @param vec float64_t* vector
* @param len length of the vector
*/
virtual void expand_if_required(float64_t*& vec, int32_t& len);
/** obtain the dimensionality of the feature space
*
* (not mix this up with the dimensionality of the input space, usually
* obtained via get_num_features())
*
* @return dimensionality
*/
virtual int32_t get_dim_feature_space() const;
/**
* Reduce element 'w' to max(w-gravity, 0)
*
* @param w value to truncate
* @param gravity value to truncate using
*
* @return truncated value
*/
virtual float32_t real_weight(float32_t w, float32_t gravity);
/**
* Dot product taken with another StreamingDotFeatures object.
*
* Currently only works if it is a CStreamingVwFeatures object.
* It takes the dot product of the current_vectors of both objects.
*
* @param df CStreamingDotFeatures object.
*
* @return Dot product.
*/
virtual float32_t dot(CStreamingDotFeatures *df);
/**
* Dot product of an example with a vector
*
* @param ex example, as VwExample
* @param vec2 vector to take dot product with
*
* @return dot product
*/
virtual float32_t dense_dot(VwExample* &ex, const float32_t* vec2);
/**
* Dot product of current feature vector with a dense vector
* which stores weights in hashed indices
*
* @param vec2 dense weight vector
* @param vec2_len length of weight vector (not used)
*
* @return dot product
*/
virtual float32_t dense_dot(const float32_t* vec2, int32_t vec2_len);
/**
* Dot product between a dense weight vector and a sparse feature vector.
* Assumes the features to belong to the constant namespace.
*
* @param vec1 sparse feature vector
* @param vec2 weight vector
*
* @return dot product between dense weights and a sparse feature vector
*/
virtual float32_t dense_dot(SGSparseVector<float32_t>* vec1, const float32_t* vec2);
/**
* Calculate dot product of features with another vector, truncating the elements
* of that vector by magnitude 'gravity' to a minimum final magnitude of zero.
*
* @param vec2 vector to take dot product with
* @param ex example whose features have to be taken
* @param gravity value to use for truncating
*
* @return dot product
*/
virtual float32_t dense_dot_truncated(const float32_t* vec2, VwExample* &ex, float32_t gravity);
/**
* Add alpha*an example's feature vector to another dense vector.
* Takes the absolute value of current_vector if specified
*
* @param alpha alpha
* @param ex example whose vector should be used
* @param vec2 vector to add to
* @param vec2_len length of vector
* @param abs_val true if abs of example's vector should be taken
*/
virtual void add_to_dense_vec(float32_t alpha, VwExample* &ex,
float32_t* vec2, int32_t vec2_len, bool abs_val = false);
/**
* Add alpha*current_vector to another dense vector.
* Takes the absolute value of current_vector if specified
*
* @param alpha alpha
* @param vec2 vector to add to
* @param vec2_len length of vector
* @param abs_val true if abs of current_vector should be taken
*/
virtual void add_to_dense_vec(float32_t alpha,
float32_t* vec2, int32_t vec2_len, bool abs_val = false);
/** get number of non-zero features in vector
*
* @return number of non-zero features in vector
*/
virtual int32_t get_nnz_features_for_vector();
/**
* Return the number of features in the current example.
*
* @return number of features as int
*/
virtual int32_t get_num_features();
/**
* Return the feature type, depending on T.
*
* @return Feature type as EFeatureType
*/
virtual EFeatureType get_feature_type() const;
/**
* Return the feature class
*
* @return C_STREAMING_VW
*/
virtual EFeatureClass get_feature_class() const;
/**
* Return the name.
*
* @return StreamingVwFeatures
*/
virtual const char* get_name() const { return "StreamingVwFeatures"; }
/**
* Return the number of vectors stored in this object.
*
* @return 1 if current_example exists, else 0.
*/
virtual int32_t get_num_vectors() const;
private:
/**
* Initializes members to null values.
* current_length is set to -1.
*/
virtual void init();
/**
* Calls init, and also initializes the parser with the given args.
*
* @param file StreamingFile to read from
* @param is_labelled whether labelled or not
* @param size number of examples in the parser's ring
*/
virtual void init(CStreamingVwFile *file, bool is_labelled, int32_t size);
/**
* Init function when input is from a cache file
*
* @param file StreamingVwCacheFile to read from
* @param is_labelled whether labelled or not
* @param size number of examples in the parser's ring
*/
virtual void init(CStreamingVwCacheFile *file, bool is_labelled, int32_t size);
/**
* Setup the example obtained from the parser so it
* can be directly updated by the learner.
*
* @param ae example object
*/
virtual void setup_example(VwExample* ae);
protected:
/// The parser object, which reads from input and returns parsed example objects.
CInputParser<VwExample> parser;
/// Number of examples processed at a point of time
vw_size_t example_count;
/// The current example's label.
float64_t current_label;
/// Number of features in current example.
int32_t current_length;
/// Environment for VW
CVwEnvironment* env;
/// Example currently being processed
VwExample* current_example;
};
}
#endif // _STREAMING_VWFEATURES__H__
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