HashedWDFeaturesTransposed.cpp

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/*
 * 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) 2010 Soeren Sonnenburg
 * Copyright (C) 2010 Berlin Institute of Technology
 */

#include <shogun/features/hashed/HashedWDFeaturesTransposed.h>
#include <shogun/io/SGIO.h>
#include <shogun/lib/Signal.h>
#include <shogun/base/Parallel.h>

#ifdef HAVE_PTHREAD
#include <pthread.h>
#endif

using namespace shogun;

#ifndef DOXYGEN_SHOULD_SKIP_THIS
struct HASHEDWD_THREAD_PARAM
{
    CHashedWDFeaturesTransposed* hf;
    int32_t* sub_index;
    float64_t* output;
    int32_t start;
    int32_t stop;
    float64_t* alphas;
    float64_t* vec;
    float64_t bias;
    bool progress;
    uint32_t* index;
};
#endif // DOXYGEN_SHOULD_SKIP_THIS

CHashedWDFeaturesTransposed::CHashedWDFeaturesTransposed()
    :CDotFeatures()
{
    SG_UNSTABLE(
        "CHashedWDFeaturesTransposed::CHashedWDFeaturesTransposed()",
        "\n");

    strings = NULL;
    transposed_strings = NULL;

    degree = 0;
    start_degree = 0;
    from_degree = 0;
    string_length = 0;
    num_strings = 0;
    alphabet_size = 0;
    w_dim = 0;
    partial_w_dim = 0;
    wd_weights = NULL;
    mask = 0;
    m_hash_bits = 0;

    normalization_const = 0.0;
}

CHashedWDFeaturesTransposed::CHashedWDFeaturesTransposed(CStringFeatures<uint8_t>* str,
        int32_t start_order, int32_t order, int32_t from_order,
        int32_t hash_bits) : CDotFeatures()
{
    ASSERT(start_order>=0)
    ASSERT(start_order<order)
    ASSERT(order<=from_order)
    ASSERT(hash_bits>0)
    ASSERT(str)
    ASSERT(str->have_same_length())
    SG_REF(str);

    strings=str;
    int32_t transposed_num_feat=0;
    int32_t transposed_num_vec=0;
    transposed_strings=str->get_transposed(transposed_num_feat, transposed_num_vec);

    string_length=str->get_max_vector_length();
    num_strings=str->get_num_vectors();
    ASSERT(transposed_num_feat==num_strings)
    ASSERT(transposed_num_vec==string_length)

    CAlphabet* alpha=str->get_alphabet();
    alphabet_size=alpha->get_num_symbols();
    SG_UNREF(alpha);

    degree=order;
    start_degree=start_order;
    if (start_degree!=0)
        SG_NOTIMPLEMENTED
    from_degree=from_order;
    m_hash_bits=hash_bits;
    set_wd_weights();
    set_normalization_const();
}

CHashedWDFeaturesTransposed::CHashedWDFeaturesTransposed(const CHashedWDFeaturesTransposed& orig)
    : CDotFeatures(orig), strings(orig.strings), transposed_strings(orig.transposed_strings),
    degree(orig.degree), start_degree(orig.start_degree),
    from_degree(orig.from_degree), m_hash_bits(orig.m_hash_bits),
    normalization_const(orig.normalization_const)
{
    SG_REF(strings);
    string_length=strings->get_max_vector_length();
    num_strings=strings->get_num_vectors();
    CAlphabet* alpha=strings->get_alphabet();
    alphabet_size=alpha->get_num_symbols();
    SG_UNREF(alpha);

    set_wd_weights();
}

CHashedWDFeaturesTransposed::~CHashedWDFeaturesTransposed()
{
    for (int32_t i=0; i<string_length; i++)
        SG_FREE(transposed_strings[i].string);
    SG_FREE(transposed_strings);

    SG_UNREF(strings);
    SG_FREE(wd_weights);
}

float64_t CHashedWDFeaturesTransposed::dot(int32_t vec_idx1, CDotFeatures* df, int32_t vec_idx2)
{
    ASSERT(df)
    ASSERT(df->get_feature_type() == get_feature_type())
    ASSERT(df->get_feature_class() == get_feature_class())
    CHashedWDFeaturesTransposed* wdf = (CHashedWDFeaturesTransposed*) df;

    int32_t len1, len2;
    bool free_vec1, free_vec2;

    uint8_t* vec1=strings->get_feature_vector(vec_idx1, len1, free_vec1);
    uint8_t* vec2=wdf->strings->get_feature_vector(vec_idx2, len2, free_vec2);

    ASSERT(len1==len2)

    float64_t sum=0.0;

    for (int32_t i=0; i<len1; i++)
    {
        for (int32_t j=0; (i+j<len1) && (j<degree); j++)
        {
            if (vec1[i+j]!=vec2[i+j])
                break;
            if (j>=start_degree)
                sum += wd_weights[j]*wd_weights[j];
        }
    }
    strings->free_feature_vector(vec1, vec_idx1, free_vec1);
    wdf->strings->free_feature_vector(vec2, vec_idx2, free_vec2);
    return sum/CMath::sq(normalization_const);
}

float64_t CHashedWDFeaturesTransposed::dense_dot(int32_t vec_idx1, const float64_t* vec2, int32_t vec2_len)
{
    if (vec2_len != w_dim)
        SG_ERROR("Dimensions don't match, vec2_dim=%d, w_dim=%d\n", vec2_len, w_dim)

    float64_t sum=0;
    int32_t len;
    bool free_vec1;
    uint8_t* vec = strings->get_feature_vector(vec_idx1, len, free_vec1);
    uint32_t* val=SG_MALLOC(uint32_t, len);

    uint32_t offs=0;

    SGVector<uint32_t>::fill_vector(val, len, 0xDEADBEAF);

    for (int32_t i=0; i < len; i++)
    {
        uint32_t o=offs;
        uint32_t carry = 0;
        uint32_t chunk = 0;

        for (int32_t k=0; k<degree && i+k<len; k++)
        {
            const float64_t wd = wd_weights[k];
            chunk++;
            CHash::IncrementalMurmurHash3(&(val[i]), &carry, &(vec[i+k]), 1);
            uint32_t h =
                    CHash::FinalizeIncrementalMurmurHash3(val[i], carry, chunk);
#ifdef DEBUG_HASHEDWD
            SG_PRINT("vec[i]=%d, k=%d, offs=%d o=%d h=%d \n", vec[i], k,offs, o, h)
#endif
            sum+=vec2[o+(h & mask)]*wd;
            o+=partial_w_dim;
        }
        val[i] = CHash::FinalizeIncrementalMurmurHash3(val[i], carry, chunk);
        offs+=partial_w_dim*degree;
    }
    SG_FREE(val);
    strings->free_feature_vector(vec, vec_idx1, free_vec1);

    return sum/normalization_const;
}

void CHashedWDFeaturesTransposed::dense_dot_range(float64_t* output, int32_t start, int32_t stop, float64_t* alphas, float64_t* vec, int32_t dim, float64_t b)
{
    ASSERT(output)
    // write access is internally between output[start..stop] so the following
    // line is necessary to write to output[0...(stop-start-1)]
    output-=start;
    ASSERT(start>=0)
    ASSERT(start<stop)
    ASSERT(stop<=get_num_vectors())
    uint32_t* index=SG_MALLOC(uint32_t, stop);

    int32_t num_vectors=stop-start;
    ASSERT(num_vectors>0)

    int32_t num_threads=parallel->get_num_threads();
    ASSERT(num_threads>0)

    CSignal::clear_cancel();

    if (dim != w_dim)
        SG_ERROR("Dimensions don't match, vec_len=%d, w_dim=%d\n", dim, w_dim)

#ifdef HAVE_PTHREAD
    if (num_threads < 2)
    {
#endif
        HASHEDWD_THREAD_PARAM params;
        params.hf=this;
        params.sub_index=NULL;
        params.output=output;
        params.start=start;
        params.stop=stop;
        params.alphas=alphas;
        params.vec=vec;
        params.bias=b;
        params.progress=false; //true;
        params.index=index;
        dense_dot_range_helper((void*) &params);
#ifdef HAVE_PTHREAD
    }
    else
    {
        pthread_t* threads = SG_MALLOC(pthread_t, num_threads-1);
        HASHEDWD_THREAD_PARAM* params = SG_MALLOC(HASHEDWD_THREAD_PARAM, num_threads);
        int32_t step= num_vectors/num_threads;

        int32_t t;

        for (t=0; t<num_threads-1; t++)
        {
            params[t].hf = this;
            params[t].sub_index=NULL;
            params[t].output = output;
            params[t].start = start+t*step;
            params[t].stop = start+(t+1)*step;
            params[t].alphas=alphas;
            params[t].vec=vec;
            params[t].bias=b;
            params[t].progress = false;
            params[t].index=index;
            pthread_create(&threads[t], NULL,
                    CHashedWDFeaturesTransposed::dense_dot_range_helper, (void*)&params[t]);
        }

        params[t].hf = this;
        params[t].sub_index=NULL;
        params[t].output = output;
        params[t].start = start+t*step;
        params[t].stop = stop;
        params[t].alphas=alphas;
        params[t].vec=vec;
        params[t].bias=b;
        params[t].progress = false; //true;
        params[t].index=index;
        CHashedWDFeaturesTransposed::dense_dot_range_helper((void*) &params[t]);

        for (t=0; t<num_threads-1; t++)
            pthread_join(threads[t], NULL);

        SG_FREE(params);
        SG_FREE(threads);
    }
#endif
    SG_FREE(index);

#ifndef WIN32
        if ( CSignal::cancel_computations() )
            SG_INFO("prematurely stopped.           \n")
#endif
}

void CHashedWDFeaturesTransposed::dense_dot_range_subset(int32_t* sub_index, int num, float64_t* output, float64_t* alphas, float64_t* vec, int32_t dim, float64_t b)
{
    ASSERT(sub_index)
    ASSERT(output)

    uint32_t* index=SG_MALLOC(uint32_t, num);

    int32_t num_threads=parallel->get_num_threads();
    ASSERT(num_threads>0)

    CSignal::clear_cancel();

    if (dim != w_dim)
        SG_ERROR("Dimensions don't match, vec_len=%d, w_dim=%d\n", dim, w_dim)

#ifdef HAVE_PTHREAD
    if (num_threads < 2)
    {
#endif
        HASHEDWD_THREAD_PARAM params;
        params.hf=this;
        params.sub_index=sub_index;
        params.output=output;
        params.start=0;
        params.stop=num;
        params.alphas=alphas;
        params.vec=vec;
        params.bias=b;
        params.progress=false; //true;
        params.index=index;
        dense_dot_range_helper((void*) &params);
#ifdef HAVE_PTHREAD
    }
    else
    {
        pthread_t* threads = SG_MALLOC(pthread_t, num_threads-1);
        HASHEDWD_THREAD_PARAM* params = SG_MALLOC(HASHEDWD_THREAD_PARAM, num_threads);
        int32_t step= num/num_threads;

        int32_t t;

        for (t=0; t<num_threads-1; t++)
        {
            params[t].hf = this;
            params[t].sub_index=sub_index;
            params[t].output = output;
            params[t].start = t*step;
            params[t].stop = (t+1)*step;
            params[t].alphas=alphas;
            params[t].vec=vec;
            params[t].bias=b;
            params[t].progress = false;
            params[t].index=index;
            pthread_create(&threads[t], NULL,
                    CHashedWDFeaturesTransposed::dense_dot_range_helper, (void*)&params[t]);
        }

        params[t].hf = this;
        params[t].sub_index=sub_index;
        params[t].output = output;
        params[t].start = t*step;
        params[t].stop = num;
        params[t].alphas=alphas;
        params[t].vec=vec;
        params[t].bias=b;
        params[t].progress = false; //true;
        params[t].index=index;
        CHashedWDFeaturesTransposed::dense_dot_range_helper((void*) &params[t]);

        for (t=0; t<num_threads-1; t++)
            pthread_join(threads[t], NULL);

        SG_FREE(params);
        SG_FREE(threads);
        SG_FREE(index);
    }
#endif

#ifndef WIN32
        if ( CSignal::cancel_computations() )
            SG_INFO("prematurely stopped.           \n")
#endif
}

void* CHashedWDFeaturesTransposed::dense_dot_range_helper(void* p)
{
    HASHEDWD_THREAD_PARAM* par=(HASHEDWD_THREAD_PARAM*) p;
    CHashedWDFeaturesTransposed* hf=par->hf;
    int32_t* sub_index=par->sub_index;
    float64_t* output=par->output;
    int32_t start=par->start;
    int32_t stop=par->stop;
    float64_t* alphas=par->alphas;
    float64_t* vec=par->vec;
    float64_t bias=par->bias;
    bool progress=par->progress;
    uint32_t* index=par->index;
    int32_t string_length=hf->string_length;
    int32_t degree=hf->degree;
    float64_t* wd_weights=hf->wd_weights;
    SGString<uint8_t>* transposed_strings=hf->transposed_strings;
    uint32_t mask=hf->mask;
    int32_t partial_w_dim=hf->partial_w_dim;
    float64_t normalization_const=hf->normalization_const;

    if (sub_index)
    {
        for (int32_t j=start; j<stop; j++)
            output[j]=0.0;

        uint32_t offs=0;
        for (int32_t i=0; i<string_length; i++)
        {
            uint32_t o=offs;
            for (int32_t k=0; k<degree && i+k<string_length; k++)
            {
                const float64_t wd = wd_weights[k];
                uint8_t* dim=transposed_strings[i+k].string;
                uint32_t carry = 0;
                uint32_t chunk = 0;
                for (int32_t j=start; j<stop; j++)
                {
                    uint8_t bval=dim[sub_index[j]];
                    if (k==0)
                        index[j] = 0xDEADBEAF;

                    CHash::IncrementalMurmurHash3(&index[j], &carry, &bval, 1);

                    chunk++;
                    uint32_t h =
                            CHash::FinalizeIncrementalMurmurHash3(
                                    index[j], carry, chunk);

                    output[j]+=vec[o + (h & mask)]*wd;
                    index[j] = h;
                }

                index[stop-1] =
                        CHash::FinalizeIncrementalMurmurHash3(
                                index[stop-1], carry, chunk);

                o+=partial_w_dim;
            }
            offs+=partial_w_dim*degree;

            if (progress)
                hf->io->progress(i, 0,string_length, i);
        }

        for (int32_t j=start; j<stop; j++)
        {
            if (alphas)
                output[j]=output[j]*alphas[sub_index[j]]/normalization_const+bias;
            else
                output[j]=output[j]/normalization_const+bias;
        }
    }
    else
    {
        SGVector<float64_t>::fill_vector(&output[start], stop-start, 0.0);

        uint32_t offs=0;
        for (int32_t i=0; i<string_length; i++)
        {
            uint32_t o=offs;
            for (int32_t k=0; k<degree && i+k<string_length; k++)
            {
                const float64_t wd = wd_weights[k];
                uint8_t* dim=transposed_strings[i+k].string;
                uint32_t carry = 0;
                uint32_t chunk = 0;

                for (int32_t j=start; j<stop; j++)
                {
                    uint8_t bval=dim[sub_index[j]];
                    if (k==0)
                        index[j] = 0xDEADBEAF;

                    CHash::IncrementalMurmurHash3(&index[j], &carry, &bval, 1);

                    chunk++;
                    uint32_t h =
                            CHash::FinalizeIncrementalMurmurHash3(
                                    index[j], carry, chunk);

                    index[j] = h;
                    output[j]+=vec[o + (h & mask)]*wd;
                }

                index[stop-1] = CHash::FinalizeIncrementalMurmurHash3(
                        index[stop-1], carry, chunk);

                o+=partial_w_dim;
            }
            offs+=partial_w_dim*degree;

            if (progress)
                hf->io->progress(i, 0,string_length, i);
        }

        for (int32_t j=start; j<stop; j++)
        {
            if (alphas)
                output[j]=output[j]*alphas[j]/normalization_const+bias;
            else
                output[j]=output[j]/normalization_const+bias;
        }
    }

    return NULL;
}

void CHashedWDFeaturesTransposed::add_to_dense_vec(float64_t alpha, int32_t vec_idx1, float64_t* vec2, int32_t vec2_len, bool abs_val)
{
    if (vec2_len != w_dim)
        SG_ERROR("Dimensions don't match, vec2_dim=%d, w_dim=%d\n", vec2_len, w_dim)

    int32_t len;
    bool free_vec1;
    uint8_t* vec = strings->get_feature_vector(vec_idx1, len, free_vec1);
    uint32_t* val=SG_MALLOC(uint32_t, len);

    uint32_t offs=0;
    float64_t factor=alpha/normalization_const;
    if (abs_val)
        factor=CMath::abs(factor);

    SGVector<uint32_t>::fill_vector(val, len, 0xDEADBEAF);

    for (int32_t i=0; i<len; i++)
    {
        uint32_t o=offs;
        uint32_t carry = 0;
        uint32_t chunk = 0;

        for (int32_t k=0; k<degree && i+k<len; k++)
        {
            float64_t wd = wd_weights[k]*factor;
            chunk++;
            CHash::IncrementalMurmurHash3(&(val[i]), &carry, &(vec[i+k]), 1);
            uint32_t h =
                    CHash::FinalizeIncrementalMurmurHash3(val[i], carry, chunk);
#ifdef DEBUG_HASHEDWD
            SG_PRINT("offs=%d o=%d h=%d \n", offs, o, h)
            SG_PRINT("vec[i]=%d, k=%d, offs=%d o=%d\n", vec[i], k,offs, o)
#endif
            vec2[o+(h & mask)]+=wd;
            val[i] = h;
            o+=partial_w_dim;
        }

        val[i] = CHash::FinalizeIncrementalMurmurHash3(val[i], carry, chunk);
        offs+=partial_w_dim*degree;
    }

    SG_FREE(val);
    strings->free_feature_vector(vec, vec_idx1, free_vec1);
}

void CHashedWDFeaturesTransposed::set_wd_weights()
{
    ASSERT(degree>0)

    mask=(uint32_t) (((uint64_t) 1)<<m_hash_bits)-1;
    partial_w_dim=1<<m_hash_bits;
    w_dim=partial_w_dim*string_length*(degree-start_degree);

    wd_weights=SG_MALLOC(float64_t, degree);

    for (int32_t i=0; i<degree; i++)
        wd_weights[i]=sqrt(2.0*(from_degree-i)/(from_degree*(from_degree+1)));

    SG_DEBUG("created HashedWDFeaturesTransposed with d=%d (%d), alphabetsize=%d, "
            "dim=%d partial_dim=%d num=%d, len=%d\n",
            degree, from_degree, alphabet_size,
            w_dim, partial_w_dim, num_strings, string_length);
}


void CHashedWDFeaturesTransposed::set_normalization_const(float64_t n)
{
    if (n==0)
    {
        normalization_const=0;
        for (int32_t i=0; i<degree; i++)
            normalization_const+=(string_length-i)*wd_weights[i]*wd_weights[i];

        normalization_const=CMath::sqrt(normalization_const);
    }
    else
        normalization_const=n;

    SG_DEBUG("normalization_const:%f\n", normalization_const)
}

CFeatures* CHashedWDFeaturesTransposed::duplicate() const
{
    return new CHashedWDFeaturesTransposed(*this);
}

void* CHashedWDFeaturesTransposed::get_feature_iterator(int32_t vector_index)
{
    SG_NOTIMPLEMENTED
    return NULL;
}

bool CHashedWDFeaturesTransposed::get_next_feature(int32_t& index, float64_t& value, void* iterator)
{
    SG_NOTIMPLEMENTED
    return false;
}

void CHashedWDFeaturesTransposed::free_feature_iterator(void* iterator)
{
    SG_NOTIMPLEMENTED
}