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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
*/
#include <fstream>
#include <iostream>
using namespace std;
#include <unistd.h>
#include <stdlib.h>
#include <stdint.h>
#include "parse_regressor.h"
#include "loss_functions.h"
#include "global_data.h"
#include "io.h"
void initialize_regressor(regressor &r)
{
size_t length = ((size_t)1) << global.num_bits;
global.thread_mask = (global.stride * (length >> global.thread_bits)) - 1;
size_t num_threads = global.num_threads();
r.weight_vectors = (weight **)malloc(num_threads * sizeof(weight*));
for (size_t i = 0; i < num_threads; i++)
{
r.weight_vectors[i] = (weight *)calloc(global.stride*length/num_threads, sizeof(weight));
if (r.weight_vectors[i] == NULL)
{
cerr << global.program_name << ": Failed to allocate weight array: try decreasing -b <bits>" << endl;
exit (1);
}
if (global.initial_weight != 0.)
for (size_t j = 0; j < global.stride*length/num_threads; j+=global.stride)
r.weight_vectors[i][j] = global.initial_weight;
if(global.adaptive)
for (size_t j = 1; j < global.stride*length/num_threads; j+=global.stride)
r.weight_vectors[i][j] = 1;
}
}
void parse_regressor_args(po::variables_map& vm, regressor& r, string& final_regressor_name, bool quiet)
{
if (vm.count("final_regressor")) {
final_regressor_name = vm["final_regressor"].as<string>();
if (!quiet)
cerr << "final_regressor = " << vm["final_regressor"].as<string>() << endl;
}
else
final_regressor_name = "";
vector<string> regs;
if (vm.count("initial_regressor"))
regs = vm["initial_regressor"].as< vector<string> >();
/*
Read in regressors. If multiple regressors are specified, do a weighted
average. If none are specified, initialize according to global_seg &
numbits.
*/
bool initialized = false;
for (size_t i = 0; i < regs.size(); i++)
{
ifstream regressor(regs[i].c_str());
if (!regressor.is_open())
{
cout << "can't open " << regs[i].c_str() << endl << " ... exiting." << endl;
exit(1);
}
size_t v_length;
regressor.read((char*)&v_length, sizeof(v_length));
char t[v_length];
regressor.read(t,v_length);
if (strcmp(t,version.c_str()) != 0)
{
cout << "regressor has possibly incompatible version!" << endl;
exit(1);
}
regressor.read((char*)&global.min_label, sizeof(global.min_label));
regressor.read((char*)&global.max_label, sizeof(global.max_label));
size_t local_num_bits;
regressor.read((char *)&local_num_bits, sizeof(local_num_bits));
if (!initialized){
global.num_bits = local_num_bits;
}
else
if (local_num_bits != global.num_bits)
{
cout << "can't combine regressors with different feature number!" << endl;
exit (1);
}
size_t local_thread_bits;
regressor.read((char*)&local_thread_bits, sizeof(local_thread_bits));
if (!initialized){
global.thread_bits = local_thread_bits;
global.partition_bits = global.thread_bits;
}
else
if (local_thread_bits != global.thread_bits)
{
cout << "can't combine regressors trained with different numbers of threads!" << endl;
exit (1);
}
int len;
regressor.read((char *)&len, sizeof(len));
vector<string> local_pairs;
for (; len > 0; len--)
{
char pair[2];
regressor.read(pair, sizeof(char)*2);
string temp(pair, 2);
local_pairs.push_back(temp);
}
if (!initialized)
{
global.pairs = local_pairs;
initialize_regressor(r);
}
else
if (local_pairs != global.pairs)
{
cout << "can't combine regressors with different features!" << endl;
for (size_t i = 0; i < local_pairs.size(); i++)
cout << local_pairs[i] << " " << local_pairs[i].size() << " ";
cout << endl;
for (size_t i = 0; i < global.pairs.size(); i++)
cout << global.pairs[i] << " " << global.pairs[i].size() << " ";
cout << endl;
exit (1);
}
size_t local_ngram;
regressor.read((char*)&local_ngram, sizeof(local_ngram));
size_t local_skips;
regressor.read((char*)&local_skips, sizeof(local_skips));
if (!initialized)
{
global.ngram = local_ngram;
global.skips = local_skips;
initialized = true;
}
else
if (global.ngram != local_ngram || global.skips != local_skips)
{
cout << "can't combine regressors with different ngram features!" << endl;
exit(1);
}
size_t stride = global.stride;
while (regressor.good())
{
uint32_t hash;
regressor.read((char *)&hash, sizeof(hash));
weight w = 0.;
regressor.read((char *)&w, sizeof(float));
size_t num_threads = global.num_threads();
if (regressor.good())
r.weight_vectors[hash % num_threads][(hash*stride)/num_threads]
= r.weight_vectors[hash % num_threads][(hash*stride)/num_threads] + w;
}
regressor.close();
}
if (!initialized)
{
if(vm.count("noop") || vm.count("sendto"))
r.weight_vectors = NULL;
else
initialize_regressor(r);
}
}
void free_regressor(regressor &r)
{
if (r.weight_vectors != NULL)
{
for (size_t i = 0; i < global.num_threads(); i++)
if (r.weight_vectors[i] != NULL)
free(r.weight_vectors[i]);
free(r.weight_vectors);
}
}
void dump_regressor(string reg_name, regressor &r)
{
if (reg_name == string(""))
return;
string start_name = reg_name+string(".writing");
io_buf io_temp;
int f = io_temp.open_file(start_name.c_str(),io_buf::WRITE);
if (f<0)
{
cout << "can't open: " << start_name << " for writing, exiting" << endl;
exit(1);
}
size_t v_length = version.length()+1;
io_temp.write_file(f,(char*)&v_length, sizeof(v_length));
io_temp.write_file(f,version.c_str(),v_length);
io_temp.write_file(f,(char*)&global.min_label, sizeof(global.min_label));
io_temp.write_file(f,(char*)&global.max_label, sizeof(global.max_label));
io_temp.write_file(f,(char *)&global.num_bits, sizeof(global.num_bits));
io_temp.write_file(f,(char *)&global.thread_bits, sizeof(global.thread_bits));
int len = global.pairs.size();
io_temp.write_file(f,(char *)&len, sizeof(len));
for (vector<string>::iterator i = global.pairs.begin(); i != global.pairs.end();i++)
io_temp.write_file(f,i->c_str(),2);
io_temp.write_file(f,(char*)&global.ngram, sizeof(global.ngram));
io_temp.write_file(f,(char*)&global.skips, sizeof(global.skips));
uint32_t length = 1 << global.num_bits;
size_t num_threads = global.num_threads();
size_t stride = global.stride;
for(uint32_t i = 0; i < length; i++)
{
weight v = r.weight_vectors[i%num_threads][stride*i/num_threads];
if (v != 0.)
{
io_temp.write_file(f,(char *)&i, sizeof (i));
io_temp.write_file(f,(char *)&v, sizeof (v));
}
}
rename(start_name.c_str(),reg_name.c_str());
io_temp.close_file();
}
void finalize_regressor(string reg_name, regressor &r)
{
dump_regressor(reg_name,r);
free_regressor(r);
}
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