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interact.cc
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interact.cc
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// Copyright (c) by respective owners including Yahoo!, Microsoft, and
// individual contributors. All rights reserved. Released under a BSD (revised)
// license as described in the file LICENSE.
#include "vw/core/reductions/interact.h"
#include "vw/config/options.h"
#include "vw/core/global_data.h"
#include "vw/core/learner.h"
#include "vw/core/setup_base.h"
#include "vw/io/logger.h"
#include <cfloat>
#include <sstream>
using namespace VW::config;
namespace
{
class interact
{
public:
// namespaces to interact
unsigned char n1 = static_cast<unsigned char>(0);
unsigned char n2 = static_cast<unsigned char>(0);
VW::features feat_store;
VW::workspace* all = nullptr;
float n1_feat_sq = 0.f;
size_t num_features = 0;
};
bool contains_valid_namespaces(VW::features& f_src1, VW::features& f_src2, interact& in, VW::io::logger& logger)
{
// first feature must be 1 so we're sure that the anchor feature is present
if (f_src1.size() == 0 || f_src2.size() == 0) { return false; }
if (f_src1.values[0] != 1)
{
// Anchor feature must be a number instead of text so that the relative offsets functions correctly but I don't
// think we are able to test for this here.
logger.err_error("Namespace '{}' misses anchor feature with value 1", static_cast<char>(in.n1));
return false;
}
if (f_src2.values[0] != 1)
{
logger.err_error("Namespace '{}' misses anchor feature with value 1", static_cast<char>(in.n2));
return false;
}
return true;
}
void multiply(VW::features& f_dest, VW::features& f_src2, interact& in)
{
f_dest.clear();
VW::features& f_src1 = in.feat_store;
VW::workspace* all = in.all;
uint64_t weight_mask = all->weights.mask();
uint64_t base_id1 = f_src1.indices[0] & weight_mask;
uint64_t base_id2 = f_src2.indices[0] & weight_mask;
f_dest.push_back(f_src1.values[0] * f_src2.values[0], f_src1.indices[0]);
uint64_t prev_id1 = 0;
uint64_t prev_id2 = 0;
for (size_t i1 = 1, i2 = 1; i1 < f_src1.size() && i2 < f_src2.size();)
{
// calculating the relative offset from the namespace offset used to match features
uint64_t cur_id1 = static_cast<uint64_t>(((f_src1.indices[i1] & weight_mask) - base_id1) & weight_mask);
uint64_t cur_id2 = static_cast<uint64_t>(((f_src2.indices[i2] & weight_mask) - base_id2) & weight_mask);
// checking for sorting requirement
if (cur_id1 < prev_id1)
{
in.all->logger.out_error("interact features are out of order: {0} < {1}. Skipping features.", cur_id1, prev_id1);
return;
}
if (cur_id2 < prev_id2)
{
in.all->logger.out_error("interact features are out of order: {0} < {1}. Skipping features.", cur_id2, prev_id2);
return;
}
if (cur_id1 == cur_id2)
{
f_dest.push_back(f_src1.values[i1] * f_src2.values[i2], f_src1.indices[i1]);
i1++;
i2++;
}
else if (cur_id1 < cur_id2) { i1++; }
else { i2++; }
prev_id1 = cur_id1;
prev_id2 = cur_id2;
}
}
template <bool is_learn, bool print_all>
void predict_or_learn(interact& in, VW::LEARNER::learner& base, VW::example& ec)
{
VW::features& f1 = ec.feature_space[in.n1];
VW::features& f2 = ec.feature_space[in.n2];
if (!contains_valid_namespaces(f1, f2, in, in.all->logger))
{
if (is_learn) { base.learn(ec); }
else { base.predict(ec); }
return;
}
in.num_features = ec.num_features;
ec.num_features -= f1.size();
ec.num_features -= f2.size();
in.feat_store = f1;
multiply(f1, f2, in);
ec.reset_total_sum_feat_sq();
ec.num_features += f1.size();
// remove 2nd namespace
size_t n2_i = 0;
size_t indices_original_size = ec.indices.size();
for (; n2_i < indices_original_size; ++n2_i)
{
if (ec.indices[n2_i] == in.n2)
{
ec.indices.erase(ec.indices.begin() + n2_i);
break;
}
}
base.predict(ec);
if (is_learn) { base.learn(ec); }
// re-insert namespace into the right position
if (n2_i < indices_original_size) { ec.indices.insert(ec.indices.begin() + n2_i, in.n2); }
f1 = in.feat_store;
ec.num_features = in.num_features;
}
} // namespace
std::shared_ptr<VW::LEARNER::learner> VW::reductions::interact_setup(VW::setup_base_i& stack_builder)
{
options_i& options = *stack_builder.get_options();
VW::workspace& all = *stack_builder.get_all_pointer();
std::string s;
option_group_definition new_options("[Reduction] Interact via Elementwise Multiplication");
new_options.add(make_option("interact", s)
.keep()
.necessary()
.help("Put weights on feature products from namespaces <n1> and <n2>"));
if (!options.add_parse_and_check_necessary(new_options)) { return nullptr; }
if (s.length() != 2)
{
all.logger.err_error("Need two namespace arguments to interact: {} won't do EXITING", s);
return nullptr;
}
auto data = VW::make_unique<interact>();
data->n1 = static_cast<unsigned char>(s[0]);
data->n2 = static_cast<unsigned char>(s[1]);
all.logger.err_info("Interacting namespaces {0:c} and {1:c}", data->n1, data->n2);
data->all = &all;
auto l = make_reduction_learner(std::move(data), require_singleline(stack_builder.setup_base_learner()),
predict_or_learn<true, true>, predict_or_learn<false, true>, stack_builder.get_setupfn_name(interact_setup))
.build();
return l;
}