Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

fix: Fixing model version check for Active reduction #4655

Merged
merged 3 commits into from
Oct 17, 2023
Merged

fix: Fixing model version check for Active reduction #4655

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
f7e8efe
Fixing model version check for Active reduction
peterychang Oct 12, 2023
527ad32
adding additional check to account for models generated between 9.0 a…
peterychang Oct 12, 2023
e038514
lint
peterychang Oct 12, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 10 additions & 2 deletions vowpalwabbit/core/include/vw/core/reductions/active.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,10 +16,18 @@ namespace reductions
class active
{
public:
active(float active_c0, VW::workspace* all) : active_c0(active_c0), _all(all) {}
active(float active_c0, std::shared_ptr<shared_data> shared_data, std::shared_ptr<rand_state> random_state,
VW::version_struct model_version)
: active_c0(active_c0)
, _shared_data(shared_data)
, _random_state(std::move(random_state))
, _model_version{std::move(model_version)}
{
}

float active_c0;
VW::workspace* _all = nullptr;
std::shared_ptr<shared_data> _shared_data; // statistics, loss
std::shared_ptr<rand_state> _random_state;

float _min_seen_label = 0.f;
float _max_seen_label = 1.f;
Expand Down
2 changes: 2 additions & 0 deletions vowpalwabbit/core/include/vw/core/vw_versions.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -59,6 +59,8 @@ constexpr VW::version_struct VERSION_PASS_UINT64{8, 3, 3};

/// Added serialized seen min and max labels in the --active reduction
constexpr VW::version_struct VERSION_FILE_WITH_ACTIVE_SEEN_LABELS{9, 0, 0};
/// Active seen labels was accidentally reverted out in 9.4.0
constexpr VW::version_struct VERSION_FILE_WITH_ACTIVE_SEEN_LABELS_FIXED{9, 10, 0};

/// Moved option values from command line to model data
constexpr VW::version_struct VERSION_FILE_WITH_L1_AND_L2_STATE_IN_MODEL_DATA{9, 0, 0};
Expand Down
16 changes: 8 additions & 8 deletions vowpalwabbit/core/src/reductions/active.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -50,13 +50,13 @@ float query_decision(const active& a, float ec_revert_weight, float k)
if (k <= 1.f) { bias = 1.f; }
else
{
const auto weighted_queries = static_cast<float>(a._all->sd->weighted_labeled_examples);
const float avg_loss = (static_cast<float>(a._all->sd->sum_loss) / k) +
const auto weighted_queries = static_cast<float>(a._shared_data->weighted_labeled_examples);
const float avg_loss = (static_cast<float>(a._shared_data->sum_loss) / k) +
std::sqrt((1.f + 0.5f * std::log(k)) / (weighted_queries + 0.0001f));
bias = get_active_coin_bias(k, avg_loss, ec_revert_weight / k, a.active_c0);
}

return (a._all->get_random_state()->get_and_update_random() < bias) ? 1.f / bias : -1.f;
return (a._random_state->get_and_update_random() < bias) ? 1.f / bias : -1.f;
}

template <bool is_learn>
Expand All @@ -66,15 +66,15 @@ void predict_or_learn_simulation(active& a, learner& base, VW::example& ec)

if (is_learn)
{
const auto k = static_cast<float>(a._all->sd->t);
const auto k = static_cast<float>(a._shared_data->t);
constexpr float threshold = 0.f;

ec.confidence = fabsf(ec.pred.scalar - threshold) / base.sensitivity(ec);
const float importance = query_decision(a, ec.confidence, k);

if (importance > 0.f)
{
a._all->sd->queries += 1;
a._shared_data->queries += 1;
ec.weight *= importance;
base.learn(ec);
}
Expand All @@ -94,7 +94,7 @@ void predict_or_learn_active(active& a, learner& base, VW::example& ec)

if (ec.l.simple.label == FLT_MAX)
{
const float threshold = (a._all->sd->max_label + a._all->sd->min_label) * 0.5f;
const float threshold = (a._shared_data->max_label + a._shared_data->min_label) * 0.5f;
// We want to understand the change in prediction if the label were to be
// the opposite of what was predicted. 0 and 1 are used for the expected min
// and max labels to be coming in from the active interactor.
Expand Down Expand Up @@ -130,7 +130,7 @@ void active_print_result(
void save_load(active& a, VW::io_buf& io, bool read, bool text)
{
if (io.num_files() == 0) { return; }
if (a._model_version >= VW::version_definitions::VERSION_FILE_WITH_ACTIVE_SEEN_LABELS)
if (a._model_version >= VW::version_definitions::VERSION_FILE_WITH_ACTIVE_SEEN_LABELS_FIXED)
{
if (read)
{
Expand Down Expand Up @@ -195,7 +195,7 @@ std::shared_ptr<VW::LEARNER::learner> VW::reductions::active_setup(VW::setup_bas
if (!options.add_parse_and_check_necessary(new_options)) { return nullptr; }

if (options.was_supplied("lda")) { THROW("lda cannot be combined with active learning") }
auto data = VW::make_unique<active>(active_c0, &all);
auto data = VW::make_unique<active>(active_c0, all.sd, all.get_random_state(), all.runtime_state.model_file_ver);
auto base = require_singleline(stack_builder.setup_base_learner());

using learn_pred_func_t = void (*)(active&, VW::LEARNER::learner&, VW::example&);
Expand Down