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fix: cbzo ppw fix #4519

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merged 3 commits into from
Mar 7, 2023
Merged

fix: cbzo ppw fix #4519

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7a0ddd5
fix: cbzo ppw fix
bassmang Mar 3, 2023
0b70df6
Merge branch 'master' into cbzo_fix
bassmang Mar 3, 2023
d636312
Merge branch 'master' into cbzo_fix
bassmang Mar 7, 2023
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25 changes: 12 additions & 13 deletions vowpalwabbit/core/src/reductions/cbzo.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -46,38 +46,38 @@ class linear_update_data
};

// uint64_t index variant of VW::get_weight
inline float get_weight(VW::workspace& all, uint64_t index, uint32_t offset)
inline float get_weight(VW::workspace& all, uint64_t index)
{
return (&all.weights[(index) << all.weights.stride_shift()])[offset];
return all.weights[(index) << all.weights.stride_shift()];
}

// uint64_t index variant of VW::set_weight
inline void set_weight(VW::workspace& all, uint64_t index, uint32_t offset, float value)
inline void set_weight(VW::workspace& all, uint64_t index, float value)
{
(&all.weights[(index) << all.weights.stride_shift()])[offset] = value;
all.weights[(index) << all.weights.stride_shift()] = value;
}

float l1_grad(VW::workspace& all, uint64_t fi)
{
if (all.no_bias && fi == VW::details::CONSTANT) { return 0.0f; }

float fw = get_weight(all, fi, 0);
float fw = get_weight(all, fi);
return fw >= 0.0f ? all.l1_lambda : -all.l1_lambda;
}

float l2_grad(VW::workspace& all, uint64_t fi)
{
if (all.no_bias && fi == VW::details::CONSTANT) { return 0.0f; }

float fw = get_weight(all, fi, 0);
float fw = get_weight(all, fi);
return all.l2_lambda * fw;
}

inline void accumulate_dotprod(float& dotprod, float x, float& fw) { dotprod += x * fw; }

inline float constant_inference(VW::workspace& all)
{
float wt = get_weight(all, VW::details::CONSTANT, 0);
float wt = get_weight(all, VW::details::CONSTANT);
return wt;
}

Expand All @@ -102,27 +102,27 @@ float inference(VW::workspace& all, VW::example& ec)
template <bool feature_mask_off>
void constant_update(cbzo& data, VW::example& ec)
{
float fw = get_weight(*data.all, VW::details::CONSTANT, 0);
float fw = get_weight(*data.all, VW::details::CONSTANT);
if (feature_mask_off || fw != 0.0f)
{
float action_centroid = inference<CONSTANT_POLICY>(*data.all, ec);
float grad = ec.l.cb_cont.costs[0].cost / (ec.l.cb_cont.costs[0].action - action_centroid);
float update =
-data.all->eta * (grad + l1_grad(*data.all, VW::details::CONSTANT) + l2_grad(*data.all, VW::details::CONSTANT));

set_weight(*data.all, VW::details::CONSTANT, 0, fw + update);
set_weight(*data.all, VW::details::CONSTANT, fw + update);
}
}

template <bool feature_mask_off>
void linear_per_feature_update(linear_update_data& upd_data, float x, uint64_t fi)
{
float fw = get_weight(*upd_data.all, fi, 0);
float fw = get_weight(*upd_data.all, fi);

if (feature_mask_off || fw != 0.0f)
{
float update = upd_data.mult * (upd_data.part_grad * x + (l1_grad(*upd_data.all, fi) + l2_grad(*upd_data.all, fi)));
set_weight(*upd_data.all, fi, 0, fw + update);
set_weight(*upd_data.all, fi, fw + update);
}
}

Expand Down Expand Up @@ -236,7 +236,7 @@ void save_load(cbzo& data, VW::io_buf& model_file, bool read, bool text)
if (read)
{
VW::details::initialize_regressor(all);
if (data.all->initial_constant != 0.0f) { set_weight(all, VW::details::CONSTANT, 0, data.all->initial_constant); }
if (data.all->initial_constant != 0.0f) { set_weight(all, VW::details::CONSTANT, data.all->initial_constant); }
}
if (model_file.num_files() > 0) { save_load_regressor(all, model_file, read, text); }
}
Expand Down Expand Up @@ -368,7 +368,6 @@ std::shared_ptr<VW::LEARNER::learner> VW::reductions::cbzo_setup(VW::setup_base_

auto l = make_bottom_learner(std::move(data), get_learn(all, policy, feature_mask_off), get_predict(all, policy),
stack_builder.get_setupfn_name(cbzo_setup), prediction_type_t::PDF, label_type_t::CONTINUOUS)
.set_params_per_weight(0)
.set_save_load(save_load)
.set_output_example_prediction(output_example_prediction_cbzo)
.set_print_update(print_update_cbzo)
Expand Down