refactor: [workspace] split 'all' into multiple structs. split config…

… and runtime vars. (#4493)

cs/cli/vowpalwabbit.cpp

@@ -32,16 +32,16 @@ VowpalWabbit::VowpalWabbit(VowpalWabbitSettings^ settings)
   }
 
   if (settings->ParallelOptions != nullptr)
-  { m_vw->selected_all_reduce_type = all_reduce_type::THREAD;
+  { m_vw->runtime_config.selected_all_reduce_type = all_reduce_type::THREAD;
     auto total = settings->ParallelOptions->MaxDegreeOfParallelism;
 
     if (settings->Root == nullptr)
-    { m_vw->all_reduce.reset(new all_reduce_threads(total, settings->Node));
+    { m_vw->runtime_state.all_reduce.reset(new all_reduce_threads(total, settings->Node));
     }
     else
-    { auto parent_all_reduce = (all_reduce_threads*)settings->Root->m_vw->all_reduce.get();
+    { auto parent_all_reduce = (all_reduce_threads*)settings->Root->m_vw->runtime_state.all_reduce.get();
 
-      m_vw->all_reduce.reset(new all_reduce_threads(parent_all_reduce, total, settings->Node));
+      m_vw->runtime_state.all_reduce.reset(new all_reduce_threads(parent_all_reduce, total, settings->Node));
     }
   }
 
@@ -64,9 +64,9 @@ void VowpalWabbit::Driver()
 }
 
 void VowpalWabbit::RunMultiPass()
-{ if (m_vw->numpasses > 1)
+{ if (m_vw->runtime_config.numpasses > 1)
   { try
-    { m_vw->do_reset_source = true;
+    { m_vw->runtime_state.do_reset_source = true;
       VW::start_parser(*m_vw);
       LEARNER::generic_driver(*m_vw);
       VW::end_parser(*m_vw);
@@ -79,17 +79,17 @@ VowpalWabbitPerformanceStatistics^ VowpalWabbit::PerformanceStatistics::get()
 { // see parse_args.cc:finish(...)
   auto stats = gcnew VowpalWabbitPerformanceStatistics();
 
-  if (m_vw->current_pass == 0)
+  if (m_vw->passes_config.current_pass == 0)
   { stats->NumberOfExamplesPerPass = m_vw->sd->example_number;
   }
   else
-  { stats->NumberOfExamplesPerPass = m_vw->sd->example_number / m_vw->current_pass;
+  { stats->NumberOfExamplesPerPass = m_vw->sd->example_number / m_vw->passes_config.current_pass;
   }
 
   stats->WeightedExampleSum = m_vw->sd->weighted_examples();
   stats->WeightedLabelSum = m_vw->sd->weighted_labels;
 
-  if (m_vw->holdout_set_off)
+  if (m_vw->passes_config.holdout_set_off)
 	  if (m_vw->sd->weighted_labeled_examples > 0)
 		  stats->AverageLoss = m_vw->sd->sum_loss / m_vw->sd->weighted_labeled_examples;
 	  else
@@ -100,7 +100,7 @@ VowpalWabbitPerformanceStatistics^ VowpalWabbit::PerformanceStatistics::get()
 	  stats->AverageLoss = m_vw->sd->holdout_best_loss;
 
   float best_constant; float best_constant_loss;
-  if (get_best_constant(*m_vw->loss, *m_vw->sd, best_constant, best_constant_loss))
+  if (get_best_constant(*m_vw->loss_config.loss, *m_vw->sd, best_constant, best_constant_loss))
   { stats->BestConstant = best_constant;
     if (best_constant_loss != FLT_MIN)
     { stats->BestConstantLoss = best_constant_loss;
@@ -124,7 +124,7 @@ uint64_t VowpalWabbit::HashSpace(String^ s)
 }
 
 uint64_t VowpalWabbit::HashFeature(String^ s, size_t u)
-{ auto newHash = m_hasher(s, u) & m_vw->parse_mask;
+{ auto newHash = m_hasher(s, u) & m_vw->runtime_state.parse_mask;
 
 #ifdef _DEBUG
   auto oldHash = HashFeatureNative(s, u);
@@ -321,7 +321,7 @@ List<VowpalWabbitExample^>^ VowpalWabbit::ParseDecisionServiceJson(cli::array<By
 
 			VW::parsers::json::decision_service_interaction interaction;
 
-			if (m_vw->audit)
+			if (m_vw->output_config.audit)
 				VW::parsers::json::read_line_decision_service_json<true>(*m_vw, examples, reinterpret_cast<char*>(data), length, copyJson, std::bind(get_example_from_pool, &state), &interaction);
 			else
 				VW::parsers::json::read_line_decision_service_json<false>(*m_vw, examples, reinterpret_cast<char*>(data), length, copyJson, std::bind(get_example_from_pool, &state), &interaction);
@@ -385,7 +385,7 @@ List<VowpalWabbitExample^>^ VowpalWabbit::ParseDecisionServiceJson(cli::array<By
 
 			  interior_ptr<ParseJsonState^> state_ptr = &state;
 
-			  if (m_vw->audit)
+			  if (m_vw->output_config.audit)
 				VW::parsers::json::read_line_json<true>(*m_vw, examples, reinterpret_cast<char*>(valueHandle.AddrOfPinnedObject().ToPointer()), (size_t)bytes->Length, std::bind(get_example_from_pool, &state));
 			  else
 				VW::parsers::json::read_line_json<false>(*m_vw, examples, reinterpret_cast<char*>(valueHandle.AddrOfPinnedObject().ToPointer()), (size_t)bytes->Length, std::bind(get_example_from_pool, &state));
@@ -793,15 +793,15 @@ VowpalWabbitExample^ VowpalWabbit::GetOrCreateNativeExample()
   { try
     {
       auto ex = new VW::example;
-      m_vw->example_parser->lbl_parser.default_label(ex->l);
+      m_vw->parser_runtime.example_parser->lbl_parser.default_label(ex->l);
       return gcnew VowpalWabbitExample(this, ex);
     }
     CATCHRETHROW
   }
 
   try
   { VW::empty_example(*m_vw, *ex->m_example);
-    m_vw->example_parser->lbl_parser.default_label(ex->m_example->l);
+    m_vw->parser_runtime.example_parser->lbl_parser.default_label(ex->m_example->l);
 
     return ex;
   }
@@ -833,9 +833,9 @@ void VowpalWabbit::ReturnExampleToPool(VowpalWabbitExample^ ex)
 }
 
 cli::array<List<VowpalWabbitFeature^>^>^ VowpalWabbit::GetTopicAllocation(int top)
-{ uint64_t length = (uint64_t)1 << m_vw->num_bits;
+{ uint64_t length = (uint64_t)1 << m_vw->initial_weights_config.num_bits;
   // using jagged array to enable LINQ
-  auto K = (int)m_vw->lda;
+  auto K = (int)m_vw->reduction_state.lda;
   auto allocation = gcnew cli::array<List<VowpalWabbitFeature^>^>(K);
 
   // TODO: better way of peaking into lda?
@@ -858,10 +858,10 @@ cli::array<List<VowpalWabbitFeature^>^>^ VowpalWabbit::GetTopicAllocation(int to
 template<typename T>
 cli::array<cli::array<float>^>^ VowpalWabbit::FillTopicAllocation(T& weights)
 {
-	uint64_t length = (uint64_t)1 << m_vw->num_bits;
+	uint64_t length = (uint64_t)1 << m_vw->initial_weights_config.num_bits;
 
 	// using jagged array to enable LINQ
-	auto K = (int)m_vw->lda;
+	auto K = (int)m_vw->reduction_state.lda;
 	auto allocation = gcnew cli::array<cli::array<float>^>(K);
 	for (int k = 0; k < K; k++)
 		allocation[k] = gcnew cli::array<float>((int)length);

cs/cli/vw_arguments.h

@@ -36,18 +36,17 @@ public ref class VowpalWabbitArguments
   float m_power_t;
 
   internal : VowpalWabbitArguments(VW::workspace* vw)
-      : m_data(gcnew String(vw->data_filename.c_str()))
-      , m_finalRegressor(gcnew String(vw->final_regressor_name.c_str()))
-      , m_testonly(!vw->training)
-      , m_passes((int)vw->numpasses)
+      : m_data(gcnew String(vw->parser_runtime.data_filename.c_str()))
+      , m_finalRegressor(gcnew String(vw->output_model_config.final_regressor_name.c_str()))
+      , m_testonly(!vw->runtime_config.training)
+      , m_passes((int)vw->runtime_config.numpasses)
   {
     auto options = vw->options.get();
 
-    if (vw->initial_regressors.size() > 0)
+    if (vw->initial_weights_config.initial_regressors.size() > 0)
     { m_regressors = gcnew List<String^>;
 
-      for (auto& r : vw->initial_regressors)
-        m_regressors->Add(gcnew String(r.c_str()));
+      for (auto& r : vw->initial_weights_config.initial_regressors) m_regressors->Add(gcnew String(r.c_str()));
     }
 
     VW::config::cli_options_serializer serializer;
@@ -66,8 +65,8 @@ public ref class VowpalWabbitArguments
       m_numberOfActions = (int)options->get_typed_option<uint32_t>("cb").value();
     }
 
-    m_learning_rate = vw->eta;
-    m_power_t = vw->power_t;
+    m_learning_rate = vw->update_rule_config.eta;
+    m_power_t = vw->update_rule_config.power_t;
   }
 
 public:

cs/cli/vw_base.cpp

@@ -150,7 +150,7 @@ void VowpalWabbitBase::InternalDispose()
   try
   { if (m_vw != nullptr)
     {
-      VW::details::reset_source(*m_vw, m_vw->num_bits);
+      VW::details::reset_source(*m_vw, m_vw->initial_weights_config.num_bits);
 
       // make sure don't try to free m_vw twice in case VW::finish throws.
       VW::workspace* vw_tmp = m_vw;
@@ -187,7 +187,7 @@ void VowpalWabbitBase::Reload([System::Runtime::InteropServices::Optional] Strin
 
   try
   {
-    VW::details::reset_source(*m_vw, m_vw->num_bits);
+    VW::details::reset_source(*m_vw, m_vw->initial_weights_config.num_bits);
 
     auto buffer = std::make_shared<std::vector<char>>();
     {
@@ -225,7 +225,7 @@ void VowpalWabbitBase::ID::set(String^ value)
 }
 
 void VowpalWabbitBase::SaveModel()
-{ std::string name = m_vw->final_regressor_name;
+{ std::string name = m_vw->output_model_config.final_regressor_name;
   if (name.empty())
   { return;
   }

cs/cli/vw_example.cpp

@@ -73,7 +73,7 @@ bool VowpalWabbitExample::IsNewLine::get()
 
 ILabel^ VowpalWabbitExample::Label::get()
 { ILabel^ label;
-  auto lp = m_owner->Native->m_vw->example_parser->lbl_parser;
+  auto lp = m_owner->Native->m_vw->parser_runtime.example_parser->lbl_parser;
   if (!memcmp(&lp, &VW::simple_label_parser_global, sizeof(lp)))
     label = gcnew SimpleLabel();
   else if (!memcmp(&lp, &VW::cb_label_parser_global, sizeof(lp)))
@@ -103,7 +103,7 @@ void VowpalWabbitExample::Label::set(ILabel^ label)
 	label->UpdateExample(m_owner->Native->m_vw, m_example);
 
 	// we need to update the example weight as setup_example() can be called prior to this call.
-	m_example->weight = m_owner->Native->m_vw->example_parser->lbl_parser.get_weight(m_example->l, m_example->ex_reduction_features);
+	m_example->weight = m_owner->Native->m_vw->parser_runtime.example_parser->lbl_parser.get_weight(m_example->l, m_example->ex_reduction_features);
 }
 
 void VowpalWabbitExample::MakeEmpty(VowpalWabbit^ vw)
@@ -389,7 +389,7 @@ uint64_t VowpalWabbitFeature::WeightIndex::get()
     throw gcnew InvalidOperationException("VowpalWabbitFeature must be initialized with example");
 
   VW::workspace* vw = m_example->Owner->Native->m_vw;
-  return ((m_weight_index + m_example->m_example->ft_offset) >> vw->weights.stride_shift()) & vw->parse_mask;
+  return ((m_weight_index + m_example->m_example->ft_offset) >> vw->weights.stride_shift()) & vw->runtime_state.parse_mask;
 }
 
 float VowpalWabbitFeature::Weight::get()

cs/cli/vw_prediction.cpp

@@ -155,8 +155,8 @@ cli::array<float>^ VowpalWabbitTopicPredictionFactory::Create(VW::workspace* vw,
 { if (ex == nullptr)
     throw gcnew ArgumentNullException("ex");
 
-  auto values = gcnew cli::array<float>(vw->lda);
-  Marshal::Copy(IntPtr(ex->pred.scalars.begin()), values, 0, vw->lda);
+  auto values = gcnew cli::array<float>(vw->reduction_state.lda);
+  Marshal::Copy(IntPtr(ex->pred.scalars.begin()), values, 0, vw->reduction_state.lda);
 
   return values;
 }

cs/vw.net.native/vw.net.arguments.cc

@@ -6,10 +6,10 @@
 API void GetWorkspaceBasicArguments(
     vw_net_native::workspace_context* workspace, vw_net_native::vw_basic_arguments_t* args)
 {
-  args->is_test_only = !workspace->vw->training;
-  args->num_passes = (int)workspace->vw->numpasses;
-  args->learning_rate = workspace->vw->eta;
-  args->power_t = workspace->vw->power_t;
+  args->is_test_only = !workspace->vw->runtime_config.training;
+  args->num_passes = (int)workspace->vw->runtime_config.numpasses;
+  args->learning_rate = workspace->vw->update_rule_config.eta;
+  args->power_t = workspace->vw->update_rule_config.power_t;
 
   if (workspace->vw->options->was_supplied("cb"))
   {
@@ -19,12 +19,12 @@ API void GetWorkspaceBasicArguments(
 
 API const char* GetWorkspaceDataFilename(vw_net_native::workspace_context* workspace)
 {
-  return workspace->vw->data_filename.c_str();
+  return workspace->vw->parser_runtime.data_filename.c_str();
 }
 
 API const char* GetFinalRegressorFilename(vw_net_native::workspace_context* workspace)
 {
-  return workspace->vw->final_regressor_name.c_str();
+  return workspace->vw->output_model_config.final_regressor_name.c_str();
 }
 
 API char* SerializeCommandLine(vw_net_native::workspace_context* workspace)
@@ -42,20 +42,23 @@ API char* SerializeCommandLine(vw_net_native::workspace_context* workspace)
 
 API size_t GetInitialRegressorFilenamesCount(vw_net_native::workspace_context* workspace)
 {
-  return workspace->vw->initial_regressors.size();
+  return workspace->vw->initial_weights_config.initial_regressors.size();
 }
 
 API vw_net_native::dotnet_size_t GetInitialRegressorFilenames(
     vw_net_native::workspace_context* workspace, const char** filenames, vw_net_native::dotnet_size_t count)
 {
-  std::vector<std::string>& initial_regressors = workspace->vw->initial_regressors;
+  std::vector<std::string>& initial_regressors = workspace->vw->initial_weights_config.initial_regressors;
   size_t size = initial_regressors.size();
   if ((size_t)count < size)
   {
     return vw_net_native::size_to_neg_dotnet_size(size);  // Not enough space in destination buffer
   }
 
-  for (size_t i = 0; i < size; i++) { filenames[i] = workspace->vw->initial_regressors[i].c_str(); }
+  for (size_t i = 0; i < size; i++)
+  {
+    filenames[i] = workspace->vw->initial_weights_config.initial_regressors[i].c_str();
+  }
 
-  return workspace->vw->initial_regressors.size();
+  return workspace->vw->initial_weights_config.initial_regressors.size();
 }

cs/vw.net.native/vw.net.example.cc

@@ -10,7 +10,7 @@
 API VW::example* CreateExample(vw_net_native::workspace_context* workspace)
 {
   auto* ex = new VW::example;
-  workspace->vw->example_parser->lbl_parser.default_label(ex->l);
+  workspace->vw->parser_runtime.example_parser->lbl_parser.default_label(ex->l);
   return ex;
 }
 
@@ -189,12 +189,13 @@ API void MakeIntoNewlineExample(vw_net_native::workspace_context* workspace, VW:
 
 API void MakeLabelDefault(vw_net_native::workspace_context* workspace, VW::example* example)
 {
-  workspace->vw->example_parser->lbl_parser.default_label(example->l);
+  workspace->vw->parser_runtime.example_parser->lbl_parser.default_label(example->l);
 }
 
 API void UpdateExampleWeight(vw_net_native::workspace_context* workspace, VW::example* example)
 {
-  example->weight = workspace->vw->example_parser->lbl_parser.get_weight(example->l, example->ex_reduction_features);
+  example->weight =
+      workspace->vw->parser_runtime.example_parser->lbl_parser.get_weight(example->l, example->ex_reduction_features);
 }
 
 API vw_net_native::namespace_enumerator* CreateNamespaceEnumerator(
@@ -256,7 +257,7 @@ API VW::feature_index GetShiftedWeightIndex(
     vw_net_native::workspace_context* workspace, VW::example* example, VW::feature_index feature_index)
 {
   VW::workspace* vw = workspace->vw;
-  return ((feature_index + example->ft_offset) >> vw->weights.stride_shift()) & vw->parse_mask;
+  return ((feature_index + example->ft_offset) >> vw->weights.stride_shift()) & vw->runtime_state.parse_mask;
 }
 
 API float GetWeight(vw_net_native::workspace_context* workspace, VW::example* example, VW::feature_index feature_index)

cs/vw.net.native/vw.net.predictions.cc

@@ -80,14 +80,17 @@ API vw_net_native::dotnet_size_t GetPredictionActionScores(
   return vw_net_native::v_copy_to_managed(ex->pred.a_s, values, count);
 }
 
-API size_t GetPredictionTopicProbsCount(VW::workspace* vw, VW::example* ex) { return static_cast<size_t>(vw->lda); }
+API size_t GetPredictionTopicProbsCount(VW::workspace* vw, VW::example* ex)
+{
+  return static_cast<size_t>(vw->reduction_state.lda);
+}
 
 API vw_net_native::dotnet_size_t GetPredictionTopicProbs(
     VW::workspace* vw, VW::example* ex, float* values, vw_net_native::dotnet_size_t count)
 {
-  if (count < vw->lda)
+  if (count < vw->reduction_state.lda)
   {
-    return vw_net_native::size_to_neg_dotnet_size(vw->lda);  // not enough space in the output array
+    return vw_net_native::size_to_neg_dotnet_size(vw->reduction_state.lda);  // not enough space in the output array
   }
 
   const v_array<float>& scalars = ex->pred.scalars;