Class: LightGBM::Booster

Inherits:
Object
  • Object
show all
Includes:
Utils
Defined in:
lib/lightgbm/booster.rb

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(params: nil, train_set: nil, model_file: nil, model_str: nil) ⇒ Booster

Returns a new instance of Booster.



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# File 'lib/lightgbm/booster.rb', line 5

def initialize(params: nil, train_set: nil, model_file: nil, model_str: nil)
  @handle = ::FFI::MemoryPointer.new(:pointer)
  if model_str
    model_from_string(model_str)
  elsif model_file
    out_num_iterations = ::FFI::MemoryPointer.new(:int)
    check_result FFI.LGBM_BoosterCreateFromModelfile(model_file, out_num_iterations, @handle)
  else
    params ||= {}
    set_verbosity(params)
    check_result FFI.LGBM_BoosterCreate(train_set.handle_pointer, params_str(params), @handle)
  end
  ObjectSpace.define_finalizer(self, self.class.finalize(handle_pointer))

  self.best_iteration = -1

  # TODO get names when loaded from file
  @name_valid_sets = []
end

Instance Attribute Details

#best_iteration ⇒ Object

Returns the value of attribute best_iteration.



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# File 'lib/lightgbm/booster.rb', line 3

def best_iteration
  @best_iteration
end

#train_data_name ⇒ Object

Returns the value of attribute train_data_name.



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# File 'lib/lightgbm/booster.rb', line 3

def train_data_name
  @train_data_name
end

Class Method Details

.finalize(pointer) ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 162

def self.finalize(pointer)
  # must use proc instead of stabby lambda
  proc { FFI.LGBM_BoosterFree(pointer) }
end

Instance Method Details

#add_valid(data, name) ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 25

def add_valid(data, name)
  check_result FFI.LGBM_BoosterAddValidData(handle_pointer, data.handle_pointer)
  @name_valid_sets << name
  self # consistent with Python API
end

#current_iteration ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 31

def current_iteration
  out = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterGetCurrentIteration(handle_pointer, out)
  out.read_int
end

#dump_model(num_iteration: nil, start_iteration: 0) ⇒ Object Also known as: to_json 



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# File 'lib/lightgbm/booster.rb', line 37

def dump_model(num_iteration: nil, start_iteration: 0)
  num_iteration ||= best_iteration
  buffer_len = 1 << 20
  out_len = ::FFI::MemoryPointer.new(:int64)
  out_str = ::FFI::MemoryPointer.new(:char, buffer_len)
  feature_importance_type = 0 # TODO add option
  check_result FFI.LGBM_BoosterDumpModel(handle_pointer, start_iteration, num_iteration, feature_importance_type, buffer_len, out_len, out_str)
  actual_len = read_int64(out_len)
  if actual_len > buffer_len
    out_str = ::FFI::MemoryPointer.new(:char, actual_len)
    check_result FFI.LGBM_BoosterDumpModel(handle_pointer, start_iteration, num_iteration, feature_importance_type, actual_len, out_len, out_str)
  end
  out_str.read_string
end

#eval_train ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 57

def eval_train
  inner_eval(train_data_name, 0)
end

#eval_valid ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 53

def eval_valid
  @name_valid_sets.each_with_index.map { |n, i| inner_eval(n, i + 1) }.flatten(1)
end

#feature_importance(iteration: nil, importance_type: "split") ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 61

def feature_importance(iteration: nil, importance_type: "split")
  iteration ||= best_iteration
  importance_type =
    case importance_type
    when "split"
      0
    when "gain"
      1
    else
      -1
    end

  num_feature = self.num_feature
  out_result = ::FFI::MemoryPointer.new(:double, num_feature)
  check_result FFI.LGBM_BoosterFeatureImportance(handle_pointer, iteration, importance_type, out_result)
  out_result.read_array_of_double(num_feature).map(&:to_i)
end

#model_from_string(model_str) ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 79

def model_from_string(model_str)
  out_num_iterations = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterLoadModelFromString(model_str, out_num_iterations, @handle)
  self
end

#model_to_string(num_iteration: nil, start_iteration: 0) ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 85

def model_to_string(num_iteration: nil, start_iteration: 0)
  num_iteration ||= best_iteration
  buffer_len = 1 << 20
  out_len = ::FFI::MemoryPointer.new(:int64)
  out_str = ::FFI::MemoryPointer.new(:char, buffer_len)
  feature_importance_type = 0 # TODO add option
  check_result FFI.LGBM_BoosterSaveModelToString(handle_pointer, start_iteration, num_iteration, feature_importance_type, buffer_len, out_len, out_str)
  actual_len = read_int64(out_len)
  if actual_len > buffer_len
    out_str = ::FFI::MemoryPointer.new(:char, actual_len)
    check_result FFI.LGBM_BoosterSaveModelToString(handle_pointer, start_iteration, num_iteration, feature_importance_type, actual_len, out_len, out_str)
  end
  out_str.read_string
end

#num_feature ⇒ Object Also known as: num_features 



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# File 'lib/lightgbm/booster.rb', line 100

def num_feature
  out = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterGetNumFeature(handle_pointer, out)
  out.read_int
end

#num_model_per_iteration ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 107

def num_model_per_iteration
  out = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterNumModelPerIteration(handle_pointer, out)
  out.read_int
end

#num_trees ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 113

def num_trees
  out = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterNumberOfTotalModel(handle_pointer, out)
  out.read_int
end

#predict(input, start_iteration: nil, num_iteration: nil, **params) ⇒ Object

TODO support different prediction types



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# File 'lib/lightgbm/booster.rb', line 120

def predict(input, start_iteration: nil, num_iteration: nil, **params)
  input =
    if daru?(input)
      input.map_rows(&:to_a)
    else
      input.to_a
    end

  singular = !input.first.is_a?(Array)
  input = [input] if singular

  start_iteration ||= 0
  num_iteration ||= best_iteration
  num_class ||= num_class()

  flat_input = input.flatten
  handle_missing(flat_input)
  data = ::FFI::MemoryPointer.new(:double, input.count * input.first.count)
  data.write_array_of_double(flat_input)

  out_len = ::FFI::MemoryPointer.new(:int64)
  out_result = ::FFI::MemoryPointer.new(:double, num_class * input.count)
  check_result FFI.LGBM_BoosterPredictForMat(handle_pointer, data, 1, input.count, input.first.count, 1, 0, start_iteration, num_iteration, params_str(params), out_len, out_result)
  out = out_result.read_array_of_double(read_int64(out_len))
  out = out.each_slice(num_class).to_a if num_class > 1

  singular ? out.first : out
end

#save_model(filename, num_iteration: nil, start_iteration: 0) ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 149

def save_model(filename, num_iteration: nil, start_iteration: 0)
  num_iteration ||= best_iteration
  feature_importance_type = 0 # TODO add
  check_result FFI.LGBM_BoosterSaveModel(handle_pointer, start_iteration, num_iteration, feature_importance_type, filename)
  self # consistent with Python API
end

#update ⇒ Object 



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# File 'lib/lightgbm/booster.rb', line 156

def update
  finished = ::FFI::MemoryPointer.new(:int)
  check_result FFI.LGBM_BoosterUpdateOneIter(handle_pointer, finished)
  finished.read_int == 1
end