class_docstr: Repeat last known value of time series to the future -
  LOCF (last observation carried forward)
docstr: Determine how many elements to repeat during forecasting 
docstr_tok: ["Determine","how","many","elements","to","repeat","during","forecasting"]
code: def fit(self, input_data):
      """Determine how many elements to repeat during forecasting"""
      if self.part_for_repeat == -1:
          self.elements_to_repeat = 1
          return self
  
      elements_to_repeat = round(
          len(input_data.features) * self.part_for_repeat
      )
      if elements_to_repeat < 1:
          # Minimum number of elements is one
          self.elements_to_repeat = 1
      else:
          self.elements_to_repeat = elements_to_repeat
  
      if (
          self.elements_to_repeat
          > input_data.task.task_params.forecast_length
      ):
          self.elements_to_repeat = (
              input_data.task.task_params.forecast_length
          )
      return self
  
imports: from copy import copy
  import numpy
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import ts_to_table, transform_features_and_target_into_lagged
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
label_desc: Use image node_id 3 for calling the RepeatLastValueImplementation obj's underlying member method code with example usage: obj.fit(input_data) and returns: self, self