code: def fit(self, input_data: InputData):
      iter_ = 0
  
      while iter_ < self.max_iter:
          try:
              self.operation.inlier_mask_ = None
              self.operation.fit(input_data.features, input_data.target)
              return self.operation
          except ValueError:
              self.log.info(
                  "RANSAC: multiplied residual_threshold on 2"
              )
              residual_threshold = self.params.get("residual_threshold")
              self.params.update(
                  residual_threshold=residual_threshold * 2
              )
              iter_ += 1
  
      return self.operation
  
imports: from copy import copy
  from typing import Optional
  import numpy
  import sklearn
  from golem.core.log import default_log
  from pkg_resources import parse_version
  from sklearn.ensemble import IsolationForest
  from sklearn.linear_model import LinearRegression, RANSACRegressor
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.tree import DecisionTreeRegressor
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
label_desc: Use image node_id 2 for calling the RegRANSACImplementation obj's underlying member method code with example usage: obj.fit(input_data) and returns: self, self