code: def __init__(self, intercept=0, slope=1, foo=0):
      self._num_calls = 0
      self.intercept = intercept
      self.slope = slope
      self.foo = foo
      super(LinearFunction, self).__init__()
  
imports: import os
  from ast import literal_eval
  import numpy
  from distributed import Lock, Variable, get_worker
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.validation import _num_samples, check_array
label_desc: Use image node_id 1 to create a new LinearFunction object from inherited base classes: BaseEstimator with example: obj = LinearFunction(intercept, slope, foo)