class_docstr: The abstract base class `BaseEstimator` defines the basic requirements of an estimator in ART. The BaseEstimator is
  is the highest abstraction of a machine learning model in ART.
class_docstr_tok: ["The","abstract","base","class","`","BaseEstimator","`","defines","the","basic","requirements","of","an","estimator","in","ART",".","The","BaseEstimator","is","is","the","highest","abstraction","of","a","machine","learning","model","in","ART","."]
code: def __repr__(self):
      class_name = self.__class__.__name__
      attributes = {}
      for k, value in self.__dict__.items():
          k = k[1:] if k[0] == "_" else k
          attributes[k] = value
      attributes = [f"{k}={v}" for k, v in attributes.items()]
      repr_string = class_name + "(" + ", ".join(attributes) + ")"
      return repr_string
  
imports: from abc import ABC, abstractmethod
  from typing import Any, Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import trange
  from art.config import ART_NUMPY_DTYPE
label_desc: Use image node_id 19 for calling the BaseEstimator obj's underlying member method code with example usage: obj.__repr__() and returns: repr_string