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","."]
docstr: Perform prediction of the estimator for input `x`.
  
  :param x: Samples.
  :type x: Format as expected by the `model`
  :return: Predictions by the model.
  :rtype: Format as produced by the `model`
code: def predict(self, x, **kwargs) -> Any:
      """
      Perform prediction of the estimator for input `x`.
  
      :param x: Samples.
      :type x: Format as expected by the `model`
      :return: Predictions by the model.
      :rtype: Format as produced by the `model`
      """
      raise NotImplementedError
  
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 10 for calling the BaseEstimator obj's underlying member method code with example usage: obj.predict(x) without return types