class_docstr: Estimator class for TensorFlow v2 models.
class_docstr_tok: ["Estimator","class","for","TensorFlow","v2","models","."]
docstr: Take a dictionary of parameters and apply checks before setting them as attributes.
  
  :param kwargs: A dictionary of attributes.
docstr_tok: ["Take","a","dictionary","of","parameters","and","apply","checks","before","setting","them","as","attributes",".",":","param","kwargs",":","A","dictionary","of","attributes","."]
code: def set_params(self, **kwargs) -> None:
      """
      Take a dictionary of parameters and apply checks before setting them as attributes.
  
      :param kwargs: A dictionary of attributes.
      """
      super().set_params(**kwargs)
      self._check_params()
  
imports: import logging
  from typing import Any, Tuple, TYPE_CHECKING
  import numpy
  from art import config
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin, NeuralNetworkMixin
label_desc: Use image node_id 4 for calling the TensorFlowV2Estimator obj's underlying member method code with example usage: obj.set_params() without return types