class_docstr: Estimator class for TensorFlow v2 models.
class_docstr_tok: ["Estimator","class","for","TensorFlow","v2","models","."]
docstr: Estimator class for TensorFlow v2 models.
docstr_tok: ["Estimator","class","for","TensorFlow","v2","models","."]
code: def __init__(self, **kwargs):
      """
      Estimator class for TensorFlow v2 models.
      """
      preprocessing = kwargs.get("preprocessing")
      if isinstance(preprocessing, tuple):
          from art.preprocessing.standardisation_mean_std.tensorflow import (
              StandardisationMeanStdTensorFlow,
          )
  
          kwargs["preprocessing"] = StandardisationMeanStdTensorFlow(
              mean=preprocessing[0], std=preprocessing[1]
          )
  
      super().__init__(**kwargs)
      TensorFlowV2Estimator._check_params(self)
  
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 1 to create a new TensorFlowV2Estimator object from inherited base classes: NeuralNetworkMixin, LossGradientsMixin, BaseEstimator with example: obj = TensorFlowV2Estimator()