class_docstr: This class implements a classifier with the TensorFlow v2 framework.
class_docstr_tok: ["This","class","implements","a","classifier","with","the","TensorFlow","v2","framework","."]
docstr: Perform prediction for a batch of inputs.
  
  :param x: Input samples.
  :param training_mode: `True` for model set to training mode and `'False` for model set to evaluation mode.
  :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
docstr_tok: ["Perform","prediction","for","a","batch","of","inputs",".",":","param","x",":","Input","samples",".",":","param","training_mode",":","`","True","`","for","model","set","to","training","mode","and","`","'False","`","for","model","set","to","evaluation","mode",".",":","return",":","Array","of","predictions","of","shape","`","(","nb_inputs",",","nb_classes",")","`","."]
code: def _predict_framework(
      self, x: "tf.Tensor", training_mode: bool = False
  ) -> "tf.Tensor":
      """
      Perform prediction for a batch of inputs.
  
      :param x: Input samples.
      :param training_mode: `True` for model set to training mode and `'False` for model set to evaluation mode.
      :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
      """
      # Apply preprocessing
      x_preprocessed, _ = self._apply_preprocessing(
          x, y=None, fit=False
      )
  
      return self._model(x_preprocessed, training=training_mode)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import random
  import shutil
  import time
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  from tqdm.auto import tqdm
  import numpy
  import six
  from art import config
  from art.estimators.classification.classifier import ClassGradientsMixin, ClassifierMixin
  from art.estimators.tensorflow import TensorFlowEstimator, TensorFlowV2Estimator
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 7 for calling the TensorFlowV2Classifier obj's underlying member method code with example usage: obj._predict_framework(x, training_mode) and returns: self