class_docstr: Mixin abstract base class defining additional functionality required for neural network estimators. This base class
  has to be mixed in with class `BaseEstimator`.
class_docstr_tok: ["Mixin","abstract","base","class","defining","additional","functionality","required","for","neural","network","estimators",".","This","base","class","has","to","be","mixed","in","with","class","`","BaseEstimator","`","."]
docstr: Perform prediction of the neural network for samples `x`.
  
  :param x: Input samples.
  :param batch_size: Batch size.
  :return: Predictions.
  :rtype: Format as expected by the `model`
code: def predict(self, x: np.ndarray, batch_size: int = 128, **kwargs):
      """
      Perform prediction of the neural network for samples `x`.
  
      :param x: Input samples.
      :param batch_size: Batch size.
      :return: Predictions.
      :rtype: Format as expected 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 2 for calling the NeuralNetworkMixin obj's underlying member method code with example usage: obj.predict(x, batch_size) without return types