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: Return the output of a specific layer for samples `x` where `layer` is the index of the layer between 0 and
  `nb_layers - 1 or the name of the layer. The number of layers can be determined by counting the results
  returned by calling `layer_names`.
  
  :param x: Samples
  :param layer: Index or name of the layer.
  :param batch_size: Batch size.
  :param framework: If true, return the intermediate tensor representation of the activation.
  :return: The output of `layer`, where the first dimension is the batch size corresponding to `x`.
code: def get_activations(
      self,
      x: np.ndarray,
      layer: Union[int, str],
      batch_size: int,
      framework: bool = False,
  ) -> np.ndarray:
      """
      Return the output of a specific layer for samples `x` where `layer` is the index of the layer between 0 and
      `nb_layers - 1 or the name of the layer. The number of layers can be determined by counting the results
      returned by calling `layer_names`.
  
      :param x: Samples
      :param layer: Index or name of the layer.
      :param batch_size: Batch size.
      :param framework: If true, return the intermediate tensor representation of the activation.
      :return: The output of `layer`, where the first dimension is the batch size corresponding to `x`.
      """
      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 5 for calling the NeuralNetworkMixin obj's underlying member method code with example usage: obj.get_activations(x, layer, batch_size, framework) without return types