class_docstr: Class allowing to aggregate multiple classifiers as an ensemble. The individual classifiers are expected to be
  trained when the ensemble is created and no training procedures are provided through this class.
docstr: Return the output of the specified layer for input `x`. `layer` is specified by layer index (between 0 and
  `nb_layers - 1`) or by name. The number of layers can be determined by counting the results returned by
  calling `layer_names`. This function is not supported for ensembles.
  
  :param x: Input for computing the activations.
  :param layer: Layer for computing the activations.
  :param batch_size: Size of batches.
  :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`.
  :raises `NotImplementedException`: This method is not supported for ensembles.
docstr_tok: ["Return","the","output","of","the","specified","layer","for","input","`","x","`",".","`","layer","`","is","specified","by","layer","index","(","between","0","and","`","nb_layers","-","1","`",")","or","by","name",".","The","number","of","layers","can","be","determined","by","counting","the","results","returned","by","calling","`","layer_names","`",".","This","function","is","not","supported","for","ensembles",".",":","param","x",":","Input","for","computing","the","activations",".",":","param","layer",":","Layer","for","computing","the","activations",".",":","param","batch_size",":","Size","of","batches",".",":","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","`",".",":","raises","`","NotImplementedException","`",":","This","method","is","not","supported","for","ensembles","."]
code: def get_activations(
      self,
      x: np.ndarray,
      layer: Union[int, str],
      batch_size: int = 128,
      framework: bool = False,
  ) -> np.ndarray:
      """
      Return the output of the specified layer for input `x`. `layer` is specified by layer index (between 0 and
      `nb_layers - 1`) or by name. The number of layers can be determined by counting the results returned by
      calling `layer_names`. This function is not supported for ensembles.
  
      :param x: Input for computing the activations.
      :param layer: Layer for computing the activations.
      :param batch_size: Size of batches.
      :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`.
      :raises `NotImplementedException`: This method is not supported for ensembles.
      """
      raise NotImplementedError
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import List, Optional, Union, Tuple, TYPE_CHECKING
  import numpy
  from art.estimators.classification.classifier import ClassifierNeuralNetwork
  from art.estimators.estimator import NeuralNetworkMixin
label_desc: Use image node_id 9 for calling the EnsembleClassifier obj's underlying member method code with example usage: obj.get_activations(x, layer, batch_size, framework) without return types