class_docstr: Simple wrapper of the for models with session object for TCAV.
  
  Supports easy inference with no need to deal with the feed_dicts.
class_docstr_tok: ["Simple","wrapper","of","the","for","models","with","session","object","for","TCAV",".","Supports","easy","inference","with","no","need","to","deal","with","the","feed_dicts","."]
docstr: Get activations at a bottleneck for provided examples.
  
  Args:
    examples: example data to feed into network.
    bottleneck_name: string, should be key of self.bottlenecks_tensors
  
  Returns:
    Activations in the given layer.
code: def run_examples(self, examples, bottleneck_name):
      """Get activations at a bottleneck for provided examples.
  
      Args:
        examples: example data to feed into network.
        bottleneck_name: string, should be key of self.bottlenecks_tensors
  
      Returns:
        Activations in the given layer.
      """
      return self.sess.run(
          self.bottlenecks_tensors[bottleneck_name],
          {self.ends["input"]: examples},
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from abc import ABCMeta
  from abc import abstractmethod
  from six.moves import zip
  import numpy
  import six
  import tensorflow
  from google.protobuf import text_format
label_desc: Use image node_id 11 for calling the ModelWrapper obj's underlying member method code with example usage: obj.run_examples(examples, bottleneck_name) and returns: self