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 prediction of the examples.
  
  Args:
    imgs: array of examples to get predictions
  
  Returns:
    array of predictions
code: def get_predictions(self, examples):
      """Get prediction of the examples.
  
      Args:
        imgs: array of examples to get predictions
  
      Returns:
        array of predictions
      """
      return self.adjust_prediction(
          self.sess.run(
              self.ends["prediction"], {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 6 for calling the ModelWrapper obj's underlying member method code with example usage: obj.get_predictions(examples) and returns: self