class_docstr: Abstract base PyTorch compressor
docstr: To obtain all the wrapped modules.
  
  Returns
  -------
  list
      a list of the wrapped modules
docstr_tok: ["To","obtain","all","the","wrapped","modules",".","Returns","--","--","--","-","list","a","list","of","the","wrapped","modules"]
code: def get_modules_wrapper(self):
      """
      To obtain all the wrapped modules.
  
      Returns
      -------
      list
          a list of the wrapped modules
      """
      return self.modules_wrapper
  
imports: import types
  import logging
  import torch
  from .None import default_layers
label_desc: Use image node_id 10 for calling the Compressor obj's underlying member method code with example usage: obj.get_modules_wrapper() and returns: self