class_docstr: A data structure to cache the sequence of functional calls.
  
  Each autoobject contains a callcache object. The call sequences will
  be gradually passed down to the last function call.
  Internally, it containes a callqueue which collects the function calls in    order and a tensors table which is used to collect the resulting    tensors from function execution.
class_docstr_tok: ["A","data","structure","to","cache","the","sequence","of","functional","calls",".","Each","autoobject","contains","a","callcache","object",".","The","call","sequences","will","be","gradually","passed","down","to","the","last","function","call",".","Internally",",","it","containes","a","callqueue","which","collects","the","function","calls","in","order","and","a","tensors","table","which","is","used","to","collect","the","resulting","tensors","from","function","execution","."]
docstr: Get all the call queue.
docstr_tok: ["Get","all","the","call","queue","."]
code: def calls(self):
      """Get all the call queue."""
      return self.callqueue_
  
file_path: BigDL/python/nano/src/bigdl/nano/automl/hpo/callgraph.py
imports: from .space import AutoObject
  from enum import Enum
  from bigdl.nano.utils.common import invalidInputError
label_desc: Use image node_id 7 for calling the CallCache obj's underlying member method code with example usage: obj.calls() and returns: self