class_docstr: A simple example of the search policy which always returns
  the initial naive schedule (state).
  
  Parameters
  ----------
  task : SearchTask
      The SearchTask for the computation declaration.
  init_search_callbacks : Optional[List[SearchCallback]]
      Callback functions called before the search process.
class_docstr_tok: ["A","simple","example","of","the","search","policy","which","always","returns","the","initial","naive","schedule","(","state",")",".","Parameters","--","--","--","--","--","task",":","SearchTask","The","SearchTask","for","the","computation","declaration",".","init_search_callbacks",":","Optional","[","List","[","SearchCallback","]","]","Callback","functions","called","before","the","search","process","."]
code: def __init__(self, task, init_search_callbacks=None):
      self.__init_handle_by_constructor__(
          _ffi_api.EmptyPolicy, task, init_search_callbacks
      )
  
imports: import random
  import tvm._ffi
  from tvm.runtime import Object
  from .cost_model import RandomModel
  from .None import _ffi_api
label_desc: Use image node_id 1 to create a new EmptyPolicy object from inherited base classes: SearchPolicy with example: obj = EmptyPolicy(task, init_search_callbacks)