class_docstr: General interface of graph applications.
  
  Parameters:
      dim (int): dimension of embeddings
      gpus (list of int, optional): GPU ids, default is all GPUs
      cpu_per_gpu (int, optional): number of CPU threads per GPU, default is all CPUs
      gpu_memory_limit (int, optional): memory limit per GPU in bytes, default is all memory
      float_type (dtype, optional): type of parameters
      index_type (dtype, optional): type of graph indexes
class_docstr_tok: ["General","interface","of","graph","applications",".","Parameters",":","dim","(","int",")",":","dimension","of","embeddings","gpus","(","list","of","int",",","optional",")",":","GPU","ids",",","default","is","all","GPUs","cpu_per_gpu","(","int",",","optional",")",":","number","of","CPU","threads","per","GPU",",","default","is","all","CPUs","gpu_memory_limit","(","int",",","optional",")",":","memory","limit","per","GPU","in","bytes",",","default","is","all","memory","float_type","(","dtype",",","optional",")",":","type","of","parameters","index_type","(","dtype",",","optional",")",":","type","of","graph","indexes"]
code: def get_mapping(self, id2name, name2id):
      mapping = []
      for name in id2name:
          if name not in name2id:
              raise ValueError(
                  "Can't find the embedding for `%s`" % name
              )
          mapping.append(name2id[name])
      return mapping
  
imports: from __future__ import print_function, absolute_import, unicode_literals, division
  import os
  import re
  import pickle
  import logging
  import multiprocessing
  from collections import defaultdict
  from future.builtins import str, map, range
  from easydict import EasyDict
  import numpy
  from ..None import lib, cfg, auto
  from ..None import graph, solver
  from ..util import assert_in, monitor, SharedNDArray
label_desc: Use image node_id 11 for calling the ApplicationMixin obj's underlying member method code with example usage: obj.get_mapping(id2name, name2id) and returns: mapping