class_docstr: Corpus handles input in `GibbsLda++ format <https://gibbslda.sourceforge.net/>`_.
  
  **Format description**
  
  Both data for training/estimating the model and new data (i.e., previously unseen data) have the same format
  as follows ::
  
      [M]
      [document1]
      [document2]
      ...
      [documentM]
  
  in which the first line is the total number for documents [M]. Each line after that is one document.
  [documenti] is the ith document of the dataset that consists of a list of Ni words/terms ::
  
      [documenti] = [wordi1] [wordi2] ... [wordiNi]
  
  in which all [wordij] (i=1..M, j=1..Ni) are text strings and they are separated by the blank character.
  
  Examples
  --------
  .. sourcecode:: pycon
  
      >>> from gensim.test.utils import get_tmpfile, common_texts
      >>> from gensim.corpora import LowCorpus
      >>> from gensim.corpora import Dictionary
      >>>
      >>> # Prepare needed data
      >>> dictionary = Dictionary(common_texts)
      >>> corpus = [dictionary.doc2bow(doc) for doc in common_texts]
      >>>
      >>> # Write corpus in GibbsLda++ format to disk
      >>> output_fname = get_tmpfile("corpus.low")
      >>> LowCorpus.serialize(output_fname, corpus, dictionary)
      >>>
      >>> # Read corpus
      >>> loaded_corpus = LowCorpus(output_fname)
class_docstr_tok: ["Corpus","handles","input","in","`","GibbsLda++","format","<","https",":","\/\/gibbslda.sourceforge.net\/",">","`","_",".","*","*","Format","description","*","*","Both","data","for","training\/estimating","the","model","and","new","data","(","i.e.",",","previously","unseen","data",")","have","the","same","format","as","follows",":",":","[","M","]","[","document1","]","[","document2","]","...","[","documentM","]","in","which","the","first","line","is","the","total","number","for","documents","[","M","]",".","Each","line","after","that","is","one","document",".","[","documenti","]","is","the","ith","document","of","the","dataset","that","consists","of","a","list","of","Ni","words\/terms",":",":","[","documenti","]","=","[","wordi1","]","[","wordi2","]","...","[","wordiNi","]","in","which","all","[","wordij","]","(","i=1","..","M",",","j=1","..","Ni",")","are","text","strings","and","they","are","separated","by","the","blank","character",".","Examples","--","--","--","--","..","sourcecode",":",":","pycon",">",">",">","from","gensim.test.utils","import","get_tmpfile",",","common_texts",">",">",">","from","gensim.corpora","import","LowCorpus",">",">",">","from","gensim.corpora","import","Dictionary",">",">",">",">",">",">","#","Prepare","needed","data",">",">",">","dictionary","=","Dictionary","(","common_texts",")",">",">",">","corpus","=","[","dictionary.doc2bow","(","doc",")","for","doc","in","common_texts","]",">",">",">",">",">",">","#","Write","corpus","in","GibbsLda++","format","to","disk",">",">",">","output_fname","=","get_tmpfile","(","``","corpus.low","''",")",">",">",">","LowCorpus.serialize","(","output_fname",",","corpus",",","dictionary",")",">",">",">",">",">",">","#","Read","corpus",">",">",">","loaded_corpus","=","LowCorpus","(","output_fname",")"]
docstr: Get mapping between words and their ids.
docstr_tok: ["Get","mapping","between","words","and","their","ids","."]
code: def id2word(self):
      """Get mapping between words and their ids."""
      return self._id2word
  
file_path: gensim/gensim/corpora/lowcorpus.py
imports: import logging
  from collections import Counter
  from gensim import utils
  from gensim.corpora import IndexedCorpus
  from gensim.parsing.preprocessing import split_on_space
label_desc: Use image node_id 8 for calling the LowCorpus obj's underlying member method code with example usage: obj.id2word() and returns: self