class_docstr: Corpus in Blei's LDA-C format.
  
  The corpus is represented as two files: one describing the documents, and another
  describing the mapping between words and their ids.
  
  Each document is one line::
  
      N fieldId1:fieldValue1 fieldId2:fieldValue2 ... fieldIdN:fieldValueN
  
  
  The vocabulary is a file with words, one word per line; word at line K has an implicit `id=K`.
class_docstr_tok: ["Corpus","in","Blei","'s","LDA-C","format",".","The","corpus","is","represented","as","two","files",":","one","describing","the","documents",",","and","another","describing","the","mapping","between","words","and","their","ids",".","Each","document","is","one","line",":",":","N","fieldId1",":","fieldValue1","fieldId2",":","fieldValue2","...","fieldIdN",":","fieldValueN","The","vocabulary","is","a","file","with","words",",","one","word","per","line",";","word","at","line","K","has","an","implicit","`","id=K","`","."]
docstr: Iterate over the corpus, returning one sparse (BoW) vector at a time.
  
  Yields
  ------
  list of (int, float)
      Document's BoW representation.
docstr_tok: ["Iterate","over","the","corpus",",","returning","one","sparse","(","BoW",")","vector","at","a","time",".","Yields","--","--","--","list","of","(","int",",","float",")","Document","'s","BoW","representation","."]
code: def __iter__(self):
      """Iterate over the corpus, returning one sparse (BoW) vector at a time.
  
      Yields
      ------
      list of (int, float)
          Document's BoW representation.
  
      """
      lineno = -1
      with utils.open(self.fname, "rb") as fin:
          for lineno, line in enumerate(fin):
              yield self.line2doc(line)
      self.length = lineno + 1
  
file_path: gensim/gensim/corpora/bleicorpus.py
imports: from __future__ import with_statement
  from os import path
  import logging
  from gensim import utils
  from gensim.corpora import IndexedCorpus
label_desc: Use image node_id 2 for calling the BleiCorpus obj's underlying member method code with example usage: obj.__iter__() without return types