Remove outdated bz2 examples from tutorials[2] (#1868)

* Revert "Remove outdated `bz2` + `MmCorpus` examples from tutorials (#1867)"

This reverts commit 5342153.

* remove bz2 wrapper

* remove bz2 wrapper[2]

docs/src/dist_lsi.rst

@@ -127,6 +127,7 @@ the corpus iterator with::
     >>> id2word = gensim.corpora.Dictionary.load_from_text('wiki_en_wordids.txt')
     >>> # load corpus iterator
     >>> mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm')
+    >>> # mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm.bz2') # use this if you compressed the TFIDF output
 
     >>> print(mm)
     MmCorpus(3199665 documents, 100000 features, 495547400 non-zero entries)

docs/src/wiki.rst

@@ -45,6 +45,7 @@ First let's load the corpus iterator and dictionary, created in the second step
     >>> id2word = gensim.corpora.Dictionary.load_from_text('wiki_en_wordids.txt')
     >>> # load corpus iterator
     >>> mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm')
+    >>> # mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm.bz2') # use this if you compressed the TFIDF output (recommended)
 
     >>> print(mm)
     MmCorpus(3931787 documents, 100000 features, 756379027 non-zero entries)
@@ -99,6 +100,7 @@ As with Latent Semantic Analysis above, first load the corpus iterator and dicti
     >>> id2word = gensim.corpora.Dictionary.load_from_text('wiki_en_wordids.txt')
     >>> # load corpus iterator
     >>> mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm')
+    >>> # mm = gensim.corpora.MmCorpus('wiki_en_tfidf.mm.bz2') # use this if you compressed the TFIDF output
 
     >>> print(mm)
     MmCorpus(3931787 documents, 100000 features, 756379027 non-zero entries)