# Buggy code
def evaluate_word_pairs(
    self,
    pairs,
    delimiter="\t",
    restrict_vocab=300000,
    case_insensitive=True,
    dummy4unknown=False,
):
    """
    Compute correlation of the model with human similarity judgments. `pairs` is a filename of a dataset where
    lines are 3-tuples, each consisting of a word pair and a similarity value, separated by `delimiter'.
    An example dataset is included in Gensim (test/test_data/wordsim353.tsv). More datasets can be found at
    http://technion.ac.il/~ira.leviant/MultilingualVSMdata.html or https://www.cl.cam.ac.uk/~fh295/simlex.html.

    The model is evaluated using Pearson correlation coefficient and Spearman rank-order correlation coefficient
    between the similarities from the dataset and the similarities produced by the model itself.
    The results are printed to log and returned as a triple (pearson, spearman, ratio of pairs with unknown words).

    Use `restrict_vocab` to ignore all word pairs containing a word not in the first `restrict_vocab`
    words (default 300,000). This may be meaningful if you've sorted the vocabulary by descending frequency.
    If `case_insensitive` is True, the first `restrict_vocab` words are taken, and then case normalization
    is performed.

    Use `case_insensitive` to convert all words in the pairs and vocab to their uppercase form before
    evaluating the model (default True). Useful when you expect case-mismatch between training tokens
    and words pairs in the dataset. If there are multiple case variants of a single word, the vector for the first
    occurrence (also the most frequent if vocabulary is sorted) is taken.

    Use `dummy4unknown=True' to produce zero-valued similarities for pairs with out-of-vocabulary words.
    Otherwise (default False), these pairs are skipped entirely.
    """
    ok_vocab = [(w, self.vocab[w]) for w in self.index2word[:restrict_vocab]]
    ok_vocab = (
        dict((w.upper(), v) for w, v in reversed(ok_vocab))
        if case_insensitive
        else dict(ok_vocab)
    )

    similarity_gold = []
    similarity_model = []
    oov = 0

    original_vocab = self.vocab
    self.vocab = ok_vocab

    for line_no, line in enumerate(utils.smart_open(pairs)):
        line = utils.to_unicode(line)
        if line.startswith("#"):
            # May be a comment
            continue
        else:
            try:
                if case_insensitive:
                    a, b, sim = [word.upper() for word in line.split(delimiter)]
                else:
                    a, b, sim = [word for word in line.split(delimiter)]
                sim = float(sim)
            except:
                logger.info("skipping invalid line #%d in %s", line_no, pairs)
                continue
            if a not in ok_vocab or b not in ok_vocab:
                oov += 1
                if dummy4unknown:
                    similarity_model.append(0.0)
                    similarity_gold.append(sim)
                    continue
                else:
                    logger.debug(
                        "skipping line #%d with OOV words: %s", line_no, line.strip()
                    )
                    continue
            similarity_gold.append(sim)  # Similarity from the dataset
            similarity_model.append(self.similarity(a, b))  # Similarity from the model
    self.vocab = original_vocab
    spearman = stats.spearmanr(similarity_gold, similarity_model)
    pearson = stats.pearsonr(similarity_gold, similarity_model)
    oov_ratio = float(oov) / (len(similarity_gold) + oov) * 100

    logger.debug(
        "Pearson correlation coefficient against %s: %f with p-value %f",
        pairs,
        pearson[0],
        pearson[1],
    )
    logger.debug(
        "Spearman rank-order correlation coefficient against %s: %f with p-value %f",
        pairs,
        spearman[0],
        spearman[1],
    )
    logger.debug("Pairs with unknown words: %d" % oov)
    self.log_evaluate_word_pairs(pearson, spearman, oov_ratio, pairs)
    return pearson, spearman, oov_ratio


# Traceback (ImportError)
rm -rf _build/*
sphinx-build -b html -d _build/doctrees   . _build/html
Running Sphinx v1.5.3
making output directory...
loading pickled environment... not yet created
building [mo]: targets for 0 po files that are out of date
building [html]: targets for 82 source files that are out of date
updating environment: 82 added, 0 changed, 0 removed
reading sources... [  1%] about
reading sources... [  2%] apiref
reading sources... [  3%] changes_080
reading sources... [  4%] corpora/bleicorpus
reading sources... [  6%] corpora/corpora
reading sources... [  7%] corpora/csvcorpus
reading sources... [  8%] corpora/dictionary
reading sources... [  9%] corpora/hashdictionary
reading sources... [ 10%] corpora/indexedcorpus
reading sources... [ 12%] corpora/lowcorpus
reading sources... [ 13%] corpora/malletcorpus
reading sources... [ 14%] corpora/mmcorpus
reading sources... [ 15%] corpora/sharded_corpus
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/_max_len_seq.py:8: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from ._max_len_seq_inner import _max_len_seq_inner
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/_max_len_seq.py:8: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from ._max_len_seq_inner import _max_len_seq_inner
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/_upfirdn.py:36: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from ._upfirdn_apply import _output_len, _apply
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/_upfirdn.py:36: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from ._upfirdn_apply import _output_len, _apply
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/spatial/__init__.py:93: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from .ckdtree import *
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/spatial/__init__.py:93: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from .ckdtree import *
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/spatial/__init__.py:94: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from .qhull import *
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/spatial/__init__.py:94: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from .qhull import *
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/ndimage/measurements.py:36: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from . import _ni_label
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/ndimage/measurements.py:36: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from . import _ni_label
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/spectral.py:10: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  from ._spectral import lombscargle
/home/lev/miniconda2/lib/python2.7/site-packages/scipy/signal/spectral.py:10: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192, got 176
  from ._spectral import lombscargle
reading sources... [ 17%] corpora/svmlightcorpus
reading sources... [ 18%] corpora/textcorpus
reading sources... [ 19%] corpora/ucicorpus
reading sources... [ 20%] corpora/wikicorpus
reading sources... [ 21%] dist_lda
reading sources... [ 23%] dist_lsi
reading sources... [ 24%] distributed
reading sources... [ 25%] indextoc
reading sources... [ 26%] install
reading sources... [ 28%] interfaces
reading sources... [ 29%] intro
reading sources... [ 30%] matutils
reading sources... [ 31%] models/atmodel
reading sources... [ 32%] models/coherencemodel
reading sources... [ 34%] models/doc2vec
reading sources... [ 35%] models/hdpmodel
reading sources... [ 36%] models/keyedvectors
reading sources... [ 37%] models/lda_dispatcher
reading sources... [ 39%] models/lda_worker
reading sources... [ 40%] models/ldamodel
reading sources... [ 41%] models/ldamulticore
reading sources... [ 42%] models/ldaseqmodel
reading sources... [ 43%] models/logentropy_model
reading sources... [ 45%] models/lsi_dispatcher
reading sources... [ 46%] models/lsi_worker
reading sources... [ 47%] models/lsimodel
reading sources... [ 48%] models/models
reading sources... [ 50%] models/normmodel
reading sources... [ 51%] models/phrases
reading sources... [ 52%] models/rpmodel
reading sources... [ 53%] models/tfidfmodel
reading sources... [ 54%] models/word2vec
reading sources... [ 56%] models/wrappers/dtmmodel
reading sources... [ 57%] models/wrappers/fasttext
reading sources... [ 58%] models/wrappers/ldamallet
reading sources... [ 59%] models/wrappers/ldavowpalwabbit
reading sources... [ 60%] models/wrappers/varembed
reading sources... [ 62%] models/wrappers/wordrank
reading sources... [ 63%] models/wrappers/wrappers
reading sources... [ 64%] parsing/porter
reading sources... [ 65%] parsing/preprocessing
reading sources... [ 67%] scripts/glove2word2vec
reading sources... [ 68%] scripts/make_wikicorpus
reading sources... [ 69%] scripts/word2vec_standalone
reading sources... [ 70%] similarities/docsim
reading sources... [ 71%] similarities/index
reading sources... [ 73%] similarities/simserver
reading sources... [ 74%] simserver
reading sources... [ 75%] sklearn_integration/sklearn_wrapper_gensim_ldamodel
reading sources... [ 76%] summarization/bm25
reading sources... [ 78%] summarization/commons
reading sources... [ 79%] summarization/graph
reading sources... [ 80%] summarization/keywords
reading sources... [ 81%] summarization/pagerank_weighted
reading sources... [ 82%] summarization/summariser
reading sources... [ 84%] summarization/syntactic_unit
reading sources... [ 85%] summarization/textcleaner
reading sources... [ 86%] support
reading sources... [ 87%] topic_coherence/aggregation
reading sources... [ 89%] topic_coherence/direct_confirmation_measure
reading sources... [ 90%] topic_coherence/indirect_confirmation_measure
reading sources... [ 91%] topic_coherence/probability_estimation
reading sources... [ 92%] topic_coherence/segmentation
reading sources... [ 93%] tut1
reading sources... [ 95%] tut2
reading sources... [ 96%] tut3
reading sources... [ 97%] tutorial
reading sources... [ 98%] utils
reading sources... [100%] wiki

/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/corpora/malletcorpus.rst:2: WARNING: Title underline too short.

:mod:`corpora.malletcorpus` -- Corpus in Mallet format of List-Of-Words.
==========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/corpora/sharded_corpus.rst:2: WARNING: Title underline too short.

:mod:`corpora.sharded_corpus` -- Corpus stored in separate files
==========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/install.rst:118: WARNING: nonlocal image URI found: https://api.travis-ci.org/piskvorky/gensim.png?branch=develop
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/install.rst:118: WARNING: nonlocal image URI found: https://api.travis-ci.org/piskvorky/gensim.png?branch=develop
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel:10: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel:11: WARNING: Explicit markup ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:25: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:25: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:39: WARNING: Definition list ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:41: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:42: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/coherencemodel.py:docstring of gensim.models.coherencemodel.CoherenceModel:55: WARNING: Definition list ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/keyedvectors.py:docstring of gensim.models.keyedvectors.KeyedVectors.evaluate_word_pairs:1: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/keyedvectors.py:docstring of gensim.models.keyedvectors.KeyedVectors.evaluate_word_pairs:20: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/models/ldaseqmodel.rst:2: WARNING: Title underline too short.

:mod:`models.ldaseqmodel` -- Dynamic Topic Modeling in Python
================================
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/ldaseqmodel.py:docstring of gensim.models.ldaseqmodel.LdaSeqModel.fit_lda_seq:6: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/ldaseqmodel.py:docstring of gensim.models.ldaseqmodel.sslm.compute_post_variance:5: WARNING: Inline substitution_reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/ldaseqmodel.py:docstring of gensim.models.ldaseqmodel.sslm.compute_post_variance:8: WARNING: Inline substitution_reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/word2vec.py:docstring of gensim.models.word2vec:31: WARNING: Literal block expected; none found.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/word2vec.py:docstring of gensim.models.word2vec.Word2Vec.score:13: WARNING: duplicate citation taddy, other instance in /home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/models/doc2vec.rst
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/word2vec.py:docstring of gensim.models.word2vec.Word2Vec.score:14: WARNING: duplicate citation deepir, other instance in /home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/models/doc2vec.rst
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/dtmmodel.py:docstring of gensim.models.wrappers.dtmmodel.DtmModel.dtm_coherence:4: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/fasttext.py:docstring of gensim.models.wrappers.fasttext.FastTextKeyedVectors.evaluate_word_pairs:1: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/fasttext.py:docstring of gensim.models.wrappers.fasttext.FastTextKeyedVectors.evaluate_word_pairs:20: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/fasttext.py:docstring of gensim.models.wrappers.fasttext.FastText.score:13: WARNING: duplicate citation taddy, other instance in /home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/models/word2vec.rst
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/fasttext.py:docstring of gensim.models.wrappers.fasttext.FastText.score:14: WARNING: duplicate citation deepir, other instance in /home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/models/word2vec.rst
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldamallet.py:docstring of gensim.models.wrappers.ldamallet.malletmodel2ldamodel:6: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldamallet.py:docstring of gensim.models.wrappers.ldamallet.malletmodel2ldamodel:6: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldamallet.py:docstring of gensim.models.wrappers.ldamallet.malletmodel2ldamodel:12: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldamallet.py:docstring of gensim.models.wrappers.ldamallet.malletmodel2ldamodel:12: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldavowpalwabbit.py:docstring of gensim.models.wrappers.ldavowpalwabbit.vwmodel2ldamodel:6: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldavowpalwabbit.py:docstring of gensim.models.wrappers.ldavowpalwabbit.vwmodel2ldamodel:6: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldavowpalwabbit.py:docstring of gensim.models.wrappers.ldavowpalwabbit.vwmodel2ldamodel:11: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/ldavowpalwabbit.py:docstring of gensim.models.wrappers.ldavowpalwabbit.vwmodel2ldamodel:11: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/varembed.py:docstring of gensim.models.wrappers.varembed.VarEmbed.evaluate_word_pairs:1: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/varembed.py:docstring of gensim.models.wrappers.varembed.VarEmbed.evaluate_word_pairs:20: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/wordrank.py:docstring of gensim.models.wrappers.wordrank.Wordrank.evaluate_word_pairs:1: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/models/wrappers/wordrank.py:docstring of gensim.models.wrappers.wordrank.Wordrank.evaluate_word_pairs:20: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/parsing/preprocessing.rst:2: WARNING: Title underline too short.

:mod:`parsing.preprocessing` -- Functions to preprocess raw text
=========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/scripts/glove2word2vec.rst:2: WARNING: Title underline too short.

:mod:`scripts.glove2word2vec` -- Convert glove format to word2vec
=========================================================
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/scripts/glove2word2vec.py:docstring of gensim.scripts.glove2word2vec:3: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/scripts/glove2word2vec.py:docstring of gensim.scripts.glove2word2vec.glove2word2vec:1: WARNING: Inline interpreted text or phrase reference start-string without end-string.
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/scripts/make_wikicorpus.rst:2: WARNING: Title underline too short.

:mod:`scripts.make_wikicorpus` -- Convert articles from a Wikipedia dump to vectors.
=========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/scripts/word2vec_standalone.rst:2: WARNING: Title underline too short.

:mod:`scripts.word2vec_standalone` -- Train word2vec on text file CORPUS
=========================================================
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/similarities/docsim.py:docstring of gensim.similarities.docsim.WmdSimilarity:28: ERROR: Unexpected indentation.
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/similarities/index.rst:2: WARNING: Title underline too short.

:mod:`similarities.index` -- Fast Approximate Nearest Neighbor Similarity with Annoy package
========================================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/similarities/simserver.rst:4: WARNING: autodoc: failed to import module u'simserver.simserver'; the following exception was raised:
Traceback (most recent call last):
  File "/home/lev/miniconda2/lib/python2.7/site-packages/sphinx/ext/autodoc.py", line 551, in import_object
    __import__(self.modname)
ImportError: No module named simserver.simserver
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/sklearn_integration/sklearn_wrapper_gensim_ldamodel.rst:2: WARNING: Title underline too short.

:mod:`sklearn_integration.sklearn_wrapper_gensim_ldamodel.SklearnWrapperLdaModel` -- Scikit learn wrapper for Latent Dirichlet Allocation
======================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/sklearn_integration/sklearn_wrapper_gensim_ldamodel.rst:4: WARNING: autodoc: failed to import module u'gensim.sklearn_integration.sklearn_wrapper_gensim_ldamodel.SklearnWrapperLdaModel'; the following exception was raised:
Traceback (most recent call last):
  File "/home/lev/miniconda2/lib/python2.7/site-packages/sphinx/ext/autodoc.py", line 551, in import_object
    __import__(self.modname)
ImportError: No module named SklearnWrapperLdaModel
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/summarization/keywords.rst:2: WARNING: Title underline too short.

:mod:`summarization.keywords` -- Keywords for TextRank summarization algorithm
=========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/summarization/pagerank_weighted.rst:2: WARNING: Title underline too short.

:mod:`summarization.pagerank_weighted` -- Weighted PageRank algorithm
=========================================================
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/summarization/summarizer.py:docstring of gensim.summarization.summarizer.summarize:13: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/summarization/summarizer.py:docstring of gensim.summarization.summarizer.summarize:14: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/summarization/summarizer.py:docstring of gensim.summarization.summarizer.summarize:16: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/summarization/summarizer.py:docstring of gensim.summarization.summarizer.summarize:17: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/summarization/syntactic_unit.rst:2: WARNING: Title underline too short.

:mod:`summarization.syntactic_unit` -- Syntactic Unit class
=========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/summarization/textcleaner.rst:2: WARNING: Title underline too short.

:mod:`summarization.textcleaner` -- Summarization pre-processing
=========================================================
/home/lev/Dropbox/raretech/os/release/fix/gensim/docs/src/summarization/textcleaner.rst:10: WARNING: Explicit markup ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/aggregation.py:docstring of gensim.topic_coherence.aggregation.arithmetic_mean:5: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/aggregation.py:docstring of gensim.topic_coherence.aggregation.arithmetic_mean:5: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/aggregation.py:docstring of gensim.topic_coherence.aggregation.arithmetic_mean:9: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/aggregation.py:docstring of gensim.topic_coherence.aggregation.arithmetic_mean:9: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_conditional_probability:6: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_conditional_probability:6: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_conditional_probability:12: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_conditional_probability:12: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_ratio_measure:13: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_ratio_measure:13: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_ratio_measure:19: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/direct_confirmation_measure.py:docstring of gensim.topic_coherence.direct_confirmation_measure.log_ratio_measure:19: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:4: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:5: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:8: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:12: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:15: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:15: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:24: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/indirect_confirmation_measure.py:docstring of gensim.topic_coherence.indirect_confirmation_measure.cosine_similarity:24: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_document:5: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_document:5: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_document:10: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_document:10: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_sliding_window:7: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_sliding_window:7: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_sliding_window:14: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/probability_estimation.py:docstring of gensim.topic_coherence.probability_estimation.p_boolean_sliding_window:14: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:3: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:4: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:11: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:11: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:15: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_one:15: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:3: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:4: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:11: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:11: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:15: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_pre:15: SEVERE: Unexpected section title.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:3: ERROR: Unexpected indentation.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:4: WARNING: Block quote ends without a blank line; unexpected unindent.
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:12: WARNING: Title underline too short.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:12: SEVERE: Unexpected section title.

Args:
----
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:16: WARNING: Title underline too short.

Returns:
-------
/home/lev/miniconda2/lib/python2.7/site-packages/gensim-1.0.1-py2.7-linux-x86_64.egg/gensim/topic_coherence/segmentation.py:docstring of gensim.topic_coherence.segmentation.s_one_set:16: SEVERE: Unexpected section title.

Returns:
-------
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# Fixed code
def evaluate_word_pairs(
    self,
    pairs,
    delimiter="\t",
    restrict_vocab=300000,
    case_insensitive=True,
    dummy4unknown=False,
):
    """
    Compute correlation of the model with human similarity judgments. `pairs` is a filename of a dataset where
    lines are 3-tuples, each consisting of a word pair and a similarity value, separated by `delimiter`.
    An example dataset is included in Gensim (test/test_data/wordsim353.tsv). More datasets can be found at
    http://technion.ac.il/~ira.leviant/MultilingualVSMdata.html or https://www.cl.cam.ac.uk/~fh295/simlex.html.

    The model is evaluated using Pearson correlation coefficient and Spearman rank-order correlation coefficient
    between the similarities from the dataset and the similarities produced by the model itself.
    The results are printed to log and returned as a triple (pearson, spearman, ratio of pairs with unknown words).

    Use `restrict_vocab` to ignore all word pairs containing a word not in the first `restrict_vocab`
    words (default 300,000). This may be meaningful if you've sorted the vocabulary by descending frequency.
    If `case_insensitive` is True, the first `restrict_vocab` words are taken, and then case normalization
    is performed.

    Use `case_insensitive` to convert all words in the pairs and vocab to their uppercase form before
    evaluating the model (default True). Useful when you expect case-mismatch between training tokens
    and words pairs in the dataset. If there are multiple case variants of a single word, the vector for the first
    occurrence (also the most frequent if vocabulary is sorted) is taken.

    Use `dummy4unknown=True` to produce zero-valued similarities for pairs with out-of-vocabulary words.
    Otherwise (default False), these pairs are skipped entirely.
    """
    ok_vocab = [(w, self.vocab[w]) for w in self.index2word[:restrict_vocab]]
    ok_vocab = (
        dict((w.upper(), v) for w, v in reversed(ok_vocab))
        if case_insensitive
        else dict(ok_vocab)
    )

    similarity_gold = []
    similarity_model = []
    oov = 0

    original_vocab = self.vocab
    self.vocab = ok_vocab

    for line_no, line in enumerate(utils.smart_open(pairs)):
        line = utils.to_unicode(line)
        if line.startswith("#"):
            # May be a comment
            continue
        else:
            try:
                if case_insensitive:
                    a, b, sim = [word.upper() for word in line.split(delimiter)]
                else:
                    a, b, sim = [word for word in line.split(delimiter)]
                sim = float(sim)
            except:
                logger.info("skipping invalid line #%d in %s", line_no, pairs)
                continue
            if a not in ok_vocab or b not in ok_vocab:
                oov += 1
                if dummy4unknown:
                    similarity_model.append(0.0)
                    similarity_gold.append(sim)
                    continue
                else:
                    logger.debug(
                        "skipping line #%d with OOV words: %s", line_no, line.strip()
                    )
                    continue
            similarity_gold.append(sim)  # Similarity from the dataset
            similarity_model.append(self.similarity(a, b))  # Similarity from the model
    self.vocab = original_vocab
    spearman = stats.spearmanr(similarity_gold, similarity_model)
    pearson = stats.pearsonr(similarity_gold, similarity_model)
    oov_ratio = float(oov) / (len(similarity_gold) + oov) * 100

    logger.debug(
        "Pearson correlation coefficient against %s: %f with p-value %f",
        pairs,
        pearson[0],
        pearson[1],
    )
    logger.debug(
        "Spearman rank-order correlation coefficient against %s: %f with p-value %f",
        pairs,
        spearman[0],
        spearman[1],
    )
    logger.debug("Pairs with unknown words: %d" % oov)
    self.log_evaluate_word_pairs(pearson, spearman, oov_ratio, pairs)
    return pearson, spearman, oov_ratio