Merge branch 'release-3.0.1'

Author: menshikh-iv

CHANGELOG.md

@@ -1,5 +1,38 @@
 Changes
 ===========
+## 3.0.1, 2017-10-12
+
+
+:red_circle: Bug fixes:
+* Fix Keras import, speedup importing time. Fix #1614 (@menshikh-v, [#1615](https://github.com/RaRe-Technologies/gensim/pull/1615))
+* Fix Sphinx warnings and retreive all missing .rst (@anotherbugmaster and @menshikh-iv, [#1612](https://github.com/RaRe-Technologies/gensim/pull/1612))
+* Fix logger message in lsi_dispatcher (@lorosanu, [#1603](https://github.com/RaRe-Technologies/gensim/pull/1603))
+
+
+:books: Tutorial and doc improvements:
+* Fix spelling (@jberkel, [#1625](https://github.com/RaRe-Technologies/gensim/pull/1625))
+
+:warning: Deprecation part (will come into force in the next release)
+* Remove
+	- `gensim.examples`
+	- `gensim.nosy`
+	- `gensim.scripts.word2vec_standalone`
+	- `gensim.scripts.make_wiki_lemma`
+	- `gensim.scripts.make_wiki_online`
+	- `gensim.scripts.make_wiki_online_lemma`
+	- `gensim.scripts.make_wiki_online_nodebug`
+	- `gensim.scripts.make_wiki`
+
+* Move
+	- `gensim.scripts.make_wikicorpus` ➡ `gensim.scripts.make_wiki.py`
+	- `gensim.summarization` ➡ `gensim.models.summarization`
+	- `gensim.topic_coherence` ➡ `gensim.models._coherence`
+	- `gensim.utils` ➡ `gensim.utils.utils` (old imports will continue to work)
+	- `gensim.parsing.*` ➡ `gensim.utils.text_utils`
+
+Also, we'll create `experimental` subpackage for unstable models. Specific lists will be available in the next release.
+
+
 ## 3.0.0, 2017-09-27
 
 

continuous_integration/travis/flake8_diff.sh

@@ -153,3 +153,6 @@ else
         jupyter nbconvert --to script --stdout ${fname} | flake8 - --show-source --ignore=E501,E731,E12,W503,E402 --builtins=get_ipython || true
     done
 fi
+
+echo "Build documentation"
+pip install .[docs] && cd docs/src && make clean html

docs/notebooks/FastText_Tutorial.ipynb

@@ -279,7 +279,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The word vector lookup operation only works if atleast one of the component character ngrams is present in the training corpus. For example -"
+    "The word vector lookup operation only works if at least one of the component character ngrams is present in the training corpus. For example -"
    ]
   },
   {
@@ -346,7 +346,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Similarity operations work the same way as word2vec. **Out-of-vocabulary words can also be used, provided they have atleast one character ngram present in the training data.**"
+    "Similarity operations work the same way as word2vec. **Out-of-vocabulary words can also be used, provided they have at least one character ngram present in the training data.**"
    ]
   },
   {

docs/notebooks/Word2Vec_FastText_Comparison.ipynb

@@ -466,7 +466,7 @@
     "Both these subtractions would result in a very similar set of remaining ngrams.\n",
     "No surprise the fastText embeddings do extremely well on this.\n",
     "\n",
-    "Let's do a small test to validate this hypothesis - fastText differs from word2vec only in that it uses char n-gram embeddings as well as the actual word embedding in the scoring function to calculate scores and then likelihoods for each word, given a context word. In case char n-gram embeddings are not present, this reduces (atleast theoretically) to the original word2vec model. This can be implemented by setting 0 for the max length of char n-grams for fastText.\n"
+    "Let's do a small test to validate this hypothesis - fastText differs from word2vec only in that it uses char n-gram embeddings as well as the actual word embedding in the scoring function to calculate scores and then likelihoods for each word, given a context word. In case char n-gram embeddings are not present, this reduces (at least theoretically) to the original word2vec model. This can be implemented by setting 0 for the max length of char n-grams for fastText.\n"
    ]
   },
   {
@@ -1081,4 +1081,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}