Failed
dariah_topics.postprocessing._ (from nosetests)
Failing for the past 1 build
(Since Failed )
Error Message
Failed doctest test for dariah_topics.postprocessing._ File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 254, in _ ---------------------------------------------------------------------- File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 272, in dariah_topics.postprocessing._ Failed example: sparse_bow = create_sparse_bow(doc_labels, doc_tokens, type_dictionary, doc_dictionary) Exception raised: Traceback (most recent call last): File "/usr/lib/python3.5/doctest.py", line 1321, in __run compileflags, 1), test.globs) File "<doctest dariah_topics.postprocessing._[4]>", line 1, in <module> sparse_bow = create_sparse_bow(doc_labels, doc_tokens, type_dictionary, doc_dictionary) NameError: name 'create_sparse_bow' is not defined ---------------------------------------------------------------------- File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 279, in dariah_topics.postprocessing._ Failed example: make_doc2bow_list(sparse_bow) Exception raised: Traceback (most recent call last): File "/usr/lib/python3.5/doctest.py", line 1321, in __run compileflags, 1), test.globs) File "<doctest dariah_topics.postprocessing._[11]>", line 1, in <module> make_doc2bow_list(sparse_bow) NameError: name 'make_doc2bow_list' is not defined -------------------- >> begin captured logging << -------------------- gensim.models.doc2vec: DEBUG: Fast version of gensim.models.doc2vec is being used summa.preprocessing.cleaner: INFO: 'pattern' package not found; tag filters are not available for English gensim.corpora.dictionary: INFO: adding document #0 to Dictionary(0 unique tokens: []) gensim.corpora.dictionary: INFO: built Dictionary(4 unique tokens: ['test', 'corpus', 'testing', 'for']) from 2 documents (total 4 corpus positions) gensim.models.ldamodel: INFO: using symmetric alpha at 1.0 gensim.models.ldamodel: INFO: using symmetric eta at 0.25 gensim.models.ldamodel: INFO: using serial LDA version on this node gensim.models.ldamodel: INFO: running online (single-pass) LDA training, 1 topics, 1 passes over the supplied corpus of 2 documents, updating model once every 2 documents, evaluating perplexity every 2 documents, iterating 1x with a convergence threshold of 0.001000 gensim.models.ldamodel: WARNING: too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy gensim.models.ldamodel: DEBUG: bound: at document #0 gensim.models.ldamodel: INFO: -1.689 per-word bound, 3.2 perplexity estimate based on a held-out corpus of 2 documents with 4 words gensim.models.ldamodel: INFO: PROGRESS: pass 0, at document #2/2 gensim.models.ldamodel: DEBUG: performing inference on a chunk of 2 documents gensim.models.ldamodel: DEBUG: 0/2 documents converged within 1 iterations gensim.models.ldamodel: DEBUG: updating topics gensim.models.ldamodel: INFO: topic #0 (1.000): 0.250*"test" + 0.250*"corpus" + 0.250*"for" + 0.250*"testing" gensim.models.ldamodel: INFO: topic diff=0.241321, rho=1.000000 --------------------- >> end captured logging << ---------------------
Stacktrace
File "/usr/lib/python3.5/unittest/case.py", line 59, in testPartExecutor yield File "/usr/lib/python3.5/unittest/case.py", line 601, in run testMethod() File "/usr/lib/python3.5/doctest.py", line 2190, in runTest raise self.failureException(self.format_failure(new.getvalue())) Failed doctest test for dariah_topics.postprocessing._ File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 254, in _ ---------------------------------------------------------------------- File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 272, in dariah_topics.postprocessing._ Failed example: sparse_bow = create_sparse_bow(doc_labels, doc_tokens, type_dictionary, doc_dictionary) Exception raised: Traceback (most recent call last): File "/usr/lib/python3.5/doctest.py", line 1321, in __run compileflags, 1), test.globs) File "<doctest dariah_topics.postprocessing._[4]>", line 1, in <module> sparse_bow = create_sparse_bow(doc_labels, doc_tokens, type_dictionary, doc_dictionary) NameError: name 'create_sparse_bow' is not defined ---------------------------------------------------------------------- File "/mnt/data/jenkins/workspace/DARIAH-Topics/dariah_topics/postprocessing.py", line 279, in dariah_topics.postprocessing._ Failed example: make_doc2bow_list(sparse_bow) Exception raised: Traceback (most recent call last): File "/usr/lib/python3.5/doctest.py", line 1321, in __run compileflags, 1), test.globs) File "<doctest dariah_topics.postprocessing._[11]>", line 1, in <module> make_doc2bow_list(sparse_bow) NameError: name 'make_doc2bow_list' is not defined -------------------- >> begin captured logging << -------------------- gensim.models.doc2vec: DEBUG: Fast version of gensim.models.doc2vec is being used summa.preprocessing.cleaner: INFO: 'pattern' package not found; tag filters are not available for English gensim.corpora.dictionary: INFO: adding document #0 to Dictionary(0 unique tokens: []) gensim.corpora.dictionary: INFO: built Dictionary(4 unique tokens: ['test', 'corpus', 'testing', 'for']) from 2 documents (total 4 corpus positions) gensim.models.ldamodel: INFO: using symmetric alpha at 1.0 gensim.models.ldamodel: INFO: using symmetric eta at 0.25 gensim.models.ldamodel: INFO: using serial LDA version on this node gensim.models.ldamodel: INFO: running online (single-pass) LDA training, 1 topics, 1 passes over the supplied corpus of 2 documents, updating model once every 2 documents, evaluating perplexity every 2 documents, iterating 1x with a convergence threshold of 0.001000 gensim.models.ldamodel: WARNING: too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy gensim.models.ldamodel: DEBUG: bound: at document #0 gensim.models.ldamodel: INFO: -1.689 per-word bound, 3.2 perplexity estimate based on a held-out corpus of 2 documents with 4 words gensim.models.ldamodel: INFO: PROGRESS: pass 0, at document #2/2 gensim.models.ldamodel: DEBUG: performing inference on a chunk of 2 documents gensim.models.ldamodel: DEBUG: 0/2 documents converged within 1 iterations gensim.models.ldamodel: DEBUG: updating topics gensim.models.ldamodel: INFO: topic #0 (1.000): 0.250*"test" + 0.250*"corpus" + 0.250*"for" + 0.250*"testing" gensim.models.ldamodel: INFO: topic diff=0.241321, rho=1.000000 --------------------- >> end captured logging << ---------------------