Comments (4)
You may notice the 'word2vec_inner.pyx' file. This is the code of cython which have been modified by author. You need to compile it at first, then you can import 'train_sentence_topic' defined in it.
Give more hints you may feel useful when running code.
- In all three models, author have modified the source code of gensim and included them, so you needn't to install the gensim by yourself.
- I failed to compile the word2vec_inner.pyx.pyx in the original folder. Then I only copied the word2vec_inner.pyx and head file to new folder. It succeed this time.
- If you have compiled the *.pyx, only import the word2_inner.pyx is enough. You can delete import 'pyximport' that can prevent some errors.
- When compiling *.pyx, you may meet the the error of scipy ‘from scipy.... import fabls’, it may happen for the version of scipy. You can change the code, in word2vec_inner.pyx, 'from 'scipy.linalg.blas import fblas' to 'import scipy.linalg.blas as fblas'
from topical_word_embeddings.
Speaking of the cython issue:
When I try to compile word2vec_inner.pyx, I get the following issue:
Error compiling Cython file:
------------------------------------------------------------
...
k = sentence_len
for j in range(j, k):
if j == i or codelens[j] == 0:
continue
if hs:
fast_sentence_topic(points[i], codes[i], codelens[i], syn0, syn1, syn0_topic, size, topic[j], _alpha, work)
^
------------------------------------------------------------
word2vec_inner.pyx:890:109: Cannot assign type 'uint32_t *' to 'uint32_t'
has anyone seen this before or know how to resolve it?
I already tried the fixes above and it seems like this issue is stopping me from running the code.
from topical_word_embeddings.
I meet the same error.
from topical_word_embeddings.
I also met the same error.
from topical_word_embeddings.
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from topical_word_embeddings.