doc to vec error in Sentiment140_W2V_Pipeline.py

[Sandy4321]

at line
model.train(np.random.permutation(labeled_sent))

in code
for epoch in xrange(epoch_num):
logging.info("Epoch %s..." % epoch)
# Temporarily sets logging level to show only if its at least WARNING
# This prevents model.train from overloading the log
logging.getLogger().setLevel(logging.WARN)
# Numpy random permutation method shuffles data in place
# Shuffling improves the accuracy of the model
model.train(np.random.permutation(labeled_sent))
logging.getLogger().setLevel(logging.INFO)

error massage is

File "C:\Anaconda\Lib\threading.py", line 774, in __bootstrap
self.__bootstrap_inner()
File "C:\Anaconda\Lib\threading.py", line 801, in __bootstrap_inner
self.run()
File "C:\Anaconda\Lib\threading.py", line 754, in run
self.__target(_self.__args, *_self.__kwargs)
File "C:\Anaconda\Lib\site-packages\gensim\models\word2vec.py", line 701, in worker_loop
if not worker_one_job(job, init):
File "C:\Anaconda\Lib\site-packages\gensim\models\word2vec.py", line 692, in worker_one_job
tally, raw_tally = self._do_train_job(items, alpha, inits)
File "C:\Anaconda\Lib\site-packages\gensim\models\doc2vec.py", line 638, in _do_train_job
indexed_doctags = self.docvecs.indexed_doctags(doc.tags)

AttributeError: 'numpy.ndarray' object has no attribute 'tags'

my check resuts
doc.tags
Traceback (most recent call last):
Debug Probe, prompt 14, line 1
AttributeError: 'numpy.ndarray' object has no attribute 'tags'

thanks
I use windows pc

by the way is word2vec or doc2vec methos??

[kfoss]

@Sandy4321 We're using Word2Vec methods. The broader issue is similar to #80, where your best bet is to run everything within the project's Docker containers. The project has several dependencies, including CUDA, Keras, Neon, Gensim, etc. The Docker containers encapsulate everything you need so you're guaranteed to run the same/correct environment we used to build the project.

For this issue, you'll want to build and run frameworks/docker/sentiment-ml since that contains all the necessary NLP (including gensim) libraries. Within that folder, the accompanying 1-build.sh and 2-run.sh scripts will build and run the containers.

[Sandy4321]

Thanks, but I never used Docket, may recommend some link for docker
tutorials
On Mar 18, 2016 12:25, "Kyle Foster" notifications@github.com wrote:

@Sandy4321 https://github.com/Sandy4321 We're using Word2Vec methods.
The broader issue is similar to #80
#80, where your best bet
is to run everything within the project's Docker containers. The project
has several dependencies, including CUDA, Keras, Neon, Gensim, etc. The
Docker containers encapsulate everything you need so you're guaranteed to
run the same/correct environment we used to build the project.

For this issue, you'll want to build and run
frameworks/docker/sentiment-ml since that contains all the necessary NLP
(including gensim) libraries. Within that folder, the accompanying
1-build.sh and 2-run.sh scripts will build and run the containers.

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