old_contents: """
  	Train word2vec
  """
  
  import logging
  import os.path
  import sys
  import multiprocessing
  #import gensim.models.word2vec
  
  from gensim.models.word2vec import Word2Vec
  from gensim.models.word2vec import LineSentence
  
  import os
  
  
  if __name__ == '__main__':
  	program = os.path.basename(sys.argv[0])
  	logger = logging.getLogger(program)
  
  	logging.basicConfig(format='%(asctime)s: %(levelname)s: %(message)s')
  	logging.root.setLevel(level=logging.INFO)
  	logger.info("running %s" % ' '.join(sys.argv))
  
  
  
  	file_path = "../data/cmu/review/processed_comments.json"
  
  	model_path = "model"
  	vector_path = "vector"
  
  	count = multiprocessing.cpu_count()
  	
  	model = Word2Vec(LineSentence(file_path),size=200, window=10, min_count=5, workers=count)
  
  	model.save(model_path)
  	model.save_word2vec_format(vector_path, binary=False)
new_contents: """
  	Train word2vec
  """
  
  import logging
  import os.path
  import sys
  import multiprocessing
  #import gensim.models.word2vec
  
  from gensim.models.word2vec import Word2Vec
  from gensim.models.word2vec import LineSentence
  
  import os
  
  
  if __name__ == '__main__':
  	program = os.path.basename(sys.argv[0])
  	logger = logging.getLogger(program)
  
  	logging.basicConfig(format='%(asctime)s: %(levelname)s: %(message)s')
  	logging.root.setLevel(level=logging.INFO)
  	logger.info("running %s" % ' '.join(sys.argv))
  
  
  
  	file_path = "./dummy/processed_reviews.txt"
  
  	# store the model to file
  	model_path = "./dummy/model.model"
  
  	# save processed vector to file
  	vector_path = "./dummy/vector.txt"
  
  	count = multiprocessing.cpu_count()
  	
  	model = Word2Vec(LineSentence(file_path),size=200, window=10, min_count=5, workers=count)
  
  	model.save(model_path)
  	model.save_word2vec_format(vector_path, binary=False)
subject: Fix path errors in src/w2v_train.py