old_contents: # -*- coding: utf-8 -*-
  '''
  Code by https://github.com/cstorm125/thai2vec/blob/master/notebooks/examples.ipynb
  '''
  from __future__ import absolute_import,unicode_literals
  import six
  import sys
  if six.PY2:
  	print("Thai sentiment in pythainlp. Not support python 2.7")
  	sys.exit(0)
  try:
  	from gensim.models import KeyedVectors
  	import numpy as np
  except ImportError:
  	import pip
  	pip.main(['install','gensim','numpy'])
  	try:
  		from gensim.models import KeyedVectors
  		import numpy as np
  	except ImportError:
  		print("Error ! using 'pip install gensim numpy'")
  		sys.exit(0)
  from pythainlp.tokenize import word_tokenize
  import os
  
  def download():
  	path = os.path.join(os.path.expanduser("~"), 'pythainlp-data')
  	if not os.path.exists(path):
  		os.makedirs(path)
  	path = os.path.join(path, 'thai2vec.vec')
  	if not os.path.exists(path):
  		print("Download models...")
  		from urllib import request
  		request.urlretrieve("https://www.dropbox.com/sh/t9qfj2ethst8g20/AAC_vnHM5xmiyz1B9ouz_8Kna/data/thaiwiki/models/thai2vec.vec?dl=1",path)
  		print("OK.")
  	return path
  def get_model():
  	return KeyedVectors.load_word2vec_format(download(),binary=False)
  def most_similar_cosmul(positive,negative):
  	'''
  	การใช้งาน
  	input list
  	'''
  	return get_model().most_similar_cosmul(positive=positive, negative=negative)
  def doesnt_match(listdata):
  	return get_model().doesnt_match(listdata)
  def similarity(word1,word2):
  	return get_model().similarity(word1,word2)
  def sentence_vectorizer(ss,dim=300,use_mean=False):
      s = word_tokenize(ss)
      vec = np.zeros((1,dim))
      for word in s:
          if word in get_model().wv.index2word:
              vec+= get_model().wv.word_vec(word)
          else: pass
      if use_mean: vec /= len(s)
      return(vec)
  def about():
  	return '''
  	thai2vec
  	Language Modeling, Word2Vec and Text Classification in Thai Language. Created as part of pyThaiNLP.
  	
  	Development : Charin Polpanumas
  	GitHub : https://github.com/cstorm125/thai2vec
  	'''
new_contents: # -*- coding: utf-8 -*-
  '''
  Code by https://github.com/cstorm125/thai2vec/blob/master/notebooks/examples.ipynb
  '''
  from __future__ import absolute_import,unicode_literals
  import six
  import sys
  if six.PY2:
  	print("Thai sentiment in pythainlp. Not support python 2.7")
  	sys.exit(0)
  try:
  	from gensim.models import KeyedVectors
  	import numpy as np
  except ImportError:
  	import pip
  	pip.main(['install','gensim','numpy'])
  	try:
  		from gensim.models import KeyedVectors
  		import numpy as np
  	except ImportError:
  		print("Error ! using 'pip install gensim numpy'")
  		sys.exit(0)
  from pythainlp.tokenize import word_tokenize
  import os
  
  def download():
  	path = os.path.join(os.path.expanduser("~"), 'pythainlp-data')
  	if not os.path.exists(path):
  		os.makedirs(path)
  	path = os.path.join(path, 'thai2vec.vec')
  	if not os.path.exists(path):
  		print("Download models...")
  		from urllib import request
  		request.urlretrieve("https://www.dropbox.com/s/upnbmiebkfma7oy/thai2vec.vec?dl=1",path)
  		print("OK.")
  	return path
  def get_model():
  	return KeyedVectors.load_word2vec_format(download(),binary=False)
  def most_similar_cosmul(positive,negative):
  	'''
  	การใช้งาน
  	input list
  	'''
  	return get_model().most_similar_cosmul(positive=positive, negative=negative)
  def doesnt_match(listdata):
  	return get_model().doesnt_match(listdata)
  def similarity(word1,word2):
  	return get_model().similarity(word1,word2)
  def sentence_vectorizer(ss,dim=300,use_mean=False):
      s = word_tokenize(ss)
      vec = np.zeros((1,dim))
      for word in s:
          if word in get_model().wv.index2word:
              vec+= get_model().wv.word_vec(word)
          else: pass
      if use_mean: vec /= len(s)
      return(vec)
  def about():
  	return '''
  	thai2vec
  	Language Modeling, Word2Vec and Text Classification in Thai Language. Created as part of pyThaiNLP.
  	
  	Development : Charin Polpanumas
  	GitHub : https://github.com/cstorm125/thai2vec
  	'''
  
subject: edit dropbox url @cstorm125