seed = 777 #For reproducibility
opt_adam = Adam(lr = learn_rate, beta_1 = beta_1, beta_2 = beta_2, epsilon = epsilon, decay = decay_rate, amsgrad = amsgrad)
def fetch_profiles(filename, n):
f = open(filename, 'r')
profiles = f.read().splitlines()
f.close()
return(list(set(profiles[:n])))
sqlite_file = '../../data/database/deeplearning.sqlite'
profilename = '../../data/profiles.txt'
table_name = 'tweets'
profiles = fetch_profiles(profilename, 15)
profiles = [p.strip('@') for p in profiles]
cd = c.CleanData(sqlite_file, table_name)
q = 'SELECT * FROM {} WHERE AUTHOR IN ("{}");'.format(table_name, '", "'.join(profiles))
word_model = Word2Vec.load("word2vec.model")
np.random.seed(seed)
def word2idx(word):
return word_model.wv.vocab[word].index
def idx2word(idx):
return word_model.wv.index2word[idx]
cd.set_table(q)
raw_data = cd.get_clean_table()
raw_data = raw_data.CleanText.values
data = ''
