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# -*- coding: utf-8 -*-
import numpy as np
import gensim, cython, codecs, os, logging, re

database_name = "twitter-data"
collection_name = "roland_garros_2017"

DATA_DIR = '/home/nipg1/Documents/summer_project/data/'+ collection_name
LOG_DIR = '/home/nipg1/Documents/summer_project/data/'+ collection_name + '/embedding_logs'


    

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feature = np.load(os.path.join(DATA_DIR, 'feature.npy'))


    

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import tensorflow as tf
import os
from tensorflow.contrib.tensorboard.plugins import projector

embedding_var = tf.Variable(feature,  name=collection_name)
sess = tf.Session()
sess.run(embedding_var.initializer)
summary_writer = tf.summary.FileWriter(LOG_DIR)
config = projector.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = embedding_var.name

embedding.metadata_path = os.path.join(DATA_DIR, 'metadata.tsv')

projector.visualize_embeddings(summary_writer, config)
saver = tf.train.Saver([embedding_var])
saver.save(sess, os.path.join(LOG_DIR, 'model_ckpt'), 1)