sample.py

# -*- coding: utf-8 -*-
from __future__ import print_function

import tensorflow as tf
import numpy as np
import copy
import cPickle
import sys
import os
from models.charrnn import CharRNN
from utils import TextLoader, normalize_unicodes, UNK_ID

def main(_):
  if len(sys.argv) < 2:
    print("Please enter a prime")
    sys.exit()

  prime = sys.argv[1]
  prime = prime.decode('utf-8')

  with open("./log/hyperparams.pkl", 'rb') as f:
    config = cPickle.load(f)

  if not os.path.exists(config['checkpoint_dir']):
    print(" [*] Creating checkpoint directory...")
    os.makedirs(config['checkpoint_dir'])

  data_loader = TextLoader(os.path.join(config['data_dir'], config['dataset_name']),
                            config['batch_size'], config['seq_length'])
  vocab_size = data_loader.vocab_size

  with tf.variable_scope('model'):
     model = CharRNN(vocab_size, 1, config['rnn_size'],
                     config['layer_depth'], config['num_units'],
                     1, config['keep_prob'],
                     config['grad_clip'],
                     is_training=False)

  with tf.Session() as sess:
    ckpt = tf.train.get_checkpoint_state(config['checkpoint_dir'] + '/' + config['dataset_name'])
    tf.train.Saver().restore(sess, ckpt.model_checkpoint_path)

    res = model.sample(sess, data_loader.chars, data_loader.vocab, UNK_ID, 100, prime)

    print(res)


if __name__ == '__main__':
  tf.app.run()