def create_model(session, reverse_target_vocab_table, is_training):
"""Create model and initialize or load parameters in session."""
model = Model.BiGRUModel(FLAGS.doc_vocab_size, FLAGS.sum_vocab_size,
_buckets, FLAGS.size, FLAGS.embsize,
FLAGS.max_gradient, FLAGS.batch_size,
FLAGS.beam_size, reverse_target_vocab_table,
is_training, FLAGS.learning_rate)
if FLAGS.checkpoint != "":
ckpt = FLAGS.checkpoint
else:
ckpt = tf.train.get_checkpoint_state(FLAGS.train_dir)
if ckpt:
ckpt = ckpt.model_checkpoint_path
if ckpt and tf.train.checkpoint_exists(ckpt):
logging.info("Reading model parameters from %s" % ckpt)
model.saver.restore(session, ckpt)
else:
logging.info("Created model with fresh parameters.")
session.run(tf.global_variables_initializer())
return model
