def main(_):
"""Trains Language Model."""
tf.logging.set_verbosity(tf.logging.INFO)
with tf.device(tf.train.replica_device_setter(FLAGS.ps_tasks)):
model = graphs.get_model()
train_op, loss, global_step = model.language_model_training()
train_utils.run_training(train_op, loss, global_step)
def main(_):
"""Trains Language Model."""
tf.logging.set_verbosity(tf.logging.INFO)
with tf.device(tf.train.replica_device_setter(FLAGS.ps_tasks)):
model = graphs.get_model()
train_op, loss, global_step = model.language_model_training()
train_utils.run_training(train_op, loss, global_step)
def main(_):
"""Trains LSTM classification model."""
tf.logging.set_verbosity(tf.logging.INFO)
with tf.device(tf.train.replica_device_setter(FLAGS.ps_tasks)):
model = graphs.get_model()
train_op, loss, global_step = model.classifier_training()
train_utils.run_training(
train_op,
loss,
global_step,
variables_to_restore=model.pretrained_variables,
pretrained_model_dir=FLAGS.pretrained_model_dir)
def main(_):
"""Trains LSTM classification model."""
tf.logging.set_verbosity(tf.logging.INFO)
with tf.device(tf.train.replica_device_setter(FLAGS.ps_tasks)):
model = graphs.get_model()
train_op, loss, global_step = model.classifier_training()
train_utils.run_training(
train_op,
loss,
global_step,
variables_to_restore=model.pretrained_variables,
pretrained_model_dir=FLAGS.pretrained_model_dir)
