def main(_):
pp.pprint(flags.FLAGS.__flags)
if not os.path.exists(FLAGS.checkpoint_dir):
print(" [*] Creating checkpoint directory...")
os.makedirs(FLAGS.checkpoint_dir)
if FLAGS.game_name == "home":
game = HomeGame(game_dir=FLAGS.game_dir, seq_length=FLAGS.seq_length)
else:
raise Exception(" [!] %s not implemented yet" % self.game_name)
with tf.device('/cpu:0'):
model = LSTMDQN(game,
checkpoint_dir=FLAGS.checkpoint_dir,
seq_length=FLAGS.seq_length,
embed_dim=FLAGS.embed_dim,
layer_depth=FLAGS.layer_depth,
batch_size=FLAGS.batch_size,
start_epsilon=FLAGS.start_epsilon,
forward_only=FLAGS.forward_only,
max_episode_length=FLAGS.max_episode_length)
if not FLAGS.forward_only:
model.train()
else:
test_loss = model.test(2)
print(" [*] Test loss: %2.6f, perplexity: %2.6f" %
(test_loss, np.exp(test_loss)))
def main(_):
pp.pprint(flags.FLAGS.__flags)
if not os.path.exists(FLAGS.checkpoint_dir):
print(" [*] Creating checkpoint directory...")
os.makedirs(FLAGS.checkpoint_dir)
if FLAGS.game_name == "home":
game = HomeGame(game_dir=FLAGS.game_dir, seq_length=FLAGS.seq_length)
else:
raise Exception(" [!] %s not implemented yet" % self.game_name)
with tf.device('/cpu:0'):
model = LSTMDQN(game, checkpoint_dir=FLAGS.checkpoint_dir,
seq_length=FLAGS.seq_length,
embed_dim=FLAGS.embed_dim,
layer_depth=FLAGS.layer_depth,
batch_size=FLAGS.batch_size,
start_epsilon=FLAGS.start_epsilon,
forward_only=FLAGS.forward_only)
if not FLAGS.forward_only:
model.train()
else:
test_loss = model.test(2)
print(" [*] Test loss: %2.6f, perplexity: %2.6f" % (test_loss, np.exp(test_loss)))
def main(_):
pp.pprint(flags.FLAGS.__flags)
if not os.path.exists(FLAGS.checkpoint_dir):
print(" [*] Creating checkpoint directory...")
os.makedirs(FLAGS.checkpoint_dir)
with tf.Session() as sess:
model = LSTMDQN(checkpoint_dir=FLAGS.checkpoint_dir,
seq_length=FLAGS.seq_length,
embed_dim=FLAGS.embed_dim,
layer_depth=FLAGS.layer_depth,
batch_size=FLAGS.batch_size,
forward_only=FLAGS.forward_only,
game_name=FLAGS.game_name,
game_dir=FLAGS.game_dir)
if not FLAGS.forward_only:
model.run()
else:
test_loss = model.test(2)
print(" [*] Test loss: %2.6f, perplexity: %2.6f" % (test_loss, np.exp(test_loss)))
