def main(unused_argv):
tf.logging.set_verbosity(tf.logging.INFO)
base_run_experiment.load_gin_configs(FLAGS.gin_files, FLAGS.gin_bindings)
replay_data_dir = os.path.join(FLAGS.replay_dir, 'replay_logs')
create_agent_fn = functools.partial(create_agent,
replay_data_dir=replay_data_dir)
runner = run_experiment.FixedReplayRunner(FLAGS.base_dir, create_agent_fn)
runner.run_experiment()
def main(unused_argv):
path, split = osp.split(FLAGS.exp_dir)
path, game = osp.split(path)
gin.bind_parameter('atari_lib.create_atari_environment.game_name', game)
if FLAGS.use_preference_rewards:
training_log_path = create_logs_for_training(FLAGS)
agent_name = "_".join([
FLAGS.agent_name, FLAGS.preference_model_type,
FLAGS.reward_model_type
])
FLAGS.replay_dir = training_log_path
else:
raise NotImplementedError
tf.logging.set_verbosity(tf.logging.INFO)
base_run_experiment.load_gin_configs(FLAGS.gin_files, FLAGS.gin_bindings)
replay_data_dir = os.path.join(FLAGS.replay_dir, 'replay_logs')
create_agent_fn = functools.partial(create_agent,
replay_data_dir=replay_data_dir)
runner = run_experiment.FixedReplayRunner(
osp.join(FLAGS.exp_dir, agent_name), create_agent_fn)
runner.run_experiment()
pack_agents(FLAGS)
def main(configs):
tf.logging.set_verbosity(tf.logging.INFO)
base_run_experiment.load_gin_configs(configs.gin_files, configs.gin_bindings)
replay_data_dir = os.path.join(configs.replay_dir, "replay_logs")
create_agent_fn = functools.partial(
create_agent,
replay_data_dir=replay_data_dir,
agent_name=configs.agent_name,
init_checkpoint_dir=configs.init_checkpoint_dir,
)
create_environment_fn = functools.partial(create_environment)
runner = run_experiment.FixedReplayRunner(
configs.base_dir, create_agent_fn, create_environment_fn=create_environment_fn
)
dataset_path = os.path.join(
os.path.realpath("."), "data/processed/v5_dataset/test_dataset_users/"
)
chkpt_path = os.path.join(
os.path.realpath("."), "models/reward_pred_v0_model/release/80_input"
)
runner.set_offline_evaluation(dataset_path, chkpt_path)
runner.run_experiment()