From 6344afdaafe8509a556faef98848922110b289ed Mon Sep 17 00:00:00 2001 From: Craig Quiter Date: Thu, 20 Dec 2018 21:07:34 -0700 Subject: [PATCH] Rename experiment_name to experiment --- README.md | 4 ++-- agents/bootstrap_rl/train/train.py | 2 +- api/server.py | 2 +- deepdrive.py | 8 ++++---- main.py | 6 +++--- 5 files changed, 11 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 48399c8..cfb563a 100644 --- a/README.md +++ b/README.md @@ -53,12 +53,12 @@ If you run into issues, try starting the sim directly as Unreal may need to inst Run the **baseline** agent ``` -python main.py --baseline --experiment-name my-baseline-test +python main.py --baseline --experiment my-baseline-test ``` Run in-game path follower ``` -python main.py --path-follower --experiment-name my-path-follower-test +python main.py --path-follower --experiment my-path-follower-test ``` **Record** training data for imitation learning / behavioral cloning diff --git a/agents/bootstrap_rl/train/train.py b/agents/bootstrap_rl/train/train.py index ca40b28..2056acf 100644 --- a/agents/bootstrap_rl/train/train.py +++ b/agents/bootstrap_rl/train/train.py @@ -103,7 +103,7 @@ def run(env_id, bootstrap_net_path, sess_1 = tf.Session(config=tf_config) with sess_1.as_default(): - dagger_gym_env = deepdrive.start(experiment_name=experiment, env_id=env_id, cameras=camera_rigs, render=render, fps=fps, + dagger_gym_env = deepdrive.start(experiment=experiment, env_id=env_id, cameras=camera_rigs, render=render, fps=fps, combine_box_action_spaces=True, is_sync=is_sync, driving_style=driving_style, is_remote_client=is_remote_client) diff --git a/api/server.py b/api/server.py index 3b714ad..bbf06cf 100644 --- a/api/server.py +++ b/api/server.py @@ -52,7 +52,7 @@ def run(self): resp = 'No environment started, please send start request' log.error('Client sent request with no environment started') elif method == m.START: - allowed_args = ['experiment_name', 'env', 'cameras', 'combine_box_action_spaces', 'is_discrete', + allowed_args = ['experiment', 'env', 'cameras', 'combine_box_action_spaces', 'is_discrete', 'preprocess_with_tensorflow', 'is_sync'] if c.IS_EVAL: allowed_args.remove('env') diff --git a/deepdrive.py b/deepdrive.py index 9bdf23e..2cec0bf 100644 --- a/deepdrive.py +++ b/deepdrive.py @@ -21,7 +21,7 @@ log = logs.get_log(__name__) def start(**kwargs): - all_kwargs = dict(experiment_name=None, env_id='Deepdrive-v0', sess=None, start_dashboard=True, + all_kwargs = dict(experiment=None, env_id='Deepdrive-v0', sess=None, start_dashboard=True, should_benchmark=True, cameras=None, use_sim_start_command=False, render=False, fps=c.DEFAULT_FPS, combine_box_action_spaces=False, is_discrete=False, preprocess_with_tensorflow=False, is_sync=False, driving_style=DrivingStyle.NORMAL, @@ -46,8 +46,8 @@ def start(**kwargs): env = gym.make(kwargs['env_id']) env.seed(c.RNG_SEED) - if kwargs['experiment_name'] is None: - kwargs['experiment_name'] = '' + if kwargs['experiment'] is None: + kwargs['experiment'] = '' deepdrive_env = env.unwrapped @@ -59,7 +59,7 @@ def start(**kwargs): deepdrive_env.reset_returns_zero = kwargs['reset_returns_zero'] deepdrive_env.init_action_space() deepdrive_env.fps = kwargs['fps'] - deepdrive_env.experiment = kwargs['experiment_name'].replace(' ', '_') + deepdrive_env.experiment = kwargs['experiment'].replace(' ', '_') deepdrive_env.period = deepdrive_env.sync_step_time = 1. / kwargs['fps'] deepdrive_env.driving_style = kwargs['driving_style'] deepdrive_env.should_render = kwargs['render'] diff --git a/main.py b/main.py index f755e83..80a2c43 100644 --- a/main.py +++ b/main.py @@ -78,7 +78,7 @@ def main(): parser.add_argument('-v', '--verbose', help='Increase output verbosity', action='store_true') parser.add_argument('--camera-rigs', nargs='?', default=None, help='Name of camera rigs to use') - parser.add_argument('-n', '--experiment-name', nargs='?', default=None, help='Name of your experiment') + parser.add_argument('--experiment', nargs='?', default=None, help='Name of your experiment') parser.add_argument('--fps', type=int, default=c.DEFAULT_FPS, help='Frames / steps per second') parser.add_argument('--agent', nargs='?', default=c.DAGGER_MNET2, help='Agent type (%s, %s, %s)' % (c.DAGGER, @@ -118,7 +118,7 @@ def main(): def run_agent(args, camera_rigs, driving_style): from agents.dagger import agent - agent.run(args.experiment_name, + agent.run(args.experiment, should_record=args.record, net_path=args.net_path, env_id=args.env_id, run_baseline_agent=args.baseline, run_mnet2_baseline_agent=args.mnet2_baseline, run_ppo_baseline_agent=args.ppo_baseline, render=args.render, camera_rigs=camera_rigs, @@ -138,7 +138,7 @@ def run_path_follower(args, driving_style, camera_rigs): cams = camera_rigs if isinstance(camera_rigs[0], list): cams = cams[0] - gym_env = deepdrive.start(experiment_name=args.experiment_name, env_id=args.env_id, fps=args.fps, + gym_env = deepdrive.start(experiment=args.experiment, env_id=args.env_id, fps=args.fps, driving_style=driving_style, is_remote_client=args.is_remote_client, render=args.render, cameras=cams) log.info('Path follower drive mode')