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13
README.md
13
README.md
@ -52,16 +52,19 @@ while an evaluation entry:
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```
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which just tells the expected reward `ER` evaluating current policy after `S` steps. Note that `ER` is average evaluation performance over `num_eval_episodes` episodes (usually 10).
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### Running the natural video setting
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You can download the Kinetics 400 dataset and grab the driving_car label from the train dataset to replicate our setup. Some instructions for downloading the dataset can be found here: https://github.com/Showmax/kinetics-downloader.
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## CARLA
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Download CARLA from https://github.com/carla-simulator/carla/releases, e.g.:
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1. https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/CARLA_0.9.8.tar.gz
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2. https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/AdditionalMaps_0.9.8.tar.gz
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1. https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/CARLA_0.9.6.tar.gz
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2. https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/AdditionalMaps_0.9.6.tar.gz
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Add to your python path:
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```
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.8/PythonAPI
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.8/PythonAPI/carla
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.8/PythonAPI/carla/dist/carla-0.9.8-py3.5-linux-x86_64.egg
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.6/PythonAPI
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.6/PythonAPI/carla
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export PYTHONPATH=$PYTHONPATH:/home/rmcallister/code/bisim_metric/CARLA_0.9.6/PythonAPI/carla/dist/carla-0.9.8-py3.5-linux-x86_64.egg
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```
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and merge the directories.
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@ -13,7 +13,7 @@ dependencies:
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- git+git://github.com/deepmind/dm_control.git
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- git+git://github.com/1nadequacy/dmc2gym.git
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- opencv-python
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- pillow=6.1
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- pillow==6.1
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- scikit-image
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- scikit-video
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- tb-nightly
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28
train.py
28
train.py
@ -20,7 +20,7 @@ from video import VideoRecorder
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from agent.baseline_agent import BaselineAgent
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from agent.bisim_agent import BisimAgent
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from agent.deepmdp_agent import DeepMDPAgent
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from agents.navigation.carla_env import CarlaEnv
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#from agents.navigation.carla_env import CarlaEnv
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def parse_args():
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@ -34,14 +34,15 @@ def parse_args():
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parser.add_argument('--resource_files', type=str)
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parser.add_argument('--eval_resource_files', type=str)
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parser.add_argument('--img_source', default=None, type=str, choices=['color', 'noise', 'images', 'video', 'none'])
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parser.add_argument('--total_frames', default=1000, type=int)
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parser.add_argument('--total_frames', default=100, type=int)
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parser.add_argument('--high_noise', action='store_true')
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# replay buffer
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parser.add_argument('--replay_buffer_capacity', default=1000000, type=int)
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parser.add_argument('--replay_buffer_capacity', default=50000, type=int)
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# train
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parser.add_argument('--agent', default='bisim', type=str, choices=['baseline', 'bisim', 'deepmdp'])
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parser.add_argument('--init_steps', default=1000, type=int)
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parser.add_argument('--num_train_steps', default=1000000, type=int)
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parser.add_argument('--batch_size', default=512, type=int)
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parser.add_argument('--num_train_steps', default=1000050, type=int)
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parser.add_argument('--batch_size', default=128, type=int) # 512
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parser.add_argument('--hidden_dim', default=256, type=int)
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parser.add_argument('--k', default=3, type=int, help='number of steps for inverse model')
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parser.add_argument('--bisim_coef', default=0.5, type=float, help='coefficient for bisim terms')
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@ -50,12 +51,12 @@ def parse_args():
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parser.add_argument('--eval_freq', default=10, type=int) # TODO: master had 10000
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parser.add_argument('--num_eval_episodes', default=20, type=int)
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# critic
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parser.add_argument('--critic_lr', default=1e-3, type=float)
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parser.add_argument('--critic_lr', default=1e-5, type=float)
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parser.add_argument('--critic_beta', default=0.9, type=float)
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parser.add_argument('--critic_tau', default=0.005, type=float)
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parser.add_argument('--critic_target_update_freq', default=2, type=int)
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# actor
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parser.add_argument('--actor_lr', default=1e-3, type=float)
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parser.add_argument('--actor_lr', default=1e-5, type=float)
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parser.add_argument('--actor_beta', default=0.9, type=float)
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parser.add_argument('--actor_log_std_min', default=-10, type=float)
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parser.add_argument('--actor_log_std_max', default=2, type=float)
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@ -63,19 +64,19 @@ def parse_args():
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# encoder/decoder
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parser.add_argument('--encoder_type', default='pixel', type=str, choices=['pixel', 'pixelCarla096', 'pixelCarla098', 'identity'])
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parser.add_argument('--encoder_feature_dim', default=50, type=int)
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parser.add_argument('--encoder_lr', default=1e-3, type=float)
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parser.add_argument('--encoder_lr', default=1e-5, type=float)
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parser.add_argument('--encoder_tau', default=0.005, type=float)
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parser.add_argument('--encoder_stride', default=1, type=int)
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parser.add_argument('--decoder_type', default='pixel', type=str, choices=['pixel', 'identity', 'contrastive', 'reward', 'inverse', 'reconstruction'])
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parser.add_argument('--decoder_lr', default=1e-3, type=float)
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parser.add_argument('--decoder_lr', default=1e-5, type=float)
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parser.add_argument('--decoder_update_freq', default=1, type=int)
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parser.add_argument('--decoder_weight_lambda', default=0.0, type=float)
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parser.add_argument('--num_layers', default=4, type=int)
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parser.add_argument('--num_filters', default=32, type=int)
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# sac
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parser.add_argument('--discount', default=0.99, type=float)
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parser.add_argument('--init_temperature', default=0.01, type=float)
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parser.add_argument('--alpha_lr', default=1e-3, type=float)
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parser.add_argument('--init_temperature', default=0.1, type=float)
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parser.add_argument('--alpha_lr', default=1e-4, type=float)
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parser.add_argument('--alpha_beta', default=0.9, type=float)
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# misc
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parser.add_argument('--seed', default=1, type=int)
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@ -88,6 +89,9 @@ def parse_args():
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parser.add_argument('--render', default=False, action='store_true')
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parser.add_argument('--port', default=2000, type=int)
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args = parser.parse_args()
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#from dmc2gym.wrappers import set_global_var
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#set_global_var(args.high_noise)
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return args
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@ -318,7 +322,7 @@ def main():
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)
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# stack several consecutive frames together
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if args.encoder_type == 'pixel':
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if args.encoder_type.startswith('pixel'):
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env = utils.FrameStack(env, k=args.frame_stack)
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eval_env = utils.FrameStack(eval_env, k=args.frame_stack)
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2
video.py
2
video.py
@ -22,7 +22,7 @@ class VideoRecorder(object):
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self.frames = []
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if resource_files:
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files = glob.glob(os.path.expanduser(resource_files))
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self._bg_source = RandomVideoSource((height, width), files, grayscale=False, total_frames=1000)
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self._bg_source = RandomVideoSource((height, width), files, grayscale=False, max_videos=50, random_bg=False)
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else:
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self._bg_source = None
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