- Description:
RL Unplugged is suite of benchmarks for offline reinforcement learning. The RL Unplugged is designed around the following considerations: to facilitate ease of use, we provide the datasets with a unified API which makes it easy for the practitioner to work with all data in the suite once a general pipeline has been established.
The datasets follow the RLDS format to represent steps and episodes.
Examples in the dataset represent SAR transitions stored when running a partially online trained agent as described in https://arxiv.org/abs/1904.12901 We follow the RLDS dataset format, as specified in https://github.com/google-research/rlds#dataset-format
We release 40 datasets on 8 tasks in total -- with no combined challenge and easy combined challenge on the cartpole, walker, quadruped, and humanoid tasks. Each task contains 5 different sizes of datasets, 1%, 5%, 20%, 40%, and 100%. Note that the smaller dataset is not guaranteed to be a subset of the larger ones. For details on how the dataset was generated, please refer to the paper.
Homepage: https://github.com/deepmind/deepmind-research/tree/master/rl_unplugged
Source code:
tfds.rl_unplugged.rlu_rwrl.RluRwrl
Versions:
1.0.0
: Initial release.1.0.1
(default): Fixes a bug in RLU RWRL dataset where there are duplicated episode ids in one of the humanoid datasets.
Download size:
Unknown size
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Citation:
@misc{gulcehre2020rl,
title={RL Unplugged: Benchmarks for Offline Reinforcement Learning},
author={Caglar Gulcehre and Ziyu Wang and Alexander Novikov and Tom Le Paine
and Sergio Gómez Colmenarejo and Konrad Zolna and Rishabh Agarwal and
Josh Merel and Daniel Mankowitz and Cosmin Paduraru and Gabriel
Dulac-Arnold and Jerry Li and Mohammad Norouzi and Matt Hoffman and
Ofir Nachum and George Tucker and Nicolas Heess and Nando deFreitas},
year={2020},
eprint={2006.13888},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
rlu_rwrl/cartpole_swingup_combined_challenge_none_1_percent (default config)
Dataset size:
172.43 KiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
5 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_none_5_percent
Dataset size:
862.13 KiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
25 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_none_20_percent
Dataset size:
3.37 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
100 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_none_40_percent
Dataset size:
6.74 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_none_100_percent
Dataset size:
16.84 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
500 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_none_1_percent
Dataset size:
1.77 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
5 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_none_5_percent
Dataset size:
8.86 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
25 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_none_20_percent
Dataset size:
35.46 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
100 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_none_40_percent
Dataset size:
70.92 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_none_100_percent
Dataset size:
177.29 MiB
Auto-cached (documentation): Only when
shuffle_files=False
(train)Splits:
Split | Examples |
---|---|
'train' |
500 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_none_1_percent
Dataset size:
6.27 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
50 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_none_5_percent
Dataset size:
31.34 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
250 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_none_20_percent
Dataset size:
125.37 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
1,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_none_40_percent
Dataset size:
250.75 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
2,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_none_100_percent
Dataset size:
626.86 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
5,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_none_1_percent
Dataset size:
69.40 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_none_5_percent
Dataset size:
346.98 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_none_20_percent
Dataset size:
1.36 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
4,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_none_40_percent
Dataset size:
2.71 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
8,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_none_100_percent
Dataset size:
6.78 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
20,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_easy_1_percent
Dataset size:
369.84 KiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
5 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_easy_5_percent
Dataset size:
1.81 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
25 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_easy_20_percent
Dataset size:
7.22 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
100 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_easy_40_percent
Dataset size:
14.45 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/cartpole_swingup_combined_challenge_easy_100_percent
Dataset size:
36.12 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
500 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(1,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'position': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(2,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (1,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/position | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (2,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_easy_1_percent
Dataset size:
1.97 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
5 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_easy_5_percent
Dataset size:
9.83 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
25 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_easy_20_percent
Dataset size:
39.31 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
100 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_easy_40_percent
Dataset size:
78.63 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/quadruped_walk_combined_challenge_easy_100_percent
Dataset size:
196.57 MiB
Auto-cached (documentation): Only when
shuffle_files=False
(train)Splits:
Split | Examples |
---|---|
'train' |
500 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(12,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'egocentric_state': Tensor(shape=(44,), dtype=float32),
'force_torque': Tensor(shape=(24,), dtype=float32),
'imu': Tensor(shape=(6,), dtype=float32),
'torso_upright': Tensor(shape=(1,), dtype=float32),
'torso_velocity': Tensor(shape=(3,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (12,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/egocentric_state | Tensor | (44,) | float32 | |
steps/observation/force_torque | Tensor | (24,) | float32 | |
steps/observation/imu | Tensor | (6,) | float32 | |
steps/observation/torso_upright | Tensor | (1,) | float32 | |
steps/observation/torso_velocity | Tensor | (3,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_easy_1_percent
Dataset size:
8.20 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
50 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_easy_5_percent
Dataset size:
40.98 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
250 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_easy_20_percent
Dataset size:
163.93 MiB
Auto-cached (documentation): Only when
shuffle_files=False
(train)Splits:
Split | Examples |
---|---|
'train' |
1,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_easy_40_percent
Dataset size:
327.86 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
2,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/walker_walk_combined_challenge_easy_100_percent
Dataset size:
819.65 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
5,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(6,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'height': Tensor(shape=(1,), dtype=float32),
'orientations': Tensor(shape=(14,), dtype=float32),
'velocity': Tensor(shape=(9,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (6,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/height | Tensor | (1,) | float32 | |
steps/observation/orientations | Tensor | (14,) | float32 | |
steps/observation/velocity | Tensor | (9,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_easy_1_percent
Dataset size:
77.11 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
200 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_easy_5_percent
Dataset size:
385.54 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_easy_20_percent
Dataset size:
1.51 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
4,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype=float32),
'dummy-4': Tensor(shape=(1,), dtype=float32),
'dummy-5': Tensor(shape=(1,), dtype=float32),
'dummy-6': Tensor(shape=(1,), dtype=float32),
'dummy-7': Tensor(shape=(1,), dtype=float32),
'dummy-8': Tensor(shape=(1,), dtype=float32),
'dummy-9': Tensor(shape=(1,), dtype=float32),
'extremities': Tensor(shape=(12,), dtype=float32),
'head_height': Tensor(shape=(1,), dtype=float32),
'joint_angles': Tensor(shape=(21,), dtype=float32),
'torso_vertical': Tensor(shape=(3,), dtype=float32),
'velocity': Tensor(shape=(27,), dtype=float32),
}),
'reward': Tensor(shape=(1,), dtype=float32),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_return | Tensor | float32 | ||
steps | Dataset | |||
steps/action | Tensor | (21,) | float32 | |
steps/discount | Tensor | (1,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | FeaturesDict | |||
steps/observation/com_velocity | Tensor | (3,) | float32 | |
steps/observation/dummy-0 | Tensor | (1,) | float32 | |
steps/observation/dummy-1 | Tensor | (1,) | float32 | |
steps/observation/dummy-2 | Tensor | (1,) | float32 | |
steps/observation/dummy-3 | Tensor | (1,) | float32 | |
steps/observation/dummy-4 | Tensor | (1,) | float32 | |
steps/observation/dummy-5 | Tensor | (1,) | float32 | |
steps/observation/dummy-6 | Tensor | (1,) | float32 | |
steps/observation/dummy-7 | Tensor | (1,) | float32 | |
steps/observation/dummy-8 | Tensor | (1,) | float32 | |
steps/observation/dummy-9 | Tensor | (1,) | float32 | |
steps/observation/extremities | Tensor | (12,) | float32 | |
steps/observation/head_height | Tensor | (1,) | float32 | |
steps/observation/joint_angles | Tensor | (21,) | float32 | |
steps/observation/torso_vertical | Tensor | (3,) | float32 | |
steps/observation/velocity | Tensor | (27,) | float32 | |
steps/reward | Tensor | (1,) | float32 |
- Examples (tfds.as_dataframe):
rlu_rwrl/humanoid_walk_combined_challenge_easy_40_percent
Dataset size:
3.01 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
8,000 |
- Feature structure:
FeaturesDict({
'episode_return': float32,
'steps': Dataset({
'action': Tensor(shape=(21,), dtype=float32),
'discount': Tensor(shape=(1,), dtype=float32),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'com_velocity': Tensor(shape=(3,), dtype=float32),
'dummy-0': Tensor(shape=(1,), dtype=float32),
'dummy-1': Tensor(shape=(1,), dtype=float32),
'dummy-2': Tensor(shape=(1,), dtype=float32),
'dummy-3': Tensor(shape=(1,), dtype