- Description:
D4RL is an open-source benchmark for offline reinforcement learning. It provides standardized environments and datasets for training and benchmarking algorithms.
The datasets follow the RLDS format to represent steps and episodes.
Config description: See more details about the task and its versions in https://github.com/rail-berkeley/d4rl/wiki/Tasks#gym
Source code:
tfds.d4rl.d4rl_mujoco_ant.D4rlMujocoAnt
Versions:
1.0.0
: Initial release.1.1.0
: Added is_last.1.2.0
(default): Updated to take into account the next observation.
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Citation:
@misc{fu2020d4rl,
title={D4RL: Datasets for Deep Data-Driven Reinforcement Learning},
author={Justin Fu and Aviral Kumar and Ofir Nachum and George Tucker and Sergey Levine},
year={2020},
eprint={2004.07219},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
d4rl_mujoco_ant/v0-expert (default config)
Download size:
131.34 MiB
Dataset size:
464.94 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,288 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v0-medium
Download size:
131.39 MiB
Dataset size:
464.78 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,122 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v0-medium-expert
Download size:
262.73 MiB
Dataset size:
929.71 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
2,410 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v0-mixed
Download size:
104.63 MiB
Dataset size:
464.93 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,320 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v0-random
Download size:
139.50 MiB
Dataset size:
464.97 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,377 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-expert
Download size:
220.72 MiB
Dataset size:
968.63 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,033 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'policy': FeaturesDict({
'fc0': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 111), dtype=float32),
}),
'fc1': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 256), dtype=float32),
}),
'last_fc': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'last_fc_log_std': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'nonlinearity': string,
'output_distribution': string,
}),
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float32,
'qpos': Tensor(shape=(15,), dtype=float32),
'qvel': Tensor(shape=(14,), dtype=float32),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
policy | FeaturesDict | |||
policy/fc0 | FeaturesDict | |||
policy/fc0/bias | Tensor | (256,) | float32 | |
policy/fc0/weight | Tensor | (256, 111) | float32 | |
policy/fc1 | FeaturesDict | |||
policy/fc1/bias | Tensor | (256,) | float32 | |
policy/fc1/weight | Tensor | (256, 256) | float32 | |
policy/last_fc | FeaturesDict | |||
policy/last_fc/bias | Tensor | (8,) | float32 | |
policy/last_fc/weight | Tensor | (8, 256) | float32 | |
policy/last_fc_log_std | FeaturesDict | |||
policy/last_fc_log_std/bias | Tensor | (8,) | float32 | |
policy/last_fc_log_std/weight | Tensor | (8, 256) | float32 | |
policy/nonlinearity | Tensor | string | ||
policy/output_distribution | Tensor | string | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float32 | ||
steps/infos/qpos | Tensor | (15,) | float32 | |
steps/infos/qvel | Tensor | (14,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-medium
Download size:
222.39 MiB
Dataset size:
1023.71 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,179 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'policy': FeaturesDict({
'fc0': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 111), dtype=float32),
}),
'fc1': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 256), dtype=float32),
}),
'last_fc': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'last_fc_log_std': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'nonlinearity': string,
'output_distribution': string,
}),
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float32,
'qpos': Tensor(shape=(15,), dtype=float32),
'qvel': Tensor(shape=(14,), dtype=float32),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
policy | FeaturesDict | |||
policy/fc0 | FeaturesDict | |||
policy/fc0/bias | Tensor | (256,) | float32 | |
policy/fc0/weight | Tensor | (256, 111) | float32 | |
policy/fc1 | FeaturesDict | |||
policy/fc1/bias | Tensor | (256,) | float32 | |
policy/fc1/weight | Tensor | (256, 256) | float32 | |
policy/last_fc | FeaturesDict | |||
policy/last_fc/bias | Tensor | (8,) | float32 | |
policy/last_fc/weight | Tensor | (8, 256) | float32 | |
policy/last_fc_log_std | FeaturesDict | |||
policy/last_fc_log_std/bias | Tensor | (8,) | float32 | |
policy/last_fc_log_std/weight | Tensor | (8, 256) | float32 | |
policy/nonlinearity | Tensor | string | ||
policy/output_distribution | Tensor | string | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float32 | ||
steps/infos/qpos | Tensor | (15,) | float32 | |
steps/infos/qvel | Tensor | (14,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-medium-expert
Download size:
442.25 MiB
Dataset size:
1.13 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
2,211 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float32,
'qpos': Tensor(shape=(15,), dtype=float32),
'qvel': Tensor(shape=(14,), dtype=float32),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float32 | ||
steps/infos/qpos | Tensor | (15,) | float32 | |
steps/infos/qvel | Tensor | (14,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-medium-replay
Download size:
132.05 MiB
Dataset size:
175.27 MiB
Auto-cached (documentation): Only when
shuffle_files=False
(train)Splits:
Split | Examples |
---|---|
'train' |
485 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float64),
'discount': float64,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float64),
'reward': float64,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float64 | |
steps/discount | Tensor | float64 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float64 | |
steps/reward | Tensor | float64 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-full-replay
Download size:
437.57 MiB
Dataset size:
580.09 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,319 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float64),
'discount': float64,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float64),
'reward': float64,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float64 | |
steps/discount | Tensor | float64 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float64 | |
steps/reward | Tensor | float64 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v1-random
Download size:
225.18 MiB
Dataset size:
583.83 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
5,741 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float32,
'qpos': Tensor(shape=(15,), dtype=float32),
'qvel': Tensor(shape=(14,), dtype=float32),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float32 | ||
steps/infos/qpos | Tensor | (15,) | float32 | |
steps/infos/qvel | Tensor | (14,) | float32 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-expert
Download size:
355.94 MiB
Dataset size:
969.38 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,035 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'policy': FeaturesDict({
'fc0': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 111), dtype=float32),
}),
'fc1': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 256), dtype=float32),
}),
'last_fc': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'last_fc_log_std': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'nonlinearity': string,
'output_distribution': string,
}),
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
policy | FeaturesDict | |||
policy/fc0 | FeaturesDict | |||
policy/fc0/bias | Tensor | (256,) | float32 | |
policy/fc0/weight | Tensor | (256, 111) | float32 | |
policy/fc1 | FeaturesDict | |||
policy/fc1/bias | Tensor | (256,) | float32 | |
policy/fc1/weight | Tensor | (256, 256) | float32 | |
policy/last_fc | FeaturesDict | |||
policy/last_fc/bias | Tensor | (8,) | float32 | |
policy/last_fc/weight | Tensor | (8, 256) | float32 | |
policy/last_fc_log_std | FeaturesDict | |||
policy/last_fc_log_std/bias | Tensor | (8,) | float32 | |
policy/last_fc_log_std/weight | Tensor | (8, 256) | float32 | |
policy/nonlinearity | Tensor | string | ||
policy/output_distribution | Tensor | string | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-full-replay
Download size:
428.57 MiB
Dataset size:
580.09 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,319 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-medium
Download size:
358.81 MiB
Dataset size:
1.01 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
1,203 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'policy': FeaturesDict({
'fc0': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 111), dtype=float32),
}),
'fc1': FeaturesDict({
'bias': Tensor(shape=(256,), dtype=float32),
'weight': Tensor(shape=(256, 256), dtype=float32),
}),
'last_fc': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'last_fc_log_std': FeaturesDict({
'bias': Tensor(shape=(8,), dtype=float32),
'weight': Tensor(shape=(8, 256), dtype=float32),
}),
'nonlinearity': string,
'output_distribution': string,
}),
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
policy | FeaturesDict | |||
policy/fc0 | FeaturesDict | |||
policy/fc0/bias | Tensor | (256,) | float32 | |
policy/fc0/weight | Tensor | (256, 111) | float32 | |
policy/fc1 | FeaturesDict | |||
policy/fc1/bias | Tensor | (256,) | float32 | |
policy/fc1/weight | Tensor | (256, 256) | float32 | |
policy/last_fc | FeaturesDict | |||
policy/last_fc/bias | Tensor | (8,) | float32 | |
policy/last_fc/weight | Tensor | (8, 256) | float32 | |
policy/last_fc_log_std | FeaturesDict | |||
policy/last_fc_log_std/bias | Tensor | (8,) | float32 | |
policy/last_fc_log_std/weight | Tensor | (8, 256) | float32 | |
policy/nonlinearity | Tensor | string | ||
policy/output_distribution | Tensor | string | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-medium-expert
Download size:
713.67 MiB
Dataset size:
1.13 GiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
2,237 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-medium-replay
Download size:
130.16 MiB
Dataset size:
175.27 MiB
Auto-cached (documentation): Only when
shuffle_files=False
(train)Splits:
Split | Examples |
---|---|
'train' |
485 |
- Feature structure:
FeaturesDict({
'algorithm': string,
'iteration': int32,
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
algorithm | Tensor | string | ||
iteration | Tensor | int32 | ||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):
d4rl_mujoco_ant/v2-random
Download size:
366.66 MiB
Dataset size:
583.90 MiB
Auto-cached (documentation): No
Splits:
Split | Examples |
---|---|
'train' |
5,822 |
- Feature structure:
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'action_log_probs': float64,
'qpos': Tensor(shape=(15,), dtype=float64),
'qvel': Tensor(shape=(14,), dtype=float64),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': Tensor(shape=(111,), dtype=float32),
'reward': float32,
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
steps | Dataset | |||
steps/action | Tensor | (8,) | float32 | |
steps/discount | Tensor | float32 | ||
steps/infos | FeaturesDict | |||
steps/infos/action_log_probs | Tensor | float64 | ||
steps/infos/qpos | Tensor | (15,) | float64 | |
steps/infos/qvel | Tensor | (14,) | float64 | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/observation | Tensor | (111,) | float32 | |
steps/reward | Tensor | float32 |
- Examples (tfds.as_dataframe):