d4rl_antmaze
Stay organized with collections
Save and categorize content based on your preferences.
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.
FeaturesDict({
'steps': Dataset({
'action': Tensor(shape=(8,), dtype=float32),
'discount': float32,
'infos': FeaturesDict({
'goal': Tensor(shape=(2,), dtype=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=(29,), dtype=float32),
'reward': float32,
}),
})
| Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
| steps |
Dataset |
|
|
|
| steps/action |
Tensor |
(8,) |
float32 |
|
| steps/discount |
Tensor |
|
float32 |
|
| steps/infos |
FeaturesDict |
|
|
|
| steps/infos/goal |
Tensor |
(2,) |
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 |
(29,) |
float32 |
|
| steps/reward |
Tensor |
|
float32 |
|
@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_antmaze/umaze-v0 (default config)
| Split |
Examples |
'train' |
10,154 |
d4rl_antmaze/umaze-diverse-v0
| Split |
Examples |
'train' |
1,154 |
d4rl_antmaze/medium-play-v0
| Split |
Examples |
'train' |
10,695 |
d4rl_antmaze/medium-diverse-v0
| Split |
Examples |
'train' |
2,924 |
d4rl_antmaze/large-diverse-v0
| Split |
Examples |
'train' |
7,141 |
d4rl_antmaze/large-play-v0
| Split |
Examples |
'train' |
13,458 |
d4rl_antmaze/umaze-v2
| Split |
Examples |
'train' |
10,154 |
d4rl_antmaze/umaze-diverse-v2
| Split |
Examples |
'train' |
1,036 |
d4rl_antmaze/medium-play-v2
| Split |
Examples |
'train' |
10,768 |
d4rl_antmaze/medium-diverse-v2
| Split |
Examples |
'train' |
2,959 |
d4rl_antmaze/large-diverse-v2
| Split |
Examples |
'train' |
7,189 |
d4rl_antmaze/large-play-v2
| Split |
Examples |
'train' |
13,517 |
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2024-05-08 UTC.
[null,null,["Last updated 2024-05-08 UTC."],[],[],null,["# d4rl_antmaze\n\n\u003cbr /\u003e\n\n- **Description**:\n\nD4RL is an open-source benchmark for offline reinforcement learning. It provides\nstandardized environments and datasets for training and benchmarking algorithms.\n\nThe datasets follow the [RLDS format](https://github.com/google-research/rlds)\nto represent steps and episodes.\n\n- **Config description** : See more details about the task and its versions in\n \u003chttps://github.com/rail-berkeley/d4rl/wiki/Tasks#antmaze\u003e\n\n- **Homepage** :\n \u003chttps://sites.google.com/view/d4rl-anonymous\u003e\n\n- **Source code** :\n [`tfds.d4rl.d4rl_antmaze.D4rlAntmaze`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/d4rl/d4rl_antmaze/d4rl_antmaze.py)\n\n- **Versions**:\n\n - `1.0.0`: Initial release.\n - **`1.1.1`** (default): Added v2 datasets.\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Feature structure**:\n\n FeaturesDict({\n 'steps': Dataset({\n 'action': Tensor(shape=(8,), dtype=float32),\n 'discount': float32,\n 'infos': FeaturesDict({\n 'goal': Tensor(shape=(2,), dtype=float32),\n 'qpos': Tensor(shape=(15,), dtype=float32),\n 'qvel': Tensor(shape=(14,), dtype=float32),\n }),\n 'is_first': bool,\n 'is_last': bool,\n 'is_terminal': bool,\n 'observation': Tensor(shape=(29,), dtype=float32),\n 'reward': float32,\n }),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|-------------------|--------------|-------|---------|-------------|\n| | FeaturesDict | | | |\n| steps | Dataset | | | |\n| steps/action | Tensor | (8,) | float32 | |\n| steps/discount | Tensor | | float32 | |\n| steps/infos | FeaturesDict | | | |\n| steps/infos/goal | Tensor | (2,) | float32 | |\n| steps/infos/qpos | Tensor | (15,) | float32 | |\n| steps/infos/qvel | Tensor | (14,) | float32 | |\n| steps/is_first | Tensor | | bool | |\n| steps/is_last | Tensor | | bool | |\n| steps/is_terminal | Tensor | | bool | |\n| steps/observation | Tensor | (29,) | float32 | |\n| steps/reward | Tensor | | float32 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Citation**:\n\n @misc{fu2020d4rl,\n title={D4RL: Datasets for Deep Data-Driven Reinforcement Learning},\n author={Justin Fu and Aviral Kumar and Ofir Nachum and George Tucker and Sergey Levine},\n year={2020},\n eprint={2004.07219},\n archivePrefix={arXiv},\n primaryClass={cs.LG}\n }\n\nd4rl_antmaze/umaze-v0 (default config)\n--------------------------------------\n\n- **Download size** : `221.76 MiB`\n\n- **Dataset size** : `274.83 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 10,154 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/umaze-diverse-v0\n-----------------------------\n\n- **Download size** : `220.16 MiB`\n\n- **Dataset size** : `270.23 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 1,154 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/medium-play-v0\n---------------------------\n\n- **Download size** : `220.40 MiB`\n\n- **Dataset size** : `275.20 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 10,695 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/medium-diverse-v0\n------------------------------\n\n- **Download size** : `220.39 MiB`\n\n- **Dataset size** : `271.18 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 2,924 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/large-diverse-v0\n-----------------------------\n\n- **Download size** : `220.47 MiB`\n\n- **Dataset size** : `273.36 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 7,141 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/large-play-v0\n--------------------------\n\n- **Download size** : `220.19 MiB`\n\n- **Dataset size** : `276.61 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 13,458 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/umaze-v2\n---------------------\n\n- **Download size** : `221.76 MiB`\n\n- **Dataset size** : `274.83 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 10,154 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/umaze-diverse-v2\n-----------------------------\n\n- **Download size** : `220.16 MiB`\n\n- **Dataset size** : `270.20 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 1,036 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/medium-play-v2\n---------------------------\n\n- **Download size** : `220.40 MiB`\n\n- **Dataset size** : `275.22 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 10,768 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/medium-diverse-v2\n------------------------------\n\n- **Download size** : `220.39 MiB`\n\n- **Dataset size** : `271.19 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 2,959 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/large-diverse-v2\n-----------------------------\n\n- **Download size** : `220.47 MiB`\n\n- **Dataset size** : `273.38 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 7,189 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nd4rl_antmaze/large-play-v2\n--------------------------\n\n- **Download size** : `220.18 MiB`\n\n- **Dataset size** : `276.63 MiB`\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 13,517 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]
