plex_robosuite

Note: This dataset was added recently and is only available in our tfds-nightly package .

• Description:

A dataset of high-qualty demonstration trajectories for Robosuite's Door, Stack, PickPlaceMilk, PickPlaceBread, PickPlaceCereal, and NutAssemblyRound tasks, 75 demonstrations per each.

• Homepage: https://microsoft.github.io/PLEX/

• Source code: tfds.robotics.rtx.PlexRobosuite

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: Unknown size

• Auto-cached (documentation): Unknown

• Splits:

Split	Examples

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'episode_id': string,
    }),
    'steps': Dataset({
        'action': Tensor(shape=(7,), dtype=float64),
        'discount': Scalar(shape=(), dtype=float32),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'language_embedding': Tensor(shape=(512,), dtype=float32),
        'language_instruction': string,
        'observation': FeaturesDict({
            'image': Image(shape=(128, 128, 3), dtype=uint8),
            'state': Tensor(shape=(32,), dtype=float64),
            'wrist_image': Image(shape=(128, 128, 3), dtype=uint8),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
episode_metadata	FeaturesDict
episode_metadata/episode_id	Tensor		string
steps	Dataset
steps/action	Tensor	(7,)	float64
steps/discount	Scalar		float32
steps/is_first	Tensor		bool
steps/is_last	Tensor		bool
steps/is_terminal	Tensor		bool
steps/language_embedding	Tensor	(512,)	float32
steps/language_instruction	Tensor		string
steps/observation	FeaturesDict
steps/observation/image	Image	(128, 128, 3)	uint8
steps/observation/state	Tensor	(32,)	float64
steps/observation/wrist_image	Image	(128, 128, 3)	uint8
steps/reward	Scalar		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe): Missing.

• Citation:

https://doi.org/10.48550/arXiv.2303.08789