import datasets

_DESCRIPTION = """\
    Dataset of pre-processed samples from a small portion of the \
    Waymo Open Motion Data for our risk-biased prediction task.
"""

_CITATION = """\
    @InProceedings{NiMe:2022,
    author = {Haruki Nishimura, Jean Mercat, Blake Wulfe, Rowan McAllister},
    title = {RAP: Risk-Aware Prediction for Robust Planning},
    booktitle = {Proceedings of the 2022 IEEE International Conference on Robot Learning (CoRL)},
    month = {December},
    year = {2022},
    address = {Grafton Road, Auckland CBD, Auckland 1010},
    url = {},
}
"""


class RAPConfig(datasets.BuilderConfig):
    """BuilderConfig for RiskBiasedDataset."""

    def __init__(self, **kwargs):
        """BuilderConfig for RiskBiasedDataset.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(RAPConfig, self).__init__(version=datasets.Version("0.0.0", ""), **kwargs)



class RiskBiasedDataset(datasets.Dataset):
    """Dataset of pre-processed samples from a portion of the 
    Waymo Open Motion Data for the risk-biased prediction task."""
    
    BUILDER_CONFIGS = [
        RAPConfig(
            name="json_lists",
            description="JSON lists sample format"
        )
    ]
    
    def _info(self):
        return datasets.DatasetInfo(
            description= _DESCRIPTION,
            features=datasets.Features(
                {"x": datasets.Sequence(datasets.Value("float32")),
                 "mask_x": datasets.Sequence(datasets.Value("bool")),
                 "y": datasets.Sequence(datasets.Value("float32")),
                 "mask_y": datasets.Sequence(datasets.Value("bool")),
                 "mask_loss": datasets.Sequence(datasets.Value("bool")),
                 "map_data": datasets.Sequence(datasets.Value("float32")),
                 "mask_map": datasets.Sequence(datasets.Value("bool")),
                 "offset": datasets.Sequence(datasets.Value("float32")),
                 "x_ego": datasets.Sequence(datasets.Value("float32")),
                 "y_ego": datasets.Sequence(datasets.Value("float32")),
                 }
            ),
            supervised_keys=None,
            homepage="https://sites.google.com/d/1cwohIm9fzTZEPAo7b_Di4h9iNgMiKHRo/p/1nPdTBSee6E40dmUXNyqxzUtb4_NnkI_6/edit",
            citation=_CITATION,
        )