Upload risk_biased_dataset.py

risk_biased_dataset.py

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+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,
+        )