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benjaminrwilson
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Looks really nice. Left a few minor comments.
| NUM_PRED_TIMESTEPS: Final[int] = 60 | ||
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| @dataclass |
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Can this be frozen?
| """ | ||
| for scenario_predictions in self.predictions.values(): | ||
| for track_predictions in scenario_predictions.values(): | ||
| if track_predictions.shape[-2:] != (NUM_PRED_TIMESTEPS, 2): |
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I think it'd be nice to assign track_predictions.shape[-2:] to a descriptive variable name.
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| TrackPredictions = NDArrayNumber # Track predictions are expected to be of shape (*, NUM_PRED_TIMESTEPS, 2) | ||
| ScenarioPredictions = Dict[str, TrackPredictions] # Mapping from track ID to track predictions | ||
| PredictionRow = Tuple[str, str, int, NDArrayNumber, NDArrayNumber] |
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[nit] A docstring can be useful here as well
| SUBMISSION_COL_NAMES: Final[List[str]] = [ | ||
| "scenario_id", | ||
| "track_id", | ||
| "prediction_rank", |
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Does this mean we don't expect probabilities?
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Updated to add probabilities as an input.
| "predicted_trajectory_x", | ||
| "predicted_trajectory_y", | ||
| ] | ||
| NUM_PRED_TIMESTEPS: Final[int] = 60 |
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[nit] Can we make this more visible? Seems like an important constant. Probably a config shared across the API as well.
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PR Summary
This PR adds a dataclass to help researchers build submission files for the AV2 motion forecasting challenge.
Challenge submissions are initialized using a mapping from scenario and track IDs to a numpy array of predicted trajectories. The data dict is then serialized to a parquet file, which will be submittable to an evaluation server.
Testing
Added unit tests for data validation and (de)serialization.
In order to ensure this PR works as intended, it is:
Compliance with Standards
As the author, I certify that this PR conforms to the following standards: