Reset the state of the inner optimizer.

This module is in charge of warning in case of a collision and managing possible tailgating chances. :param location: cu

Compute the average precision, given the recall and precision curves # Arguments recall: The recall curve (list) precision: Th

Modified from the codes of Waymo Open Dataset. Convert range images to point cloud. Args: frame: open dataset frame range

Create image depth feature volume by multiplying image features with depth distributions Args: image_features: (N, C, H,

Create dataset_infos files in order not to have it in a preprocessed pickle file with the info for each sample See PandasetDataset.get_in

download the model checkpoint artifact if the resume path starts with WANDB_ARTIFACT_PREFIX arguments: opt (namespace) -- Co

Draw a list of waypoints at a certain height given in z. :param world: carla.world object :param waypoints: list or iterable con

commit the log_dict, model artifacts and Tables to W&B and flush the log_dict. arguments: best_result (boolean): Boolean rep

x: Features to be visualized module_type: Module type stage: Module stage within model n: Maxim

Removes layers from pretrained state dict that are not used or changed in model Args: model_dict: dict, Default model sta

Finds all spconv keys that need to have weight's transposed

:param xyz: (N1 + N2 ..., 3) tensor of the xyz coordinates of the features :param xyz_batch_cnt: (batch_size), [N1, N2, ...]

Args: points: (B, N, 3) point_features: (B, N, C) boxes3d: (B, M, 7), [x, y, z, dx, dy, dz, heading]

:param input_data: input dict :return: