Implements the multihead softmax attention. Arguments --------- q: The tensor containing the query. (B, T, H, D)

x: (batch, seqlen, hidden_dim) (where hidden_dim = num heads * head dim) key_padding_mask: bool tensor of shape (batch, seqlen)

run forward.

Returns the data path as well as all annotations related to that sample_data. Note that the boxes are transformed into the current sensor's c

Get testing data after pipeline. Args: idx (int): Index of data. Returns: dict: Testing data after pipeline

Get training data and annotations after pipeline. Args: idx (int): Index of data. Returns: dict: Training da

Render selected annotation. :param anntoken: Sample_annotation token. :param margin: How many meters in each direction to include in LIDA

Creates a summary plot with PR and TP curves for each class. :param md_list: DetectionMetricDataList instance. :param metrics: DetectionM

symbolic function for creating onnx op.

Visualizes a sample from BEV with annotations and detection results. :param nusc: NuScenes object. :param sample_token: The nuScenes samp

bool: Whether the detector has a neck in image branch.