def __new__(cls, num_track_ids, reid_embed_size, num_fc_layers, classification_loss, task_loss_weight=1.0):
    'Constructor with default values for TrackParams.\n\n    Args:\n      num_track_ids: int. The maximum track ID in the dataset. Used for ReID\n        embedding classification task.\n      reid_embed_size: int. The embedding size for ReID task.\n      num_fc_layers: int. The number of (fully-connected, batch-norm, relu)\n        layers for track ID classification head.\n      classification_loss: an object_detection.core.losses.Loss object to\n        compute the loss for the ReID embedding in CenterNet.\n      task_loss_weight: float, the loss weight for the tracking task.\n\n    Returns:\n      An initialized TrackParams namedtuple.\n    '
    return super(TrackParams, cls).__new__(cls, num_track_ids, reid_embed_size, num_fc_layers, classification_loss, task_loss_weight)
Constructor with default values for TrackParams.

Args:
  num_track_ids: int. The maximum track ID in the dataset. Used for ReID
    embedding classification task.
  reid_embed_size: int. The embedding size for ReID task.
  num_fc_layers: int. The number of (fully-connected, batch-norm, relu)
    layers for track ID classification head.
  classification_loss: an object_detection.core.losses.Loss object to
    compute the loss for the ReID embedding in CenterNet.
  task_loss_weight: float, the loss weight for the tracking task.

Returns:
  An initialized TrackParams namedtuple.
def __new__(cls, num_track_ids, reid_embed_size, num_fc_layers, classification_loss, task_loss_weight=1.0):
    'Constructor with default values for TrackParams.\n\n    Args:\n      num_track_ids: int. The maximum track ID in the dataset. Used for ReID\n        embedding classification task.\n      reid_embed_size: int. The embedding size for ReID task.\n      num_fc_layers: int. The number of (fully-connected, batch-norm, relu)\n        layers for track ID classification head.\n      classification_loss: an object_detection.core.losses.Loss object to\n        compute the loss for the ReID embedding in CenterNet.\n      task_loss_weight: float, the loss weight for the tracking task.\n\n    Returns:\n      An initialized TrackParams namedtuple.\n    '
    return super(TrackParams, cls).__new__(cls, num_track_ids, reid_embed_size, num_fc_layers, classification_loss, task_loss_weight)