class_docstr: Word Region Alignment from UNITER.
  Optimal Transport (OT) distance between text and image
  features is used to optimize for WRA.
  OT transport plan (T) is approximated through IPOT.
code: def __init__(
      self,
      loss_name: str = "wra_loss",
      ot_inputs_key: str = "wra_info",
      wra_label_key: str = "is_correct",
      *args,
      **kwargs,
  ):
      super().__init__()
      self.loss_name = loss_name
      self.ot_inputs_key = ot_inputs_key
      self.wra_label_key = wra_label_key
  
imports: from typing import Dict
  from mmf.common.registry import registry
  from mmf.modules.ot import optimal_transport_dist
  from torch import nn, Tensor
label_desc: Use image node_id 1 to create a new WRA object from inherited base classes: nn with example: obj = WRA(loss_name, ot_inputs_key, wra_label_key)