code: def forward(
      self, gt_region, gt_affinity, pred_region, pred_affinity, conf_map
  ):
      loss = torch.mean(
          (
              (gt_region - pred_region).pow(2)
              + (gt_affinity - pred_affinity).pow(2)
          )
          * conf_map
      )
      return loss
  
file_path: EasyOCR/trainer/craft/loss/mseloss.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the Loss obj's underlying member method code with example usage: obj.forward(gt_region, gt_affinity, pred_region, pred_affinity, conf_map) and returns: loss