code: def _forward_output(self, sample_list, fwd_results):
      mmt_dec_output = fwd_results["mmt_dec_output"]
      mmt_ocr_output = fwd_results["mmt_ocr_output"]
      ocr_mask = fwd_results["ocr_mask"]
  
      fixed_scores = self.classifier(mmt_dec_output)
      dynamic_ocr_scores = self.ocr_ptr_net(
          mmt_dec_output, mmt_ocr_output, ocr_mask
      )
      scores = torch.cat([fixed_scores, dynamic_ocr_scores], dim=-1)
      fwd_results["scores"] = scores
  
imports: import functools
  import logging
  import math
  import torch
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.layers import ClassifierLayer
  from mmf.utils.build import build_image_encoder
  from omegaconf import OmegaConf
  from torch import nn
label_desc: Use image node_id 15 for calling the M4C obj's underlying member method code with example usage: obj._forward_output(sample_list, fwd_results) without return types