code: def forward(self, sample_list):
      # fwd_results holds intermediate forward pass results
      # TODO possibly replace it with another sample list
      fwd_results = {}
      self._forward_txt_encoding(sample_list, fwd_results)
      self._forward_obj_encoding(sample_list, fwd_results)
      self._forward_ocr_encoding(sample_list, fwd_results)
      self._forward_mmt_and_output(sample_list, fwd_results)
  
      # only keep scores in the forward pass results
      results = {"scores": fwd_results["scores"]}
      return results
  
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 10 for calling the M4C obj's underlying member method code with example usage: obj.forward(sample_list) and returns: results