code: def preprocess_image(self, sample_list) -> Tuple:
      if self._is_direct_features_input:
          return sample_list.image_feature_0.permute(0, 2, 1).unsqueeze(
              3
          )
          # return shape is B x 2048 x 1 x 1
      else:
          return sample_list.image
  
imports: import math
  from copy import deepcopy
  from dataclasses import dataclass
  from typing import Any, Tuple
  import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.encoders import IdentityEncoder
  from mmf.modules.layers import AttnPool1d
  from mmf.utils.build import build_classifier_layer, build_image_encoder, build_text_encoder
  from mmf.utils.general import filter_grads
  from mmf.utils.modeling import get_bert_configured_parameters
  from mmf.utils.transform import transform_to_batch_sequence
  from omegaconf import MISSING
label_desc: Use image node_id 6 for calling the CMSharedTransformer obj's underlying member method code with example usage: obj.preprocess_image(sample_list) and returns: sample_list, sample_list