code: def __getitem__(self, idx):
      sample_info = self.annotation_db[idx]
      current_sample = Sample()
      plot = sample_info["plot"]
      if isinstance(plot, list):
          plot = plot[0]
      processed_sentence = self.text_processor({"text": plot})
  
      current_sample.text = processed_sentence["text"]
      if "input_ids" in processed_sentence:
          current_sample.update(processed_sentence)
  
      if self._use_features is True:
          features = self.features_db[idx]
          if hasattr(self, "transformer_bbox_processor"):
              features[
                  "image_info_0"
              ] = self.transformer_bbox_processor(
                  features["image_info_0"]
              )
          current_sample.update(features)
  
      processed = self.answer_processor(
          {"answers": sample_info["genres"]}
      )
      current_sample.answers = processed["answers"]
      current_sample.targets = processed["answers_scores"]
  
      return current_sample
  
file_path: mmf/mmf/datasets/builders/mmimdb/dataset.py
imports: import copy
  import json
  import torch
  from mmf.common.sample import Sample
  from mmf.datasets.mmf_dataset import MMFDataset
label_desc: Use image node_id 2 for calling the MMIMDbFeaturesDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: current_sample