code: def __getitem__(self, idx: int) -> Sample:
      sample_info = self.annotation_db[idx]
      current_sample = Sample()
      processed_caption = self.masked_token_processor(
          {
              "text_a": sample_info["caption"],
              "text_b": "",
              "is_correct": True,
          }
      )
      current_sample.update(processed_caption)
      current_sample.image_id = sample_info["image_id"]
      current_sample.feature_path = sample_info["feature_path"]
  
      # Get the image features
      if self._use_features:
          features = self.features_db[idx]
          image_info_0 = features["image_info_0"]
          if image_info_0 and "image_id" in image_info_0.keys():
              image_info_0["feature_path"] = image_info_0["image_id"]
              image_info_0.pop("image_id")
          current_sample.update(features)
      elif self._use_images:
          image_id = sample_info["image_id"]
          dataset = sample_info["dataset_id"]
          if "mscoco" in dataset:
              image_id = image_id.rjust(12, "0")
  
          assert (
              len(self.image_db.from_path(image_id)["images"]) != 0
          ), f"image id: {image_id} not found"
          current_sample.image = self.image_db.from_path(image_id)[
              "images"
          ][0]
  
      return current_sample
  
file_path: mmf/mmf/datasets/builders/localized_narratives/masked_dataset.py
imports: from abc import ABC
  from mmf.common.sample import Sample
  from mmf.common.typings import MMFDatasetConfigType
  from mmf.datasets.builders.localized_narratives.database import LocalizedNarrativesAnnotationDatabase
  from mmf.datasets.mmf_dataset import MMFDataset
label_desc: Use image node_id 2 for calling the MaskedLocalizedNarrativesDatasetMixin obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: current_sample