code: def load_item(self, idx):
      sample_info = self.annotation_db[idx]
      current_sample = Sample()
  
      if self._use_features:
          features = self.features_db[idx]
          if hasattr(self, "transformer_bbox_processor"):
              features[
                  "image_info_0"
              ] = self.transformer_bbox_processor(
                  features["image_info_0"]
              )
  
          if self.config.get("use_image_feature_masks", False):
              current_sample.update(
                  {
                      "image_labels": self.masked_region_processor(
                          features["image_feature_0"]
                      )
                  }
              )
  
          current_sample.update(features)
      else:
          image_path = str(sample_info["image_name"]) + ".jpg"
          current_sample.image = self.image_db.from_path(image_path)[
              "images"
          ][0]
  
      current_sample = self._add_masked_caption(
          sample_info, current_sample
      )
      return current_sample
  
file_path: mmf/mmf/datasets/builders/coco/masked_dataset.py
imports: import random
  from mmf.common.sample import Sample
  from mmf.datasets.builders.coco import COCODataset
label_desc: Use image node_id 2 for calling the MaskedCOCODataset obj's underlying member method code with example usage: obj.load_item(idx) and returns: current_sample