code: def __getitem__(self, index):
      item = {}
      if isinstance(self.res, list):
          for resolution in self.res:
              image_key = f"images_{resolution}"
              item[image_key] = torch.randn(3, resolution, resolution)
      else:
          item["images"] = torch.randn(3, self.res, self.res)
  
      item["raw_text"] = f"fake text {index}"
      if not self.no_embedding:
          item[f"{self.out_key}_embeddings"] = torch.randn(
              self.token_length, self.embed_dim
          )
          item[f"{self.out_key}_mask"] = torch.ones(
              self.token_length, dtype=torch.long
          )
      return item
  
file_path: NeMo/nemo/collections/multimodal/data/imagen/imagen_dataset.py
imports: import torch
  from nemo.collections.multimodal.data.common.webdataset import WebDatasetCommon
  from nemo.collections.multimodal.data.imagen.augmentations.augmentations import PickleTransform, build_resolution_filter
  from nemo.collections.multimodal.data.imagen.augmentations.corruption import ImagePyramidNoCorruptions
  from nemo.collections.multimodal.data.stable_diffusion.augmentation.augmentations import construct_image_augmentations, identical_transform
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 2 for calling the ImagenSyntheticDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: item