code: def _build_functions_no_pickles(data_cfg):
      def tuple_to_dict(inp):
          for input in inp:
              out_dict = dict()
              out_dict["images"] = input[0]
              out_dict["raw_text"] = input[1]
              yield out_dict
  
      def transform_fn(sample):
          image, text = sample["jpg"], sample["txt"]
          img_transform = construct_image_augmentations(
              data_cfg.train.get("augmentations"), normalize=True
          )
          text_transform = identical_transform
          return img_transform(image), text_transform(text)
  
      return tuple_to_dict, transform_fn
  
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 a global function with example usage: _build_functions_no_pickles(data_cfg) and returns: tuple_to_dict,  transform_fn, img_transform,  text_transform