code: def get_ray_parquet_dataset(parquet_data_root, parallelism=None):
      if parallelism is not None:
          ray_dataset = ray.data.read_parquet(
              parquet_data_root, parallelism=parallelism
          )
      else:
          ray_dataset = ray.data.read_parquet(parquet_data_root)
      ray_dataset = ray_dataset.map(decode_image_crop_and_flip)
      return ray_dataset
  
imports: import ray
  import torch
  import torchvision
  from torchvision.transforms.functional import pil_to_tensor
  import os
  import tensorflow
  import numpy
  from PIL import Image
  from typing import TYPE_CHECKING, Iterator, Callable, Any
  import pandas
  from benchmark import Benchmark
  import streaming
  from streaming import LocalDataset, StreamingDataset
  from ray.data._internal.delegating_block_builder import DelegatingBlockBuilder
label_desc: Use image node_id 13 for calling a global function with example usage: get_ray_parquet_dataset(parquet_data_root, parallelism) and returns: ray_dataset