code: def __init__(
      self,
      s3_bucket: str,
      num_physical_nodes,
      cache_dir: str,
      transforms: Callable,
      cache_limit=None,
      epoch_size=None,
  ) -> None:
      super().__init__(
          remote=s3_bucket,
          local=cache_dir,
          cache_limit=cache_limit,
          epoch_size=epoch_size,
          # Set StreamingDataset to read sequentially.
          shuffle=False,
          num_canonical_nodes=num_physical_nodes,
      )
      self.transforms = transforms
  
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 1 to create a new S3MosaicDataset object from inherited base classes: StreamingDataset with example: obj = S3MosaicDataset(s3_bucket, num_physical_nodes, cache_dir, transforms, cache_limit, epoch_size)