code: def _read_stream(
      self, f: "pyarrow.NativeFile", path: str
  ) -> Iterator[ray.data.block.Block]:
      file_info = streaming.base.format.base.reader.FileInfo(
          basename=os.path.basename(path),
          bytes=os.stat(path).st_size,
          hashes={},
      )
      reader = streaming.base.format.mds.MDSReader(
          dirname=os.path.dirname(path),
          split=None,
          column_encodings=["pil", "int"],
          column_names=["image", "label"],
          column_sizes=[None, 8],
          compression=None,
          hashes=[],
          raw_data=file_info,
          samples=-1,
          size_limit=None,
          zip_data=None,
      )
  
      i = 0
      while True:
          try:
              row = reader.decode_sample(reader.get_sample_data(i))
          except IndexError:
              break
          row["image"] = np.array(row["image"])
          builder = DelegatingBlockBuilder()
          builder.add(row)
          block = builder.build()
          yield block
  
          i += 1
  
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 for calling the MdsDatasource obj's underlying member method code with example usage: obj._read_stream(f, path) without return types