class_docstr: The Pytree Loader is the default loader of the Cache object.
class_docstr_tok: ["The","Pytree","Loader","is","the","default","loader","of","the","Cache","object","."]
docstr: Deserialize the raw bytes into their python equivalent.
docstr_tok: ["Deserialize","the","raw","bytes","into","their","python","equivalent","."]
code: def deserialize(self, raw_item_data: bytes) -> "PyTree":
      """Deserialize the raw bytes into their python equivalent."""
      idx = len(self._config["data_format"]) * 4
      sizes = np.frombuffer(raw_item_data[:idx], np.uint32)
      data = []
      for size, data_format in zip(sizes, self._config["data_format"]):
          serializer = self._serializers[data_format]
          data_bytes = raw_item_data[idx : idx + size]
          data.append(serializer.deserialize(data_bytes))
          idx += size
      return tree_unflatten(data, self._config["data_spec"])
  
imports: import os
  from abc import ABC, abstractmethod
  from time import sleep
  from typing import Any, Dict, List, Optional, Tuple
  import numpy
  import torch
  from lightning.data.streaming.constants import _TORCH_DTYPES_MAPPING, _TORCH_GREATER_EQUAL_2_1_0
  from lightning.data.streaming.serializers import Serializer
label_desc: Use image node_id 5 for calling the PyTreeLoader obj's underlying member method code with example usage: obj.deserialize(raw_item_data) and returns: tree_unflatten