code: def sharded_prefetch(
      iterable: Iterable[types.NestedArray],
      buffer_size: int = 5,
      num_threads: int = 1,
      split_fn: Optional[_SplitFunction] = None,
      devices: Optional[Sequence[jax.Device]] = None,
  ) -> core.PrefetchingIterator:
      """Performs sharded prefetching from an iterable in separate threads.
  
      Elements from the resulting generator are intended to be used in a jax.pmap
      call. Every element is a sharded prefetched array with an additional replica
      dimension and corresponds to jax.local_device_count() elements from the
      original iterable.
  
      Args:
        iterable: A python iterable. This is used to build the python prefetcher.
          Note that each iterable should only be passed to this function once as
          iterables aren't thread safe.
        buffer_size (int): Number of elements to keep in the prefetch buffer.
        num_threads (int): Number of threads.
        split_fn: Optional function applied to every element from the iterable to
          split the parts of it that will be kept in the host and the parts that
          will sent to the device.
        devices: Devices used for prefecthing. Optional, jax.local_devices() by
          default.
  
      Returns:
        Prefetched elements from the original iterable with additional replica
        dimension.
      Raises:
        ValueError if the buffer_size <= 1.
        Any error thrown by the iterable_function. Note this is not raised inside
          the producer, but after it finishes executing.
      """
  
      devices = devices or jax.local_devices()
  
      iterable = PutToDevicesIterable(
          iterable=iterable,
          pmapped_user=True,
          devices=devices,
          split_fn=split_fn,
      )
  
      return prefetch(
          iterable, buffer_size, device=None, num_threads=num_threads
      )
  
imports: import functools
  import itertools
  import queue
  import threading
  from typing import Callable, Iterable, Iterator, NamedTuple, Optional, Sequence, Tuple, TypeVar
  from absl import logging
  from acme import core
  from acme import types
  from acme.jax import types
  import haiku
  import jax
  import jax.numpy
  import numpy
  import reverb
  import tree
label_desc: Use image node_id 19 for calling a global function with example usage: sharded_prefetch(iterable, buffer_size, num_threads, split_fn, devices) and returns: prefetch