code: def input_spec_to_jax_shape_dtype_struct(
      spec: Union[Tuple[Tuple[int, ...], jnp.dtype], Tuple[int, ...]],
      batch_size: Optional[int] = None,
  ) -> jax.ShapeDtypeStruct:
      """Parse an input specs into a jax.ShapeDtypeStruct."""
      spec = tuple(spec)
      if batch_size and len(spec) == 1:
          raise ValueError(
              "batch_size unsupported when len(spec) is 1."
          )
      if len(spec) == 2 and isinstance(spec[0], abc.Iterable):
          shape = (
              (batch_size,) + tuple(spec[0][1:])
              if batch_size
              else spec[0]
          )
          dtype = spec[1]
      else:
          shape = (
              (batch_size,) + tuple(spec[1:]) if batch_size else spec
          )
          dtype = jnp.float32
      return jax.ShapeDtypeStruct(shape, dtype)
  
imports: from collections import abc
  from concurrent import futures
  import json
  import operator
  import threading
  from typing import Any, Callable, Optional, Sequence, Set, Tuple, Union
  from absl import logging
  from clu import parameter_overview
  import jax
  import jax.numpy
  from jax.tree_util import tree_map
  import ml_collections
label_desc: Use image node_id 3 for calling a global function with example usage: input_spec_to_jax_shape_dtype_struct(spec, batch_size) and returns: jax