code: def promote_dtype(*args, dtype=None, inexact=True) -> List[Array]:
      """ "Promotes input arguments to a specified or inferred dtype.
  
      All args are cast to the same dtype. See ``canonicalize_dtype`` for how
      this dtype is determined.
  
      The behavior of promote_dtype is mostly a convinience wrapper around
      ``jax.numpy.promote_types``. The differences being that it automatically casts
      all input to the inferred dtypes, allows inference to be overridden by a
      forced dtype, and has an optional check to garantuee the resulting dtype is
      inexact.
  
      Args:
        *args: JAX array compatible values. None values are returned as is.
        dtype: Optional dtype override. If specified the arguments are cast to the
          specified dtype instead and dtype inference is disabled.
        inexact: When True, the output dtype must be a subdtype of `jnp.inexact`.
          Inexact dtypes are real or complex floating points. This is useful when
          you want to apply operations that don't work directly on integers like
          taking a mean for example.
  
      Returns:
        The arguments cast to arrays of the same dtype.
      """
      dtype = canonicalize_dtype(*args, dtype=dtype, inexact=inexact)
      return [
          jnp.asarray(x, dtype) if x is not None else None for x in args
      ]
  
label_desc: Use image node_id 2 for calling a global function with example usage: promote_dtype() and returns: unknown