code: def canonicalize_dtype(
      *args, dtype: Optional[Dtype] = None, inexact: bool = True
  ) -> Dtype:
      """Canonicalize an optional dtype to the definitive dtype.
  
      If the ``dtype`` is None this function will infer the dtype. If it is not
      None it will be returned unmodified or an exceptions is raised if the dtype
      is invalid.
      from the input arguments using ``jnp.result_type``.
  
      Args:
        *args: JAX array compatible values. None values
          are ignored.
        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 dtype that *args should be cast to.
      """
      if dtype is None:
          args_filtered = [
              jnp.asarray(x) for x in args if x is not None
          ]
          dtype = jnp.result_type(*args_filtered)
          if inexact and not jnp.issubdtype(dtype, jnp.inexact):
              dtype = jnp.promote_types(jnp.float32, dtype)
      if inexact and not jnp.issubdtype(dtype, jnp.inexact):
          raise ValueError(f"Dtype must be inexact: {dtype}")
      return dtype
  
imports: from typing import Any, Optional
  from jax import numpy
  from typing_extensions import TypeVarTuple, Unpack
label_desc: Use image node_id 1 for calling a global function with example usage: canonicalize_dtype() and returns: dtype