code: def _validate_accelerator_type(accelerator_type):
      """Raises a ``ValueError`` if ``accelerator_type`` is invalid."""
      if (
          not accelerator_type.startswith("ml.eia")
          and accelerator_type != "local_sagemaker_notebook"
      ):
          raise ValueError(
              "Invalid SageMaker Elastic Inference accelerator type: {}. "
              "See https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html".format(
                  accelerator_type
              )
          )
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  import re
  from typing import Optional
  from packaging.version import Version
  from sagemaker import utils
  from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_SESSION
  from sagemaker.jumpstart.utils import is_jumpstart_model_input
  from sagemaker.spark import defaults
  from sagemaker.jumpstart import artifacts
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.utilities import override_pipeline_parameter_var
  from sagemaker.fw_utils import GRAVITON_ALLOWED_TARGET_INSTANCE_FAMILY, GRAVITON_ALLOWED_FRAMEWORKS
label_desc: Use image node_id 10 for calling a global function with example usage: _validate_accelerator_type(accelerator_type) without return types