code: def validate_mp_config(config):
      """Validate the configuration dictionary for model parallelism.
  
      Args:
         config (dict): Dictionary holding configuration keys and values.
  
      Raises:
          ValueError: If any of the keys have incorrect values.
      """
  
      def validate_positive(key):
          try:
              if not isinstance(config[key], int) or config[key] < 1:
                  raise ValueError(
                      f"The number of {key} must be a positive integer."
                  )
          except KeyError:
              pass
  
      def validate_in(key, vals):
          try:
              if config[key] not in vals:
                  raise ValueError(f"{key} must be a value in: {vals}.")
          except KeyError:
              pass
  
      def validate_bool(keys):
          validate_in(keys, [True, False])
  
      validate_in(
          "pipeline", ["simple", "interleaved", "_only_forward"]
      )
      validate_in("placement_strategy", ["spread", "cluster"])
      validate_in("optimize", ["speed", "memory"])
  
      for key in ["microbatches", "partitions", "active_microbatches"]:
          validate_positive(key)
  
      for key in [
          "auto_partition",
          "contiguous",
          "load_partition",
          "horovod",
          "ddp",
          "deterministic_server",
      ]:
          validate_bool(key)
  
      if "partition_file" in config and not isinstance(
          config.get("partition_file"), str
      ):
          raise ValueError("'partition_file' must be a str.")
  
      if (
          config.get("auto_partition") is False
          and "default_partition" not in config
      ):
          raise ValueError(
              "default_partition must be supplied if auto_partition is set to False!"
          )
  
      if (
          "default_partition" in config
          and config["default_partition"] >= config["partitions"]
      ):
          raise ValueError(
              "default_partition must be less than the number of partitions!"
          )
  
      if "memory_weight" in config and (
          config["memory_weight"] > 1.0 or config["memory_weight"] < 0.0
      ):
          raise ValueError("memory_weight must be between 0.0 and 1.0!")
  
      if "ddp_port" in config and "ddp" not in config:
          raise ValueError("`ddp_port` needs `ddp` to be set as well")
  
      if "ddp_dist_backend" in config and "ddp" not in config:
          raise ValueError(
              "`ddp_dist_backend` needs `ddp` to be set as well"
          )
  
      if "ddp_port" in config:
          if (
              not isinstance(config["ddp_port"], int)
              or config["ddp_port"] < 0
          ):
              value = config["ddp_port"]
              raise ValueError(f"Invalid port number {value}.")
  
      if config.get("horovod", False) and config.get("ddp", False):
          raise ValueError(
              "'ddp' and 'horovod' cannot be simultaneously enabled."
          )
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  import re
  import time
  import shutil
  import tempfile
  from collections import namedtuple
  from typing import List, Optional, Union, Dict
  from packaging import version
  import sagemaker.image_uris
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.s3_utils import s3_path_join
  from sagemaker.session_settings import SessionSettings
  import sagemaker.utils
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.deprecations import renamed_warning, renamed_kwargs
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.deprecations import deprecation_warn_base
label_desc: Use image node_id 5 for calling a global function with example usage: validate_mp_config(config) without return types