class_docstr: An unsupervised learning algorithm that attempts to find discrete groupings within data.
  
  As the result of KMeans, members of a group are as similar as possible to one another and as
  different as possible from members of other groups. You define the attributes that you want
  the algorithm to use to determine similarity.
docstr: Return a :class:`~sagemaker.amazon.kmeans.KMeansModel`.
  
  It references the latest s3 model data produced by this Estimator.
  
  Args:
      vpc_config_override (dict[str, list[str]]): Optional override for
          VpcConfig set on the model.
          Default: use subnets and security groups from this Estimator.
          * 'Subnets' (list[str]): List of subnet ids.
          * 'SecurityGroupIds' (list[str]): List of security group ids.
      **kwargs: Additional kwargs passed to the KMeansModel constructor.
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code: def create_model(
      self, vpc_config_override=VPC_CONFIG_DEFAULT, **kwargs
  ):
      """Return a :class:`~sagemaker.amazon.kmeans.KMeansModel`.
  
      It references the latest s3 model data produced by this Estimator.
  
      Args:
          vpc_config_override (dict[str, list[str]]): Optional override for
              VpcConfig set on the model.
              Default: use subnets and security groups from this Estimator.
              * 'Subnets' (list[str]): List of subnet ids.
              * 'SecurityGroupIds' (list[str]): List of security group ids.
          **kwargs: Additional kwargs passed to the KMeansModel constructor.
      """
      return KMeansModel(
          self.model_data,
          self.role,
          self.sagemaker_session,
          vpc_config=self.get_vpc_config(vpc_config_override),
          **kwargs,
      )
  
imports: from __future__ import absolute_import
  from typing import Union, Optional, List
  from sagemaker import image_uris
  from sagemaker.amazon.amazon_estimator import AmazonAlgorithmEstimatorBase
  from sagemaker.amazon.common import RecordSerializer, RecordDeserializer
  from sagemaker.amazon.hyperparameter import Hyperparameter
  from sagemaker.amazon.validation import gt, isin, ge, le
  from sagemaker.predictor import Predictor
  from sagemaker.model import Model
  from sagemaker.session import Session
  from sagemaker.utils import pop_out_unused_kwarg
  from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 2 for calling the KMeans obj's underlying member method code with example usage: obj.create_model(vpc_config_override) and returns: KMeansModel