class_docstr: An XGBoost SageMaker ``Model`` that can be deployed to a SageMaker ``Endpoint``.
class_docstr_tok: ["An","XGBoost","SageMaker","``","Model","``","that","can","be","deployed","to","a","SageMaker","``","Endpoint","``","."]
docstr: Return a container definition with framework configuration.
  
  The framework configuration is set in model environment variables.
  
  Args:
      instance_type (str): The EC2 instance type to deploy this Model to.
      accelerator_type (str): The Elastic Inference accelerator type to deploy to the
      instance for loading and making inferences to the model. This parameter is
          unused because accelerator types are not supported by XGBoostModel.
      serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
          Specifies configuration related to serverless endpoint. Instance type is
          not provided in serverless inference. So this is used to find image URIs.
      accept_eula (bool): For models that require a Model Access Config, specify True or
          False to indicate whether model terms of use have been accepted.
          The `accept_eula` value must be explicitly defined as `True` in order to
          accept the end-user license agreement (EULA) that some
          models require. (Default: None).
  
  Returns:
      dict[str, str]: A container definition object usable with the CreateModel API.
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code: def prepare_container_def(
      self,
      instance_type=None,
      accelerator_type=None,
      serverless_inference_config=None,
      accept_eula=None,
  ):
      """Return a container definition with framework configuration.
  
      The framework configuration is set in model environment variables.
  
      Args:
          instance_type (str): The EC2 instance type to deploy this Model to.
          accelerator_type (str): The Elastic Inference accelerator type to deploy to the
          instance for loading and making inferences to the model. This parameter is
              unused because accelerator types are not supported by XGBoostModel.
          serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
              Specifies configuration related to serverless endpoint. Instance type is
              not provided in serverless inference. So this is used to find image URIs.
          accept_eula (bool): For models that require a Model Access Config, specify True or
              False to indicate whether model terms of use have been accepted.
              The `accept_eula` value must be explicitly defined as `True` in order to
              accept the end-user license agreement (EULA) that some
              models require. (Default: None).
  
      Returns:
          dict[str, str]: A container definition object usable with the CreateModel API.
      """
      deploy_image = self.image_uri
      if not deploy_image:
          deploy_image = self.serving_image_uri(
              self.sagemaker_session.boto_region_name,
              instance_type,
              serverless_inference_config=serverless_inference_config,
          )
  
      deploy_key_prefix = model_code_key_prefix(
          self.key_prefix, self.name, deploy_image
      )
      self._upload_code(
          key_prefix=deploy_key_prefix,
          repack=self.enable_network_isolation(),
      )
      deploy_env = dict(self.env)
      deploy_env.update(self._script_mode_env_vars())
  
      if self.model_server_workers:
          deploy_env[
              MODEL_SERVER_WORKERS_PARAM_NAME.upper()
          ] = to_string(self.model_server_workers)
      model_data = (
          self.repacked_model_data
          if self.enable_network_isolation()
          else self.model_data
      )
      return sagemaker.container_def(
          deploy_image,
          model_data,
          deploy_env,
          accept_eula=accept_eula,
      )
  
imports: from __future__ import absolute_import
  import logging
  from typing import Optional, Union, List, Dict
  import sagemaker
  from sagemaker import image_uris, ModelMetrics
  from sagemaker.deserializers import CSVDeserializer
  from sagemaker.drift_check_baselines import DriftCheckBaselines
  from sagemaker.fw_utils import model_code_key_prefix
  from sagemaker.metadata_properties import MetadataProperties
  from sagemaker.model import FrameworkModel, MODEL_SERVER_WORKERS_PARAM_NAME
  from sagemaker.predictor import Predictor
  from sagemaker.serializers import LibSVMSerializer
  from sagemaker.utils import to_string
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.xgboost.defaults import XGBOOST_NAME
  from sagemaker.xgboost.utils import validate_py_version, validate_framework_version
label_desc: Use image node_id 3 for calling the XGBoostModel obj's underlying member method code with example usage: obj.prepare_container_def(instance_type, accelerator_type, serverless_inference_config, accept_eula) and returns: sagemaker