class_docstr: Make prediction requests to an Amazon SageMaker endpoint.
class_docstr_tok: ["Make","prediction","requests","to","an","Amazon","SageMaker","endpoint","."]
docstr: Updates the DataCaptureConfig for the Predictor's associated Amazon SageMaker Endpoint.
  
  Update is done using the provided DataCaptureConfig.
  
  Args:
      data_capture_config (sagemaker.model_monitor.DataCaptureConfig): The
          DataCaptureConfig to update the predictor's endpoint to use.
docstr_tok: ["Updates","the","DataCaptureConfig","for","the","Predictor","'s","associated","Amazon","SageMaker","Endpoint",".","Update","is","done","using","the","provided","DataCaptureConfig",".","Args",":","data_capture_config","(","sagemaker.model_monitor.DataCaptureConfig",")",":","The","DataCaptureConfig","to","update","the","predictor","'s","endpoint","to","use","."]
code: def update_data_capture_config(self, data_capture_config):
      """Updates the DataCaptureConfig for the Predictor's associated Amazon SageMaker Endpoint.
  
      Update is done using the provided DataCaptureConfig.
  
      Args:
          data_capture_config (sagemaker.model_monitor.DataCaptureConfig): The
              DataCaptureConfig to update the predictor's endpoint to use.
      """
      endpoint_desc = (
          self.sagemaker_session.sagemaker_client.describe_endpoint(
              EndpointName=self.endpoint_name
          )
      )
  
      new_config_name = name_from_base(base=self.endpoint_name)
  
      data_capture_config_dict = None
      if data_capture_config is not None:
          data_capture_config_dict = (
              data_capture_config._to_request_dict()
          )
  
      self.sagemaker_session.create_endpoint_config_from_existing(
          existing_config_name=endpoint_desc["EndpointConfigName"],
          new_config_name=new_config_name,
          new_data_capture_config_dict=data_capture_config_dict,
      )
  
      self.sagemaker_session.update_endpoint(
          endpoint_name=self.endpoint_name,
          endpoint_config_name=new_config_name,
      )
  
imports: from __future__ import print_function, absolute_import
  import abc
  import datetime
  from typing import Any, Dict, Optional, Tuple, Union
  import logging
  from sagemaker.enums import EndpointType
  from sagemaker.deprecations import deprecated_class, deprecated_deserialize, deprecated_serialize, removed_kwargs, renamed_kwargs, renamed_warning
  from sagemaker.deserializers import BytesDeserializer, CSVDeserializer, JSONDeserializer, NumpyDeserializer, StreamDeserializer, StringDeserializer
  from sagemaker.jumpstart.payload_utils import PayloadSerializer
  from sagemaker.jumpstart.types import JumpStartSerializablePayload
  from sagemaker.jumpstart.utils import get_jumpstart_content_bucket
  from sagemaker.model_monitor import DataCaptureConfig, DefaultModelMonitor, ModelBiasMonitor, ModelExplainabilityMonitor, ModelMonitor, ModelQualityMonitor
  from sagemaker.serializers import CSVSerializer, IdentitySerializer, JSONSerializer, NumpySerializer
  from sagemaker.session import production_variant, Session
  from sagemaker.utils import name_from_base, stringify_object, format_tags
  from sagemaker.model_monitor.model_monitoring import DEFAULT_REPOSITORY_NAME
  from sagemaker.lineage.context import EndpointContext
  from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements
label_desc: Use image node_id 14 for calling the Predictor obj's underlying member method code with example usage: obj.update_data_capture_config(data_capture_config) without return types