class_docstr: Make async prediction requests to an Amazon SageMaker endpoint.
class_docstr_tok: ["Make","async","prediction","requests","to","an","Amazon","SageMaker","endpoint","."]
docstr: Retrieves the lineage context object representing the endpoint.
  
  Examples:
      .. code-block:: python
  
          predictor = Predictor()
          context = predictor.endpoint_context()
          models = context.models()
  
  Returns:
      ContextEndpoint: The context for the endpoint.
docstr_tok: ["Retrieves","the","lineage","context","object","representing","the","endpoint",".","Examples",":","..","code-block",":",":","python","predictor","=","Predictor","(",")","context","=","predictor.endpoint_context","(",")","models","=","context.models","(",")","Returns",":","ContextEndpoint",":","The","context","for","the","endpoint","."]
code: def endpoint_context(self):
      """Retrieves the lineage context object representing the endpoint.
  
      Examples:
          .. code-block:: python
  
              predictor = Predictor()
              context = predictor.endpoint_context()
              models = context.models()
  
      Returns:
          ContextEndpoint: The context for the endpoint.
      """
  
      return self.predictor.endpoint_context()
  
imports: from __future__ import absolute_import
  import threading
  import time
  import uuid
  from botocore.exceptions import WaiterError
  from sagemaker import s3
  from sagemaker.exceptions import PollingTimeoutError, AsyncInferenceModelError
  from sagemaker.async_inference import WaiterConfig, AsyncInferenceResponse
  from sagemaker.s3 import parse_s3_url
  from sagemaker.session import Session
  from sagemaker.utils import name_from_base, sagemaker_timestamp, format_tags
label_desc: Use image node_id 17 for calling the AsyncPredictor obj's underlying member method code with example usage: obj.endpoint_context() and returns: self