class_docstr: Configuration object passed in when deploying models to Amazon SageMaker Endpoints.
  
  This object specifies configuration related to async endpoint. Use this configuration
  when trying to create async endpoint and make async inference
class_docstr_tok: ["Configuration","object","passed","in","when","deploying","models","to","Amazon","SageMaker","Endpoints",".","This","object","specifies","configuration","related","to","async","endpoint",".","Use","this","configuration","when","trying","to","create","async","endpoint","and","make","async","inference"]
docstr: Generates a request dictionary using the parameters provided to the class.
docstr_tok: ["Generates","a","request","dictionary","using","the","parameters","provided","to","the","class","."]
code: def _to_request_dict(self):
      """Generates a request dictionary using the parameters provided to the class."""
      request_dict = {
          "OutputConfig": {
              "S3OutputPath": self.output_path,
              "S3FailurePath": self.failure_path,
          },
      }
  
      if self.max_concurrent_invocations_per_instance:
          request_dict["ClientConfig"] = {
              "MaxConcurrentInvocationsPerInstance": self.max_concurrent_invocations_per_instance
          }
  
      if self.kms_key_id:
          request_dict["OutputConfig"]["KmsKeyId"] = self.kms_key_id
  
      if self.notification_config:
          request_dict["OutputConfig"][
              "NotificationConfig"
          ] = self.notification_config
  
      return request_dict
  
imports: from __future__ import print_function, absolute_import
label_desc: Use image node_id 2 for calling the AsyncInferenceConfig obj's underlying member method code with example usage: obj._to_request_dict() and returns: request_dict