class_docstr: Make async prediction requests to an Amazon SageMaker endpoint.
class_docstr_tok: ["Make","async","prediction","requests","to","an","Amazon","SageMaker","endpoint","."]
docstr: Create request args for ``invoke_endpoint_async``
docstr_tok: ["Create","request","args","for","``","invoke_endpoint_async","``"]
code: def _create_request_args(
      self,
      input_path,
      initial_args=None,
      inference_id=None,
  ):
      """Create request args for ``invoke_endpoint_async``"""
      args = dict(initial_args) if initial_args else {}
      args["InputLocation"] = input_path
      if "EndpointName" not in args:
          args["EndpointName"] = self.predictor.endpoint_name
  
      if "Accept" not in args:
          args["Accept"] = ", ".join(self.predictor.accept)
  
      if inference_id:
          args["InferenceId"] = inference_id
  
      return args
  
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 5 for calling the AsyncPredictor obj's underlying member method code with example usage: obj._create_request_args(input_path, initial_args, inference_id) and returns: args