class_docstr: Instance of ``AbstractRun`` corresponding to a subprocess launched to run an entry point command on aws sagemaker.
code: def __init__(
      self,
      training_job_name: str,
      client: "boto3.Client",
      log_client: Optional["boto3.Client"] = None,
  ) -> None:
      super().__init__()
      self.client = client
      self.log_client = log_client
      self.training_job_name = training_job_name
      self._status = Status("running")
  
imports: import asyncio
  import logging
  from typing import Any, Dict, List, Optional, cast
  import wandb
  from wandb.apis.internal import Api
  from wandb.sdk.launch.environment.aws_environment import AwsEnvironment
  from wandb.sdk.launch.errors import LaunchError
  from .._project_spec import EntryPoint, LaunchProject, get_entry_point_command
  from ..builder.build import get_env_vars_dict
  from ..registry.abstract import AbstractRegistry
  from ..utils import LOG_PREFIX, MAX_ENV_LENGTHS, PROJECT_SYNCHRONOUS, event_loop_thread_exec, to_camel_case
  from .abstract import AbstractRun, AbstractRunner, Status
label_desc: Use image node_id 1 to create a new SagemakerSubmittedRun object from inherited base classes: AbstractRun with example: obj = SagemakerSubmittedRun(training_job_name, client, log_client)