class_docstr: Retrieves job specific data from the environment.
docstr: Loads source arn of current job from environment.
  
  Args:
      training_job_arn_env (str): The environment key for training job ARN
          (default: `TRAINING_JOB_ARN`).
      processing_job_config_path (str): The processing job config path
          (default: `/opt/ml/config/processingjobconfig.json`).
      transform_job_arn_env (str): The environment key for transform job ARN
          (default: `TRANSFORM_JOB_ARN_ENV`).
  
  Returns:
      _RunEnvironment: Job data loaded from the environment. None if config does not exist.
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code: def load(
      cls,
      training_job_arn_env: str = TRAINING_JOB_ARN_ENV,
      processing_job_config_path: str = PROCESSING_JOB_CONFIG_PATH,
      transform_job_arn_env: str = TRANSFORM_JOB_ARN_ENV,
  ):
      """Loads source arn of current job from environment.
  
      Args:
          training_job_arn_env (str): The environment key for training job ARN
              (default: `TRAINING_JOB_ARN`).
          processing_job_config_path (str): The processing job config path
              (default: `/opt/ml/config/processingjobconfig.json`).
          transform_job_arn_env (str): The environment key for transform job ARN
              (default: `TRANSFORM_JOB_ARN_ENV`).
  
      Returns:
          _RunEnvironment: Job data loaded from the environment. None if config does not exist.
      """
      if training_job_arn_env in os.environ:
          environment_type = _EnvironmentType.SageMakerTrainingJob
          source_arn = os.environ.get(training_job_arn_env)
          return _RunEnvironment(environment_type, source_arn)
      if os.path.exists(processing_job_config_path):
          environment_type = _EnvironmentType.SageMakerProcessingJob
          source_arn = json.loads(
              open(processing_job_config_path).read()
          )["ProcessingJobArn"]
          return _RunEnvironment(environment_type, source_arn)
      if transform_job_arn_env in os.environ:
          environment_type = _EnvironmentType.SageMakerTransformJob
          # TODO: need to update to get source_arn from config file once Transform side ready
          source_arn = os.environ.get(transform_job_arn_env)
          return _RunEnvironment(environment_type, source_arn)
  
      return None
  
file_path: sagemaker-python-sdk/src/sagemaker/experiments/_environment.py
imports: from __future__ import absolute_import
  import enum
  import json
  import logging
  import os
  from sagemaker import Session
  from sagemaker.experiments import trial_component
  from sagemaker.utils import retry_with_backoff
label_desc: Use image node_id 2 for calling the _RunEnvironment obj's underlying member method code with example usage: obj.load(cls, training_job_arn_env, processing_job_config_path, transform_job_arn_env) and returns: None, _RunEnvironment, _RunEnvironment, _RunEnvironment