class_docstr: A class for interacting with CreateAutoMLJob API.
docstr: Constructs a dict of arguments for an Amazon SageMaker AutoML job.
  
  Args:
      auto_ml (sagemaker.automl.AutoML): AutoML object
          created by the user.
      inputs (str or list[str] or AutoMLInput or list[AutoMLInput]):
          Parameters used when called
          :meth:`~sagemaker.automl.AutoML.fit`.
  
  Returns:
      Dict: dict for `sagemaker.session.Session.auto_ml` method
docstr_tok: ["Constructs","a","dict","of","arguments","for","an","Amazon","SageMaker","AutoML","job",".","Args",":","auto_ml","(","sagemaker.automl.AutoML",")",":","AutoML","object","created","by","the","user",".","inputs","(","str","or","list","[","str","]","or","AutoMLInput","or","list","[","AutoMLInput","]",")",":","Parameters","used","when","called",":","meth",":","`","~sagemaker.automl.AutoML.fit","`",".","Returns",":","Dict",":","dict","for","`","sagemaker.session.Session.auto_ml","`","method"]
code: def _get_auto_ml_args(cls, auto_ml, inputs):
      """Constructs a dict of arguments for an Amazon SageMaker AutoML job.
  
      Args:
          auto_ml (sagemaker.automl.AutoML): AutoML object
              created by the user.
          inputs (str or list[str] or AutoMLInput or list[AutoMLInput]):
              Parameters used when called
              :meth:`~sagemaker.automl.AutoML.fit`.
  
      Returns:
          Dict: dict for `sagemaker.session.Session.auto_ml` method
      """
      config = cls._load_config(inputs, auto_ml)
      auto_ml_args = config.copy()
      auto_ml_args["job_name"] = auto_ml.current_job_name
      auto_ml_args["problem_type"] = auto_ml.problem_type
      auto_ml_args["job_objective"] = auto_ml.job_objective
      auto_ml_args["tags"] = auto_ml.tags
  
      return auto_ml_args
  
imports: from __future__ import absolute_import
  import logging
  from typing import Optional, List, Dict
  from six import string_types
  from sagemaker import Model, PipelineModel, s3
  from sagemaker.automl.candidate_estimator import CandidateEstimator
  from sagemaker.config import AUTO_ML_ROLE_ARN_PATH, AUTO_ML_KMS_KEY_ID_PATH, AUTO_ML_VPC_CONFIG_PATH, AUTO_ML_VOLUME_KMS_KEY_ID_PATH, AUTO_ML_INTER_CONTAINER_ENCRYPTION_PATH
  from sagemaker.job import _Job
  from sagemaker.session import Session
  from sagemaker.utils import name_from_base, resolve_value_from_config, format_tags, Tags
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.workflow.pipeline_context import runnable_by_pipeline
label_desc: Use image node_id 2 for calling the AutoMLJob obj's underlying member method code with example usage: obj._get_auto_ml_args(cls, auto_ml, inputs) and returns: auto_ml_args