class_docstr: A class for creating and interacting with SageMaker AutoML jobs.
docstr: Set any values in the AutoMLJob that need to be set before creating request.
  
  Args:
      job_name (str): The name of the AutoML job. If None, a job name will be
          created from base_job_name or "sagemaker-auto-ml".
docstr_tok: ["Set","any","values","in","the","AutoMLJob","that","need","to","be","set","before","creating","request",".","Args",":","job_name","(","str",")",":","The","name","of","the","AutoML","job",".","If","None",",","a","job","name","will","be","created","from","base_job_name","or","``","sagemaker-auto-ml","''","."]
code: def _prepare_for_auto_ml_job(self, job_name=None):
      """Set any values in the AutoMLJob that need to be set before creating request.
  
      Args:
          job_name (str): The name of the AutoML job. If None, a job name will be
              created from base_job_name or "sagemaker-auto-ml".
      """
      if job_name is not None:
          self.current_job_name = job_name
      else:
          if self.base_job_name:
              base_name = self.base_job_name
          else:
              base_name = "automl"
          # CreateAutoMLJob API validates that member length less than or equal to 32
          self.current_job_name = name_from_base(
              base_name, max_length=32
          )
  
      if self.output_path is None:
          self.output_path = s3.s3_path_join(
              "s3://",
              self.sagemaker_session.default_bucket(),
              self.sagemaker_session.default_bucket_prefix,
              with_end_slash=True,
          )
  
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 10 for calling the AutoML obj's underlying member method code with example usage: obj._prepare_for_auto_ml_job(job_name) without return types