class_docstr: A class for interacting with CreateAutoMLJob API.
docstr: Wait for the AutoML job to finish.
  
  Args:
      logs (bool): indicate whether to output logs.
docstr_tok: ["Wait","for","the","AutoML","job","to","finish",".","Args",":","logs","(","bool",")",":","indicate","whether","to","output","logs","."]
code: def wait(self, logs=True):
      """Wait for the AutoML job to finish.
  
      Args:
          logs (bool): indicate whether to output logs.
      """
      if logs:
          self.sagemaker_session.logs_for_auto_ml_job(
              self.job_name, wait=True
          )
      else:
          self.sagemaker_session.wait_for_auto_ml_job(self.job_name)
  
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 8 for calling the AutoMLJob obj's underlying member method code with example usage: obj.wait(logs) without return types