class_docstr: A class for creating and interacting with SageMaker AutoML jobs.
docstr: Returns the inference keys supported by the container.
  
  Args:
      container (dict): Dictionary representing container
      default (object): The value to be returned if the container definition
                        has no marker environment variable
  
  Returns:
      List of keys the container support or default
  
  Raises:
      KeyError if the default is None and the container definition has
      no marker environment variable SAGEMAKER_INFERENCE_SUPPORTED.
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code: def _get_supported_inference_keys(cls, container, default=None):
      """Returns the inference keys supported by the container.
  
      Args:
          container (dict): Dictionary representing container
          default (object): The value to be returned if the container definition
                            has no marker environment variable
  
      Returns:
          List of keys the container support or default
  
      Raises:
          KeyError if the default is None and the container definition has
          no marker environment variable SAGEMAKER_INFERENCE_SUPPORTED.
      """
      try:
          return [
              x.strip()
              for x in container["Environment"][
                  "SAGEMAKER_INFERENCE_SUPPORTED"
              ].split(",")
          ]
      except KeyError:
          if default is None:
              raise
      return default
  
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 11 for calling the AutoML obj's underlying member method code with example usage: obj._get_supported_inference_keys(cls, container, default) and returns: default, unknown