class_docstr: A class for SageMaker AutoML Job Candidate
docstr: Get the step job of a candidate so that users can construct estimators/transformers
  
  Returns:
      list: a list of dictionaries that provide information about each step job's name,
          type, inputs and description
docstr_tok: ["Get","the","step","job","of","a","candidate","so","that","users","can","construct","estimators\/transformers","Returns",":","list",":","a","list","of","dictionaries","that","provide","information","about","each","step","job","'s","name",",","type",",","inputs","and","description"]
code: def get_steps(self):
      """Get the step job of a candidate so that users can construct estimators/transformers
  
      Returns:
          list: a list of dictionaries that provide information about each step job's name,
              type, inputs and description
      """
      candidate_steps = []
      for step in self.steps:
          step_type = step["type"]
          step_name = step["name"]
          if step_type == "TrainingJob":
              training_job = self.sagemaker_session.sagemaker_client.describe_training_job(
                  TrainingJobName=step_name
              )
  
              inputs = training_job["InputDataConfig"]
              candidate_step = CandidateStep(
                  step_name, inputs, step_type, training_job
              )
              candidate_steps.append(candidate_step)
          elif step_type == "TransformJob":
              transform_job = self.sagemaker_session.sagemaker_client.describe_transform_job(
                  TransformJobName=step_name
              )
              inputs = transform_job["TransformInput"]
              candidate_step = CandidateStep(
                  step_name, inputs, step_type, transform_job
              )
              candidate_steps.append(candidate_step)
      return candidate_steps
  
imports: from __future__ import absolute_import
  from six import string_types
  from sagemaker.config import TRAINING_JOB_VPC_CONFIG_PATH, TRAINING_JOB_VOLUME_KMS_KEY_ID_PATH, TRAINING_JOB_INTER_CONTAINER_ENCRYPTION_PATH
  from sagemaker.session import Session
  from sagemaker.job import _Job
  from sagemaker.utils import name_from_base, resolve_value_from_config
label_desc: Use image node_id 2 for calling the CandidateEstimator obj's underlying member method code with example usage: obj.get_steps() and returns: candidate_steps