class_docstr: Base class for Amazon first-party Estimator implementations.
  
  This class isn't intended to be instantiated directly.
class_docstr_tok: ["Base","class","for","Amazon","first-party","Estimator","implementations",".","This","class","is","n't","intended","to","be","instantiated","directly","."]
docstr: Convert the job description to init params that can be handled by the class constructor.
  
  Args:
      job_details: the returned job details from a describe_training_job
          API call.
      model_channel_name (str): Name of the channel where pre-trained
          model data will be downloaded.
  
  Returns:
      dictionary: The transformed init_params
code: def _prepare_init_params_from_job_description(
      cls, job_details, model_channel_name=None
  ):
      """Convert the job description to init params that can be handled by the class constructor.
  
      Args:
          job_details: the returned job details from a describe_training_job
              API call.
          model_channel_name (str): Name of the channel where pre-trained
              model data will be downloaded.
  
      Returns:
          dictionary: The transformed init_params
      """
      init_params = super(
          AmazonAlgorithmEstimatorBase, cls
      )._prepare_init_params_from_job_description(
          job_details, model_channel_name
      )
  
      # The hyperparam names may not be the same as the class attribute that holds them,
      # for instance: local_lloyd_init_method is called local_init_method. We need to map these
      # and pass the correct name to the constructor.
      for attribute, value in cls.__dict__.items():
          if isinstance(value, hp):
              if value.name in init_params["hyperparameters"]:
                  init_params[attribute] = init_params[
                      "hyperparameters"
                  ][value.name]
  
      del init_params["hyperparameters"]
      del init_params["image_uri"]
      return init_params
  
imports: from __future__ import absolute_import
  import json
  import logging
  import tempfile
  from typing import Union, Optional, Dict
  from six.moves.urllib.parse import urlparse
  from sagemaker import image_uris, s3_utils
  from sagemaker.amazon import validation
  from sagemaker.amazon.hyperparameter import Hyperparameter
  from sagemaker.amazon.common import write_numpy_to_dense_tensor
  from sagemaker.deprecations import renamed_warning
  from sagemaker.estimator import EstimatorBase, _TrainingJob
  from sagemaker.inputs import FileSystemInput, TrainingInput
  from sagemaker.utils import sagemaker_timestamp, check_and_get_run_experiment_config
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.workflow.pipeline_context import runnable_by_pipeline
  from sagemaker.workflow import is_pipeline_variable
label_desc: Use image node_id 6 for calling the AmazonAlgorithmEstimatorBase obj's underlying member method code with example usage: obj._prepare_init_params_from_job_description(cls, job_details, model_channel_name) and returns: init_params