class_docstr: A class for handling creating and interacting with Amazon SageMaker transform jobs.
docstr: Convert the transform job description to init params.
  
  It can be handled by the class constructor.
  
  Args:
      job_details (dict): the returned job details from a
          describe_transform_job API call.
  
  Returns:
      dict: The transformed init_params
docstr_tok: ["Convert","the","transform","job","description","to","init","params",".","It","can","be","handled","by","the","class","constructor",".","Args",":","job_details","(","dict",")",":","the","returned","job","details","from","a","describe_transform_job","API","call",".","Returns",":","dict",":","The","transformed","init_params"]
code: def _prepare_init_params_from_job_description(cls, job_details):
      """Convert the transform job description to init params.
  
      It can be handled by the class constructor.
  
      Args:
          job_details (dict): the returned job details from a
              describe_transform_job API call.
  
      Returns:
          dict: The transformed init_params
      """
      init_params = dict()
  
      init_params["model_name"] = job_details["ModelName"]
      init_params["instance_count"] = job_details["TransformResources"][
          "InstanceCount"
      ]
      init_params["instance_type"] = job_details["TransformResources"][
          "InstanceType"
      ]
      init_params["volume_kms_key"] = job_details[
          "TransformResources"
      ].get("VolumeKmsKeyId")
      init_params["strategy"] = job_details.get("BatchStrategy")
      init_params["assemble_with"] = job_details["TransformOutput"].get(
          "AssembleWith"
      )
      init_params["output_path"] = job_details["TransformOutput"][
          "S3OutputPath"
      ]
      init_params["output_kms_key"] = job_details[
          "TransformOutput"
      ].get("KmsKeyId")
      init_params["accept"] = job_details["TransformOutput"].get(
          "Accept"
      )
      init_params["max_concurrent_transforms"] = job_details.get(
          "MaxConcurrentTransforms"
      )
      init_params["max_payload"] = job_details.get("MaxPayloadInMB")
      init_params["base_transform_job_name"] = job_details[
          "TransformJobName"
      ]
  
      return init_params
  
imports: from __future__ import absolute_import
  from typing import Union, Optional, Dict
  import logging
  import copy
  import time
  from botocore import exceptions
  from sagemaker import s3
  from sagemaker.config import TRANSFORM_JOB_ENVIRONMENT_PATH, TRANSFORM_OUTPUT_KMS_KEY_ID_PATH, TRANSFORM_JOB_KMS_KEY_ID_PATH, TRANSFORM_RESOURCES_VOLUME_KMS_KEY_ID_PATH, PIPELINE_ROLE_ARN_PATH
  from sagemaker.job import _Job
  from sagemaker.session import Session, get_execution_role
  from sagemaker.inputs import BatchDataCaptureConfig
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow.pipeline_context import runnable_by_pipeline, PipelineSession
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from sagemaker.utils import base_name_from_image, name_from_base, check_and_get_run_experiment_config, resolve_value_from_config, resolve_class_attribute_from_config, format_tags, Tags
label_desc: Use image node_id 11 for calling the Transformer obj's underlying member method code with example usage: obj._prepare_init_params_from_job_description(cls, job_details) and returns: init_params