class_docstr: Repacks model artifacts with custom inference entry points.
  
  The SDK automatically adds this step to pipelines that have RegisterModelSteps with models
  that have a custom entry point.
class_docstr_tok: ["Repacks","model","artifacts","with","custom","inference","entry","points",".","The","SDK","automatically","adds","this","step","to","pipelines","that","have","RegisterModelSteps","with","models","that","have","a","custom","entry","point","."]
docstr: Prepares the source for the estimator.
docstr_tok: ["Prepares","the","source","for","the","estimator","."]
code: def _prepare_for_repacking(self):
      """Prepares the source for the estimator."""
      if self._source_dir is None:
          self._establish_source_dir()
  
      self._inject_repack_script_and_launcher()
  
imports: from __future__ import absolute_import
  import logging
  import os
  import shutil
  import tarfile
  import tempfile
  from typing import List, Union, Optional, TYPE_CHECKING
  from sagemaker import image_uris
  from sagemaker.inputs import TrainingInput
  from sagemaker.estimator import EstimatorBase
  from sagemaker.sklearn.estimator import SKLearn
  from sagemaker.workflow.entities import RequestType
  from sagemaker.workflow.properties import Properties
  from sagemaker.session import get_create_model_package_request, get_model_package_args
  from sagemaker.workflow.steps import StepTypeEnum, TrainingStep, Step, ConfigurableRetryStep
  from sagemaker.utils import _save_model, download_file_from_url, format_tags
  from sagemaker.workflow.retry import RetryPolicy
  from sagemaker.workflow.utilities import trim_request_dict
label_desc: Use image node_id 2 for calling the _RepackModelStep obj's underlying member method code with example usage: obj._prepare_for_repacking() without return types