class_docstr: Managing interactions with SageMaker APIs and AWS services needed under Pipeline Context
  
  This class inherits the SageMaker session, it provides convenient methods
  for manipulating entities and resources that Amazon SageMaker uses,
  such as training jobs, endpoints, and input datasets in S3. When composing
  SageMaker Model-Building Pipeline, PipelineSession is recommended over
  regular SageMaker Session
class_docstr_tok: ["Managing","interactions","with","SageMaker","APIs","and","AWS","services","needed","under","Pipeline","Context","This","class","inherits","the","SageMaker","session",",","it","provides","convenient","methods","for","manipulating","entities","and","resources","that","Amazon","SageMaker","uses",",","such","as","training","jobs",",","endpoints",",","and","input","datasets","in","S3",".","When","composing","SageMaker","Model-Building","Pipeline",",","PipelineSession","is","recommended","over","regular","SageMaker","Session"]
docstr: Create a `_ModelStepArguments` (if not exist) as pipeline context
  
  Args:
      model (Model or PipelineModel): A `sagemaker.model.Model`
          or `sagemaker.pipeline.PipelineModel` instance
docstr_tok: ["Create","a","`","_ModelStepArguments","`","(","if","not","exist",")","as","pipeline","context","Args",":","model","(","Model","or","PipelineModel",")",":","A","`","sagemaker.model.Model","`","or","`","sagemaker.pipeline.PipelineModel","`","instance"]
code: def init_model_step_arguments(self, model):
      """Create a `_ModelStepArguments` (if not exist) as pipeline context
  
      Args:
          model (Model or PipelineModel): A `sagemaker.model.Model`
              or `sagemaker.pipeline.PipelineModel` instance
      """
      if not isinstance(self._context, _ModelStepArguments):
          self._context = _ModelStepArguments(model)
  
imports: from __future__ import absolute_import
  import warnings
  import inspect
  from functools import wraps
  from typing import Dict, Optional, Callable
  from sagemaker.session import Session, SessionSettings
  from sagemaker.local import LocalSession
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
label_desc: Use image node_id 5 for calling the PipelineSession obj's underlying member method code with example usage: obj.init_model_step_arguments(model) without return types