class_docstr: QualityCheck step for workflow.
class_docstr_tok: ["QualityCheck","step","for","workflow","."]
docstr: Generates a dict with ProcessingInput objects
  
  Generates a dict with three ProcessingInput objects: baseline_dataset_input,
      post_processor_script_input and record_preprocessor_script_input
  
  Returns:
      dict: with three ProcessingInput objects as baseline job inputs
docstr_tok: ["Generates","a","dict","with","ProcessingInput","objects","Generates","a","dict","with","three","ProcessingInput","objects",":","baseline_dataset_input",",","post_processor_script_input","and","record_preprocessor_script_input","Returns",":","dict",":","with","three","ProcessingInput","objects","as","baseline","job","inputs"]
code: def _generate_baseline_job_inputs(self):
      """Generates a dict with ProcessingInput objects
  
      Generates a dict with three ProcessingInput objects: baseline_dataset_input,
          post_processor_script_input and record_preprocessor_script_input
  
      Returns:
          dict: with three ProcessingInput objects as baseline job inputs
      """
      baseline_dataset = self.quality_check_config.baseline_dataset
      baseline_dataset_des = str(
          pathlib.PurePosixPath(
              _CONTAINER_BASE_PATH,
              _CONTAINER_INPUT_PATH,
              _BASELINE_DATASET_INPUT_NAME,
          )
      )
      if is_pipeline_variable(baseline_dataset):
          baseline_dataset_input = ProcessingInput(
              source=self.quality_check_config.baseline_dataset,
              destination=baseline_dataset_des,
              input_name=_BASELINE_DATASET_INPUT_NAME,
          )
      else:
          baseline_dataset_input = self._model_monitor._upload_and_convert_to_processing_input(
              source=self.quality_check_config.baseline_dataset,
              destination=baseline_dataset_des,
              name=_BASELINE_DATASET_INPUT_NAME,
          )
  
      post_processor_script_input = self._model_monitor._upload_and_convert_to_processing_input(
          source=self.quality_check_config.post_analytics_processor_script,
          destination=str(
              pathlib.PurePosixPath(
                  _CONTAINER_BASE_PATH,
                  _CONTAINER_INPUT_PATH,
                  _POST_ANALYTICS_PROCESSOR_SCRIPT_INPUT_NAME,
              )
          ),
          name=_POST_ANALYTICS_PROCESSOR_SCRIPT_INPUT_NAME,
      )
  
      record_preprocessor_script_input = None
      if isinstance(self.quality_check_config, DataQualityCheckConfig):
          record_preprocessor_script_input = self._model_monitor._upload_and_convert_to_processing_input(
              source=self.quality_check_config.record_preprocessor_script,
              destination=str(
                  pathlib.PurePosixPath(
                      _CONTAINER_BASE_PATH,
                      _CONTAINER_INPUT_PATH,
                      _RECORD_PREPROCESSOR_SCRIPT_INPUT_NAME,
                  )
              ),
              name=_RECORD_PREPROCESSOR_SCRIPT_INPUT_NAME,
          )
      return dict(
          baseline_dataset_input=baseline_dataset_input,
          post_processor_script_input=post_processor_script_input,
          record_preprocessor_script_input=record_preprocessor_script_input,
      )
  
imports: from __future__ import absolute_import
  from abc import ABC
  from typing import List, Union, Optional
  import os
  import pathlib
  import attr
  from sagemaker import s3
  from sagemaker.model_monitor import ModelMonitor
  from sagemaker.processing import ProcessingOutput, ProcessingJob, Processor, ProcessingInput
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.entities import RequestType, PipelineVariable
  from sagemaker.workflow.properties import Properties
  from sagemaker.workflow.step_collections import StepCollection
  from sagemaker.workflow.steps import Step, StepTypeEnum, CacheConfig
  from sagemaker.workflow.check_job_config import CheckJobConfig
  from sagemaker.workflow.utilities import trim_request_dict
label_desc: Use image node_id 5 for calling the QualityCheckStep obj's underlying member method code with example usage: obj._generate_baseline_job_inputs() and returns: dict