class_docstr: Accepts drift check baselines parameters for conversion to request dict.
docstr: Initialize a ``DriftCheckBaselines`` instance and turn parameters into dict.
  
  Args:
      model_statistics (MetricsSource): A metric source object that represents
          model statistics (default: None).
      model_constraints (MetricsSource): A metric source object that represents
          model constraints (default: None).
      model_data_statistics (MetricsSource): A metric source object that represents
          model data statistics (default: None).
      model_data_constraints (MetricsSource): A metric source object that represents
          model data constraints (default: None).
      bias_config_file (FileSource): A file source object that represents bias config
          (default: None).
      bias_pre_training_constraints (MetricsSource):
          A metric source object that represents Pre-training constraints (default: None).
      bias_post_training_constraints (MetricsSource):
          A metric source object that represents Post-training constraits (default: None).
      explainability_constraints (MetricsSource):
          A metric source object that represents explainability constraints (default: None).
      explainability_config_file (FileSource): A file source object that represents
          explainability config (default: None).
docstr_tok: ["Initialize","a","``","DriftCheckBaselines","``","instance","and","turn","parameters","into","dict",".","Args",":","model_statistics","(","MetricsSource",")",":","A","metric","source","object","that","represents","model","statistics","(","default",":","None",")",".","model_constraints","(","MetricsSource",")",":","A","metric","source","object","that","represents","model","constraints","(","default",":","None",")",".","model_data_statistics","(","MetricsSource",")",":","A","metric","source","object","that","represents","model","data","statistics","(","default",":","None",")",".","model_data_constraints","(","MetricsSource",")",":","A","metric","source","object","that","represents","model","data","constraints","(","default",":","None",")",".","bias_config_file","(","FileSource",")",":","A","file","source","object","that","represents","bias","config","(","default",":","None",")",".","bias_pre_training_constraints","(","MetricsSource",")",":","A","metric","source","object","that","represents","Pre-training","constraints","(","default",":","None",")",".","bias_post_training_constraints","(","MetricsSource",")",":","A","metric","source","object","that","represents","Post-training","constraits","(","default",":","None",")",".","explainability_constraints","(","MetricsSource",")",":","A","metric","source","object","that","represents","explainability","constraints","(","default",":","None",")",".","explainability_config_file","(","FileSource",")",":","A","file","source","object","that","represents","explainability","config","(","default",":","None",")","."]
code: def __init__(
      self,
      model_statistics: Optional[MetricsSource] = None,
      model_constraints: Optional[MetricsSource] = None,
      model_data_statistics: Optional[MetricsSource] = None,
      model_data_constraints: Optional[MetricsSource] = None,
      bias_config_file: Optional[FileSource] = None,
      bias_pre_training_constraints: Optional[MetricsSource] = None,
      bias_post_training_constraints: Optional[MetricsSource] = None,
      explainability_constraints: Optional[MetricsSource] = None,
      explainability_config_file: Optional[FileSource] = None,
  ):
      """Initialize a ``DriftCheckBaselines`` instance and turn parameters into dict.
  
      Args:
          model_statistics (MetricsSource): A metric source object that represents
              model statistics (default: None).
          model_constraints (MetricsSource): A metric source object that represents
              model constraints (default: None).
          model_data_statistics (MetricsSource): A metric source object that represents
              model data statistics (default: None).
          model_data_constraints (MetricsSource): A metric source object that represents
              model data constraints (default: None).
          bias_config_file (FileSource): A file source object that represents bias config
              (default: None).
          bias_pre_training_constraints (MetricsSource):
              A metric source object that represents Pre-training constraints (default: None).
          bias_post_training_constraints (MetricsSource):
              A metric source object that represents Post-training constraits (default: None).
          explainability_constraints (MetricsSource):
              A metric source object that represents explainability constraints (default: None).
          explainability_config_file (FileSource): A file source object that represents
              explainability config (default: None).
      """
      self.model_statistics = model_statistics
      self.model_constraints = model_constraints
      self.model_data_statistics = model_data_statistics
      self.model_data_constraints = model_data_constraints
      self.bias_config_file = bias_config_file
      self.bias_pre_training_constraints = bias_pre_training_constraints
      self.bias_post_training_constraints = (
          bias_post_training_constraints
      )
      self.explainability_constraints = explainability_constraints
      self.explainability_config_file = explainability_config_file
  
imports: from __future__ import absolute_import
  from typing import Optional
  from sagemaker.model_metrics import MetricsSource, FileSource
label_desc: Use image node_id 1 to create a new DriftCheckBaselines object from inherited base classes: object with example: obj = DriftCheckBaselines(model_statistics, model_constraints, model_data_statistics, model_data_constraints, bias_config_file, bias_pre_training_constraints, bias_post_training_constraints, explainability_constraints, explainability_config_file)