class_docstr: Top level parser for model monitor model quality metric type
class_docstr_tok: ["Top","level","parser","for","model","monitor","model","quality","metric","type"]
docstr: Implement ParserBase._parse.
  
  Args:
      json_data (dict): Raw metric data.
docstr_tok: ["Implement","ParserBase._parse",".","Args",":","json_data","(","dict",")",":","Raw","metric","data","."]
code: def _parse(self, json_data: dict):
      """Implement ParserBase._parse.
  
      Args:
          json_data (dict): Raw metric data.
      """
      result = {"metric_groups": []}
      if "regression_metrics" in json_data:
          result = RegressionParser().run(json_data)
      elif (
          "binary_classification_metrics" in json_data
          or "multiclass_classification_metrics" in json_data
      ):
          result = ClassificationParser().run(json_data)
  
      return result
  
imports: from __future__ import absolute_import
  from abc import ABC, abstractmethod
  from enum import Enum
  from collections import defaultdict
  from typing import Union, List
  from sagemaker.model_card.schema_constraints import PYTHON_TYPE_TO_METRIC_VALUE_TYPE, METRIC_VALUE_TYPE_MAP, MetricTypeEnum
label_desc: Use image node_id 2 for calling the ModelMonitorModelQualityParser obj's underlying member method code with example usage: obj._parse(json_data) and returns: result