class_docstr: Evaluation Result Summary
class_docstr_tok: ["Evaluation","Result","Summary"]
docstr: Add information of training performance to the result
  
  Args:
      evaluation_result (dict): evaluation metric
          - key: metric_name
          - value: metric_value: single float value for average/overall metric,
                                  list for class metrics
          sample input 1: {'precision': 0.5}, report value directly
          sample input 2: {'precision': {'class':[0.5,0.4,0.3],'average':0.5}},
                                          report "average" value
          sample input 3: {'precision': {'class':[0.5,0.4,0.3]},
                          report unweighted average for "class" value
      notes (str, Optional): explain the block
docstr_tok: ["Add","information","of","training","performance","to","the","result","Args",":","evaluation_result","(","dict",")",":","evaluation","metric","-","key",":","metric_name","-","value",":","metric_value",":","single","float","value","for","average\/overall","metric",",","list","for","class","metrics","sample","input","1",":","{","'precision","'",":","0.5","}",",","report","value","directly","sample","input","2",":","{","'precision","'",":","{","'class","'",":","[","0.5,0.4,0.3","]",",","'average':0.5","}","}",",","report","``","average","''","value","sample","input","3",":","{","'precision","'",":","{","'class","'",":","[","0.5,0.4,0.3","]","}",",","report","unweighted","average","for","``","class","''","value","notes","(","str",",","Optional",")",":","explain","the","block"]
code: def __init__(self, evaluation_result: dict, notes=None) -> None:
      """
      Add information of training performance to the result
  
      Args:
          evaluation_result (dict): evaluation metric
              - key: metric_name
              - value: metric_value: single float value for average/overall metric,
                                      list for class metrics
              sample input 1: {'precision': 0.5}, report value directly
              sample input 2: {'precision': {'class':[0.5,0.4,0.3],'average':0.5}},
                                              report "average" value
              sample input 3: {'precision': {'class':[0.5,0.4,0.3]},
                              report unweighted average for "class" value
          notes (str, Optional): explain the block
      """
      super(EvaluationResultSummary, self).__init__(
          evaluation_result, notes
      )
      self._evaluation_result = evaluation_result
      if not (notes is None):
          self._notes = notes
      else:
          self._notes = "Evaluation Result Summary"
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import List, Tuple
  from xai.formatter.contents.base import Content
  from xai.formatter.writer.base import Writer
label_desc: Use image node_id 1 to create a new EvaluationResultSummary object from inherited base classes: Content with example: obj = EvaluationResultSummary(evaluation_result, notes)