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# flake8: noqa
import pandas as pd
class TaskSchema(object):
def __init__(self,
passage=None,
question=None,
options=None,
label=None,
answer=None,
other=None):
self.passage = passage
self.question = question
self.options = options
self.label = label
self.answer = answer
self.other = other
def to_dict(self):
return {
'passage': self.passage,
'question': self.question,
'options': self.options,
'label': self.label,
'answer': self.answer,
'other': self.other
}
# define README.json
class MedBenchInstance(object):
def __init__(self, task_description, data_source, task_schema, output,
evaluation_metric, task_example):
self.task_description = task_description
self.data_source = data_source
self.task_schema = task_schema
self.output = output
self.evaluation_metric = evaluation_metric
self.task_example = task_example
def to_dict(self):
return {
'task description': self.task_description,
'data source': self.data_source,
'task schema': self.task_schema.to_dict(),
'output': self.output,
'evaluation metric': self.evaluation_metric,
'task example': self.task_example
}
class ChatGPTSchema(object):
def __init__(self, context=None, metadata=''):
self.context = context
self.metadata = metadata
def to_dict(self):
return {'context': self.context, 'metadata': self.metadata}
class ResultsForHumanSchema(object):
def __init__(self,
index,
problem_input,
label,
model_input='',
model_output='',
parse_result='',
first_stage_output='',
second_stage_input='',
is_correct=False):
self.index = index
self.problem_input = problem_input
self.model_input = model_input
self.model_output = model_output
self.parse_result = parse_result
self.label = label
self.first_stage_output = first_stage_output
self.second_stage_input = second_stage_input
self.is_correct = is_correct
def to_dict(self):
return {
'index': self.index,
'problem_input': self.problem_input,
'model_input': self.model_input,
'model_output': self.model_output,
'parse_result': self.parse_result,
'label': self.label,
'is_correct': self.is_correct,
'first_stage_output': self.first_stage_output,
'second_stage_input': self.second_stage_input,
}
@staticmethod
def to_tsv(result_list, path):
result_json = [item.to_dict() for item in result_list]
table = pd.json_normalize(result_json)
table.to_excel(path, index=False)
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