OpenCompass/.github/scripts/oc_score_assert.py
zhulinJulia24 0919b08ec8
[Feature] Add daily test case (#864)
* add daily test case

* Update pr-run-test.yml

* Update daily-run-test.yml

* Update daily-run-test.yml

* Update pr-run-test.yml

---------

Co-authored-by: zhulin1 <zhulin1@pjlab.org.cn>
2024-02-02 12:03:05 +08:00

94 lines
2.8 KiB
Python

import csv
import os
import pytest
import yaml
output_path = 'regression_result_daily'
model_list = ['internlm-7b-hf', 'internlm-chat-7b-hf']
dataset_list = ['ARC-c', 'chid-dev', 'chid-test', 'openai_humaneval']
@pytest.fixture()
def baseline_scores(request):
config_path = os.path.join(request.config.rootdir,
'.github/scripts/oc_score_baseline.yaml')
with open(config_path) as f:
config = yaml.load(f.read(), Loader=yaml.SafeLoader)
return config
@pytest.fixture()
def result_scores():
file = find_csv_files(output_path)
if file is None:
return None
return read_csv_file(file)
@pytest.mark.usefixtures('result_scores')
@pytest.mark.usefixtures('baseline_scores')
class TestChat:
"""Test cases for chat model."""
@pytest.mark.parametrize('model, dataset', [(p1, p2) for p1 in model_list
for p2 in dataset_list])
def test_demo_default(self, baseline_scores, result_scores, model,
dataset):
base_score = baseline_scores.get(model).get(dataset)
result_score = result_scores.get(model).get(dataset)
assert_score(result_score, base_score)
def assert_score(score, baseline):
if score is None or score == '-':
assert False, 'value is none'
if float(score) < (baseline * 1.03) and float(score) > (baseline * 0.97):
print(score + ' between ' + str(baseline * 0.97) + ' and ' +
str(baseline * 1.03))
assert True
else:
assert False, score + ' not between ' + str(
baseline * 0.97) + ' and ' + str(baseline * 1.03)
def find_csv_files(directory):
csv_files = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith('.csv'):
csv_files.append(os.path.join(root, file))
if len(csv_files) > 1:
raise 'have more than 1 result file, please check the result manually'
if len(csv_files) == 0:
return None
return csv_files[0]
def read_csv_file(file_path):
with open(file_path, 'r') as csvfile:
reader = csv.DictReader(csvfile)
filtered_data = []
for row in reader:
filtered_row = {
k: v
for k, v in row.items()
if k not in ['version', 'metric', 'mode']
}
filtered_data.append(filtered_row)
result = {}
for data in filtered_data:
dataset = data.get('dataset')
for key in data.keys():
if key == 'dataset':
continue
else:
if key in result.keys():
result.get(key)[dataset] = data.get(key)
else:
result[key] = {dataset: data.get(key)}
return result