OpenCompass/configs/datasets/mbpp/sanitized_mbpp_mdblock_gen_a447ff.py
Xingjun.Wang edab1c07ba
[Feature] Support ModelScope datasets (#1289)
* add ceval, gsm8k modelscope surpport

* update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest

* update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets

* format file

* format file

* update dataset format

* support ms_dataset

* udpate dataset for modelscope support

* merge myl_dev and update test_ms_dataset

* udpate dataset for modelscope support

* update readme

* update eval_api_zhipu_v2

* remove unused code

* add get_data_path function

* update readme

* remove tydiqa japanese subset

* add ceval, gsm8k modelscope surpport

* update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest

* update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets

* format file

* format file

* update dataset format

* support ms_dataset

* udpate dataset for modelscope support

* merge myl_dev and update test_ms_dataset

* update readme

* udpate dataset for modelscope support

* update eval_api_zhipu_v2

* remove unused code

* add get_data_path function

* remove tydiqa japanese subset

* update util

* remove .DS_Store

* fix md format

* move util into package

* update docs/get_started.md

* restore eval_api_zhipu_v2.py, add environment setting

* Update dataset

* Update

* Update

* Update

* Update

---------

Co-authored-by: Yun lin <yunlin@U-Q9X2K4QV-1904.local>
Co-authored-by: Yunnglin <mao.looper@qq.com>
Co-authored-by: Yun lin <yunlin@laptop.local>
Co-authored-by: Yunnglin <maoyl@smail.nju.edu.cn>
Co-authored-by: zhangsongyang <zhangsongyang@pjlab.org.cn>
2024-07-29 13:48:32 +08:00

42 lines
2.9 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import SanitizedMBPPDataset, MBPPEvaluator
sanitized_mbpp_reader_cfg = dict(input_columns=['text', 'test_list'], output_column='test_list_2')
sanitized_mbpp_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(role='HUMAN', prompt='You are an expert Python programmer, and here is your task:\nWrite a function to find the similar elements from the given two tuple lists.\nYour code should pass these tests:\n\nassert similar_elements((3, 4, 5, 6),(5, 7, 4, 10)) == (4, 5)\nassert similar_elements((1, 2, 3, 4),(5, 4, 3, 7)) == (3, 4)\nassert similar_elements((11, 12, 14, 13),(17, 15, 14, 13)) == (13, 14)\n',),
dict(role='BOT', prompt='```python\ndef similar_elements(test_tup1, test_tup2):\n res = tuple(set(test_tup1) & set(test_tup2))\n return (res)```',),
dict(role='HUMAN', prompt='You are an expert Python programmer, and here is your task:\nWrite a python function to identify non-prime numbers.\nYour code should pass these tests:\n\nassert is_not_prime(2) == False\nassert is_not_prime(10) == True\nassert is_not_prime(35) == True\n',),
dict(role='BOT', prompt='```python\nimport math\ndef is_not_prime(n):\n result = False\n for i in range(2,int(math.sqrt(n)) + 1):\n if n %% i == 0:\n result = True\n return result```',),
dict(role='HUMAN', prompt='You are an expert Python programmer, and here is your task:\nWrite a function to find the largest integers from a given list of numbers using heap queue algorithm.\nYour code should pass these tests:\n\nassert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]\nassert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],2)==[85, 75]\nassert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[85, 75, 65, 58, 35]\n',),
dict(role='BOT', prompt='```python\nimport heapq as hq\ndef heap_queue_largest(nums,n):\n largest_nums = hq.nlargest(n, nums)\n return largest_nums```',),
dict(role='HUMAN', prompt='You are an expert Python programmer, and here is your task:\n{text}\nYour code should pass these tests:\n\n{test_list}\n',),
],
),
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512),
)
sanitized_mbpp_eval_cfg = dict(evaluator=dict(type=MBPPEvaluator), pred_role='BOT')
sanitized_mbpp_datasets = [
dict(
type=SanitizedMBPPDataset,
abbr='sanitized_mbpp',
path='opencompass/sanitized_mbpp',
reader_cfg=sanitized_mbpp_reader_cfg,
infer_cfg=sanitized_mbpp_infer_cfg,
eval_cfg=sanitized_mbpp_eval_cfg,
)
]