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39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets import HumanevalDataset, HumanEvalEvaluator, humaneval_postprocess_v2
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humaneval_reader_cfg = dict(
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input_columns=['prompt'], output_column='task_id', train_split='test')
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# TODO: allow empty output-column
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humaneval_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(round=[
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dict(
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role='HUMAN',
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prompt='完成以下Python代码任务:\n{prompt}'),
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])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=512))
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humaneval_eval_cfg = dict(
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evaluator=dict(type=HumanEvalEvaluator),
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pred_role='BOT',
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k=[1, 10, 100], # the parameter only for humaneval
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pred_postprocessor=dict(type=humaneval_postprocess_v2),
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)
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humaneval_cn_datasets = [
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dict(
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abbr='openai_humaneval_cn_repeat10',
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type=HumanevalDataset,
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path='./data/humaneval_cn/human-eval-cn-v2-20210705.jsonl',
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num_repeats=10,
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reader_cfg=humaneval_reader_cfg,
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infer_cfg=humaneval_infer_cfg,
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eval_cfg=humaneval_eval_cfg)
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]
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