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* Create eval_longbenchv2.py * Create longbenchv2_gen.py * Update __init__.py * Create longbenchv2.py * Update datasets_info.py * update * update * update * update * update * update --------- Co-authored-by: abrohamLee <146956824+abrohamLee@users.noreply.github.com>
44 lines
1.7 KiB
Python
44 lines
1.7 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 LongBenchv2Dataset, LongBenchv2Evaluator
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from opencompass.utils.text_postprocessors import first_option_postprocess
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LongBenchv2_reader_cfg = dict(
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input_columns=['context', 'question', 'choice_A', 'choice_B', 'choice_C', 'choice_D', 'difficulty', 'length'],
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output_column='answer',
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)
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LongBenchv2_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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round=[
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dict(
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role='HUMAN',
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prompt='Please read the following text and answer the questions below.\n <text> \n {context} \n </text> \n \n What is the correct answer to this question: {question} \n \n Choices: \n (A) {choice_A} \n (B) {choice_B} \n (C) {choice_C} \n (D) {choice_D} \n Let’s think step by step. Based on the above, what is the single, most likely answer choice? Format your response as follows: "The correct answer is (insert answer here)',
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),
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],
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),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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LongBenchv2_eval_cfg = dict(
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evaluator=dict(type=LongBenchv2Evaluator),
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pred_role='BOT',
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pred_postprocessor=dict(type=first_option_postprocess, options='ABCD')
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)
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LongBenchv2_datasets = [
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dict(
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type=LongBenchv2Dataset,
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abbr='LongBenchv2',
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path='opencompass/longbenchv2',
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reader_cfg=LongBenchv2_reader_cfg,
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infer_cfg=LongBenchv2_infer_cfg,
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eval_cfg=LongBenchv2_eval_cfg,
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)
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]
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