2023-07-04 21:34:55 +08:00
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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.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import OBQADataset
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2023-08-11 17:33:00 +08:00
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from opencompass.utils.text_postprocessors import first_option_postprocess
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2023-07-04 21:34:55 +08:00
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_input_columns = [
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["question_stem", "A", "B", "C", "D"],
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["question_stem", "A", "B", "C", "D", "fact1"],
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]
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_template = [
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dict(
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round=[
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dict(
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role="HUMAN",
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2023-08-11 17:33:00 +08:00
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prompt=
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"Question: {question_stem}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nAnswer:"
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2023-07-04 21:34:55 +08:00
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),
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], ),
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dict(
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round=[
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dict(
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role="HUMAN",
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2023-08-11 17:33:00 +08:00
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prompt=
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"Given the fact: {fact1}\nQuestion: {question_stem}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nAnswer:",
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2023-07-04 21:34:55 +08:00
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),
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], ),
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]
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obqa_datasets = [
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dict(
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abbr="openbookqa",
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type=OBQADataset,
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2023-11-13 13:00:37 +08:00
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path='./data/openbookqa/Main/test.jsonl',
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2023-07-04 21:34:55 +08:00
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),
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dict(
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abbr="openbookqa_fact",
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type=OBQADataset,
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2023-11-13 13:00:37 +08:00
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path='./data/openbookqa/Additional/test_complete.jsonl',
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2023-07-04 21:34:55 +08:00
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),
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]
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for _i in range(2):
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obqa_reader_cfg = dict(
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input_columns=_input_columns[_i], output_column="answerKey")
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obqa_infer_cfg = dict(
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2023-08-11 17:33:00 +08:00
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prompt_template=dict(type=PromptTemplate, template=_template[_i]),
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2023-07-04 21:34:55 +08:00
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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obqa_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_role="BOT",
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2023-08-11 17:33:00 +08:00
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pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'),
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2023-07-04 21:34:55 +08:00
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)
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obqa_datasets[_i]["reader_cfg"] = obqa_reader_cfg
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obqa_datasets[_i]["infer_cfg"] = obqa_infer_cfg
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obqa_datasets[_i]["eval_cfg"] = obqa_eval_cfg
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