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48 lines
2.0 KiB
Python
48 lines
2.0 KiB
Python
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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 MathBenchDataset, Math401Evaluator, mathbench_postprocess
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cloze_prompt = [
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dict(role='HUMAN', prompt='Q: Calculate 2.9-0.11.'),
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dict(role='BOT', prompt='A: Let\'s think step by step, 2.9 - 0.11 equals 2.7900. The answer is 2.7900.\n'),
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dict(role='HUMAN', prompt='Q: Calculate 0.15-0.032.'),
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dict(role='BOT', prompt='A: Let\'s think step by step, 0.15 - 0.032 equals 0.1180. The answer is 0.1180.\n'),
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dict(role='HUMAN', prompt='Q: Calculate 78*64.'),
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dict(role='BOT', prompt='A: Let\'s think step by step, 78 multiplied by 64 equals 4992. The answer is 4992.\n'),
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dict(role='HUMAN', prompt='Q: Calculate 62×42.'),
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dict(role='BOT', prompt='A: Let\'s think step by step, 62 multiplied by 42 equals 2604. The answer is 2604.\n'),
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dict(role='HUMAN', prompt='Q: Calculate {question}'),
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dict(role='BOT', prompt='A: {answer}\n')]
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math401_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=cloze_prompt,
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),
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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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)
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math401_eval_cfg = dict(
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evaluator=dict(type=Math401Evaluator),
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pred_postprocessor=dict(type=mathbench_postprocess, name='en'))
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math401_datasets = [
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dict(
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abbr="math401",
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type=MathBenchDataset,
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path=f"./data/math401/",
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with_circular=False,
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name="cloze_en",
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reader_cfg=dict(
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input_columns=["question"],
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output_column="answer"
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),
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infer_cfg=math401_infer_cfg,
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eval_cfg=math401_eval_cfg,
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)]
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