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52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
from opencompass.datasets.PHYBench.PHYBench import PHYBenchDataset, PHYBenchEvaluator
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from opencompass.openicl.icl_inferencer import GenInferencer
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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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SYSTEM_PROMPT = 'You are a physics expert. Please read the following question and provide a step-by-step solution. Put your final answer, which must be a readable LaTeX formula, in a \\boxed{} environment.'
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ZERO_SHOT_PROMPT = 'Solve the following physics problem:\n\n{content}\n\nFinal Answer: The final answer is $'
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# Reader configuration
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reader_cfg = dict(
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input_columns=['content'], # Updated to match the field in dataset.map
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output_column='answer', # Using answer as the reference answer
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)
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# Inference configuration
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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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begin=[
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dict(role='SYSTEM', fallback_role='HUMAN', prompt=SYSTEM_PROMPT),
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],
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round=[
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dict(
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role='HUMAN',
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prompt=ZERO_SHOT_PROMPT,
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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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# Evaluation configuration
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eval_cfg = dict(
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evaluator=dict(type=PHYBenchEvaluator),
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pred_role='BOT',
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)
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# Dataset configuration
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PHYBench_dataset = dict(
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type=PHYBenchDataset,
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path='Eureka-Lab/PHYBench',
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abbr='PHYBench',
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reader_cfg=reader_cfg,
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infer_cfg=infer_cfg,
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eval_cfg=eval_cfg,
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)
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PHYBench_datasets = [PHYBench_dataset]
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