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a244453d9e
* commit inference ppl datasets * revised format * revise * revise * revise * revise * revise * revise
39 lines
1.2 KiB
Python
39 lines
1.2 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 InferencePPLOnlyInferencer
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from opencompass.openicl.icl_evaluator import AverageInferencePPLEvaluator
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from opencompass.datasets import InferencePPLDataset
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# Build InferencePPLDataset
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inference_ppl_datasets = []
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llm_cmp_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template='{text}',
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),
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# No in-context example, using ZeroRetriever
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retriever=dict(type=ZeroRetriever),
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# compute inference-ppl
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inferencer=dict(type=InferencePPLOnlyInferencer),
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)
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# Average the inference-ppl scores
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llm_cmp_eval_cfg = dict(evaluator=dict(type=AverageInferencePPLEvaluator))
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inference_ppl_datasets.append(
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dict(
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abbr=f'inference-ppl',
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type=InferencePPLDataset,
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path='./data/inference_ppl',
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name='cn-reasoning-val',
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samples=None, # Set small samples for testing
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reader_cfg=dict(
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input_columns=['text'],
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output_column=None,
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),
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infer_cfg=llm_cmp_infer_cfg,
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eval_cfg=llm_cmp_eval_cfg,
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))
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