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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.datasets import (DS1000Dataset, ds1000_postprocess, |
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ds1000_matplotlib_postprocess, |
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DS1000Evaluator) |
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ds1000_reader_cfg = dict( |
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input_columns=["prompt"], |
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output_column="test_column", |
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train_split='test', |
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test_split='test') |
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ds1000_infer_cfg = dict( |
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prompt_template=dict( |
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type=PromptTemplate, |
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template=dict(round=[ |
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dict( |
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role="HUMAN", |
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prompt="{prompt}", |
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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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ds1000_eval_cfg = dict( |
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evaluator=dict(type=DS1000Evaluator), |
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pred_role="BOT", |
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pred_postprocessor=dict(type=ds1000_postprocess), |
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) |
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ds1000_datasets = [ |
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dict( |
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abbr=f"ds1000_{lib}", |
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type=DS1000Dataset, |
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path="./data/ds1000_data/", |
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libs=f"{lib}", |
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reader_cfg=ds1000_reader_cfg, |
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infer_cfg=ds1000_infer_cfg, |
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eval_cfg=ds1000_eval_cfg, |
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) for lib in [ |
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'Pandas', |
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'Numpy', |
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'Tensorflow', |
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'Scipy', |
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'Sklearn', |
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'Pytorch', |
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] |
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] |
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ds1000_datasets.append( |
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dict( |
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abbr="ds1000_Matplotlib", |
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type=DS1000Dataset, |
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path="./data/ds1000_data/", |
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libs="Matplotlib", |
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reader_cfg=ds1000_reader_cfg, |
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infer_cfg=ds1000_infer_cfg, |
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eval_cfg=dict( |
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evaluator=dict(type=DS1000Evaluator), |
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pred_role="BOT", |
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pred_postprocessor=dict(type=ds1000_matplotlib_postprocess), |
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), |
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)) |
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