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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.OpenFinData import OpenFinDataDataset, OpenFinDataKWEvaluator |
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from opencompass.utils.text_postprocessors import last_capital_postprocess |
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OpenFinData_datasets = [] |
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OpenFinData_3choices_list = ['emotion_identification', 'entity_disambiguation', 'financial_facts'] |
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OpenFinData_4choices_list = ['data_inspection', 'financial_terminology', 'metric_calculation', 'value_extraction'] |
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OpenFinData_5choices_list = ['intent_understanding'] |
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OpenFinData_keyword_list = ['entity_recognition'] |
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OpenFinData_all_list = OpenFinData_3choices_list + OpenFinData_4choices_list + OpenFinData_5choices_list + OpenFinData_keyword_list |
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OpenFinData_eval_cfg = dict(evaluator=dict(type=AccEvaluator), pred_postprocessor=dict(type=last_capital_postprocess)) |
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OpenFinData_KW_eval_cfg = dict(evaluator=dict(type=OpenFinDataKWEvaluator)) |
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for _name in OpenFinData_all_list: |
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if _name in OpenFinData_3choices_list: |
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OpenFinData_infer_cfg = dict( |
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ice_template=dict(type=PromptTemplate, template=dict(begin="</E>", round=[ |
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dict(role="HUMAN", prompt=f"{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\n答案: "), |
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dict(role="BOT", prompt="{answer}")]), |
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ice_token="</E>"), retriever=dict(type=ZeroRetriever), inferencer=dict(type=GenInferencer)) |
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OpenFinData_datasets.append( |
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dict( |
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type=OpenFinDataDataset, |
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path="./data/openfindata_release", |
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name=_name, |
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abbr="OpenFinData-" + _name, |
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reader_cfg=dict( |
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input_columns=["question", "A", "B", "C"], |
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output_column="answer"), |
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infer_cfg=OpenFinData_infer_cfg, |
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eval_cfg=OpenFinData_eval_cfg, |
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)) |
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if _name in OpenFinData_4choices_list: |
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OpenFinData_infer_cfg = dict( |
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ice_template=dict(type=PromptTemplate, template=dict(begin="</E>", round=[ |
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dict(role="HUMAN", prompt=f"{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: "), |
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dict(role="BOT", prompt="{answer}")]), |
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ice_token="</E>"), retriever=dict(type=ZeroRetriever), inferencer=dict(type=GenInferencer)) |
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OpenFinData_datasets.append( |
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dict( |
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type=OpenFinDataDataset, |
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path="./data/openfindata_release", |
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name=_name, |
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abbr="OpenFinData-" + _name, |
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reader_cfg=dict( |
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input_columns=["question", "A", "B", "C", "D"], |
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output_column="answer"), |
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infer_cfg=OpenFinData_infer_cfg, |
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eval_cfg=OpenFinData_eval_cfg, |
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)) |
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if _name in OpenFinData_5choices_list: |
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OpenFinData_infer_cfg = dict( |
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ice_template=dict(type=PromptTemplate, template=dict(begin="</E>", round=[ |
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dict(role="HUMAN", prompt=f"{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nE. {{E}}\n答案: "), |
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dict(role="BOT", prompt="{answer}")]), |
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ice_token="</E>"), retriever=dict(type=ZeroRetriever), inferencer=dict(type=GenInferencer)) |
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OpenFinData_datasets.append( |
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dict( |
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type=OpenFinDataDataset, |
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path="./data/openfindata_release", |
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name=_name, |
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abbr="OpenFinData-" + _name, |
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reader_cfg=dict( |
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input_columns=["question", "A", "B", "C", "D", "E"], |
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output_column="answer"), |
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infer_cfg=OpenFinData_infer_cfg, |
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eval_cfg=OpenFinData_eval_cfg, |
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)) |
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if _name in OpenFinData_keyword_list: |
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OpenFinData_infer_cfg = dict( |
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ice_template=dict(type=PromptTemplate, template=dict(begin="</E>", round=[ |
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dict(role="HUMAN", prompt=f"{{question}}\n答案: "), |
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dict(role="BOT", prompt="{answer}")]), |
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ice_token="</E>"), retriever=dict(type=ZeroRetriever), inferencer=dict(type=GenInferencer)) |
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OpenFinData_datasets.append( |
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dict( |
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type=OpenFinDataDataset, |
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path="./data/openfindata_release", |
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name=_name, |
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abbr="OpenFinData-" + _name, |
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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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infer_cfg=OpenFinData_infer_cfg, |
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eval_cfg=OpenFinData_KW_eval_cfg, |
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)) |
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del _name |
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