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c09fc79ba8
* [Feature] Support import configs/models/summarizers from whl * Update * Update openai sdk * Update * Update gemma
161 lines
9.1 KiB
Python
161 lines
9.1 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 GenInferencer
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from opencompass.datasets import CaLMDataset, CaLMEvaluator
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task_hiearchy_dict = {
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# association/
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# correlation/
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'CORR-B_correlation_CN':'association/correlation/',
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'CORR-B_correlation_EN':'association/correlation/',
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# explaining_away_effect/
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'EAE-B_exp-away_CN':'association/explaining_away_effect/',
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'EAE-B_exp-away_EN':'association/explaining_away_effect/',
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# causal_discovery/
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# abstract_reasoning/
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'AR-B_CaLM-AR_CN':'causal_discovery/abstract_reasoning/',
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'AR-B_CaLM-AR_EN':'causal_discovery/abstract_reasoning/',
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# causal_attribution/
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'CA-B_FA_CN':'causal_discovery/causal_attribution/',
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'CA-B_FA_EN':'causal_discovery/causal_attribution/',
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'CA-B_FP_CN':'causal_discovery/causal_attribution/',
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'CA-B_FP_EN':'causal_discovery/causal_attribution/',
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# event_causality_identification/
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'ECI-B_CTB_CN':'causal_discovery/event_causality_identification/',
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'ECI-B_CTB_EN':'causal_discovery/event_causality_identification/',
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'ECI-B_ESC_CN':'causal_discovery/event_causality_identification/',
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'ECI-B_ESC_EN':'causal_discovery/event_causality_identification/',
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'ECI-B_MAVEN-ERE_CN':'causal_discovery/event_causality_identification/',
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'ECI-B_MAVEN-ERE_EN':'causal_discovery/event_causality_identification/',
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# pairwise_causal_discovery/
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'PCD-B_COPA_CN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-B_COPA_EN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-B_E-CARE_CN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-B_E-CARE_EN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-C_COPA_CN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-C_COPA_EN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-C_E-CARE_CN':'causal_discovery/pairwise_causal_discovery/',
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'PCD-C_E-CARE_EN':'causal_discovery/pairwise_causal_discovery/',
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# counterfactual/
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# actual_causality/
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'AC-B_causal_judgement_CN':'counterfactual/actual_causality/',
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'AC-B_causal_judgement_EN':'counterfactual/actual_causality/',
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# causal_explanation_generation/
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'CEG-O_E-CARE_CN':'counterfactual/causal_explanation_generation/',
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'CEG-O_E-CARE_EN':'counterfactual/causal_explanation_generation/',
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# counterfactual_reasoning/
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'CR-B_det-counterfactual_CN':'counterfactual/counterfactual_reasoning/',
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'CR-B_det-counterfactual_EN':'counterfactual/counterfactual_reasoning/',
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'CR-C_CRASS_CN':'counterfactual/counterfactual_reasoning/',
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'CR-C_CRASS_EN':'counterfactual/counterfactual_reasoning/',
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# effect_of_the_treatment_on_the_treated/
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'ETT-B_ETT-natural_CN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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'ETT-B_ETT-natural_EN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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'ETT-P_ETT-basic_CN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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'ETT-P_ETT-basic_EN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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'ETT-P_ETT-hard_CN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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'ETT-P_ETT-hard_EN':'counterfactual/effect_of_the_treatment_on_the_treated/',
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# natural_direct_effect/
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'NDE-B_NDE-natural_CN':'counterfactual/natural_direct_effect/',
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'NDE-B_NDE-natural_EN':'counterfactual/natural_direct_effect/',
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'NDE-P_NDE-basic_CN':'counterfactual/natural_direct_effect/',
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'NDE-P_NDE-basic_EN':'counterfactual/natural_direct_effect/',
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'NDE-P_NDE-hard_CN':'counterfactual/natural_direct_effect/',
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'NDE-P_NDE-hard_EN':'counterfactual/natural_direct_effect/',
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# natural_indirect_effect/
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'NIE-B_NIE-natural_CN':'counterfactual/natural_indirect_effect/',
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'NIE-B_NIE-natural_EN':'counterfactual/natural_indirect_effect/',
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'NIE-P_NIE-basic_CN':'counterfactual/natural_indirect_effect/',
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'NIE-P_NIE-basic_EN':'counterfactual/natural_indirect_effect/',
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'NIE-P_NIE-hard_CN':'counterfactual/natural_indirect_effect/',
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'NIE-P_NIE-hard_EN':'counterfactual/natural_indirect_effect/',
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# probability_of_necessity/
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'PN-P_PN-basic_CN':'counterfactual/probability_of_necessity/',
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'PN-P_PN-basic_EN':'counterfactual/probability_of_necessity/',
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'PN-P_PN-hard_CN':'counterfactual/probability_of_necessity/',
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'PN-P_PN-hard_EN':'counterfactual/probability_of_necessity/',
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# probability_of_sufficiency/
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'PS-P_PS-basic_CN':'counterfactual/probability_of_sufficiency/',
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'PS-P_PS-basic_EN':'counterfactual/probability_of_sufficiency/',
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'PS-P_PS-hard_CN':'counterfactual/probability_of_sufficiency/',
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'PS-P_PS-hard_EN':'counterfactual/probability_of_sufficiency/',
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# intervention/
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# average_treatment_effect/
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'ATE-B_ATE-natural_CN':'intervention/average_treatment_effect/',
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'ATE-B_ATE-natural_EN':'intervention/average_treatment_effect/',
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'ATE-P_ATE-basic_CN':'intervention/average_treatment_effect/',
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'ATE-P_ATE-basic_EN':'intervention/average_treatment_effect/',
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'ATE-P_ATE-hard_CN':'intervention/average_treatment_effect/',
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'ATE-P_ATE-hard_EN':'intervention/average_treatment_effect/',
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# backdoor_adjustment_set/
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'BAS-B_backadj_CN':'intervention/backdoor_adjustment_set/',
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'BAS-B_backadj_EN':'intervention/backdoor_adjustment_set/',
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'BAS-C_max-BAS_CN':'intervention/backdoor_adjustment_set/',
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'BAS-C_max-BAS_EN':'intervention/backdoor_adjustment_set/',
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'BAS-C_min-BAS_CN':'intervention/backdoor_adjustment_set/',
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'BAS-C_min-BAS_EN':'intervention/backdoor_adjustment_set/',
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'BAS-C_mix-BAS_CN':'intervention/backdoor_adjustment_set/',
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'BAS-C_mix-BAS_EN':'intervention/backdoor_adjustment_set/',
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# causal_effect_identification/
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'CEI-B_0.2-UC_CN':'intervention/causal_effect_identification/',
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'CEI-B_0.2-UC_EN':'intervention/causal_effect_identification/',
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'CEI-B_0.4-UC_CN':'intervention/causal_effect_identification/',
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'CEI-B_0.4-UC_EN':'intervention/causal_effect_identification/',
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'CEI-B_0.6-UC_CN':'intervention/causal_effect_identification/',
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'CEI-B_0.6-UC_EN':'intervention/causal_effect_identification/',
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'CEI-B_0.8-UC_CN':'intervention/causal_effect_identification/',
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'CEI-B_0.8-UC_EN':'intervention/causal_effect_identification/',
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# collider_bias/
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'CB-B_collider-bias_CN':'intervention/collider_bias/',
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'CB-B_collider-bias_EN':'intervention/collider_bias/',
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# controlled_direct_effect/
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'CDE-B_CDE-natural_CN':'intervention/controlled_direct_effect/',
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'CDE-B_CDE-natural_EN':'intervention/controlled_direct_effect/',
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'CDE-P_CDE-basic_CN':'intervention/controlled_direct_effect/',
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'CDE-P_CDE-basic_EN':'intervention/controlled_direct_effect/',
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'CDE-P_CDE-hard_CN':'intervention/controlled_direct_effect/',
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'CDE-P_CDE-hard_EN':'intervention/controlled_direct_effect/',
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# frontdoor_adjustment_set/
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'FAS-C_FAS_CN':'intervention/frontdoor_adjustment_set/',
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'FAS-C_FAS_EN':'intervention/frontdoor_adjustment_set/',
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# instrumental_variable/
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'IV-C_CaLM-IV_CN':'intervention/instrumental_variable/',
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'IV-C_CaLM-IV_EN':'intervention/instrumental_variable/',}
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calm_reader_cfg = dict(
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input_columns=['question'],
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output_column='gt_item')
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calm_all_sets = list(set(key[:-3] for key in task_hiearchy_dict.keys()))
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calm_datasets = []
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for _name in calm_all_sets:
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for _prompt_style in ['basic','basic-CN']:
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_task_name = _name + ('_CN' if _prompt_style.endswith('-CN') else '_EN')
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_path = f'./data/calm/{task_hiearchy_dict[_task_name]}{_task_name}.json'
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calm_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template='{question}'),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=500))
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calm_eval_cfg = dict(evaluator=dict(
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type=CaLMEvaluator,
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core_metrics=True,
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error_analysis=True,
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prompt_style=_prompt_style,
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task=_task_name))
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calm_datasets.append(
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dict(
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abbr=f'calm_{_task_name}',
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type=CaLMDataset,
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path=_path,
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prompt_style=_prompt_style,
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reader_cfg=calm_reader_cfg,
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infer_cfg=calm_infer_cfg,
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eval_cfg=calm_eval_cfg)
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)
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del _prompt_style, _task_name, _path, _name
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