__init__.py 16.4 KB
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from promptsource.templates import DatasetTemplates
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from pprint import pprint
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from typing import List, Union
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import sacrebleu
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import lm_eval.base
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from . import superglue
from . import glue
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from . import arc
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from . import coqa
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from . import race
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from . import webqs
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from . import anli
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from . import wsc273
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from . import winogrande
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from . import quac
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from . import hellaswag
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from . import openbookqa
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from . import squad
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from . import naturalqs
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from . import sat
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from . import arithmetic
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from . import lambada
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from . import race
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from . import piqa
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from . import prost
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from . import mc_taco
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from . import triviaqa
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from . import pubmedqa
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from . import sciq
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from . import webqs
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from . import qasper
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from . import qa4mre
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from . import translation
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from . import headqa
from . import mathqa
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from . import hendrycks_ethics
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from . import drop
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from . import unscramble
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from . import logiqa
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from . import hendrycks_test
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from . import hendrycks_math
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from . import cbt
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from . import lambada_cloze
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from . import pile
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from . import wikitext
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from . import lambada_multilingual
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from . import mutual
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from . import truthfulqa
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from . import blimp
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from . import asdiv
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from . import gsm8k
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from . import storycloze
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from . import hans
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webnlg  
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from . import gem_webnlg
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from . import lama
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# from . import e2e_nlg_cleaned
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from . import gem_xsum
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from . import gem_mlsum
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from . import wino_bias
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from . import e2e_nlg_cleaned
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from . import gem_asset_turk
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from . import crows_pairs_multilingual
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from . import lama
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gpt3  
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from . import HuffPost
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########################################
# Translation tasks
########################################

# 6 total
gpt3_translation_benchmarks = {
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    "wmt14": ["en-fr", "fr-en"],  # French
    "wmt16": ["en-ro", "ro-en", "de-en", "en-de"],  # German, Romanian
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}


# 28 total
selected_translation_benchmarks = {
    **gpt3_translation_benchmarks,
    "wmt20": sacrebleu.get_langpairs_for_testset("wmt20"),
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    "iwslt17": ["en-ar", "ar-en"],  # Arabic
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}

# 319 total
all_translation_benchmarks = {
    ts: sacrebleu.get_langpairs_for_testset(ts)
    for ts in sacrebleu.get_available_testsets()
}


########################################
# All tasks
########################################


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TASK_REGISTRY = {
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    # GLUE
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    "cola": glue.CoLA,
    "mnli": glue.MNLI,
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    "mnli_mismatched": glue.MNLIMismatched,
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    "mrpc": glue.MRPC,
    "rte": glue.RTE,
    "qnli": glue.QNLI,
    "qqp": glue.QQP,
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    # "stsb": glue.STSB, # not implemented yet
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    "sst": glue.SST,
    "wnli": glue.WNLI,
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    # SuperGLUE
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    "boolq": superglue.BoolQ,
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    "cb": superglue.CommitmentBank,
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    "copa": superglue.Copa,
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    "multirc": superglue.MultiRC,
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    "record": superglue.ReCoRD,
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    "wic": superglue.WordsInContext,
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wsc  
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    "wsc": superglue.SGWinogradSchemaChallenge,
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    # Order by benchmark/genre?
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    "coqa": coqa.CoQA,
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    "drop": drop.DROP,
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    "lambada": lambada.LAMBADA,
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    "lambada_cloze": lambada_cloze.LAMBADA_cloze,
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    **gem_webnlg.construct_tasks(),
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    # multilingual lambada
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    **gem_asset_turk.construct_tasks(),
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    **lambada_multilingual.construct_tasks(),
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    "wikitext": wikitext.WikiText,
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    # "cbt-cn": cbt.CBTCN, # disabled pending context length fix
    # "cbt-ne": cbt.CBTNE, # disabled pending context length fix
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    "piqa": piqa.PiQA,
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    "prost": prost.PROST,
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    "mc_taco": mc_taco.MCTACO,
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    # Science related
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    "pubmedqa": pubmedqa.Pubmed_QA,
    "sciq": sciq.SciQ,
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    "e2e_nlg_cleaned": e2e_nlg_cleaned.E2E_NLG_Cleaned,
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    "qasper": qasper.QASPER,
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    "qa4mre_2011": qa4mre.QA4MRE_2011,
    "qa4mre_2012": qa4mre.QA4MRE_2012,
    "qa4mre_2013": qa4mre.QA4MRE_2013,
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    "triviaqa": triviaqa.TriviaQA,
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    "arc_easy": arc.ARCEasy,
    "arc_challenge": arc.ARCChallenge,
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    # "quac": quac.QuAC, # not implemented yet
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    "lama_trex": lama.Trex,
    "lama_squad": lama.Squad,
    "lama_google_re": lama.google_re,
    "lama_concptnet": lama.Conceptnet,
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    "logiqa": logiqa.LogiQA,
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    "hellaswag": hellaswag.HellaSwag,
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    "openbookqa": openbookqa.OpenBookQA,
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    "squad2": squad.SQuAD2,
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    "race": race.RACE,
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    # "naturalqs": naturalqs.NaturalQs, # not implemented yet
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    "headqa": headqa.HeadQAEsDeprecated,  # for backwards compat - headqa used to default to es
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    "headqa_es": headqa.HeadQAEs,
    "headqa_en": headqa.HeadQAEn,
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    "mathqa": mathqa.MathQA,
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    "webqs": webqs.WebQs,
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    "wsc273": wsc273.WinogradSchemaChallenge273,
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    "winogrande": winogrande.Winogrande,
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    "anli_r1": anli.ANLIRound1,
    "anli_r2": anli.ANLIRound2,
    "anli_r3": anli.ANLIRound3,
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    "hans": hans.HANS,
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    "ethics_cm": hendrycks_ethics.EthicsCM,
    "ethics_deontology": hendrycks_ethics.EthicsDeontology,
    "ethics_justice": hendrycks_ethics.EthicsJustice,
    "ethics_utilitarianism_original": hendrycks_ethics.EthicsUtilitarianismOriginal,
    "ethics_utilitarianism": hendrycks_ethics.EthicsUtilitarianism,
    "ethics_virtue": hendrycks_ethics.EthicsVirtue,
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    #"tydiqa_primary" : TyDiQA.Primary, not implemented yet
    #"tydiqa_secondary" : TyDiQA.Secondary, not implemented yet
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    "truthfulqa_mc": truthfulqa.TruthfulQAMultipleChoice,
    "truthfulqa_gen": truthfulqa.TruthfulQAGeneration,
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    # dialogue
    "mutual": mutual.MuTual,
    "mutual_plus": mutual.MuTualPlus,
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    # math
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    "math_algebra": hendrycks_math.MathAlgebra,
    "math_counting_and_prob": hendrycks_math.MathCountingAndProbability,
    "math_geometry": hendrycks_math.MathGeometry,
    "math_intermediate_algebra": hendrycks_math.MathIntermediateAlgebra,
    "math_num_theory": hendrycks_math.MathNumberTheory,
    "math_prealgebra": hendrycks_math.MathPrealgebra,
    "math_precalc": hendrycks_math.MathPrecalculus,
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    "math_asdiv": asdiv.Asdiv,
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    "gsm8k": gsm8k.GradeSchoolMath8K,
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    # arithmetic
    "arithmetic_2da": arithmetic.Arithmetic2DPlus,
    "arithmetic_2ds": arithmetic.Arithmetic2DMinus,
    "arithmetic_3da": arithmetic.Arithmetic3DPlus,
    "arithmetic_3ds": arithmetic.Arithmetic3DMinus,
    "arithmetic_4da": arithmetic.Arithmetic4DPlus,
    "arithmetic_4ds": arithmetic.Arithmetic4DMinus,
    "arithmetic_5da": arithmetic.Arithmetic5DPlus,
    "arithmetic_5ds": arithmetic.Arithmetic5DMinus,
    "arithmetic_2dm": arithmetic.Arithmetic2DMultiplication,
    "arithmetic_1dc": arithmetic.Arithmetic1DComposite,
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    # TODO Perhaps make these groups of tasks
    #   e.g. anli, arithmetic, openai_translations, harness_translations
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    # hendrycksTest (57 tasks)
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    **hendrycks_test.create_all_tasks(),
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    # e.g. wmt14-fr-en
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    **translation.create_tasks_from_benchmarks(gpt3_translation_benchmarks),
    # chef's selection, mostly wmt20
    **translation.create_tasks_from_benchmarks(selected_translation_benchmarks),
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    # Word Scrambling and Manipulation Tasks
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    "anagrams1": unscramble.Anagrams1,
    "anagrams2": unscramble.Anagrams2,
    "cycle_letters": unscramble.CycleLetters,
    "random_insertion": unscramble.RandomInsertion,
    "reversed_words": unscramble.ReversedWords,
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    # Pile
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    "pile_arxiv": pile.PileArxiv,
    "pile_books3": pile.PileBooks3,
    "pile_bookcorpus2": pile.PileBookCorpus2,
    "pile_dm-mathematics": pile.PileDmMathematics,
    "pile_enron": pile.PileEnron,
    "pile_europarl": pile.PileEuroparl,
    "pile_freelaw": pile.PileFreeLaw,
    "pile_github": pile.PileGithub,
    "pile_gutenberg": pile.PileGutenberg,
    "pile_hackernews": pile.PileHackernews,
    "pile_nih-exporter": pile.PileNIHExporter,
    "pile_opensubtitles": pile.PileOpenSubtitles,
    "pile_openwebtext2": pile.PileOpenWebText2,
    "pile_philpapers": pile.PilePhilPapers,
    "pile_pile-cc": pile.PilePileCc,
    "pile_pubmed-abstracts": pile.PilePubmedAbstracts,
    "pile_pubmed-central": pile.PilePubmedCentral,
    "pile_stackexchange": pile.PileStackExchange,
    "pile_uspto": pile.PileUspto,
    "pile_ubuntu-irc": pile.PileUbuntuIrc,
    "pile_wikipedia": pile.PileWikipedia,
    "pile_youtubesubtitles": pile.PileYoutubeSubtitles,
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    # BLiMP
    "blimp_adjunct_island": blimp.BlimpAdjunctIsland,
    "blimp_anaphor_gender_agreement": blimp.BlimpAnaphorGenderAgreement,
    "blimp_anaphor_number_agreement": blimp.BlimpAnaphorNumberAgreement,
    "blimp_animate_subject_passive": blimp.BlimpAnimateSubjectPassive,
    "blimp_animate_subject_trans": blimp.BlimpAnimateSubjectTrans,
    "blimp_causative": blimp.BlimpCausative,
    "blimp_complex_NP_island": blimp.BlimpComplex_NPIsland,
    "blimp_coordinate_structure_constraint_complex_left_branch": blimp.BlimpCoordinateStructureConstraintComplexLeftBranch,
    "blimp_coordinate_structure_constraint_object_extraction": blimp.BlimpCoordinateStructureConstraintObjectExtraction,
    "blimp_determiner_noun_agreement_1": blimp.BlimpDeterminerNounAgreement_1,
    "blimp_determiner_noun_agreement_2": blimp.BlimpDeterminerNounAgreement_2,
    "blimp_determiner_noun_agreement_irregular_1": blimp.BlimpDeterminerNounAgreementIrregular_1,
    "blimp_determiner_noun_agreement_irregular_2": blimp.BlimpDeterminerNounAgreementIrregular_2,
    "blimp_determiner_noun_agreement_with_adj_2": blimp.BlimpDeterminerNounAgreementWithAdj_2,
    "blimp_determiner_noun_agreement_with_adj_irregular_1": blimp.BlimpDeterminerNounAgreementWithAdjIrregular_1,
    "blimp_determiner_noun_agreement_with_adj_irregular_2": blimp.BlimpDeterminerNounAgreementWithAdjIrregular_2,
    "blimp_determiner_noun_agreement_with_adjective_1": blimp.BlimpDeterminerNounAgreementWithAdjective_1,
    "blimp_distractor_agreement_relational_noun": blimp.BlimpDistractorAgreementRelationalNoun,
    "blimp_distractor_agreement_relative_clause": blimp.BlimpDistractorAgreementRelativeClause,
    "blimp_drop_argument": blimp.BlimpDropArgument,
    "blimp_ellipsis_n_bar_1": blimp.BlimpEllipsisNBar_1,
    "blimp_ellipsis_n_bar_2": blimp.BlimpEllipsisNBar_2,
    "blimp_existential_there_object_raising": blimp.BlimpExistentialThereObjectRaising,
    "blimp_existential_there_quantifiers_1": blimp.BlimpExistentialThereQuantifiers_1,
    "blimp_existential_there_quantifiers_2": blimp.BlimpExistentialThereQuantifiers_2,
    "blimp_existential_there_subject_raising": blimp.BlimpExistentialThereSubjectRaising,
    "blimp_expletive_it_object_raising": blimp.BlimpExpletiveItObjectRaising,
    "blimp_inchoative": blimp.BlimpInchoative,
    "blimp_intransitive": blimp.BlimpIntransitive,
    "blimp_irregular_past_participle_adjectives": blimp.BlimpIrregularPastParticipleAdjectives,
    "blimp_irregular_past_participle_verbs": blimp.BlimpIrregularPastParticipleVerbs,
    "blimp_irregular_plural_subject_verb_agreement_1": blimp.BlimpIrregularPluralSubjectVerbAgreement_1,
    "blimp_irregular_plural_subject_verb_agreement_2": blimp.BlimpIrregularPluralSubjectVerbAgreement_2,
    "blimp_left_branch_island_echo_question": blimp.BlimpLeftBranchIslandEchoQuestion,
    "blimp_left_branch_island_simple_question": blimp.BlimpLeftBranchIslandSimpleQuestion,
    "blimp_matrix_question_npi_licensor_present": blimp.BlimpMatrixQuestionNpiLicensorPresent,
    "blimp_npi_present_1": blimp.BlimpNpiPresent_1,
    "blimp_npi_present_2": blimp.BlimpNpiPresent_2,
    "blimp_only_npi_licensor_present": blimp.BlimpOnlyNpiLicensorPresent,
    "blimp_only_npi_scope": blimp.BlimpOnlyNpiScope,
    "blimp_passive_1": blimp.BlimpPassive_1,
    "blimp_passive_2": blimp.BlimpPassive_2,
    "blimp_principle_A_c_command": blimp.BlimpPrinciple_ACCommand,
    "blimp_principle_A_case_1": blimp.BlimpPrinciple_ACase_1,
    "blimp_principle_A_case_2": blimp.BlimpPrinciple_ACase_2,
    "blimp_principle_A_domain_1": blimp.BlimpPrinciple_ADomain_1,
    "blimp_principle_A_domain_2": blimp.BlimpPrinciple_ADomain_2,
    "blimp_principle_A_domain_3": blimp.BlimpPrinciple_ADomain_3,
    "blimp_principle_A_reconstruction": blimp.BlimpPrinciple_AReconstruction,
    "blimp_regular_plural_subject_verb_agreement_1": blimp.BlimpRegularPluralSubjectVerbAgreement_1,
    "blimp_regular_plural_subject_verb_agreement_2": blimp.BlimpRegularPluralSubjectVerbAgreement_2,
    "blimp_sentential_negation_npi_licensor_present": blimp.BlimpSententialNegationNpiLicensorPresent,
    "blimp_sentential_negation_npi_scope": blimp.BlimpSententialNegationNpiScope,
    "blimp_sentential_subject_island": blimp.BlimpSententialSubjectIsland,
    "blimp_superlative_quantifiers_1": blimp.BlimpSuperlativeQuantifiers_1,
    "blimp_superlative_quantifiers_2": blimp.BlimpSuperlativeQuantifiers_2,
    "blimp_tough_vs_raising_1": blimp.BlimpToughVsRaising_1,
    "blimp_tough_vs_raising_2": blimp.BlimpToughVsRaising_2,
    "blimp_transitive": blimp.BlimpTransitive,
    "blimp_wh_island": blimp.BlimpWhIsland,
    "blimp_wh_questions_object_gap": blimp.BlimpWhQuestionsObjectGap,
    "blimp_wh_questions_subject_gap": blimp.BlimpWhQuestionsSubjectGap,
    "blimp_wh_questions_subject_gap_long_distance": blimp.BlimpWhQuestionsSubjectGapLongDistance,
    "blimp_wh_vs_that_no_gap": blimp.BlimpWhVsThatNoGap,
    "blimp_wh_vs_that_no_gap_long_distance": blimp.BlimpWhVsThatNoGapLongDistance,
    "blimp_wh_vs_that_with_gap": blimp.BlimpWhVsThatWithGap,
    "blimp_wh_vs_that_with_gap_long_distance": blimp.BlimpWhVsThatWithGapLongDistance,
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    #GEM/mlsum
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    "mlsum_es":gem_mlsum.GEMMLSUMEs,
    "mlsum_de":gem_mlsum.GEMMLSUMDe,
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    "mlsum_es_covid_challenge_set":gem_mlsum.GEMMLSUMEsChallgeTestCovid,
    "mlsum_de_covid_challenge_set":gem_mlsum.GEMMLSUMDeChallgeTestCovid,

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    # Requires manual download of data.
    # "storycloze_2016": storycloze.StoryCloze2016,
    # "storycloze_2018": storycloze.StoryCloze2018,
    # "sat": sat.SATAnalogies,
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    #GEM/xum
    "gem_xsum": gem_xsum.GEMXSUM,
    "gem_xsum_challenge_sample": gem_xsum.GEMXSUMChallgeSample,
    "gem_xsum_challenge_test_backtranslation": gem_xsum.GEMXSUMChallgeTestBacktranslation,
    "gem_xsum_challenge_test_bfp_02": gem_xsum.GEMXSUMChallgeTestBFP02,
    "gem_xsum_challenge_test_bfp_05": gem_xsum.GEMXSUMChallgeTestBFP05,
    "gem_xsum_challenge_test_nopunc": gem_xsum.GEMXSUMChallgeTestNopunc,
    "gem_xsum_challenge_test_covid": gem_xsum.GEMXSUMChallgeTestCovid,
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   #LAMA
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    "lama-trex": lama.Trex,
    "lama-squad": lama.Squad,
    "lama-google_re": lama.google_re,
    "lama-concptnet": lama.Conceptnet,
    "bigscience-lama":lama.BigScienceLAMA,
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    # WinoBias
    "wino_bias_type1_pro": wino_bias.WinoBiasType1Pro,
    "wino_bias_type1_anti": wino_bias.WinoBiasType1Anti,
    "wino_bias_type2_pro": wino_bias.WinoBiasType2Pro,
    "wino_bias_type2_anti": wino_bias.WinoBiasType2Anti,
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    # Crows-Pairs
    "crows_pairs_english": crows_pairs_multilingual.CrowsPairsEnglish,
    "crows_pairs_french": crows_pairs_multilingual.CrowsPairsFrench,
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    # News
    "huffpost": HuffPost.HuffPost,
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}
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ALL_TASKS = sorted(list(TASK_REGISTRY))
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def get_task(task_name):
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    try:
        return TASK_REGISTRY[task_name]
    except KeyError as e:
        print("Available tasks:")
        pprint(TASK_REGISTRY)
        raise KeyError(f"Missing task {task_name}")
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def get_task_name_from_object(task_object):
    for name, class_ in TASK_REGISTRY.items():
        if class_ is task_object:
            return name
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    # this gives a mechanism for non-registered tasks to have a custom name anyways when reporting
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    return (
        task_object.EVAL_HARNESS_NAME
        if hasattr(task_object, "EVAL_HARNESS_NAME")
        else type(task_object).__name__
    )
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def get_task_dict(task_name_list: List[Union[str, lm_eval.base.Task]]):
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    task_name_dict = {
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        task_name: get_task(task_name)()
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        for task_name in task_name_list
        if isinstance(task_name, str)
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    }
    task_name_from_object_dict = {
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        get_task_name_from_object(task_object): task_object
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        for task_object in task_name_list
        if not isinstance(task_object, str)
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    }
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    assert set(task_name_dict.keys()).isdisjoint(set(task_name_from_object_dict.keys()))
    return {**task_name_dict, **task_name_from_object_dict}
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def get_task_dict_promptsource(task_name_list: List[str]):
    """Loads a task instance for each prompt written for that task."""
    task_name_dict = {}

    for task_name in task_name_list:
        assert isinstance(task_name, str)

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        # Static version of the Task Use this to get HF dataset path / name.
        static_task_obj = get_task(task_name)
        # Create the proper task name arg for DatasetTemplates.
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        sub_task = (
            f"/{static_task_obj.DATASET_NAME}" if static_task_obj.DATASET_NAME else ""
        )
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        ps_task_name = f"{static_task_obj.DATASET_PATH}{sub_task}"

        task_prompts = DatasetTemplates(ps_task_name)
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        for prompt_name in task_prompts.all_template_names:
            prompt = task_prompts[prompt_name]
            # NOTE: We choose a sep that can be easily split.
            task_name_dict[f"{task_name}+{prompt_name}"] = get_task(task_name)(
                prompt=prompt
            )

    return task_name_dict