__init__.py 4.11 KB
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from pprint import pprint

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import sacrebleu

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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 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 qa4mre
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from . import translation
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from . import headqa
from . import mathqa
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########################################
# Translation tasks
########################################

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


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

# 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": superglue.SGWinogradSchemaChallenge,
83
    
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    # Order by benchmark/genre?
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    "coqa": coqa.CoQA,
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    "lambada": lambada.LAMBADA,
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    "piqa": piqa.PiQA,
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    # Science related
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    "pubmedqa" : pubmedqa.Pubmed_QA,
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    "sciq" : sciq.SciQ,
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    #"qa4mre" : qa4mre.QA4MRE,
    "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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    "hellaswag": hellaswag.HellaSwag, # not implemented yet
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    "openbookqa": openbookqa.OpenBookQA,
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    # "sat": sat.SATAnalogies, # not implemented yet
    # "squad": squad.SQuAD, # not implemented yet
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    "race": race.RACE,
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    # "naturalqs": naturalqs.NaturalQs, # not implemented yet
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    "headqa": headqa.HeadQA,
    "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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    # 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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    # 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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}
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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_dict(task_name_list):
    return {
        task_name: get_task(task_name)()
        for task_name in task_name_list
    }