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import os
import datasets
import yaml
all_subtasks = [
"abstract_narrative_understanding",
"anachronisms",
"analogical_similarity",
"analytic_entailment",
"arithmetic",
"ascii_word_recognition",
"authorship_verification",
"auto_categorization",
"auto_debugging",
"bbq_lite_json",
"bridging_anaphora_resolution_barqa",
"causal_judgment",
"cause_and_effect",
"checkmate_in_one",
"chess_state_tracking",
"chinese_remainder_theorem",
"cifar10_classification",
"code_line_description",
"codenames",
"color",
"common_morpheme",
"conceptual_combinations",
"conlang_translation",
"contextual_parametric_knowledge_conflicts",
"crash_blossom",
"crass_ai",
"cryobiology_spanish",
"cryptonite",
"cs_algorithms",
"dark_humor_detection",
"date_understanding",
"disambiguation_qa",
"discourse_marker_prediction",
"disfl_qa",
"dyck_languages",
"elementary_math_qa",
"emoji_movie",
"emojis_emotion_prediction",
"empirical_judgments",
"english_proverbs",
"english_russian_proverbs",
"entailed_polarity",
"entailed_polarity_hindi",
"epistemic_reasoning",
"evaluating_information_essentiality",
"fact_checker",
"fantasy_reasoning",
"few_shot_nlg",
"figure_of_speech_detection",
"formal_fallacies_syllogisms_negation",
"gem",
"gender_inclusive_sentences_german",
"general_knowledge",
"geometric_shapes",
"goal_step_wikihow",
"gre_reading_comprehension",
"hhh_alignment",
"hindi_question_answering",
"hindu_knowledge",
"hinglish_toxicity",
"human_organs_senses",
"hyperbaton",
"identify_math_theorems",
"identify_odd_metaphor",
"implicatures",
"implicit_relations",
"intent_recognition",
"international_phonetic_alphabet_nli",
"international_phonetic_alphabet_transliterate",
"intersect_geometry",
"irony_identification",
"kanji_ascii",
"kannada",
"key_value_maps",
"known_unknowns",
"language_games",
"language_identification",
"linguistic_mappings",
"linguistics_puzzles",
"list_functions",
"logic_grid_puzzle",
"logical_args",
"logical_deduction",
"logical_fallacy_detection",
"logical_sequence",
"mathematical_induction",
"matrixshapes",
"metaphor_boolean",
"metaphor_understanding",
"minute_mysteries_qa",
"misconceptions",
"misconceptions_russian",
"mnist_ascii",
"modified_arithmetic",
"moral_permissibility",
"movie_dialog_same_or_different",
"movie_recommendation",
"mult_data_wrangling",
"multiemo",
"natural_instructions",
"navigate",
"nonsense_words_grammar",
"novel_concepts",
"object_counting",
"odd_one_out",
"operators",
"paragraph_segmentation",
"parsinlu_qa",
"parsinlu_reading_comprehension",
"penguins_in_a_table",
"periodic_elements",
"persian_idioms",
"phrase_relatedness",
"physical_intuition",
"physics",
"physics_questions",
"play_dialog_same_or_different",
"polish_sequence_labeling",
"presuppositions_as_nli",
"qa_wikidata",
"question_selection",
"real_or_fake_text",
"reasoning_about_colored_objects",
"repeat_copy_logic",
"rephrase",
"riddle_sense",
"ruin_names",
"salient_translation_error_detection",
"scientific_press_release",
"semantic_parsing_in_context_sparc",
"semantic_parsing_spider",
"sentence_ambiguity",
"similarities_abstraction",
"simp_turing_concept",
"simple_arithmetic_json",
"simple_arithmetic_json_multiple_choice",
"simple_arithmetic_json_subtasks",
"simple_arithmetic_multiple_targets_json",
"simple_ethical_questions",
"simple_text_editing",
"snarks",
"social_iqa",
"social_support",
"sports_understanding",
"strange_stories",
"strategyqa",
"sufficient_information",
"suicide_risk",
"swahili_english_proverbs",
"swedish_to_german_proverbs",
"symbol_interpretation",
"temporal_sequences",
"tense",
"timedial",
"topical_chat",
"tracking_shuffled_objects",
"understanding_fables",
"undo_permutation",
"unit_conversion",
"unit_interpretation",
"unnatural_in_context_learning",
"vitaminc_fact_verification",
"what_is_the_tao",
"which_wiki_edit",
"winowhy",
"word_sorting",
"word_unscrambling",
]
skip_tasks = [
"simple_arithmetic_json_multiple_choice",
"simple_arithmetic_multiple_targets_json",
]
def main() -> None:
for path, task_type in zip(
["multiple_choice", "generate_until"],
["multiple_choice_template_yaml", "generate_until_template_yaml"],
):
os.makedirs(path, exist_ok=True)
for task in all_subtasks:
file_name = f"{task}.yaml"
try:
template_file = task_type
if path == "multiple_choice":
print(f"Checking {task} for multiple choices")
if task in skip_tasks:
continue
data = datasets.load_dataset("hails/bigbench", task + "_zero_shot")
multiple_choice_targets = data["default"][0][
"multiple_choice_targets"
]
if len(multiple_choice_targets) == 0:
continue
else:
template_file = "multiple_choice_template_b_yaml"
if set(data["default"][0]["targets"]) < set(
multiple_choice_targets
):
template_file = "multiple_choice_template_a_yaml"
with open(f"{path}/{file_name}", "w", encoding="utf-8") as f:
f.write("# Generated by utils.py\n")
yaml.dump(
{
"include": f"../{template_file}",
"task": "bigbench_"
+ task
+ "_{}".format(task_type.split("_template_yaml")[0]),
"dataset_name": task
+ "_zero_shot", # zero-shot version of the dataset
},
f,
width=float("inf"),
allow_unicode=True,
)
except FileExistsError:
pass
if __name__ == "__main__":
main()
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