peacock-data-public-datasets-idc-llm_eval
/
lm-evaluation
/lm_eval
/tasks
/bigbench
/generate_tasks.py
import os | |
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", | |
] | |
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: | |
with open(f"{path}/{file_name}", "w", encoding="utf-8") as f: | |
f.write("# Generated by utils.py\n") | |
yaml.dump( | |
{ | |
"include": f"../{task_type}", | |
"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() | |