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from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import TopkRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import BleuEvaluator
from opencompass.datasets import FloresFirst100Dataset
_flores_lang_map = [
["eng", "eng_Latn", "English", "Indo-European-Germanic"],
["afr", "afr_Latn", "Afrikaans", "Indo-European-Germanic"],
["dan", "dan_Latn", "Danish", "Indo-European-Germanic"],
["deu", "deu_Latn", "German", "Indo-European-Germanic"],
["isl", "isl_Latn", "Icelandic", "Indo-European-Germanic"],
["ltz", "ltz_Latn", "Luxembourgish", "Indo-European-Germanic"],
["nld", "nld_Latn", "Dutch", "Indo-European-Germanic"],
["nob", "nob_Latn", "Norwegian", "Indo-European-Germanic"],
["swe", "swe_Latn", "Swedish", "Indo-European-Germanic"],
["ast", "ast_Latn", "Asturian", "Indo-European-Romance"],
["cat", "cat_Latn", "Catalan", "Indo-European-Romance"],
["fra", "fra_Latn", "French", "Indo-European-Romance"],
["glg", "glg_Latn", "Galician", "Indo-European-Romance"],
["oci", "oci_Latn", "Occitan", "Indo-European-Romance"],
["por", "por_Latn", "Portuguese", "Indo-European-Romance"],
["ron", "ron_Latn", "Romanian", "Indo-European-Romance"],
["spa", "spa_Latn", "Spanish", "Indo-European-Romance"],
["bel", "bel_Cyrl", "Belarusian", "Indo-European-Slavic"],
["bos", "bos_Latn", "Bosnian", "Indo-European-Slavic"],
["bul", "bul_Cyrl", "Bulgarian", "Indo-European-Slavic"],
["ces", "ces_Latn", "Czech", "Indo-European-Slavic"],
["hrv", "hrv_Latn", "Croatian", "Indo-European-Slavic"],
["mkd", "mkd_Cyrl", "Macedonian", "Indo-European-Slavic"],
["pol", "pol_Latn", "Polish", "Indo-European-Slavic"],
["rus", "rus_Cyrl", "Russian", "Indo-European-Slavic"],
["slk", "slk_Latn", "Slovak", "Indo-European-Slavic"],
["slv", "slv_Latn", "Slovenian", "Indo-European-Slavic"],
["srp", "srp_Cyrl", "Serbian", "Indo-European-Slavic"],
["ukr", "ukr_Cyrl", "Ukrainian", "Indo-European-Slavic"],
["asm", "asm_Beng", "Assamese", "Indo-European-Indo-Aryan"],
["ben", "ben_Beng", "Bengali", "Indo-European-Indo-Aryan"],
["guj", "guj_Gujr", "Gujarati", "Indo-European-Indo-Aryan"],
["hin", "hin_Deva", "Hindi", "Indo-European-Indo-Aryan"],
["mar", "mar_Deva", "Marathi", "Indo-European-Indo-Aryan"],
["npi", "npi_Deva", "Nepali", "Indo-European-Indo-Aryan"],
["ory", "ory_Orya", "Oriya", "Indo-European-Indo-Aryan"],
["pan", "pan_Guru", "Punjabi", "Indo-European-Indo-Aryan"],
["snd", "snd_Arab", "Sindhi", "Indo-European-Indo-Aryan"],
["urd", "urd_Arab", "Urdu", "Indo-European-Indo-Aryan"],
["ckb", "ckb_Arab", "Kurdish", "Indo-European-Other"],
["cym", "cym_Latn", "Welsh", "Indo-European-Other"],
["ell", "ell_Grek", "Greek", "Indo-European-Other"],
["fas", "pes_Arab", "Persian", "Indo-European-Other"],
["gle", "gle_Latn", "Irish", "Indo-European-Other"],
["hye", "hye_Armn", "Armenian", "Indo-European-Other"],
["ita", "ita_Latn", "Italian", "Indo-European-Other"],
["lav", "lvs_Latn", "Latvian", "Indo-European-Other"],
["lit", "lit_Latn", "Lithuanian", "Indo-European-Other"],
["pus", "pbt_Arab", "Pashto", "Indo-European-Other"],
["tgk", "tgk_Cyrl", "Tajik", "Indo-European-Other"],
["ceb", "ceb_Latn", "Cebuano", "Austronesian"],
["ind", "ind_Latn", "Indonesian", "Austronesian"],
["jav", "jav_Latn", "Javanese", "Austronesian"],
["mri", "mri_Latn", "Maori", "Austronesian"],
["msa", "zsm_Latn", "Malay", "Austronesian"],
["tgl", "tgl_Latn", "Tagalog", "Austronesian"],
["ibo", "ibo_Latn", "Igbo", "Atlantic-Congo"],
["kam", "kam_Latn", "Kamba", "Atlantic-Congo"],
["kea", "kea_Latn", "Kabuverdianu", "Atlantic-Congo"],
["lin", "lin_Latn", "Lingala", "Atlantic-Congo"],
["lug", "lug_Latn", "Luganda", "Atlantic-Congo"],
["nso", "nso_Latn", "Northern Sotho", "Atlantic-Congo"],
["nya", "nya_Latn", "Nyanja", "Atlantic-Congo"],
["sna", "sna_Latn", "Shona", "Atlantic-Congo"],
["swh", "swh_Latn", "Swahili", "Atlantic-Congo"],
["umb", "umb_Latn", "Umbundu", "Atlantic-Congo"],
["wol", "wol_Latn", "Wolof", "Atlantic-Congo"],
["xho", "xho_Latn", "Xhosa", "Atlantic-Congo"],
["yor", "yor_Latn", "Yoruba", "Atlantic-Congo"],
["zul", "zul_Latn", "Zulu", "Atlantic-Congo"],
["amh", "amh_Ethi", "Amharic", "Afro-Asiatic"],
["ara", "arb_Arab", "Arabic", "Afro-Asiatic"],
["ful", "fuv_Latn", "Fulah", "Afro-Asiatic"],
["mlt", "mlt_Latn", "Maltese", "Afro-Asiatic"],
["orm", "gaz_Latn", "Oromo", "Afro-Asiatic"],
["som", "som_Latn", "Somali", "Afro-Asiatic"],
["azj", "azj_Latn", "Azerbaijani", "Turkic"],
["kaz", "kaz_Cyrl", "Kazakh", "Turkic"],
["kir", "kir_Cyrl", "Kyrgyz", "Turkic"],
["tur", "tur_Latn", "Turkish", "Turkic"],
["uzb", "uzn_Latn", "Uzbek", "Turkic"],
["kan", "kan_Knda", "Kannada", "Dravidian"],
["mal", "mal_Mlym", "Malayalam", "Dravidian"],
["tam", "tam_Taml", "Tamil", "Dravidian"],
["tel", "tel_Telu", "Telugu", "Dravidian"],
["mya", "mya_Mymr", "Burmese", "Sino-Tibetan"],
["zho_simpl", "zho_Hans", "Chinese (Simpl)", "Sino-Tibetan"],
["zho_trad", "zho_Hant", "Chinese (Trad)", "Sino-Tibetan"],
["est", "est_Latn", "Estonian", "Other"],
["fin", "fin_Latn", "Finnish", "Other"],
["hau", "hau_Latn", "Hausa", "Other"],
["heb", "heb_Hebr", "Hebrew", "Other"],
["hun", "hun_Latn", "Hungarian", "Other"],
["jpn", "jpn_Jpan", "Japanese", "Other"],
["kat", "kat_Geor", "Georgian", "Other"],
["khm", "khm_Khmr", "Khmer", "Other"],
["kor", "kor_Hang", "Korean", "Other"],
["lao", "lao_Laoo", "Lao", "Other"],
["luo", "luo_Latn", "Luo", "Other"],
["mon", "khk_Cyrl", "Mongolian", "Other"],
["tha", "tha_Thai", "Thai", "Other"],
["vie", "vie_Latn", "Vietnamese", "Other"],
]
flores_lang_map = {i[0]: i for i in _flores_lang_map}
_flores_subtasks = [f"eng-{i}" for i in flores_lang_map if i != "eng"
] + [f"{i}-eng" for i in flores_lang_map if i != "eng"]
flores_datasets = []
for _flores_subtask in _flores_subtasks:
_src, _tgt = _flores_subtask.split("-")
_, _flores_source, _src_inst, _ = flores_lang_map[_src]
_, _flores_target, _tgt_inst, _ = flores_lang_map[_tgt]
flores_reader_cfg = dict(
input_columns=f"sentence_{_flores_source}",
output_column=f"sentence_{_flores_target}",
train_split="dev",
test_split="devtest"
)
flores_infer_cfg = dict(
ice_template=dict(
type=PromptTemplate,
template=dict(
begin="</E>",
round=[
dict(
role="HUMAN",
prompt=
f"Translate the following {_src_inst} statements to {_tgt_inst}.\n{{sentence_{_flores_source}}}"
),
dict(role="BOT", prompt=f"{{sentence_{_flores_target}}}"),
],
),
ice_token="</E>",
),
retriever=dict(type=TopkRetriever, ice_num=8),
inferencer=dict(type=GenInferencer),
)
flores_eval_cfg = dict(
evaluator=dict(type=BleuEvaluator),
pred_role="BOT",
)
if _tgt == "zho_simpl":
flores_eval_cfg["pred_postprocessor"] = dict(type="flores")
flores_eval_cfg["dataset_postprocessor"] = dict(type="flores")
flores_datasets.append(
dict(
abbr=f"flores_100_{_src}-{_tgt}",
type=FloresFirst100Dataset,
path='./data/flores_first100',
name=f"{_flores_source}-{_flores_target}",
reader_cfg=flores_reader_cfg.copy(),
infer_cfg=flores_infer_cfg.copy(),
eval_cfg=flores_eval_cfg.copy(),
))
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