# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


__UpperCAmelCase							:   str							=  {
    "Acehnese Arabic": "ace_Arab",
    "Acehnese Latin": "ace_Latn",
    "Mesopotamian Arabic": "acm_Arab",
    "Ta'izzi-Adeni Arabic": "acq_Arab",
    "Tunisian Arabic": "aeb_Arab",
    "Afrikaans": "afr_Latn",
    "South Levantine Arabic": "ajp_Arab",
    "Akan": "aka_Latn",
    "Amharic": "amh_Ethi",
    "North Levantine Arabic": "apc_Arab",
    "Modern Standard Arabic": "arb_Arab",
    "Modern Standard Arabic Romanized": "arb_Latn",
    "Najdi Arabic": "ars_Arab",
    "Moroccan Arabic": "ary_Arab",
    "Egyptian Arabic": "arz_Arab",
    "Assamese": "asm_Beng",
    "Asturian": "ast_Latn",
    "Awadhi": "awa_Deva",
    "Central Aymara": "ayr_Latn",
    "South Azerbaijani": "azb_Arab",
    "North Azerbaijani": "azj_Latn",
    "Bashkir": "bak_Cyrl",
    "Bambara": "bam_Latn",
    "Balinese": "ban_Latn",
    "Belarusian": "bel_Cyrl",
    "Bemba": "bem_Latn",
    "Bengali": "ben_Beng",
    "Bhojpuri": "bho_Deva",
    "Banjar Arabic": "bjn_Arab",
    "Banjar Latin": "bjn_Latn",
    "Standard Tibetan": "bod_Tibt",
    "Bosnian": "bos_Latn",
    "Buginese": "bug_Latn",
    "Bulgarian": "bul_Cyrl",
    "Catalan": "cat_Latn",
    "Cebuano": "ceb_Latn",
    "Czech": "ces_Latn",
    "Chokwe": "cjk_Latn",
    "Central Kurdish": "ckb_Arab",
    "Crimean Tatar": "crh_Latn",
    "Welsh": "cym_Latn",
    "Danish": "dan_Latn",
    "German": "deu_Latn",
    "Southwestern Dinka": "dik_Latn",
    "Dyula": "dyu_Latn",
    "Dzongkha": "dzo_Tibt",
    "Greek": "ell_Grek",
    "English": "eng_Latn",
    "Esperanto": "epo_Latn",
    "Estonian": "est_Latn",
    "Basque": "eus_Latn",
    "Ewe": "ewe_Latn",
    "Faroese": "fao_Latn",
    "Fijian": "fij_Latn",
    "Finnish": "fin_Latn",
    "Fon": "fon_Latn",
    "French": "fra_Latn",
    "Friulian": "fur_Latn",
    "Nigerian Fulfulde": "fuv_Latn",
    "Scottish Gaelic": "gla_Latn",
    "Irish": "gle_Latn",
    "Galician": "glg_Latn",
    "Guarani": "grn_Latn",
    "Gujarati": "guj_Gujr",
    "Haitian Creole": "hat_Latn",
    "Hausa": "hau_Latn",
    "Hebrew": "heb_Hebr",
    "Hindi": "hin_Deva",
    "Chhattisgarhi": "hne_Deva",
    "Croatian": "hrv_Latn",
    "Hungarian": "hun_Latn",
    "Armenian": "hye_Armn",
    "Igbo": "ibo_Latn",
    "Ilocano": "ilo_Latn",
    "Indonesian": "ind_Latn",
    "Icelandic": "isl_Latn",
    "Italian": "ita_Latn",
    "Javanese": "jav_Latn",
    "Japanese": "jpn_Jpan",
    "Kabyle": "kab_Latn",
    "Jingpho": "kac_Latn",
    "Kamba": "kam_Latn",
    "Kannada": "kan_Knda",
    "Kashmiri Arabic": "kas_Arab",
    "Kashmiri Devanagari": "kas_Deva",
    "Georgian": "kat_Geor",
    "Central Kanuri Arabic": "knc_Arab",
    "Central Kanuri Latin": "knc_Latn",
    "Kazakh": "kaz_Cyrl",
    "Kabiyè": "kbp_Latn",
    "Kabuverdianu": "kea_Latn",
    "Khmer": "khm_Khmr",
    "Kikuyu": "kik_Latn",
    "Kinyarwanda": "kin_Latn",
    "Kyrgyz": "kir_Cyrl",
    "Kimbundu": "kmb_Latn",
    "Northern Kurdish": "kmr_Latn",
    "Kikongo": "kon_Latn",
    "Korean": "kor_Hang",
    "Lao": "lao_Laoo",
    "Ligurian": "lij_Latn",
    "Limburgish": "lim_Latn",
    "Lingala": "lin_Latn",
    "Lithuanian": "lit_Latn",
    "Lombard": "lmo_Latn",
    "Latgalian": "ltg_Latn",
    "Luxembourgish": "ltz_Latn",
    "Luba-Kasai": "lua_Latn",
    "Ganda": "lug_Latn",
    "Luo": "luo_Latn",
    "Mizo": "lus_Latn",
    "Standard Latvian": "lvs_Latn",
    "Magahi": "mag_Deva",
    "Maithili": "mai_Deva",
    "Malayalam": "mal_Mlym",
    "Marathi": "mar_Deva",
    "Minangkabau Arabic ": "min_Arab",
    "Minangkabau Latin": "min_Latn",
    "Macedonian": "mkd_Cyrl",
    "Plateau Malagasy": "plt_Latn",
    "Maltese": "mlt_Latn",
    "Meitei Bengali": "mni_Beng",
    "Halh Mongolian": "khk_Cyrl",
    "Mossi": "mos_Latn",
    "Maori": "mri_Latn",
    "Burmese": "mya_Mymr",
    "Dutch": "nld_Latn",
    "Norwegian Nynorsk": "nno_Latn",
    "Norwegian Bokmål": "nob_Latn",
    "Nepali": "npi_Deva",
    "Northern Sotho": "nso_Latn",
    "Nuer": "nus_Latn",
    "Nyanja": "nya_Latn",
    "Occitan": "oci_Latn",
    "West Central Oromo": "gaz_Latn",
    "Odia": "ory_Orya",
    "Pangasinan": "pag_Latn",
    "Eastern Panjabi": "pan_Guru",
    "Papiamento": "pap_Latn",
    "Western Persian": "pes_Arab",
    "Polish": "pol_Latn",
    "Portuguese": "por_Latn",
    "Dari": "prs_Arab",
    "Southern Pashto": "pbt_Arab",
    "Ayacucho Quechua": "quy_Latn",
    "Romanian": "ron_Latn",
    "Rundi": "run_Latn",
    "Russian": "rus_Cyrl",
    "Sango": "sag_Latn",
    "Sanskrit": "san_Deva",
    "Santali": "sat_Olck",
    "Sicilian": "scn_Latn",
    "Shan": "shn_Mymr",
    "Sinhala": "sin_Sinh",
    "Slovak": "slk_Latn",
    "Slovenian": "slv_Latn",
    "Samoan": "smo_Latn",
    "Shona": "sna_Latn",
    "Sindhi": "snd_Arab",
    "Somali": "som_Latn",
    "Southern Sotho": "sot_Latn",
    "Spanish": "spa_Latn",
    "Tosk Albanian": "als_Latn",
    "Sardinian": "srd_Latn",
    "Serbian": "srp_Cyrl",
    "Swati": "ssw_Latn",
    "Sundanese": "sun_Latn",
    "Swedish": "swe_Latn",
    "Swahili": "swh_Latn",
    "Silesian": "szl_Latn",
    "Tamil": "tam_Taml",
    "Tatar": "tat_Cyrl",
    "Telugu": "tel_Telu",
    "Tajik": "tgk_Cyrl",
    "Tagalog": "tgl_Latn",
    "Thai": "tha_Thai",
    "Tigrinya": "tir_Ethi",
    "Tamasheq Latin": "taq_Latn",
    "Tamasheq Tifinagh": "taq_Tfng",
    "Tok Pisin": "tpi_Latn",
    "Tswana": "tsn_Latn",
    "Tsonga": "tso_Latn",
    "Turkmen": "tuk_Latn",
    "Tumbuka": "tum_Latn",
    "Turkish": "tur_Latn",
    "Twi": "twi_Latn",
    "Central Atlas Tamazight": "tzm_Tfng",
    "Uyghur": "uig_Arab",
    "Ukrainian": "ukr_Cyrl",
    "Umbundu": "umb_Latn",
    "Urdu": "urd_Arab",
    "Northern Uzbek": "uzn_Latn",
    "Venetian": "vec_Latn",
    "Vietnamese": "vie_Latn",
    "Waray": "war_Latn",
    "Wolof": "wol_Latn",
    "Xhosa": "xho_Latn",
    "Eastern Yiddish": "ydd_Hebr",
    "Yoruba": "yor_Latn",
    "Yue Chinese": "yue_Hant",
    "Chinese Simplified": "zho_Hans",
    "Chinese Traditional": "zho_Hant",
    "Standard Malay": "zsm_Latn",
    "Zulu": "zul_Latn",
}


class 					_snake_case						(			_A ):
	_A          =   'facebook/nllb-200-distilled-600M'
	_A          =   (
	    'This is a tool that translates text from a language to another. It takes three inputs: `text`, which should '
	    'be the text to translate, `src_lang`, which should be the language of the text to translate and `tgt_lang`, '
	    'which should be the language for the desired ouput language. Both `src_lang` and `tgt_lang` are written in '
	    'plain English, such as \'Romanian\', or \'Albanian\'. It returns the text translated in `tgt_lang`.'
	)
	_A          =   'translator'
	_A          =   AutoTokenizer
	_A          =   AutoModelForSeqaSeqLM
	_A          =   LANGUAGE_CODES

	_A          =   ['text', 'text', 'text']
	_A          =   ['text']






	def    lowerCAmelCase_							(		self					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase       )						->    Optional[int]:
					if src_lang not in self.lang_to_code:
									raise ValueError(f'{src_lang} is not a supported language.'       )
					if tgt_lang not in self.lang_to_code:
									raise ValueError(f'{tgt_lang} is not a supported language.'       )
					snake_case__      :Optional[Any]         =   self.lang_to_code[src_lang]
					snake_case__      :Union[str, Any]         =   self.lang_to_code[tgt_lang]
					return self.pre_processor._build_translation_inputs(
					    UpperCamelCase					,return_tensors="pt"					,src_lang=UpperCamelCase					,tgt_lang=UpperCamelCase       )






	def    lowerCAmelCase_							(		self					,UpperCamelCase       )						->    Tuple:
					return self.model.generate(**UpperCamelCase       )






	def    lowerCAmelCase_							(		self					,UpperCamelCase       )						->    List[Any]:
					return self.post_processor.decode(outputs[0].tolist()					,skip_special_tokens=UpperCamelCase       )







import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError

from transformers import (
    AlbertTokenizer,
    AutoTokenizer,
    BertTokenizer,
    BertTokenizerFast,
    GPTaTokenizerFast,
    is_tokenizers_available,
)
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers
from transformers.tokenization_utils import Trie


sys.path.append(str(Path(__file__).parent.parent / "utils"))

from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
	from test_module.custom_tokenization_fast import CustomTokenizerFast


class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					# A mock response for an HTTP head request to emulate server down
					snake_case__      :Tuple         =   mock.Mock()
					snake_case__      :List[str]         =   500
					snake_case__      :Any         =   {}
					snake_case__      :Union[str, Any]         =   HTTPError
					snake_case__      :Tuple         =   {}

					# Download this model to make sure it's in the cache.
					snake_case__      :Any         =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"       )

					# Under the mock environment we get a 500 error when trying to reach the tokenizer.
					with mock.patch("requests.Session.request"					,return_value=UpperCamelCase       ) as mock_head:
									snake_case__      :Dict         =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"       )
									# This check we did call the fake head request
									mock_head.assert_called()






	@require_tokenizers
	def    lowerCAmelCase_							(		self       )						->    Dict:
					# A mock response for an HTTP head request to emulate server down
					snake_case__      :Union[str, Any]         =   mock.Mock()
					snake_case__      :int         =   500
					snake_case__      :Any         =   {}
					snake_case__      :Dict         =   HTTPError
					snake_case__      :List[Any]         =   {}

					# Download this model to make sure it's in the cache.
					snake_case__      :Optional[int]         =   GPTaTokenizerFast.from_pretrained("gpt2"       )

					# Under the mock environment we get a 500 error when trying to reach the tokenizer.
					with mock.patch("requests.Session.request"					,return_value=UpperCamelCase       ) as mock_head:
									snake_case__      :Any         =   GPTaTokenizerFast.from_pretrained("gpt2"       )
									# This check we did call the fake head request
									mock_head.assert_called()






	def    lowerCAmelCase_							(		self       )						->    int:
					# This test is for deprecated behavior and can be removed in v5
					try:
									snake_case__      :Union[str, Any]         =   tempfile.mktemp()
									with open(UpperCamelCase					,"wb"       ) as f:
													http_get("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"					,UpperCamelCase       )

									snake_case__      :Tuple         =   AlbertTokenizer.from_pretrained(UpperCamelCase       )
					finally:
									os.remove(UpperCamelCase       )

					# Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in
					# the current folder and have the right name.
					if os.path.isfile("tokenizer.json"       ):
									# We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it.
									return
					try:
									with open("tokenizer.json"					,"wb"       ) as f:
													http_get("https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json"					,UpperCamelCase       )
									snake_case__      :Dict         =   AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2"       )
									# The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000
									self.assertEqual(tokenizer.vocab_size					,1_000       )
									# Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file.

					finally:
									os.remove("tokenizer.json"       )






	def    lowerCAmelCase_							(		self       )						->    Union[str, Any]:
					# This test is for deprecated behavior and can be removed in v5
					snake_case__      :Union[str, Any]         =   AlbertTokenizer.from_pretrained("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"       )




@is_staging_test
class 					_snake_case						(			unittest.TestCase ):
	_A          =   ['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'bla', 'blou']






	@classmethod
	def    lowerCAmelCase_							(		cls       )						->    Optional[int]:
					snake_case__      :List[str]         =   TOKEN
					HfFolder.save_token(UpperCamelCase       )






	@classmethod
	def    lowerCAmelCase_							(		cls       )						->    Union[str, Any]:
					try:
									delete_repo(token=cls._token					,repo_id="test-tokenizer"       )
					except HTTPError:
									pass

					try:
									delete_repo(token=cls._token					,repo_id="valid_org/test-tokenizer-org"       )
					except HTTPError:
									pass

					try:
									delete_repo(token=cls._token					,repo_id="test-dynamic-tokenizer"       )
					except HTTPError:
									pass






	def    lowerCAmelCase_							(		self       )						->    Optional[Any]:
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :List[str]         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :str         =   BertTokenizer(UpperCamelCase       )

					tokenizer.push_to_hub("test-tokenizer"					,use_auth_token=self._token       )
					snake_case__      :Dict         =   BertTokenizer.from_pretrained(f'{USER}/test-tokenizer'       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )

					# Reset repo
					delete_repo(token=self._token					,repo_id="test-tokenizer"       )

					# Push to hub via save_pretrained
					with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(UpperCamelCase					,repo_id="test-tokenizer"					,push_to_hub=UpperCamelCase					,use_auth_token=self._token       )

					snake_case__      :List[str]         =   BertTokenizer.from_pretrained(f'{USER}/test-tokenizer'       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )






	def    lowerCAmelCase_							(		self       )						->    Optional[int]:
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :List[Any]         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :Any         =   BertTokenizer(UpperCamelCase       )

					tokenizer.push_to_hub("valid_org/test-tokenizer-org"					,use_auth_token=self._token       )
					snake_case__      :Any         =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )

					# Reset repo
					delete_repo(token=self._token					,repo_id="valid_org/test-tokenizer-org"       )

					# Push to hub via save_pretrained
					with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(
									    UpperCamelCase					,repo_id="valid_org/test-tokenizer-org"					,push_to_hub=UpperCamelCase					,use_auth_token=self._token       )

					snake_case__      :Union[str, Any]         =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )






	@require_tokenizers
	def    lowerCAmelCase_							(		self       )						->    Any:
					CustomTokenizer.register_for_auto_class()
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :str         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :Optional[int]         =   CustomTokenizer(UpperCamelCase       )

					# No fast custom tokenizer
					tokenizer.push_to_hub("test-dynamic-tokenizer"					,use_auth_token=self._token       )

					snake_case__      :Union[str, Any]         =   AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizer"       )

					# Fast and slow custom tokenizer
					CustomTokenizerFast.register_for_auto_class()
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :int         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )

									snake_case__      :Tuple         =   BertTokenizerFast.from_pretrained(UpperCamelCase       )
									bert_tokenizer.save_pretrained(UpperCamelCase       )
									snake_case__      :List[Any]         =   CustomTokenizerFast.from_pretrained(UpperCamelCase       )

					tokenizer.push_to_hub("test-dynamic-tokenizer"					,use_auth_token=self._token       )

					snake_case__      :List[Any]         =   AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizerFast"       )
					snake_case__      :List[str]         =   AutoTokenizer.from_pretrained(
					    f'{USER}/test-dynamic-tokenizer'					,use_fast=UpperCamelCase					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizer"       )




class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					snake_case__      :int         =   Trie()
					trie.add("Hello 友達"       )
					self.assertEqual(trie.data					,{"H": {"e": {"l": {"l": {"o": {" ": {"友": {"達": {"": 1}}}}}}}}}       )
					trie.add("Hello"       )
					trie.data
					self.assertEqual(trie.data					,{"H": {"e": {"l": {"l": {"o": {"": 1, " ": {"友": {"達": {"": 1}}}}}}}}}       )






	def    lowerCAmelCase_							(		self       )						->    int:
					snake_case__      :List[str]         =   Trie()
					self.assertEqual(trie.split("[CLS] This is a extra_id_100"       )					,["[CLS] This is a extra_id_100"]       )
					trie.add("[CLS]"       )
					trie.add("extra_id_1"       )
					trie.add("extra_id_100"       )
					self.assertEqual(trie.split("[CLS] This is a extra_id_100"       )					,["[CLS]", " This is a ", "extra_id_100"]       )






	def    lowerCAmelCase_							(		self       )						->    str:
					snake_case__      :Optional[Any]         =   Trie()
					trie.add("A"       )
					self.assertEqual(trie.split("ABC"       )					,["A", "BC"]       )
					self.assertEqual(trie.split("BCA"       )					,["BC", "A"]       )






	def    lowerCAmelCase_							(		self       )						->    Dict:
					snake_case__      :Any         =   Trie()
					trie.add("TOKEN]"       )
					trie.add("[SPECIAL_TOKEN]"       )
					self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"       )					,["This is something ", "[SPECIAL_TOKEN]"]       )






	def    lowerCAmelCase_							(		self       )						->    Tuple:
					snake_case__      :List[Any]         =   Trie()
					trie.add("A"       )
					trie.add("P"       )
					trie.add("[SPECIAL_TOKEN]"       )
					self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"       )					,["This is something ", "[SPECIAL_TOKEN]"]       )






	def    lowerCAmelCase_							(		self       )						->    Tuple:
					snake_case__      :str         =   Trie()
					trie.add("AB"       )
					trie.add("B"       )
					trie.add("C"       )
					self.assertEqual(trie.split("ABC"       )					,["AB", "C"]       )






	def    lowerCAmelCase_							(		self       )						->    Union[str, Any]:
					snake_case__      :Dict         =   Trie()
					trie.add("ABC"       )
					trie.add("B"       )
					trie.add("CD"       )
					self.assertEqual(trie.split("ABCD"       )					,["ABC", "D"]       )






	def    lowerCAmelCase_							(		self       )						->    int:
					# Even if the offsets are wrong, we necessarily output correct string
					# parts.
					snake_case__      :Optional[int]         =   Trie()
					snake_case__      :Union[str, Any]         =   trie.cut_text("ABC"					,[0, 0, 2, 1, 2, 3]       )
					self.assertEqual(UpperCamelCase					,["AB", "C"]       )