"""simple docstring"""






import os
import pickle
import unittest

from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
    VOCAB_FILES_NAMES,
    BertJapaneseTokenizer,
    CharacterTokenizer,
    JumanppTokenizer,
    MecabTokenizer,
    SudachiTokenizer,
    WordpieceTokenizer,
)
from transformers.testing_utils import custom_tokenizers, require_jumanpp, require_sudachi

from ...test_tokenization_common import TokenizerTesterMixin

@custom_tokenizers
class lowerCamelCase		(_SCREAMING_SNAKE_CASE    ,    unittest.TestCase      ):






					'''simple docstring'''


					a   	=		BertJapaneseTokenizer
					a   	=		False
					a   	=		True



					def 			lowerCAmelCase_					(						self			:				Any		)							->       Optional[Any]:
									super().setUp()

									SCREAMING_SNAKE_CASE__		  =				[
									    "[UNK]",
									    "[CLS]",
									    "[SEP]",
									    "こんにちは",
									    "こん",
									    "にちは",
									    "ばんは",
									    "##こん",
									    "##にちは",
									    "##ばんは",
									    "世界",
									    "##世界",
									    "、",
									    "##、",
									    "。",
									    "##。",
									]

									SCREAMING_SNAKE_CASE__		  =				os.path.join(self.tmpdirname   , VOCAB_FILES_NAMES["vocab_file"]		)
									with open(self.vocab_file   , "w"   , encoding="utf-8"		) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)



					def 			lowerCAmelCase_					(						self			:				Optional[Any]   , _snake_case			:				int		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				"こんにちは、世界。 \nこんばんは、世界。"
									SCREAMING_SNAKE_CASE__		  =				"こんにちは 、 世界 。 こんばんは 、 世界 。"
									return input_text, output_text



					def 			lowerCAmelCase_					(						self			:				Tuple   , _snake_case			:				int		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				self.get_input_output_texts(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.encode(_snake_case   , add_special_tokens=_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.decode(_snake_case   , clean_up_tokenization_spaces=_snake_case		)
									return text, ids



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       int:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       str:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       List[str]:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class(self.vocab_file		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize("こんにちは、世界。\nこんばんは、世界。"		)
									self.assertListEqual(_snake_case   , ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"]		)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case		)   , [3, 12, 10, 14, 4, 9, 12, 10, 14]		)



					def 			lowerCAmelCase_					(						self			:				int		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class(self.vocab_file   , word_tokenizer_type="mecab"		)
									self.assertIsNotNone(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				"こんにちは、世界。\nこんばんは、世界。"
									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize(_snake_case		)
									self.assertListEqual(_snake_case   , ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"]		)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case		)   , [3, 12, 10, 14, 4, 9, 12, 10, 14]		)

									SCREAMING_SNAKE_CASE__		  =				os.path.join(self.tmpdirname   , "tokenizer.bin"		)
									with open(_snake_case   , "wb"		) as handle:
													pickle.dump(_snake_case   , _snake_case		)

									with open(_snake_case   , "rb"		) as handle:
													SCREAMING_SNAKE_CASE__		  =				pickle.load(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer_new.tokenize(_snake_case		)

									self.assertListEqual(_snake_case   , _snake_case		)



					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(mecab_dic="ipadic"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップルストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       Optional[Any]:
									try:
													SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(mecab_dic="unidic_lite"		)
									except ModuleNotFoundError:
													return

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       Any:
									try:
													SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(mecab_dic="unidic"		)
									except ModuleNotFoundError:
													return

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       str:
									SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(do_lower_case=_snake_case   , mecab_dic="ipadic"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップルストア", "で", "iphone", "8", "が", "発売", "さ", "れ", "た", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       str:
									try:
													SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(
													    do_lower_case=_snake_case   , normalize_text=_snake_case   , mecab_option="-d /usr/local/lib/mecab/dic/jumandic"		)
									except RuntimeError:
													# if dict doesn't exist in the system, previous code raises this error.
													return

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れた", "\u3000", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				Optional[int]		)							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				MecabTokenizer(normalize_text=_snake_case   , mecab_dic="ipadic"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れ", "た", "　", "。"]   , )



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				Any		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class(self.vocab_file   , word_tokenizer_type="sudachi"		)
									self.assertIsNotNone(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				"こんにちは、世界。\nこんばんは、世界。"
									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize(_snake_case		)
									self.assertListEqual(_snake_case   , ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"]		)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case		)   , [3, 12, 10, 14, 4, 9, 12, 10, 14]		)

									SCREAMING_SNAKE_CASE__		  =				os.path.join(self.tmpdirname   , "tokenizer.bin"		)
									with open(_snake_case   , "wb"		) as handle:
													pickle.dump(_snake_case   , _snake_case		)

									with open(_snake_case   , "rb"		) as handle:
													SCREAMING_SNAKE_CASE__		  =				pickle.load(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer_new.tokenize(_snake_case		)

									self.assertListEqual(_snake_case   , _snake_case		)



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				str		)							->       str:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(sudachi_dict_type="core"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , [" ", "\t", "アップル", "ストア", "で", "iPhone", "8", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", " ", "。", " ", " "]   , )



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				str		)							->       Dict:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(sudachi_dict_type="core"   , sudachi_split_mode="A"		)

									self.assertListEqual(tokenizer.tokenize("外国人参政権"		)   , ["外国", "人", "参政", "権"]		)



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				str		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(sudachi_dict_type="core"   , sudachi_split_mode="B"		)

									self.assertListEqual(tokenizer.tokenize("外国人参政権"		)   , ["外国人", "参政権"]		)



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(sudachi_dict_type="core"   , sudachi_split_mode="C"		)

									self.assertListEqual(tokenizer.tokenize("外国人参政権"		)   , ["外国人参政権"]		)



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				List[str]		)							->       Union[str, Any]:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(do_lower_case=_snake_case   , sudachi_dict_type="core"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , [" ", "\t", "アップル", "ストア", "で", "iphone", "8", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", " ", "。", " ", " "]   , )



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				int		)							->       Union[str, Any]:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(normalize_text=_snake_case   , sudachi_dict_type="core"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , [" ", "\t", "ｱｯﾌﾟﾙ", "ストア", "で", "iPhone", "８", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", "\u3000", "。", " ", " "]   , )



					@require_sudachi
					def 			lowerCAmelCase_					(						self			:				Dict		)							->       int:
									SCREAMING_SNAKE_CASE__		  =				SudachiTokenizer(trim_whitespace=_snake_case   , sudachi_dict_type="core"		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]   , )



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       Optional[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class(self.vocab_file   , word_tokenizer_type="jumanpp"		)
									self.assertIsNotNone(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				"こんにちは、世界。\nこんばんは、世界。"
									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize(_snake_case		)
									self.assertListEqual(_snake_case   , ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"]		)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case		)   , [3, 12, 10, 14, 4, 9, 12, 10, 14]		)

									SCREAMING_SNAKE_CASE__		  =				os.path.join(self.tmpdirname   , "tokenizer.bin"		)
									with open(_snake_case   , "wb"		) as handle:
													pickle.dump(_snake_case   , _snake_case		)

									with open(_snake_case   , "rb"		) as handle:
													SCREAMING_SNAKE_CASE__		  =				pickle.load(_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer_new.tokenize(_snake_case		)

									self.assertListEqual(_snake_case   , _snake_case		)



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				JumanppTokenizer()

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iPhone", "8", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]   , )



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				Union[str, Any]		)							->       str:
									SCREAMING_SNAKE_CASE__		  =				JumanppTokenizer(do_lower_case=_snake_case		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iphone", "8", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]   , )



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				int		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				JumanppTokenizer(normalize_text=_snake_case		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["ｱ", "ｯ", "ﾌ", "ﾟ", "ﾙ", "ストア", "で", "iPhone", "８", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]   , )



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				Any		)							->       Dict:
									SCREAMING_SNAKE_CASE__		  =				JumanppTokenizer(trim_whitespace=_snake_case		)

									self.assertListEqual(
									    tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "		)   , ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れた", "。"]   , )



					@require_jumanpp
					def 			lowerCAmelCase_					(						self			:				Optional[int]		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				JumanppTokenizer()

									self.assertListEqual(
									    tokenizer.tokenize("ありがとうございますm(_ _)ｍ見つけるのが大変です。"		)   , ["ありがとう", "ございます", "m(_ _)m", "見つける", "の", "が", "大変です", "。"]   , )



					def 			lowerCAmelCase_					(						self			:				Any		)							->       Dict:
									SCREAMING_SNAKE_CASE__		  =				["[UNK]", "[CLS]", "[SEP]", "こんにちは", "こん", "にちは", "ばんは", "##こん", "##にちは", "##ばんは"]

									SCREAMING_SNAKE_CASE__		  =				{}
									for i, token in enumerate(_snake_case		):
													SCREAMING_SNAKE_CASE__		  =				i
									SCREAMING_SNAKE_CASE__		  =				WordpieceTokenizer(vocab=_snake_case   , unk_token="[UNK]"		)

									self.assertListEqual(tokenizer.tokenize(""		)   , []		)

									self.assertListEqual(tokenizer.tokenize("こんにちは"		)   , ["こんにちは"]		)

									self.assertListEqual(tokenizer.tokenize("こんばんは"		)   , ["こん", "##ばんは"]		)

									self.assertListEqual(tokenizer.tokenize("こんばんは こんばんにちは こんにちは"		)   , ["こん", "##ばんは", "[UNK]", "こんにちは"]		)



					def 			lowerCAmelCase_					(						self			:				List[Any]		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				BertJapaneseTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese-with-auto-jumanpp"		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.subword_tokenizer

									SCREAMING_SNAKE_CASE__		  =				subword_tokenizer.tokenize("国境 の 長い トンネル を 抜ける と 雪国 であった 。"		)
									self.assertListEqual(_snake_case   , ["▁国境", "▁の", "▁長い", "▁トンネル", "▁を", "▁抜ける", "▁と", "▁雪", "国", "▁であった", "▁。"]		)

									SCREAMING_SNAKE_CASE__		  =				subword_tokenizer.tokenize("こんばんは こんばん にち は こんにちは"		)
									self.assertListEqual(_snake_case   , ["▁こん", "ばん", "は", "▁こん", "ばん", "▁に", "ち", "▁は", "▁こんにちは"]		)



					def 			lowerCAmelCase_					(						self			:				Union[str, Any]		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese"		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.encode("ありがとう。"   , add_special_tokens=_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.encode("どういたしまして。"   , add_special_tokens=_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.build_inputs_with_special_tokens(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.build_inputs_with_special_tokens(_snake_case   , _snake_case		)

									# 2 is for "[CLS]", 3 is for "[SEP]"
									assert encoded_sentence == [2] + text + [3]
									assert encoded_pair == [2] + text + [3] + text_a + [3]



@custom_tokenizers
class lowerCamelCase		(_SCREAMING_SNAKE_CASE    ,    unittest.TestCase      ):






					'''simple docstring'''


					a   	=		BertJapaneseTokenizer
					a   	=		False



					def 			lowerCAmelCase_					(						self			:				Optional[Any]		)							->       int:
									super().setUp()

									SCREAMING_SNAKE_CASE__		  =				["[UNK]", "[CLS]", "[SEP]", "こ", "ん", "に", "ち", "は", "ば", "世", "界", "、", "。"]

									SCREAMING_SNAKE_CASE__		  =				os.path.join(self.tmpdirname   , VOCAB_FILES_NAMES["vocab_file"]		)
									with open(self.vocab_file   , "w"   , encoding="utf-8"		) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)



					def 			lowerCAmelCase_					(						self			:				Union[str, Any]   , **_snake_case			:				str		)							->       Optional[int]:
									return BertJapaneseTokenizer.from_pretrained(self.tmpdirname   , subword_tokenizer_type="character"   , **_snake_case		)



					def 			lowerCAmelCase_					(						self			:				str   , _snake_case			:				List[Any]		)							->       List[str]:
									SCREAMING_SNAKE_CASE__		  =				"こんにちは、世界。 \nこんばんは、世界。"
									SCREAMING_SNAKE_CASE__		  =				"こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"
									return input_text, output_text



					def 			lowerCAmelCase_					(						self			:				str		)							->       Any:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Optional[int]		)							->       Tuple:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Dict		)							->       List[str]:
									pass  # TODO add if relevant



					def 			lowerCAmelCase_					(						self			:				Any		)							->       List[Any]:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class(self.vocab_file   , subword_tokenizer_type="character"		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.tokenize("こんにちは、世界。 \nこんばんは、世界。"		)
									self.assertListEqual(
									    _snake_case   , ["こ", "ん", "に", "ち", "は", "、", "世", "界", "。", "こ", "ん", "ば", "ん", "は", "、", "世", "界", "。"]		)
									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(_snake_case		)   , [3, 4, 5, 6, 7, 11, 9, 10, 12, 3, 4, 8, 4, 7, 11, 9, 10, 12]		)



					def 			lowerCAmelCase_					(						self			:				str		)							->       List[str]:
									SCREAMING_SNAKE_CASE__		  =				["[UNK]", "[CLS]", "[SEP]", "こ", "ん", "に", "ち", "は", "ば", "世", "界", "、", "。"]

									SCREAMING_SNAKE_CASE__		  =				{}
									for i, token in enumerate(_snake_case		):
													SCREAMING_SNAKE_CASE__		  =				i
									SCREAMING_SNAKE_CASE__		  =				CharacterTokenizer(vocab=_snake_case   , unk_token="[UNK]"		)

									self.assertListEqual(tokenizer.tokenize(""		)   , []		)

									self.assertListEqual(tokenizer.tokenize("こんにちは"		)   , ["こ", "ん", "に", "ち", "は"]		)

									self.assertListEqual(tokenizer.tokenize("こんにちほ"		)   , ["こ", "ん", "に", "ち", "[UNK]"]		)



					def 			lowerCAmelCase_					(						self			:				Union[str, Any]		)							->       int:
									SCREAMING_SNAKE_CASE__		  =				self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese-char"		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.encode("ありがとう。"   , add_special_tokens=_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.encode("どういたしまして。"   , add_special_tokens=_snake_case		)

									SCREAMING_SNAKE_CASE__		  =				tokenizer.build_inputs_with_special_tokens(_snake_case		)
									SCREAMING_SNAKE_CASE__		  =				tokenizer.build_inputs_with_special_tokens(_snake_case   , _snake_case		)

									# 2 is for "[CLS]", 3 is for "[SEP]"
									assert encoded_sentence == [2] + text + [3]
									assert encoded_pair == [2] + text + [3] + text_a + [3]



@custom_tokenizers
class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					def 			lowerCAmelCase_					(						self			:				Any		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				"cl-tohoku/bert-base-japanese"
									SCREAMING_SNAKE_CASE__		  =				AutoTokenizer.from_pretrained(_snake_case		)
									self.assertIsInstance(_snake_case   , _snake_case		)



class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					def 			lowerCAmelCase_					(						self			:				str		)							->       Tuple:
									SCREAMING_SNAKE_CASE__		  =				"cl-tohoku/bert-base-japanese"
									with self.assertLogs("transformers"   , level="WARNING"		) as cm:
													BertTokenizer.from_pretrained(_snake_case		)
													self.assertTrue(
													    cm.records[0].message.startswith(
													        "The tokenizer class you load from this checkpoint is not the same type as the class this function"
													        " is called from."		)		)
									SCREAMING_SNAKE_CASE__		  =				"bert-base-cased"
									with self.assertLogs("transformers"   , level="WARNING"		) as cm:
													BertJapaneseTokenizer.from_pretrained(_snake_case		)
													self.assertTrue(
													    cm.records[0].message.startswith(
													        "The tokenizer class you load from this checkpoint is not the same type as the class this function"
													        " is called from."		)		)





"""simple docstring"""






import argparse

from torch import nn

# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
    ProphetNetForConditionalGeneration as ProphetNetForConditionalGenerationOld,
)
from transformers_old.modeling_xlm_prophetnet import (
    XLMProphetNetForConditionalGeneration as XLMProphetNetForConditionalGenerationOld,
)

from transformers import ProphetNetForConditionalGeneration, XLMProphetNetForConditionalGeneration, logging


_A   					=    logging.get_logger(__name__)
logging.set_verbosity_info()




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase       )							->   List[str]:
				if "xprophetnet" in prophetnet_checkpoint_path:
								SCREAMING_SNAKE_CASE__		  =				XLMProphetNetForConditionalGenerationOld.from_pretrained(__UpperCAmelCase       )
								SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				XLMProphetNetForConditionalGeneration.from_pretrained(
								    __UpperCAmelCase  ,					output_loading_info=__UpperCAmelCase       )
				else:
								SCREAMING_SNAKE_CASE__		  =				ProphetNetForConditionalGenerationOld.from_pretrained(__UpperCAmelCase       )
								SCREAMING_SNAKE_CASE__  ,       SCREAMING_SNAKE_CASE__		  =				ProphetNetForConditionalGeneration.from_pretrained(
								    __UpperCAmelCase  ,					output_loading_info=__UpperCAmelCase       )

				SCREAMING_SNAKE_CASE__		  =				["key_proj", "value_proj", "query_proj"]

				SCREAMING_SNAKE_CASE__		  =				{
				    "self_attn": "ngram_self_attn",
				    "cross_attn": "encoder_attn",
				    "cross_attn_layer_norm": "encoder_attn_layer_norm",
				    "feed_forward_layer_norm": "final_layer_norm",
				    "feed_forward": "",
				    "intermediate": "fc1",
				    "output": "fc2",
				    "key_proj": "k_proj",
				    "query_proj": "q_proj",
				    "value_proj": "v_proj",
				    "word_embeddings": "embed_tokens",
				    "embeddings_layer_norm": "emb_layer_norm",
				    "relative_pos_embeddings": "relative_linear",
				    "ngram_embeddings": "ngram_input_embed",
				    "position_embeddings": "embed_positions",
				}

				for key in loading_info["missing_keys"]:
								SCREAMING_SNAKE_CASE__		  =				key.split("."       )

								if attributes[0] == "lm_head":
												SCREAMING_SNAKE_CASE__		  =				prophet
												SCREAMING_SNAKE_CASE__		  =				prophet_old
								else:
												SCREAMING_SNAKE_CASE__		  =				prophet.prophetnet
												SCREAMING_SNAKE_CASE__		  =				prophet_old.model

								SCREAMING_SNAKE_CASE__		  =				False
								for attribute in attributes:
												if attribute in mapping:
																SCREAMING_SNAKE_CASE__		  =				mapping[attribute]
																if not hasattr(__UpperCAmelCase  ,					__UpperCAmelCase       ) and len(__UpperCAmelCase       ) > 0:
																				SCREAMING_SNAKE_CASE__		  =				attribute
												elif hasattr(__UpperCAmelCase  ,					__UpperCAmelCase       ):
																SCREAMING_SNAKE_CASE__		  =				attribute

												if attribute == "weight":
																assert old_model.weight.shape == model.weight.shape, "Shapes have to match!"
																SCREAMING_SNAKE_CASE__		  =				old_model.weight
																logger.info(F"""{attribute} is initialized."""       )
																SCREAMING_SNAKE_CASE__		  =				True
																break
												elif attribute == "bias":
																assert old_model.bias.shape == model.bias.shape, "Shapes have to match!"
																SCREAMING_SNAKE_CASE__		  =				old_model.bias
																logger.info(F"""{attribute} is initialized"""       )
																SCREAMING_SNAKE_CASE__		  =				True
																break
												elif attribute in special_keys and hasattr(__UpperCAmelCase  ,					"in_proj_weight"       ):
																SCREAMING_SNAKE_CASE__		  =				old_model.in_proj_weight.shape[0] // 3
																SCREAMING_SNAKE_CASE__		  =				getattr(__UpperCAmelCase  ,					__UpperCAmelCase       )
																param.weight.shape == old_model.in_proj_weight[:embed_dim, :].shape, "Shapes have to match"
																param.bias.shape == old_model.in_proj_bias[:embed_dim].shape, "Shapes have to match"
																if attribute == "query_proj":
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_weight[:embed_dim, :]       )
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_bias[:embed_dim]       )

																elif attribute == "key_proj":
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_weight[embed_dim : 2 * embed_dim, :]       )
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_bias[embed_dim : 2 * embed_dim]       )
																elif attribute == "value_proj":
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_weight[2 * embed_dim :, :]       )
																				SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.in_proj_bias[2 * embed_dim :]       )
																SCREAMING_SNAKE_CASE__		  =				True
																break
												elif attribute == "position_embeddings":
																assert (
																    model.position_embeddings.weight.shape[-1] == old_model.embed_positions.weight.shape[-1]
																), "Hidden size has to match"
																assert model.position_embeddings.weight.shape[0] == 512, "We want 512 position_embeddings."
																SCREAMING_SNAKE_CASE__		  =				nn.Parameter(old_model.embed_positions.weight[:512, :]       )
																SCREAMING_SNAKE_CASE__		  =				True
																break

												if attribute.isdigit():
																SCREAMING_SNAKE_CASE__		  =				model[int(__UpperCAmelCase       )]
																SCREAMING_SNAKE_CASE__		  =				old_model[int(__UpperCAmelCase       )]
												else:
																SCREAMING_SNAKE_CASE__		  =				getattr(__UpperCAmelCase  ,					__UpperCAmelCase       )

																if old_attribute == "":
																				SCREAMING_SNAKE_CASE__		  =				old_model
																else:
																				if not hasattr(__UpperCAmelCase  ,					__UpperCAmelCase       ):
																								raise ValueError(F"""{old_model} does not have {old_attribute}"""       )
																				SCREAMING_SNAKE_CASE__		  =				getattr(__UpperCAmelCase  ,					__UpperCAmelCase       )

								if not is_key_init:
												raise ValueError(F"""{key} was not correctly initialized!"""       )

				print(F"""Saving model to {pytorch_dump_folder_path}"""       )
				prophet.save_pretrained(__UpperCAmelCase       )


if __name__ == "__main__":
						_A   					=    argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    '--prophetnet_checkpoint_path', default=None, type=str, required=True, help='Path the official PyTorch dump.'
						)
						parser.add_argument(
						    '--pytorch_dump_folder_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
						)
						_A   					=    parser.parse_args()
						convert_prophetnet_checkpoint_to_pytorch(args.prophetnet_checkpoint_path, args.pytorch_dump_folder_path)




