


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 						_UpperCAmelCase      (     _SCREAMING_SNAKE_CASE		,		unittest.TestCase							):
		lowerCamelCase_	:			Union[str, Any]       			=  BertJapaneseTokenizer
		lowerCamelCase_	:			Dict       			=  False
		lowerCamelCase_	:			Dict       			=  True






		def _snake_case		(						self				:     List[Any]):
				super().setUp()

				SCREAMING_SNAKE_CASE_				:int				     =						[
				    """[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_				:Tuple				     =						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 _snake_case		(						self				:     Optional[int]   ,  UpperCAmelCase				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:str				     =						"""こんにちは、世界。 \nこんばんは、世界。"""
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						"""こんにちは 、 世界 。 こんばんは 、 世界 。"""
				return input_text, output_text






		def _snake_case		(						self				:     Union[str, Any]   ,  UpperCAmelCase				:     List[str]):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						self.get_input_output_texts(UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:Tuple				     =						tokenizer.encode(UpperCAmelCase   ,  add_special_tokens=UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:str				     =						tokenizer.decode(UpperCAmelCase   ,  clean_up_tokenization_spaces=UpperCAmelCase)
				return text, ids






		def _snake_case		(						self				:     List[Any]):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     Any):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     List[Any]):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Dict				     =						self.tokenizer_class(self.vocab_file)

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






		def _snake_case		(						self				:     Union[str, Any]):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						self.tokenizer_class(self.vocab_file   ,  word_tokenizer_type="mecab")
				self.assertIsNotNone(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:List[Any]				     =						"""こんにちは、世界。\nこんばんは、世界。"""
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						tokenizer.tokenize(UpperCAmelCase)
				self.assertListEqual(UpperCAmelCase   ,  ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase)   ,  [3, 12, 10, 14, 4, 9, 12, 10, 14])

				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						os.path.join(self.tmpdirname   ,  "tokenizer.bin")
				with open(UpperCAmelCase   ,  "wb") as handle:
						pickle.dump(UpperCAmelCase   ,  UpperCAmelCase)

				with open(UpperCAmelCase   ,  "rb") as handle:
						SCREAMING_SNAKE_CASE_				:Any				     =						pickle.load(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:int				     =						tokenizer_new.tokenize(UpperCAmelCase)

				self.assertListEqual(UpperCAmelCase   ,  UpperCAmelCase)






		def _snake_case		(						self				:     int):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						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 _snake_case		(						self				:     List[str]):
				try:
						SCREAMING_SNAKE_CASE_				:int				     =						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 _snake_case		(						self				:     Optional[Any]):
				try:
						SCREAMING_SNAKE_CASE_				:Dict				     =						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 _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Dict				     =						MecabTokenizer(do_lower_case=UpperCAmelCase   ,  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 _snake_case		(						self				:     Tuple):
				try:
						SCREAMING_SNAKE_CASE_				:Any				     =						MecabTokenizer(
						    do_lower_case=UpperCAmelCase   ,  normalize_text=UpperCAmelCase   ,  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 _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Any				     =						MecabTokenizer(normalize_text=UpperCAmelCase   ,  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 _snake_case		(						self				:     List[Any]):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						self.tokenizer_class(self.vocab_file   ,  word_tokenizer_type="sudachi")
				self.assertIsNotNone(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						"""こんにちは、世界。\nこんばんは、世界。"""
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						tokenizer.tokenize(UpperCAmelCase)
				self.assertListEqual(UpperCAmelCase   ,  ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase)   ,  [3, 12, 10, 14, 4, 9, 12, 10, 14])

				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						os.path.join(self.tmpdirname   ,  "tokenizer.bin")
				with open(UpperCAmelCase   ,  "wb") as handle:
						pickle.dump(UpperCAmelCase   ,  UpperCAmelCase)

				with open(UpperCAmelCase   ,  "rb") as handle:
						SCREAMING_SNAKE_CASE_				:str				     =						pickle.load(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:List[Any]				     =						tokenizer_new.tokenize(UpperCAmelCase)

				self.assertListEqual(UpperCAmelCase   ,  UpperCAmelCase)






		@require_sudachi
		def _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						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 _snake_case		(						self				:     Union[str, Any]):
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						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 _snake_case		(						self				:     Union[str, Any]):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						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 _snake_case		(						self				:     List[str]):
				SCREAMING_SNAKE_CASE_				:int				     =						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 _snake_case		(						self				:     Any):
				SCREAMING_SNAKE_CASE_				:Dict				     =						SudachiTokenizer(do_lower_case=UpperCAmelCase   ,  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 _snake_case		(						self				:     List[Any]):
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						SudachiTokenizer(normalize_text=UpperCAmelCase   ,  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 _snake_case		(						self				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:Any				     =						SudachiTokenizer(trim_whitespace=UpperCAmelCase   ,  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 _snake_case		(						self				:     Any):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer_class(self.vocab_file   ,  word_tokenizer_type="jumanpp")
				self.assertIsNotNone(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:List[Any]				     =						"""こんにちは、世界。\nこんばんは、世界。"""
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						tokenizer.tokenize(UpperCAmelCase)
				self.assertListEqual(UpperCAmelCase   ,  ["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase)   ,  [3, 12, 10, 14, 4, 9, 12, 10, 14])

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

				with open(UpperCAmelCase   ,  "rb") as handle:
						SCREAMING_SNAKE_CASE_				:Tuple				     =						pickle.load(UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:List[str]				     =						tokenizer_new.tokenize(UpperCAmelCase)

				self.assertListEqual(UpperCAmelCase   ,  UpperCAmelCase)






		@require_jumanpp
		def _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						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 _snake_case		(						self				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:List[str]				     =						JumanppTokenizer(do_lower_case=UpperCAmelCase)

				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 _snake_case		(						self				:     int):
				SCREAMING_SNAKE_CASE_				:Dict				     =						JumanppTokenizer(normalize_text=UpperCAmelCase)

				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 _snake_case		(						self				:     Tuple):
				SCREAMING_SNAKE_CASE_				:Any				     =						JumanppTokenizer(trim_whitespace=UpperCAmelCase)

				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 _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:int				     =						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 _snake_case		(						self				:     int):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						["""[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_				:Optional[int]				     =						{}
				for i, token in enumerate(UpperCAmelCase):
						SCREAMING_SNAKE_CASE_				:int				     =						i
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						WordpieceTokenizer(vocab=UpperCAmelCase   ,  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 _snake_case		(						self				:     str):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						BertJapaneseTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese-with-auto-jumanpp")
				SCREAMING_SNAKE_CASE_				:Tuple				     =						tokenizer.subword_tokenizer

				SCREAMING_SNAKE_CASE_				:Any				     =						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(UpperCAmelCase   ,  ["▁国境", "▁の", "▁長い", "▁トンネル", "▁を", "▁抜ける", "▁と", "▁雪", "国", "▁であった", "▁。"])

				SCREAMING_SNAKE_CASE_				:List[str]				     =						subword_tokenizer.tokenize("こんばんは こんばん にち は こんにちは")
				self.assertListEqual(UpperCAmelCase   ,  ["▁こん", "ばん", "は", "▁こん", "ばん", "▁に", "ち", "▁は", "▁こんにちは"])







		def _snake_case		(						self				:     str):
				SCREAMING_SNAKE_CASE_				:str				     =						self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese")

				SCREAMING_SNAKE_CASE_				:int				     =						tokenizer.encode("ありがとう。"   ,  add_special_tokens=UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:str				     =						tokenizer.encode("どういたしまして。"   ,  add_special_tokens=UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:Any				     =						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase   ,  UpperCAmelCase)

				# 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 						_UpperCAmelCase      (     _SCREAMING_SNAKE_CASE		,		unittest.TestCase							):
		lowerCamelCase_	:			Any       			=  BertJapaneseTokenizer
		lowerCamelCase_	:			Optional[Any]       			=  False






		def _snake_case		(						self				:     List[Any]):
				super().setUp()

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

				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						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 _snake_case		(						self				:     List[str]   ,  **UpperCAmelCase				:     Dict):
				return BertJapaneseTokenizer.from_pretrained(self.tmpdirname   ,  subword_tokenizer_type="character"   ,  **UpperCAmelCase)






		def _snake_case		(						self				:     str   ,  UpperCAmelCase				:     Optional[int]):
				SCREAMING_SNAKE_CASE_				:Dict				     =						"""こんにちは、世界。 \nこんばんは、世界。"""
				SCREAMING_SNAKE_CASE_				:Dict				     =						"""こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"""
				return input_text, output_text






		def _snake_case		(						self				:     Tuple):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     Dict):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     List[str]):
				pass  # TODO add if relevant






		def _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						self.tokenizer_class(self.vocab_file   ,  subword_tokenizer_type="character")

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






		def _snake_case		(						self				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						["""[UNK]""", """[CLS]""", """[SEP]""", """こ""", """ん""", """に""", """ち""", """は""", """ば""", """世""", """界""", """、""", """。"""]

				SCREAMING_SNAKE_CASE_				:Tuple				     =						{}
				for i, token in enumerate(UpperCAmelCase):
						SCREAMING_SNAKE_CASE_				:Dict				     =						i
				SCREAMING_SNAKE_CASE_				:Dict				     =						CharacterTokenizer(vocab=UpperCAmelCase   ,  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 _snake_case		(						self				:     Optional[int]):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese-char")

				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer.encode("ありがとう。"   ,  add_special_tokens=UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						tokenizer.encode("どういたしまして。"   ,  add_special_tokens=UpperCAmelCase)

				SCREAMING_SNAKE_CASE_				:int				     =						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase)
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase   ,  UpperCAmelCase)

				# 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 						_UpperCAmelCase      (     unittest.TestCase							):






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




class 						_UpperCAmelCase      (     unittest.TestCase							):






		def _snake_case		(						self				:     str):
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						"""cl-tohoku/bert-base-japanese"""
				with self.assertLogs("transformers"   ,  level="WARNING") as cm:
						BertTokenizer.from_pretrained(UpperCAmelCase)
						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_				:Optional[Any]				     =						"""bert-base-cased"""
				with self.assertLogs("transformers"   ,  level="WARNING") as cm:
						BertJapaneseTokenizer.from_pretrained(UpperCAmelCase)
						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

import torch

from transformers import (
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
    WavaVecaForAudioFrameClassification,
    WavaVecaForSequenceClassification,
    WavaVecaForXVector,
    logging,
)


logging.set_verbosity_info()
__A   :    str											= logging.get_logger(__name__)







def 							UpperCamelCase_     (       A__   :  int				,       A__   :  List[Any]				,       A__   :  List[str]   ):
  '''simple docstring'''





  lowerCAmelCase_     : Dict     =  WavaVecaForSequenceClassification.from_pretrained(A__				,       config=A__   )
  lowerCAmelCase_     : str     =  downstream_dict["""projector.weight"""]
  lowerCAmelCase_     : Tuple     =  downstream_dict["""projector.bias"""]
  lowerCAmelCase_     : Tuple     =  downstream_dict["""model.post_net.linear.weight"""]
  lowerCAmelCase_     : Dict     =  downstream_dict["""model.post_net.linear.bias"""]
  return model







def 							UpperCamelCase_     (       A__   :  Dict				,       A__   :  Any				,       A__   :  List[Any]   ):
  '''simple docstring'''





  lowerCAmelCase_     : Optional[int]     =  WavaVecaForAudioFrameClassification.from_pretrained(A__				,       config=A__   )
  lowerCAmelCase_     : Dict     =  downstream_dict["""model.linear.weight"""]
  lowerCAmelCase_     : List[str]     =  downstream_dict["""model.linear.bias"""]
  return model







def 							UpperCamelCase_     (       A__   :  List[str]				,       A__   :  Any				,       A__   :  int   ):
  '''simple docstring'''





  lowerCAmelCase_     : Optional[Any]     =  WavaVecaForXVector.from_pretrained(A__				,       config=A__   )
  lowerCAmelCase_     : List[Any]     =  downstream_dict["""connector.weight"""]
  lowerCAmelCase_     : Union[str, Any]     =  downstream_dict["""connector.bias"""]
  for i, kernel_size in enumerate(hf_config.tdnn_kernel   ):
    lowerCAmelCase_     : List[str]     =  downstream_dict[
        f'model.framelevel_feature_extractor.module.{i}.kernel.weight'
    ]
    lowerCAmelCase_     : List[str]     =  downstream_dict[f'model.framelevel_feature_extractor.module.{i}.kernel.bias']

  lowerCAmelCase_     : Optional[int]     =  downstream_dict["""model.utterancelevel_feature_extractor.linear1.weight"""]
  lowerCAmelCase_     : Optional[int]     =  downstream_dict["""model.utterancelevel_feature_extractor.linear1.bias"""]
  lowerCAmelCase_     : Union[str, Any]     =  downstream_dict["""model.utterancelevel_feature_extractor.linear2.weight"""]
  lowerCAmelCase_     : Dict     =  downstream_dict["""model.utterancelevel_feature_extractor.linear2.bias"""]
  lowerCAmelCase_     : int     =  downstream_dict["""objective.W"""]
  return model







@torch.no_grad()
def 							UpperCamelCase_     (       A__   :  int				,       A__   :  int				,       A__   :  str				,       A__   :  Union[str, Any]   ):
  '''simple docstring'''





  lowerCAmelCase_     : Tuple     =  torch.load(A__				,       map_location="""cpu"""   )

  lowerCAmelCase_     : Optional[int]     =  checkpoint["""Downstream"""]

  lowerCAmelCase_     : int     =  WavaVecaConfig.from_pretrained(A__   )
  lowerCAmelCase_     : Union[str, Any]     =  WavaVecaFeatureExtractor.from_pretrained(
      A__				,       return_attention_mask=A__				,       do_normalize=A__   )

  lowerCAmelCase_     : Optional[int]     =  hf_config.architectures[0]
  if arch.endswith("""ForSequenceClassification"""   ):
    lowerCAmelCase_     : List[str]     =  convert_classification(A__				,       A__				,       A__   )
  elif arch.endswith("""ForAudioFrameClassification"""   ):
    lowerCAmelCase_     : Dict     =  convert_diarization(A__				,       A__				,       A__   )
  elif arch.endswith("""ForXVector"""   ):
    lowerCAmelCase_     : List[Any]     =  convert_xvector(A__				,       A__				,       A__   )
  else:
    raise NotImplementedError(f'S3PRL weights conversion is not supported for {arch}'   )

  if hf_config.use_weighted_layer_sum:
    lowerCAmelCase_     : Optional[int]     =  checkpoint["""Featurizer"""]["""weights"""]

  hf_feature_extractor.save_pretrained(A__   )
  hf_model.save_pretrained(A__   )


if __name__ == "__main__":
  __A   :    List[Any]											= argparse.ArgumentParser()
  parser.add_argument(
      "--base_model_name", default=None, type=str, help="Name of the huggingface pretrained base model."
  )
  parser.add_argument("--config_path", default=None, type=str, help="Path to the huggingface classifier config.")
  parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to the s3prl checkpoint.")
  parser.add_argument("--model_dump_path", default=None, type=str, help="Path to the final converted model.")
  __A   :    Tuple											= parser.parse_args()
  convert_saprl_checkpoint(args.base_model_name, args.config_path, args.checkpoint_path, args.model_dump_path)



