
import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     GPTSanJapaneseTokenizer
					SCREAMING_SNAKE_CASE           =     False
					SCREAMING_SNAKE_CASE           =     {'''do_clean_text''': False, '''add_prefix_space''': False}

					def  lowercase__   (						self       :  List[str] ):
												super().setUp()

												# fmt: off
												lowerCamelCase_					=       ["""こん""", """こんに""", """にちは""", """ばんは""", """世界,㔺界""", """、""", """。""", """<BR>""", """<SP>""", """<TAB>""", """<URL>""", """<EMAIL>""", """<TEL>""", """<DATE>""", """<PRICE>""", """<BLOCK>""", """<KIGOU>""", """<U2000U2BFF>""", """<|emoji1|>""", """<unk>""", """<|bagoftoken|>""", """<|endoftext|>"""]
												# fmt: on
												lowerCamelCase_					=       {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
												lowerCamelCase_					=       {"""unk_token""": """<unk>"""}

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

					def  lowercase__   (						self       :  Dict ,       **__UpperCamelCase       :  int ):
												kwargs.update(self.special_tokens_map )
												return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  List[str] ,       __UpperCamelCase       :  str ):
												lowerCamelCase_					=       """こんにちは、世界。 \nこんばんは、㔺界。😀"""
												lowerCamelCase_					=       """こんにちは、世界。 \nこんばんは、世界。😀"""
												return input_text, output_text

					def  lowercase__   (						self       :  str ,       __UpperCamelCase       :  Optional[int] ):
												lowerCamelCase_	, lowerCamelCase_					=       self.get_input_output_texts(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase ,       clean_up_tokenization_spaces=__UpperCamelCase )
												return text, ids

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

					def  lowercase__   (						self       :  Union[str, Any] ):
												pass  # TODO add if relevant

					def  lowercase__   (						self       :  Union[str, Any] ):
												pass  # TODO add if relevant

					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       self.get_tokenizer()

												# Testing tokenization
												lowerCamelCase_					=       """こんにちは、世界。　こんばんは、㔺界。"""
												lowerCamelCase_					=       ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
												lowerCamelCase_					=       tokenizer.tokenize(__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												# Testing conversion to ids without special tokens
												lowerCamelCase_					=       [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
												lowerCamelCase_					=       tokenizer.convert_tokens_to_ids(__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												# Testing conversion to ids with special tokens
												lowerCamelCase_					=       tokens + [tokenizer.unk_token]
												lowerCamelCase_					=       [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 1_9]
												lowerCamelCase_					=       tokenizer.convert_tokens_to_ids(__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       self.get_tokenizer()

												# Testing tokenization
												lowerCamelCase_					=       """こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"""
												lowerCamelCase_					=       """こんにちは、、、、世界。こんばんは、、、、世界。"""
												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )

					@slow
					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese""" )

												# Testing tokenization
												lowerCamelCase_					=       """こんにちは、世界。"""
												lowerCamelCase_					=       """こんばんは、㔺界。😀"""
												lowerCamelCase_					=       """こんにちは、世界。こんばんは、世界。😀"""
												lowerCamelCase_					=       tokenizer.encode(prefix_text + input_text )
												lowerCamelCase_					=       tokenizer.encode("""""" ,       prefix_text=prefix_text + input_text )
												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase ,       prefix_text=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )

					@slow
					def  lowercase__   (						self       :  List[Any] ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese""" )

												# Testing tokenization
												lowerCamelCase_					=       """こんにちは、世界。"""
												lowerCamelCase_					=       """こんばんは、㔺界。😀"""

												lowerCamelCase_					=       len(tokenizer.encode(__UpperCamelCase ) ) - 2
												lowerCamelCase_					=       len(tokenizer.encode(__UpperCamelCase ) ) - 2

												lowerCamelCase_					=       [1] + [0] * (len_prefix + len_text + 1)
												lowerCamelCase_					=       [1] * (len_prefix + len_text + 1) + [0]
												lowerCamelCase_					=       [1] + [1] * (len_prefix) + [0] * (len_text + 1)

												lowerCamelCase_					=       tokenizer(prefix_text + input_text ).token_type_ids
												lowerCamelCase_					=       tokenizer("""""" ,       prefix_text=prefix_text + input_text ).token_type_ids
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       prefix_text=__UpperCamelCase ).token_type_ids
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

					@slow
					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese""" )

												lowerCamelCase_					=       tokenizer.encode("""あンいワ""" )
												lowerCamelCase_					=       tokenizer.encode("""""" ,       prefix_text="""あンいワ""" )
												lowerCamelCase_					=       tokenizer.encode("""いワ""" ,       prefix_text="""あン""" )

												self.assertEqual(tokenizer.decode(__UpperCamelCase ) ,       tokenizer.decode(__UpperCamelCase ) )
												self.assertEqual(tokenizer.decode(__UpperCamelCase ) ,       tokenizer.decode(__UpperCamelCase ) )
												self.assertNotEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertNotEqual(__UpperCamelCase ,       __UpperCamelCase )
												self.assertEqual(x_token_a[1] ,       x_token_a[-1] )  # SEG token
												self.assertEqual(x_token_a[1] ,       x_token_a[3] )  # SEG token

					@slow
					def  lowercase__   (						self       :  Tuple ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese""" )

												lowerCamelCase_					=       [["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.batch_encode_plus(__UpperCamelCase ,       padding=__UpperCamelCase )

												# fmt: off
												lowerCamelCase_					=       [[3_5_9_9_3, 8_6_4_0, 2_5_9_4_8, 3_5_9_9_8, 3_0_6_4_7, 3_5_6_7_5, 3_5_9_9_9, 3_5_9_9_9], [3_5_9_9_3, 1_0_3_8_2, 9_8_6_8, 3_5_9_9_8, 3_0_6_4_6, 9_4_5_9, 3_0_6_4_6, 3_5_6_7_5]]
												lowerCamelCase_					=       [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
												lowerCamelCase_					=       [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
												# fmt: on
												self.assertListEqual(x_token.input_ids ,       __UpperCamelCase )
												self.assertListEqual(x_token.token_type_ids ,       __UpperCamelCase )
												self.assertListEqual(x_token.attention_mask ,       __UpperCamelCase )
												self.assertListEqual(x_token_a.input_ids ,       __UpperCamelCase )
												self.assertListEqual(x_token_a.token_type_ids ,       __UpperCamelCase )
												self.assertListEqual(x_token_a.attention_mask ,       __UpperCamelCase )

					def  lowercase__   (						self       :  int ):
												# Intentionally convert some words to accommodate character fluctuations unique to Japanese
												pass



					def  lowercase__   (						self       :  List[Any] ):
												# tokenizer has no padding token
												pass







import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		lowercase   =	None


lowercase   =	logging.get_logger(__name__)


lowercase   =	{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase   =	{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

lowercase   =	{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
lowercase   =	['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']





class    __A(					UpperCAmelCase							):
					SCREAMING_SNAKE_CASE           =     VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE           =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE           =     PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE           =     ['''input_ids''', '''attention_mask''']
					SCREAMING_SNAKE_CASE           =     MBartTokenizer

					SCREAMING_SNAKE_CASE           =     []
					SCREAMING_SNAKE_CASE           =     []

					def __init__(						self       :  Any ,       __UpperCamelCase       :  Optional[int]=None ,       __UpperCamelCase       :  int=None ,       __UpperCamelCase       :  Dict="<s>" ,       __UpperCamelCase       :  Tuple="</s>" ,       __UpperCamelCase       :  Union[str, Any]="</s>" ,       __UpperCamelCase       :  Optional[Any]="<s>" ,       __UpperCamelCase       :  Optional[Any]="<unk>" ,       __UpperCamelCase       :  Dict="<pad>" ,       __UpperCamelCase       :  Dict="<mask>" ,       __UpperCamelCase       :  Any=None ,       __UpperCamelCase       :  Optional[int]=None ,       __UpperCamelCase       :  Optional[int]=None ,       **__UpperCamelCase       :  str ,       ):
												# Mask token behave like a normal word, i.e. include the space before it
												lowerCamelCase_					=       AddedToken(__UpperCamelCase ,       lstrip=__UpperCamelCase ,       rstrip=__UpperCamelCase ) if isinstance(__UpperCamelCase ,       __UpperCamelCase ) else mask_token

												super().__init__(
												    vocab_file=__UpperCamelCase ,       tokenizer_file=__UpperCamelCase ,       bos_token=__UpperCamelCase ,       eos_token=__UpperCamelCase ,       sep_token=__UpperCamelCase ,       cls_token=__UpperCamelCase ,       unk_token=__UpperCamelCase ,       pad_token=__UpperCamelCase ,       mask_token=__UpperCamelCase ,       src_lang=__UpperCamelCase ,       tgt_lang=__UpperCamelCase ,       additional_special_tokens=__UpperCamelCase ,       **__UpperCamelCase ,       )

												lowerCamelCase_					=       vocab_file
												lowerCamelCase_					=       False if not self.vocab_file else True

												lowerCamelCase_					=       FAIRSEQ_LANGUAGE_CODES.copy()

												if additional_special_tokens is not None:
																			# Only add those special tokens if they are not already there.
																			_additional_special_tokens.extend(
																			    [t for t in additional_special_tokens if t not in _additional_special_tokens] )

												self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens} )
												lowerCamelCase_					=       {
												    lang_code: self.convert_tokens_to_ids(__UpperCamelCase ) for lang_code in FAIRSEQ_LANGUAGE_CODES
												}

												lowerCamelCase_					=       src_lang if src_lang is not None else """en_XX"""
												lowerCamelCase_					=       self.convert_tokens_to_ids(self._src_lang )
												lowerCamelCase_					=       tgt_lang
												self.set_src_lang_special_tokens(self._src_lang )

					@property
					def  lowercase__   (						self       :  List[str] ):
												return self._src_lang

					@src_lang.setter
					def  lowercase__   (						self       :  Optional[int] ,       __UpperCamelCase       :  str ):
												lowerCamelCase_					=       new_src_lang
												self.set_src_lang_special_tokens(self._src_lang )

					def  lowercase__   (						self       :  Optional[int] ,       __UpperCamelCase       :  List[int] ,       __UpperCamelCase       :  Optional[List[int]] = None ):
												if token_ids_a is None:
																			return self.prefix_tokens + token_ids_a + self.suffix_tokens
												# We don't expect to process pairs, but leave the pair logic for API consistency
												return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens

					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  List[int] ,       __UpperCamelCase       :  Optional[List[int]] = None ):
												lowerCamelCase_					=       [self.sep_token_id]
												lowerCamelCase_					=       [self.cls_token_id]

												if token_ids_a is None:
																			return len(cls + token_ids_a + sep ) * [0]
												return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]

					def  lowercase__   (						self       :  int ,       __UpperCamelCase       :  Tuple ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Optional[str] ,       __UpperCamelCase       :  Optional[str] ,       **__UpperCamelCase       :  Dict ):
												if src_lang is None or tgt_lang is None:
																			raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model""" )
												lowerCamelCase_					=       src_lang
												lowerCamelCase_					=       self(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase ,       return_tensors=__UpperCamelCase ,       **__UpperCamelCase )
												lowerCamelCase_					=       self.convert_tokens_to_ids(__UpperCamelCase )
												lowerCamelCase_					=       tgt_lang_id
												return inputs

					def  lowercase__   (						self       :  Tuple ,       __UpperCamelCase       :  List[str] ,       __UpperCamelCase       :  str = "en_XX" ,       __UpperCamelCase       :  Optional[List[str]] = None ,       __UpperCamelCase       :  str = "ro_RO" ,       **__UpperCamelCase       :  Optional[int] ,       ):
												lowerCamelCase_					=       src_lang
												lowerCamelCase_					=       tgt_lang
												return super().prepare_seqaseq_batch(__UpperCamelCase ,       __UpperCamelCase ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  int ):
												return self.set_src_lang_special_tokens(self.src_lang )

					def  lowercase__   (						self       :  Dict ):
												return self.set_tgt_lang_special_tokens(self.tgt_lang )

					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  Dict ):
												lowerCamelCase_					=       self.convert_tokens_to_ids(__UpperCamelCase )
												lowerCamelCase_					=       []
												lowerCamelCase_					=       [self.eos_token_id, self.cur_lang_code]

												lowerCamelCase_					=       self.convert_ids_to_tokens(self.prefix_tokens )
												lowerCamelCase_					=       self.convert_ids_to_tokens(self.suffix_tokens )

												lowerCamelCase_					=       processors.TemplateProcessing(
												    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str ,       pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str ,       self.prefix_tokens + self.suffix_tokens ) ) ,       )

					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  str ):
												lowerCamelCase_					=       self.convert_tokens_to_ids(__UpperCamelCase )
												lowerCamelCase_					=       []
												lowerCamelCase_					=       [self.eos_token_id, self.cur_lang_code]

												lowerCamelCase_					=       self.convert_ids_to_tokens(self.prefix_tokens )
												lowerCamelCase_					=       self.convert_ids_to_tokens(self.suffix_tokens )

												lowerCamelCase_					=       processors.TemplateProcessing(
												    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str ,       pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str ,       self.prefix_tokens + self.suffix_tokens ) ) ,       )



					def  lowercase__   (						self       :  Tuple ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Optional[str] = None ):
												if not self.can_save_slow_tokenizer:
																			raise ValueError(
																			    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
																			    """tokenizer.""" )

												if not os.path.isdir(__UpperCamelCase ):
																			logger.error(F'''Vocabulary path ({save_directory}) should be a directory.''' )
																			return
												lowerCamelCase_					=       os.path.join(
												    __UpperCamelCase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

												if os.path.abspath(self.vocab_file ) != os.path.abspath(__UpperCamelCase ):
																			copyfile(self.vocab_file ,       __UpperCamelCase )

												return (out_vocab_file,)





