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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase_							=     logging.get_logger(__name__)

lowerCamelCase_							=     "▁"

lowerCamelCase_							=     {"vocab_file": "sentencepiece.bpe.model"}

lowerCamelCase_							=     {
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    }
}

lowerCamelCase_							=     {
    "xlm-roberta-base": 5_12,
    "xlm-roberta-large": 5_12,
    "xlm-roberta-large-finetuned-conll02-dutch": 5_12,
    "xlm-roberta-large-finetuned-conll02-spanish": 5_12,
    "xlm-roberta-large-finetuned-conll03-english": 5_12,
    "xlm-roberta-large-finetuned-conll03-german": 5_12,
}




class 	__A(				__lowerCamelCase ):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__			    =			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__			    =			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__			    =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__			    =			["""input_ids""", """attention_mask"""]







  def __init__(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_="<s>"       ,			SCREAMING_SNAKE_CASE_="</s>"       ,			SCREAMING_SNAKE_CASE_="</s>"       ,			SCREAMING_SNAKE_CASE_="<s>"       ,			SCREAMING_SNAKE_CASE_="<unk>"       ,			SCREAMING_SNAKE_CASE_="<pad>"       ,			SCREAMING_SNAKE_CASE_="<mask>"       ,			SCREAMING_SNAKE_CASE_ = None       ,			**SCREAMING_SNAKE_CASE_       ,			):
       # Mask token behave like a normal word, i.e. include the space before it
       UpperCamelCase__				=				AddedToken(SCREAMING_SNAKE_CASE_       ,			lstrip=SCREAMING_SNAKE_CASE_       ,			rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_						) else mask_token

       UpperCamelCase__				=				{} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=SCREAMING_SNAKE_CASE_       ,			eos_token=SCREAMING_SNAKE_CASE_       ,			unk_token=SCREAMING_SNAKE_CASE_       ,			sep_token=SCREAMING_SNAKE_CASE_       ,			cls_token=SCREAMING_SNAKE_CASE_       ,			pad_token=SCREAMING_SNAKE_CASE_       ,			mask_token=SCREAMING_SNAKE_CASE_       ,			sp_model_kwargs=self.sp_model_kwargs       ,			**SCREAMING_SNAKE_CASE_       ,			)

       UpperCamelCase__				=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(str(SCREAMING_SNAKE_CASE_						)						)
       UpperCamelCase__				=				vocab_file

       # Original fairseq vocab and spm vocab must be "aligned":
       # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
       # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
       # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
       # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

       # Mimic fairseq token-to-id alignment for the first 4 token
       UpperCamelCase__				=				{"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

       # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
       UpperCamelCase__				=				1

       UpperCamelCase__				=				len(self.sp_model						) + self.fairseq_offset
       UpperCamelCase__				=				{v: k for k, v in self.fairseq_tokens_to_ids.items()}







  def __getstate__(self						):
       UpperCamelCase__				=				self.__dict__.copy()
       UpperCamelCase__				=				None
       UpperCamelCase__				=				self.sp_model.serialized_model_proto()
       return state







  def __setstate__(self       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				d

       # for backward compatibility
       if not hasattr(self       ,			"""sp_model_kwargs"""						):
            UpperCamelCase__				=				{}

       UpperCamelCase__				=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_ = None						):

       if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       UpperCamelCase__				=				[self.cls_token_id]
       UpperCamelCase__				=				[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_ = None       ,			SCREAMING_SNAKE_CASE_ = False						):

       if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=SCREAMING_SNAKE_CASE_       ,			token_ids_a=SCREAMING_SNAKE_CASE_       ,			already_has_special_tokens=SCREAMING_SNAKE_CASE_						)

       if token_ids_a is None:
            return [1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1]
       return [1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1]







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_ = None						):
       UpperCamelCase__				=				[self.sep_token_id]
       UpperCamelCase__				=				[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]







  @property
  def        UpperCAmelCase_					(self						):
       return len(self.sp_model						) + self.fairseq_offset + 1  # Add the <mask> token







  def        UpperCAmelCase_					(self						):
       UpperCamelCase__				=				{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_						): i for i in range(self.vocab_size						)}
       vocab.update(self.added_tokens_encoder						)
       return vocab







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       return self.sp_model.encode(SCREAMING_SNAKE_CASE_       ,			out_type=SCREAMING_SNAKE_CASE_						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       if token in self.fairseq_tokens_to_ids:
            return self.fairseq_tokens_to_ids[token]
       UpperCamelCase__				=				self.sp_model.PieceToId(SCREAMING_SNAKE_CASE_						)

       # Need to return unknown token if the SP model returned 0
       return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       if index in self.fairseq_ids_to_tokens:
            return self.fairseq_ids_to_tokens[index]
       return self.sp_model.IdToPiece(index - self.fairseq_offset						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				"""""".join(SCREAMING_SNAKE_CASE_						).replace(SCREAMING_SNAKE_CASE_       ,			""" """						).strip()
       return out_string







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_ = None						):
       if not os.path.isdir(SCREAMING_SNAKE_CASE_						):
            logger.error(F"Vocabulary path ({save_directory}) should be a directory"						)
            return
       UpperCamelCase__				=				os.path.join(
           SCREAMING_SNAKE_CASE_       ,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)

       if os.path.abspath(self.vocab_file						) != os.path.abspath(SCREAMING_SNAKE_CASE_						) and os.path.isfile(self.vocab_file						):
            copyfile(self.vocab_file       ,			SCREAMING_SNAKE_CASE_						)
       elif not os.path.isfile(self.vocab_file						):
            with open(SCREAMING_SNAKE_CASE_       ,			"""wb"""						) as fi:
                 UpperCamelCase__				=				self.sp_model.serialized_model_proto()
                 fi.write(SCREAMING_SNAKE_CASE_						)

       return (out_vocab_file,)












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     __snake_case       (							__lowerCamelCase   ,			unittest.TestCase			):





       '''simple docstring'''







       lowerCAmelCase__      		=     GPTSanJapaneseTokenizer
       lowerCAmelCase__      		=     False
       lowerCAmelCase__      		=     {"""do_clean_text""": False, """add_prefix_space""": False}




       def 							UpperCAmelCase__ (  self :    Union[str, Any]		):
         super().setUp()

         # fmt: off
         __snake_case:						str   =						["""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
         __snake_case:						List[Any]   =						{"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
         __snake_case:						Optional[int]   =						{"""unk_token""": """<unk>"""}

         __snake_case:						Any   =						os.path.join(self.tmpdirname							,				VOCAB_FILES_NAMES["""vocab_file"""]		)
         __snake_case:						int   =						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(A		)		)




       def 							UpperCAmelCase__ (  self :    Optional[int]							,				**A :    int		):
         kwargs.update(self.special_tokens_map		)
         return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname							,				**A		)




       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    Dict		):
         __snake_case:						Tuple   =						"""こんにちは、世界。 \nこんばんは、㔺界。😀"""
         __snake_case:						str   =						"""こんにちは、世界。 \nこんばんは、世界。😀"""
         return input_text, output_text




       def 							UpperCAmelCase__ (  self :    Optional[int]							,				A :    Optional[int]		):
         __snake_case  ,   __snake_case:						Optional[int]   =						self.get_input_output_texts(A		)
         __snake_case:						Optional[Any]   =						tokenizer.encode(A							,				add_special_tokens=A		)
         __snake_case:						int   =						tokenizer.decode(A							,				clean_up_tokenization_spaces=A		)
         return text, ids




       def 							UpperCAmelCase__ (  self :    int		):
         pass  # TODO add if relevant




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




       def 							UpperCAmelCase__ (  self :    Optional[int]		):
         pass  # TODO add if relevant




       def 							UpperCAmelCase__ (  self :    Union[str, Any]		):
         __snake_case:						Dict   =						self.get_tokenizer()

         # Testing tokenization
         __snake_case:						List[str]   =						"""こんにちは、世界。　こんばんは、㔺界。"""
         __snake_case:						Optional[int]   =						["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
         __snake_case:						Any   =						tokenizer.tokenize(A		)
         self.assertListEqual(A							,				A		)

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

         # Testing conversion to ids with special tokens
         __snake_case:						Optional[int]   =						tokens + [tokenizer.unk_token]
         __snake_case:						List[str]   =						[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
         __snake_case:						str   =						tokenizer.convert_tokens_to_ids(A		)
         self.assertListEqual(A							,				A		)




       def 							UpperCAmelCase__ (  self :    str		):
         __snake_case:						Union[str, Any]   =						self.get_tokenizer()

         # Testing tokenization
         __snake_case:						Optional[Any]   =						"""こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"""
         __snake_case:						Optional[Any]   =						"""こんにちは、、、、世界。こんばんは、、、、世界。"""
         __snake_case:						Union[str, Any]   =						tokenizer.encode(A		)
         __snake_case:						List[Any]   =						tokenizer.decode(A		)
         self.assertEqual(A							,				A		)




       @slow
       def 							UpperCAmelCase__ (  self :    Any		):
         __snake_case:						Dict   =						self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""		)

         # Testing tokenization
         __snake_case:						Any   =						"""こんにちは、世界。"""
         __snake_case:						Tuple   =						"""こんばんは、㔺界。😀"""
         __snake_case:						Optional[Any]   =						"""こんにちは、世界。こんばんは、世界。😀"""
         __snake_case:						int   =						tokenizer.encode(prefix_text + input_text		)
         __snake_case:						Union[str, Any]   =						tokenizer.encode(""""""							,				prefix_text=prefix_text + input_text		)
         __snake_case:						Tuple   =						tokenizer.encode(A							,				prefix_text=A		)
         __snake_case:						Union[str, Any]   =						tokenizer.decode(A		)
         __snake_case:						Dict   =						tokenizer.decode(A		)
         __snake_case:						Optional[Any]   =						tokenizer.decode(A		)
         self.assertEqual(A							,				A		)
         self.assertEqual(A							,				A		)
         self.assertEqual(A							,				A		)




       @slow
       def 							UpperCAmelCase__ (  self :    List[str]		):
         __snake_case:						int   =						self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""		)

         # Testing tokenization
         __snake_case:						Optional[int]   =						"""こんにちは、世界。"""
         __snake_case:						Any   =						"""こんばんは、㔺界。😀"""

         __snake_case:						Optional[int]   =						len(tokenizer.encode(A		)		) - 2
         __snake_case:						str   =						len(tokenizer.encode(A		)		) - 2

         __snake_case:						Dict   =						[1] + [0] * (len_prefix + len_text + 1)
         __snake_case:						str   =						[1] * (len_prefix + len_text + 1) + [0]
         __snake_case:						List[Any]   =						[1] + [1] * (len_prefix) + [0] * (len_text + 1)

         __snake_case:						int   =						tokenizer(prefix_text + input_text		).token_type_ids
         __snake_case:						Optional[int]   =						tokenizer(""""""							,				prefix_text=prefix_text + input_text		).token_type_ids
         __snake_case:						Tuple   =						tokenizer(A							,				prefix_text=A		).token_type_ids
         self.assertListEqual(A							,				A		)
         self.assertListEqual(A							,				A		)
         self.assertListEqual(A							,				A		)




       @slow
       def 							UpperCAmelCase__ (  self :    Dict		):
         __snake_case:						Dict   =						self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""		)

         __snake_case:						int   =						tokenizer.encode("""あンいワ"""		)
         __snake_case:						Optional[int]   =						tokenizer.encode(""""""							,				prefix_text="""あンいワ"""		)
         __snake_case:						List[Any]   =						tokenizer.encode("""いワ"""							,				prefix_text="""あン"""		)

         self.assertEqual(tokenizer.decode(A		)							,				tokenizer.decode(A		)		)
         self.assertEqual(tokenizer.decode(A		)							,				tokenizer.decode(A		)		)
         self.assertNotEqual(A							,				A		)
         self.assertNotEqual(A							,				A		)
         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 							UpperCAmelCase__ (  self :    int		):
         __snake_case:						List[str]   =						self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""		)

         __snake_case:						Union[str, Any]   =						[["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
         __snake_case:						Optional[int]   =						tokenizer(A							,				padding=A		)
         __snake_case:						int   =						tokenizer.batch_encode_plus(A							,				padding=A		)

         # fmt: off
         __snake_case:						List[str]   =						[[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
         __snake_case:						int   =						[[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
         __snake_case:						Dict   =						[[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
         # fmt: on
         self.assertListEqual(x_token.input_ids							,				A		)
         self.assertListEqual(x_token.token_type_ids							,				A		)
         self.assertListEqual(x_token.attention_mask							,				A		)
         self.assertListEqual(x_token_a.input_ids							,				A		)
         self.assertListEqual(x_token_a.token_type_ids							,				A		)
         self.assertListEqual(x_token_a.attention_mask							,				A		)




       def 							UpperCAmelCase__ (  self :    Union[str, Any]		):
         # Intentionally convert some words to accommodate character fluctuations unique to Japanese
         pass






       def 							UpperCAmelCase__ (  self :    List[str]		):
         # tokenizer has no padding token
         pass






