

import os
import re
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__		      =       {"vocab_file": "spiece.model"}

lowerCAmelCase__		      =       {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

lowerCAmelCase__		      =       {
    "google/bigbird-roberta-base": 4_0_9_6,
    "google/bigbird-roberta-large": 4_0_9_6,
    "google/bigbird-base-trivia-itc": 4_0_9_6,
}

class     a__  (    __lowercase	):
			"""simple docstring"""







			__lowerCamelCase       				=				VOCAB_FILES_NAMES
			__lowerCamelCase       				=				PRETRAINED_VOCAB_FILES_MAP
			__lowerCamelCase       				=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__lowerCamelCase       				=				["""input_ids""", """attention_mask"""]
			__lowerCamelCase       				=				[]


			def __init__(			self					,					lowercase					,					lowercase="<unk>"					,					lowercase="<s>"					,					lowercase="</s>"					,					lowercase="<pad>"					,					lowercase="[SEP]"					,					lowercase="[MASK]"					,					lowercase="[CLS]"					,					lowercase = None					,					**lowercase					,					)     ->  None:
							'''simple docstring'''






							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else bos_token
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else eos_token
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else unk_token
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else pad_token
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else cls_token
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else sep_token

							# Mask token behave like a normal word, i.e. include the space before it
							A__						=	AddedToken(SCREAMING_SNAKE_CASE__					,					lstrip=SCREAMING_SNAKE_CASE__					,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__				) else mask_token

							A__						=	{} 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__					,					pad_token=SCREAMING_SNAKE_CASE__					,					sep_token=SCREAMING_SNAKE_CASE__					,					mask_token=SCREAMING_SNAKE_CASE__					,					cls_token=SCREAMING_SNAKE_CASE__					,					sp_model_kwargs=self.sp_model_kwargs					,					**SCREAMING_SNAKE_CASE__					,					)

							A__						=	vocab_file

							A__						=	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
							self.sp_model.Load(SCREAMING_SNAKE_CASE__				)


			@property
			def    UpperCamelCase						(			self				)     ->  Any:
							'''simple docstring'''






							return self.sp_model.get_piece_size()


			def    UpperCamelCase						(			self				)     ->  Dict:
							'''simple docstring'''






							A__						=	{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 __getstate__(			self				)     ->  str:
							'''simple docstring'''






							A__						=	self.__dict__.copy()
							A__						=	None
							return state


			def __setstate__(			self					,					lowercase				)     ->  int:
							'''simple docstring'''






							A__						=	d

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

							A__						=	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
							self.sp_model.Load(self.vocab_file				)


			def    UpperCamelCase						(			self					,					lowercase				)     ->  List[str]:
							'''simple docstring'''






							return self.sp_model.encode(SCREAMING_SNAKE_CASE__					,					out_type=SCREAMING_SNAKE_CASE__				)


			def    UpperCamelCase						(			self					,					lowercase				)     ->  List[str]:
							'''simple docstring'''






							return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE__				)


			def    UpperCamelCase						(			self					,					lowercase				)     ->  List[Any]:
							'''simple docstring'''






							A__						=	self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__				)
							return token


			def    UpperCamelCase						(			self					,					lowercase				)     ->  Optional[int]:
							'''simple docstring'''






							A__						=	[]
							A__						=	""
							A__						=	False
							for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
															if not prev_is_special:
																			out_string += " "
															out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				) + token
															A__						=	True
															A__						=	[]
											else:
															current_sub_tokens.append(SCREAMING_SNAKE_CASE__				)
															A__						=	False
							out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				)
							return out_string.strip()


			def    UpperCamelCase						(			self					,					lowercase					,					lowercase = False					,					lowercase = None					,					lowercase = True					,					**lowercase					,					)     ->  str:
							'''simple docstring'''






							A__						=	kwargs.pop("use_source_tokenizer"					,					SCREAMING_SNAKE_CASE__				)

							A__						=	self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__					,					skip_special_tokens=SCREAMING_SNAKE_CASE__				)

							# To avoid mixing byte-level and unicode for byte-level BPT
							# we need to build string separately for added tokens and byte-level tokens
							# cf. https://github.com/huggingface/transformers/issues/1133
							A__						=	[]
							A__						=	[]
							for token in filtered_tokens:
											if skip_special_tokens and token in self.all_special_ids:
															continue
											if token in self.added_tokens_encoder:
															if current_sub_text:
																			sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__				)				)
																			A__						=	[]
															sub_texts.append(SCREAMING_SNAKE_CASE__				)
											else:
															current_sub_text.append(SCREAMING_SNAKE_CASE__				)
							if current_sub_text:
											sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__				)				)

							# Mimic the behavior of the Rust tokenizer:
							# No space before [MASK] and [SEP]
							if spaces_between_special_tokens:
											A__						=	re.sub(R" (\[(MASK|SEP)\])"					,					R"\1"					,					" ".join(SCREAMING_SNAKE_CASE__				)				)
							else:
											A__						=	"".join(SCREAMING_SNAKE_CASE__				)

							A__						=	(
							    clean_up_tokenization_spaces
							    if clean_up_tokenization_spaces is not None
							    else self.clean_up_tokenization_spaces
							)
							if clean_up_tokenization_spaces:
											A__						=	self.clean_up_tokenization(SCREAMING_SNAKE_CASE__				)
											return clean_text
							else:
											return text


			def    UpperCamelCase						(			self					,					lowercase					,					lowercase = None				)     ->  Tuple[str]:
							'''simple docstring'''






							if not os.path.isdir(SCREAMING_SNAKE_CASE__				):
											logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
											return
							A__						=	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:
															A__						=	self.sp_model.serialized_model_proto()
															fi.write(SCREAMING_SNAKE_CASE__				)

							return (out_vocab_file,)


			def    UpperCamelCase						(			self					,					lowercase					,					lowercase = None				)     ->  List[int]:
							'''simple docstring'''






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


			def    UpperCamelCase						(			self					,					lowercase					,					lowercase = None					,					lowercase = False				)     ->  List[int]:
							'''simple docstring'''






							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] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1]


			def    UpperCamelCase						(			self					,					lowercase					,					lowercase = None				)     ->  List[int]:
							'''simple docstring'''






							A__						=	[self.sep_token_id]
							A__						=	[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				) * [0] + len(token_ids_a + sep				) * [1]



from abc import ABC, abstractmethod
from argparse import ArgumentParser

class    lowerCAmelCase__     (	__lowercase			):






		@staticmethod
		@abstractmethod
		def  __A       (		SCREAMING_SNAKE_CASE__		:							ArgumentParser  )     ->							str:
						raise NotImplementedError()







		@abstractmethod
		def  __A       (		self		:							Optional[int]  )     ->							Union[str, Any]:
						raise NotImplementedError()



