



'''simple docstring'''





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


lowercase_	       =			logging.get_logger(__name__)

lowercase_	       =			{'''vocab_file''': '''spiece.model'''}

lowercase_	       =			{
    '''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'''
        ),
    }
}

lowercase_	       =			{
    '''google/bigbird-roberta-base''': 40_96,
    '''google/bigbird-roberta-large''': 40_96,
    '''google/bigbird-base-trivia-itc''': 40_96,
}






class 						__a (     SCREAMING_SNAKE_CASE				):
	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"]
	SCREAMING_SNAKE_CASE       =       []



	def __init__(						self							:    List[str]				,	snake_case_							:    Tuple				,	snake_case_							:    str="<unk>"				,	snake_case_							:    str="<s>"				,	snake_case_							:    Optional[Any]="</s>"				,	snake_case_							:    Dict="<pad>"				,	snake_case_							:    Optional[Any]="[SEP]"				,	snake_case_							:    int="[MASK]"				,	snake_case_							:    Union[str, Any]="[CLS]"				,	snake_case_							:    Optional[Dict[str, Any]] = None				,	**snake_case_							:    Tuple				,	)->							None:
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else bos_token
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else eos_token
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else unk_token
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else pad_token
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else cls_token
						__lowerCAmelCase	   =AddedToken(snake_case_				,	lstrip=snake_case_				,	rstrip=snake_case_) if isinstance(snake_case_				,	snake_case_) else sep_token

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

						__lowerCAmelCase	   ={} if sp_model_kwargs is None else sp_model_kwargs

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

						__lowerCAmelCase	   =vocab_file

						__lowerCAmelCase	   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
						self.sp_model.Load(snake_case_)



	@property
	def 		UpperCamelCase							(						self							:    Tuple)->							str:
						return self.sp_model.get_piece_size()



	def 		UpperCamelCase							(						self							:    Any)->							List[str]:
						__lowerCAmelCase	   ={self.convert_ids_to_tokens(snake_case_): i for i in range(self.vocab_size)}
						vocab.update(self.added_tokens_encoder)
						return vocab



	def __getstate__(						self							:    Any)->							List[str]:
						__lowerCAmelCase	   =self.__dict__.copy()
						__lowerCAmelCase	   =None
						return state



	def __setstate__(						self							:    Dict				,	snake_case_							:    Optional[Any])->							List[str]:
						__lowerCAmelCase	   =d

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

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



	def 		UpperCamelCase							(						self							:    Tuple				,	snake_case_							:    str)->							List[str]:
						return self.sp_model.encode(snake_case_				,	out_type=snake_case_)



	def 		UpperCamelCase							(						self							:    List[str]				,	snake_case_							:    str)->							Union[str, Any]:
						return self.sp_model.piece_to_id(snake_case_)



	def 		UpperCamelCase							(						self							:    List[str]				,	snake_case_							:    int)->							List[str]:
						__lowerCAmelCase	   =self.sp_model.IdToPiece(snake_case_)
						return token



	def 		UpperCamelCase							(						self							:    int				,	snake_case_							:    Optional[int])->							Optional[Any]:
						__lowerCAmelCase	   =[]
						__lowerCAmelCase	   =""""""
						__lowerCAmelCase	   =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(snake_case_) + token
																__lowerCAmelCase	   =True
																__lowerCAmelCase	   =[]
											else:
																current_sub_tokens.append(snake_case_)
																__lowerCAmelCase	   =False
						out_string += self.sp_model.decode(snake_case_)
						return out_string.strip()



	def 		UpperCamelCase							(						self							:    Optional[int]				,	snake_case_							:    List[int]				,	snake_case_							:    bool = False				,	snake_case_							:    bool = None				,	snake_case_							:    bool = True				,	**snake_case_							:    int				,	)->							str:
						__lowerCAmelCase	   =kwargs.pop("""use_source_tokenizer"""				,	snake_case_)

						__lowerCAmelCase	   =self.convert_ids_to_tokens(snake_case_				,	skip_special_tokens=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
						__lowerCAmelCase	   =[]
						__lowerCAmelCase	   =[]
						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(snake_case_))
																					__lowerCAmelCase	   =[]
																sub_texts.append(snake_case_)
											else:
																current_sub_text.append(snake_case_)
						if current_sub_text:
											sub_texts.append(self.convert_tokens_to_string(snake_case_))

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

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



	def 		UpperCamelCase							(						self							:    Optional[int]				,	snake_case_							:    str				,	snake_case_							:    Optional[str] = None)->							Tuple[str]:
						if not os.path.isdir(snake_case_):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
											return
						__lowerCAmelCase	   =os.path.join(
						    snake_case_				,	(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])

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

						return (out_vocab_file,)



	def 		UpperCamelCase							(						self							:    Union[str, Any]				,	snake_case_							:    List[int]				,	snake_case_							:    Optional[List[int]] = None)->							List[int]:
						if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						__lowerCAmelCase	   =[self.cls_token_id]
						__lowerCAmelCase	   =[self.sep_token_id]
						return cls + token_ids_a + sep + token_ids_a + sep



	def 		UpperCamelCase							(						self							:    Dict				,	snake_case_							:    List[int]				,	snake_case_							:    Optional[List[int]] = None				,	snake_case_							:    bool = False)->							List[int]:
						if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=snake_case_				,	token_ids_a=snake_case_				,	already_has_special_tokens=snake_case_)

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



	def 		UpperCamelCase							(						self							:    Any				,	snake_case_							:    List[int]				,	snake_case_							:    Optional[List[int]] = None)->							List[int]:
						__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) * [0] + len(token_ids_a + sep) * [1]









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_	       =			{
    '''configuration_blip_2''': [
        '''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Blip2Config''',
        '''Blip2QFormerConfig''',
        '''Blip2VisionConfig''',
    ],
    '''processing_blip_2''': ['''Blip2Processor'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''Blip2Model''',
				    '''Blip2QFormerModel''',
				    '''Blip2PreTrainedModel''',
				    '''Blip2ForConditionalGeneration''',
				    '''Blip2VisionModel''',
				]

if TYPE_CHECKING:
				from .configuration_blip_a import (
				    BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    BlipaConfig,
				    BlipaQFormerConfig,
				    BlipaVisionConfig,
				)
				from .processing_blip_a import BlipaProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_blip_a import (
								    BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BlipaForConditionalGeneration,
								    BlipaModel,
								    BlipaPreTrainedModel,
								    BlipaQFormerModel,
								    BlipaVisionModel,
								)

else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




