
import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing







class        lowercase	(      SCREAMING_SNAKE_CASE__	):




							def __init__(       self     ,A__ = "▁"     ,A__ = True     ,A__ = "<unk>"     ,A__ = "</s>"     ,A__ = "<pad>"     ,):
												lowercase					=		{
												    '''pad''': {'''id''': 0, '''token''': pad_token},
												    '''eos''': {'''id''': 1, '''token''': eos_token},
												    '''unk''': {'''id''': 2, '''token''': unk_token},
												}

												lowercase					=		[None] * len(self.special_tokens)
												for token_dict in self.special_tokens.values():
																	lowercase					=		token_dict['''token''']

												lowercase					=		Tokenizer(Unigram())

												lowercase					=		normalizers.Sequence(
												    [
												        normalizers.Nmt(),
												        normalizers.NFKC(),
												        normalizers.Replace(Regex(''' {2,}''')     ,''' '''),
												        normalizers.Lowercase(),
												    ])
												lowercase					=		pre_tokenizers.Sequence(
												    [
												        pre_tokenizers.Metaspace(replacement=A__     ,add_prefix_space=A__),
												        pre_tokenizers.Digits(individual_digits=A__),
												        pre_tokenizers.Punctuation(),
												    ])
												lowercase					=		decoders.Metaspace(replacement=A__     ,add_prefix_space=A__)

												lowercase					=		TemplateProcessing(
												    single=f'$A {self.special_tokens["eos"]["token"]}'     ,special_tokens=[(self.special_tokens['''eos''']['''token'''], self.special_tokens['''eos''']['''id'''])]     ,)

												lowercase					=		{
												    '''model''': '''SentencePieceUnigram''',
												    '''replacement''': replacement,
												    '''add_prefix_space''': add_prefix_space,
												}

												super().__init__(A__     ,A__)




							def 				A__   (       self     ,A__     ,A__ = 8_0_0_0     ,A__ = True     ,):
												lowercase					=		trainers.UnigramTrainer(
												    vocab_size=A__     ,special_tokens=self.special_tokens_list     ,show_progress=A__     ,)

												if isinstance(A__     ,A__):
																	lowercase					=		[files]
												self._tokenizer.train(A__     ,trainer=A__)

												self.add_unk_id()




							def 				A__   (       self     ,A__     ,A__ = 8_0_0_0     ,A__ = True     ,):
												lowercase					=		trainers.UnigramTrainer(
												    vocab_size=A__     ,special_tokens=self.special_tokens_list     ,show_progress=A__     ,)

												self._tokenizer.train_from_iterator(A__     ,trainer=A__)

												self.add_unk_id()





							def 				A__   (       self):
												lowercase					=		json.loads(self._tokenizer.to_str())

												lowercase					=		self.special_tokens['''unk''']['''id''']

												lowercase					=		Tokenizer.from_str(json.dumps(A__))






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__	:Tuple										=					{
    "configuration_instructblip": [
        "INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InstructBlipConfig",
        "InstructBlipQFormerConfig",
        "InstructBlipVisionConfig",
    ],
    "processing_instructblip": ["InstructBlipProcessor"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__	:List[str]										=					[
							    "INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "InstructBlipQFormerModel",
							    "InstructBlipPreTrainedModel",
							    "InstructBlipForConditionalGeneration",
							    "InstructBlipVisionModel",
							]

if TYPE_CHECKING:
							from .configuration_instructblip import (
							    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    InstructBlipConfig,
							    InstructBlipQFormerConfig,
							    InstructBlipVisionConfig,
							)
							from .processing_instructblip import InstructBlipProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_instructblip import (
														    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    InstructBlipForConditionalGeneration,
														    InstructBlipPreTrainedModel,
														    InstructBlipQFormerModel,
														    InstructBlipVisionModel,
														)

else:
							import sys

							lowercase__	:List[str]										=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




