




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCamelCase     :	Tuple         =				{
    '''configuration_mask2former''': [
        '''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Mask2FormerConfig''',
    ],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase     :	List[Any]         =				['''Mask2FormerImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase     :	int         =				[
		    '''MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''Mask2FormerForUniversalSegmentation''',
		    '''Mask2FormerModel''',
		    '''Mask2FormerPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_maskaformer import MaskaFormerImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_maskaformer import (
				    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MaskaFormerForUniversalSegmentation,
				    MaskaFormerModel,
				    MaskaFormerPreTrainedModel,
				)


else:
		import sys

		_lowerCamelCase     :	List[str]         =				_LazyModule(__name__, globals()['__file__'], _import_structure)













"""simple docstring"""





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      a						(					__snake_case		):






    def __init__(       self     :							List[Any]       ,						__SCREAMING_SNAKE_CASE     :							str = "▁"       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "<unk>"       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "</s>"       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "<pad>"       ,						)     ->		Optional[int]:
      lowerCamelCase_         =						{
          'pad': {'id': 0, 'token': pad_token},
          'eos': {'id': 1, 'token': eos_token},
          'unk': {'id': 2, 'token': unk_token},
      }

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

      lowerCamelCase_         =						Tokenizer(Unigram()					)

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

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

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

      super().__init__(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[str, List[str]]       ,						__SCREAMING_SNAKE_CASE     :							int = 8000       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						)     ->		Tuple:
      lowerCamelCase_         =						trainers.UnigramTrainer(
          vocab_size=__SCREAMING_SNAKE_CASE       ,						special_tokens=self.special_tokens_list       ,						show_progress=__SCREAMING_SNAKE_CASE       ,						)

      if isinstance(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					):
        lowerCamelCase_         =						[files]
      self._tokenizer.train(__SCREAMING_SNAKE_CASE       ,						trainer=__SCREAMING_SNAKE_CASE					)

      self.add_unk_id()






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[Iterator[str], Iterator[Iterator[str]]]       ,						__SCREAMING_SNAKE_CASE     :							int = 8000       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						)     ->		str:
      lowerCamelCase_         =						trainers.UnigramTrainer(
          vocab_size=__SCREAMING_SNAKE_CASE       ,						special_tokens=self.special_tokens_list       ,						show_progress=__SCREAMING_SNAKE_CASE       ,						)

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

      self.add_unk_id()






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Dict:
      lowerCamelCase_         =						json.loads(self._tokenizer.to_str()					)

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

      lowerCamelCase_         =						Tokenizer.from_str(json.dumps(__SCREAMING_SNAKE_CASE					)					)




