"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_ta import TaTokenizer
else:
 lowercase__ 	=     None


lowercase__ 	=     logging.get_logger(__name__)

lowercase__ 	=     {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

lowercase__ 	=     {
    'vocab_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/spiece.model',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/spiece.model',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/spiece.model',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/spiece.model',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/tokenizer.json',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/tokenizer.json',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/tokenizer.json',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/tokenizer.json',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/tokenizer.json',
    },
}


# TODO(PVP) - this should be removed in Transformers v5
lowercase__ 	=     {
    't5-small': 512,
    't5-base': 512,
    't5-large': 512,
    't5-3b': 512,
    't5-11b': 512,
}




class        __snake_case	(					__lowerCAmelCase    ):
      a__				=		VOCAB_FILES_NAMES
      a__				=		PRETRAINED_VOCAB_FILES_MAP
      a__				=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a__				=		["""input_ids""", """attention_mask"""]
      a__				=		TaTokenizer

      a__				=		[]



      def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      lowercase="</s>"   ,      lowercase="<unk>"   ,      lowercase="<pad>"   ,      lowercase=1_00   ,      lowercase=None   ,      **lowercase   ,      )     ->      Tuple:





        '''simple docstring'''





        if extra_ids > 0 and additional_special_tokens is None:
          a__:					Any      							=     [f'<extra_id_{i}>' for i in range(lowercase)]
        elif extra_ids > 0 and additional_special_tokens is not None:
          # Check that we have the right number of extra special tokens
          a__:					Tuple      							=     len(set(filter(lambda lowercase: bool('extra_id_' in str(lowercase))   ,      lowercase)))
          if extra_tokens != extra_ids:
            raise ValueError(
                f'Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'
                ' provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids'
                ' tokens')

        super().__init__(
            lowercase   ,      tokenizer_file=lowercase   ,      eos_token=lowercase   ,      unk_token=lowercase   ,      pad_token=lowercase   ,      extra_ids=lowercase   ,      additional_special_tokens=lowercase   ,      **lowercase   ,      )

        a__:					Tuple      							=     vocab_file
        a__:					str      							=     False if not self.vocab_file else True
        a__:					List[Any]      							=     extra_ids



      @staticmethod
      def   lowerCamelCase_       (						lowercase   ,      lowercase   ,      lowercase)     ->      str:





        '''simple docstring'''





        if pretrained_model_name_or_path in TaTokenizerFast.max_model_input_sizes:
          a__:					Union[str, Any]      							=     TaTokenizerFast.max_model_input_sizes[pretrained_model_name_or_path]
          if init_max_model_length is not None and init_max_model_length != max_model_length:
            return init_max_model_length
          elif init_max_model_length is None:
            warnings.warn(
                'This tokenizer was incorrectly instantiated with a model max length of'
                f' {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this'
                ' behavior is kept to avoid breaking backwards compatibility when padding/encoding with'
                ' `truncation is True`.\n- Be aware that you SHOULD NOT rely on'
                f' {pretrained_model_name_or_path} automatically truncating your input to'
                f' {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences'
                f' longer than {deprecated_max_model_length} you can either instantiate this tokenizer with'
                ' `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please'
                ' instantiate this tokenizer with `model_max_length` set to your preferred value.'   ,      lowercase   ,      )

        return max_model_length



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      Tuple[str]:





        '''simple docstring'''





        if not self.can_save_slow_tokenizer:
          raise ValueError(
              'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
              'tokenizer.')

        if not os.path.isdir(lowercase):
          logger.error(f'Vocabulary path ({save_directory}) should be a directory')
          return
        a__:					Dict      							=     os.path.join(
            lowercase   ,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

        if os.path.abspath(self.vocab_file) != os.path.abspath(lowercase):
          copyfile(self.vocab_file   ,      lowercase)
          logger.info(f'Copy vocab file to {out_vocab_file}')

        return (out_vocab_file,)



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





        '''simple docstring'''





        a__:					Tuple      							=     token_ids_a + [self.eos_token_id]
        if token_ids_a is None:
          return self.prefix_tokens + token_ids_a
        else:
          a__:					Optional[Any]      							=     token_ids_a + [self.eos_token_id]
          return self.prefix_tokens + token_ids_a + token_ids_a



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





        '''simple docstring'''





        a__:					Optional[int]      							=     [self.eos_token_id]

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



      def   lowerCamelCase_       (						self)     ->      Union[str, Any]:





        '''simple docstring'''





        return list(
            set(filter(lambda lowercase: bool(re.search(r'<extra_id_\d+>'   ,      lowercase)) is not None   ,      self.additional_special_tokens)))



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        return [self.convert_tokens_to_ids(lowercase) for token in self.get_sentinel_tokens()]



"""simple docstring"""
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


lowercase__ 	=     {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

lowercase__ 	=     {
    'vocab_file': {
        'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt',
    },
    'tokenizer_file': {
        'unc-nlp/lxmert-base-uncased': (
            'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json'
        ),
    },
}

lowercase__ 	=     {
    'unc-nlp/lxmert-base-uncased': 512,
}

lowercase__ 	=     {
    'unc-nlp/lxmert-base-uncased': {'do_lower_case': True},
}




class        __snake_case	(					__lowerCAmelCase    ):
      a__				=		VOCAB_FILES_NAMES
      a__				=		PRETRAINED_VOCAB_FILES_MAP
      a__				=		PRETRAINED_INIT_CONFIGURATION
      a__				=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a__				=		LxmertTokenizer



      def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      lowercase=True   ,      lowercase="[UNK]"   ,      lowercase="[SEP]"   ,      lowercase="[PAD]"   ,      lowercase="[CLS]"   ,      lowercase="[MASK]"   ,      lowercase=True   ,      lowercase=None   ,      **lowercase   ,      )     ->      Dict:





        '''simple docstring'''





        super().__init__(
            lowercase   ,      tokenizer_file=lowercase   ,      do_lower_case=lowercase   ,      unk_token=lowercase   ,      sep_token=lowercase   ,      pad_token=lowercase   ,      cls_token=lowercase   ,      mask_token=lowercase   ,      tokenize_chinese_chars=lowercase   ,      strip_accents=lowercase   ,      **lowercase   ,      )

        a__:					Dict      							=     json.loads(self.backend_tokenizer.normalizer.__getstate__())
        if (
            normalizer_state.get('lowercase'   ,      lowercase) != do_lower_case
            or normalizer_state.get('strip_accents'   ,      lowercase) != strip_accents
            or normalizer_state.get('handle_chinese_chars'   ,      lowercase) != tokenize_chinese_chars
        ):
          a__:					int      							=     getattr(lowercase   ,      normalizer_state.pop('type'))
          a__:					Dict      							=     do_lower_case
          a__:					Dict      							=     strip_accents
          a__:					Optional[int]      							=     tokenize_chinese_chars
          a__:					List[Any]      							=     normalizer_class(**lowercase)

        a__:					Optional[int]      							=     do_lower_case



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase=None)     ->      Tuple:





        '''simple docstring'''





        a__:					Optional[Any]      							=     [self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
          output += token_ids_a + [self.sep_token_id]

        return output



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





        '''simple docstring'''





        a__:					List[Any]      							=     [self.sep_token_id]
        a__:					List[Any]      							=     [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]



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      Tuple[str]:





        '''simple docstring'''





        a__:					List[Any]      							=     self._tokenizer.model.save(lowercase   ,      name=lowercase)
        return tuple(lowercase)


