
import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation

_UpperCAmelCase    			=					logging.get_logger(__name__)

_UpperCAmelCase    			=					{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

_UpperCAmelCase    			=					{
    "vocab_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"
        ),
    },
}

_UpperCAmelCase    			=					{
    "microsoft/deberta-base": 512,
    "microsoft/deberta-large": 512,
    "microsoft/deberta-xlarge": 512,
    "microsoft/deberta-base-mnli": 512,
    "microsoft/deberta-large-mnli": 512,
    "microsoft/deberta-xlarge-mnli": 512,
}

_UpperCAmelCase    			=					{
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}


def 		_lowerCamelCase       (   ):
  """simple docstring"""




  _lowerCamelCase      =						(
      list(range(ord('''!'''  )			,   ord('''~'''  ) + 1  )  ) + list(range(ord('''¡'''  )			,   ord('''¬'''  ) + 1  )  ) + list(range(ord('''®'''  )			,   ord('''ÿ'''  ) + 1  )  )
  )
  _lowerCamelCase      =						bs[:]
  _lowerCamelCase      =						0
  for b in range(2**8  ):
    if b not in bs:
      bs.append(__lowerCamelCase  )
      cs.append(2**8 + n  )
      n += 1
  _lowerCamelCase      =						[chr(__lowerCamelCase  ) for n in cs]
  return dict(zip(__lowerCamelCase			,   __lowerCamelCase  )  )


def 		_lowerCamelCase       (   _a  ):
  """simple docstring"""




  _lowerCamelCase      =						set()
  _lowerCamelCase      =						word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)  )
    _lowerCamelCase      =						char
  return pairs






class 		__magic_name__				( __lowerCamelCase					):


  """simple docstring"""





  _UpperCamelCase						 = VOCAB_FILES_NAMES
  _UpperCamelCase						 = PRETRAINED_VOCAB_FILES_MAP
  _UpperCamelCase						 = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCamelCase						 = ["input_ids", "attention_mask", "token_type_ids"]


  def __init__(					self	,		a__	,		a__	,		a__="replace"	,		a__="[CLS]"	,		a__="[SEP]"	,		a__="[SEP]"	,		a__="[CLS]"	,		a__="[UNK]"	,		a__="[PAD]"	,		a__="[MASK]"	,		a__=False	,		a__=False	,		**a__	,		):
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else bos_token
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else eos_token
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else sep_token
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else cls_token
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else unk_token
    _lowerCamelCase      =						AddedToken(__lowerCAmelCase	,		lstrip=__lowerCAmelCase	,		rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	,		__lowerCAmelCase		) else pad_token

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

    super().__init__(
        errors=__lowerCAmelCase	,		bos_token=__lowerCAmelCase	,		eos_token=__lowerCAmelCase	,		unk_token=__lowerCAmelCase	,		sep_token=__lowerCAmelCase	,		cls_token=__lowerCAmelCase	,		pad_token=__lowerCAmelCase	,		mask_token=__lowerCAmelCase	,		add_prefix_space=__lowerCAmelCase	,		add_bos_token=__lowerCAmelCase	,		**__lowerCAmelCase	,		)
    _lowerCamelCase      =						add_bos_token

    with open(__lowerCAmelCase	,		encoding='''utf-8'''		) as vocab_handle:
      _lowerCamelCase      =						json.load(__lowerCAmelCase		)
    _lowerCamelCase      =						{v: k for k, v in self.encoder.items()}
    _lowerCamelCase      =						errors  # how to handle errors in decoding
    _lowerCamelCase      =						bytes_to_unicode()
    _lowerCamelCase      =						{v: k for k, v in self.byte_encoder.items()}
    with open(__lowerCAmelCase	,		encoding='''utf-8'''		) as merges_handle:
      _lowerCamelCase      =						merges_handle.read().split('''\n'''		)[1:-1]
    _lowerCamelCase      =						[tuple(merge.split()		) for merge in bpe_merges]
    _lowerCamelCase      =						dict(zip(__lowerCAmelCase	,		range(len(__lowerCAmelCase		)		)		)		)
    _lowerCamelCase      =						{}
    _lowerCamelCase      =						add_prefix_space

    # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
    _lowerCamelCase      =						re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''		)


  @property
  # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
  def     _UpperCAmelCase  (					self		):
    return len(self.encoder		)


  def     _UpperCAmelCase  (					self		):
    return dict(self.encoder	,		**self.added_tokens_encoder		)


  def     _UpperCAmelCase  (					self	,		a__		):
    if token in self.cache:
      return self.cache[token]
    _lowerCamelCase      =						tuple(__lowerCAmelCase		)
    _lowerCamelCase      =						get_pairs(__lowerCAmelCase		)

    if not pairs:
      return token

    while True:
      _lowerCamelCase      =						min(__lowerCAmelCase	,		key=lambda a__		: self.bpe_ranks.get(__lowerCAmelCase	,		float('''inf'''		)		)		)
      if bigram not in self.bpe_ranks:
        break
      _lowerCamelCase    ,    _lowerCamelCase      =						bigram
      _lowerCamelCase      =						[]
      _lowerCamelCase      =						0
      while i < len(__lowerCAmelCase		):
        try:
          _lowerCamelCase      =						word.index(__lowerCAmelCase	,		__lowerCAmelCase		)
        except ValueError:
          new_word.extend(word[i:]		)
          break
        else:
          new_word.extend(word[i:j]		)
          _lowerCamelCase      =						j

        if word[i] == first and i < len(__lowerCAmelCase		) - 1 and word[i + 1] == second:
          new_word.append(first + second		)
          i += 2
        else:
          new_word.append(word[i]		)
          i += 1
      _lowerCamelCase      =						tuple(__lowerCAmelCase		)
      _lowerCamelCase      =						new_word
      if len(__lowerCAmelCase		) == 1:
        break
      else:
        _lowerCamelCase      =						get_pairs(__lowerCAmelCase		)
    _lowerCamelCase      =						''' '''.join(__lowerCAmelCase		)
    _lowerCamelCase      =						word
    return word


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    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	,		a__	,		a__ = None	,		a__ = False		):
    if already_has_special_tokens:
      return super().get_special_tokens_mask(
          token_ids_a=__lowerCAmelCase	,		token_ids_a=__lowerCAmelCase	,		already_has_special_tokens=__lowerCAmelCase		)

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


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    _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]


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						[]
    for token in re.findall(self.pat	,		__lowerCAmelCase		):
      _lowerCamelCase      =						''''''.join(
          self.byte_encoder[b] for b in token.encode('''utf-8'''		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
      bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__lowerCAmelCase		).split(''' '''		)		)
    return bpe_tokens


  def     _UpperCAmelCase  (					self	,		a__		):
    return self.encoder.get(__lowerCAmelCase	,		self.encoder.get(self.unk_token		)		)


  def     _UpperCAmelCase  (					self	,		a__		):
    return self.decoder.get(__lowerCAmelCase		)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						''''''.join(__lowerCAmelCase		)
    _lowerCamelCase      =						bytearray([self.byte_decoder[c] for c in text]		).decode('''utf-8'''	,		errors=self.errors		)
    return text


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    if not os.path.isdir(__lowerCAmelCase		):
      logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
      return
    _lowerCamelCase      =						os.path.join(
        __lowerCAmelCase	,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)
    _lowerCamelCase      =						os.path.join(
        __lowerCAmelCase	,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']		)

    with open(__lowerCAmelCase	,		'''w'''	,		encoding='''utf-8'''		) as f:
      f.write(json.dumps(self.encoder	,		indent=2	,		sort_keys=__lowerCAmelCase	,		ensure_ascii=__lowerCAmelCase		) + '''\n'''		)

    _lowerCamelCase      =						0
    with open(__lowerCAmelCase	,		'''w'''	,		encoding='''utf-8'''		) as writer:
      writer.write('''#version: 0.2\n'''		)
      for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,		key=lambda a__		: kv[1]		):
        if index != token_index:
          logger.warning(
              f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
              ''' Please check that the tokenizer is not corrupted!'''		)
          _lowerCamelCase      =						token_index
        writer.write(''' '''.join(__lowerCAmelCase		) + '''\n'''		)
        index += 1

    return vocab_file, merge_file


  def     _UpperCAmelCase  (					self	,		a__	,		a__=False	,		**a__		):
    _lowerCamelCase      =						kwargs.pop('''add_prefix_space'''	,		self.add_prefix_space		)
    if (is_split_into_words or add_prefix_space) and (len(__lowerCAmelCase		) > 0 and not text[0].isspace()):
      _lowerCamelCase      =						''' ''' + text
    return (text, kwargs)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						[]
    for is_user, text in conversation.iter_texts():
      input_ids.extend(self.encode(__lowerCAmelCase	,		add_special_tokens=__lowerCAmelCase		) + [self.eos_token_id]		)
    if len(__lowerCAmelCase		) > self.model_max_length:
      _lowerCamelCase      =						input_ids[-self.model_max_length :]
    return input_ids





'''simple docstring'''

from typing import TYPE_CHECKING

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


lowerCAmelCase_			:			Tuple    	=   {"configuration_vilt": ["VILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViltConfig"]}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_			:			Optional[int]    	=   ["ViltFeatureExtractor"]
       lowerCAmelCase_			:			str    	=   ["ViltImageProcessor"]
       lowerCAmelCase_			:			Any    	=   ["ViltProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_			:			Any    	=   [
           "VILT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "ViltForImageAndTextRetrieval",
           "ViltForImagesAndTextClassification",
           "ViltForTokenClassification",
           "ViltForMaskedLM",
           "ViltForQuestionAnswering",
           "ViltLayer",
           "ViltModel",
           "ViltPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_vilt import ViltFeatureExtractor
              from .image_processing_vilt import ViltImageProcessor
              from .processing_vilt import ViltProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vilt import (
                  VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ViltForImageAndTextRetrieval,
                  ViltForImagesAndTextClassification,
                  ViltForMaskedLM,
                  ViltForQuestionAnswering,
                  ViltForTokenClassification,
                  ViltLayer,
                  ViltModel,
                  ViltPreTrainedModel,
              )


else:
       import sys

       lowerCAmelCase_			:			str    	=   _LazyModule(__name__, globals()["__file__"], _import_structure)






