


'''simple docstring'''

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

lowerCAmelCase   :List[str]								=    logging.get_logger(__name__)

lowerCAmelCase   :List[str]								=    {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

lowerCAmelCase   :List[Any]								=    {
    '''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'''
        ),
    },
}

lowerCAmelCase   :Any								=    {
    '''microsoft/deberta-base''': 5_1_2,
    '''microsoft/deberta-large''': 5_1_2,
    '''microsoft/deberta-xlarge''': 5_1_2,
    '''microsoft/deberta-base-mnli''': 5_1_2,
    '''microsoft/deberta-large-mnli''': 5_1_2,
    '''microsoft/deberta-xlarge-mnli''': 5_1_2,
}

lowerCAmelCase   :Optional[int]								=    {
    '''microsoft/deberta-base''': {'''do_lower_case''': False},
    '''microsoft/deberta-large''': {'''do_lower_case''': False},
}





def lowerCamelCase    (    ):





	"""simple docstring"""







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





def lowerCamelCase    (    lowerCAmelCase       :			Optional[Any]	):





	"""simple docstring"""







	__magic_name__ :					List[str]  			=  set()
	__magic_name__ :					List[Any]  			=  word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)	)
		__magic_name__ :					Union[str, Any]  			=  char
	return pairs





class _lowerCamelCase (		lowercase__							):



		'''simple docstring'''







		A_			:    str   					=       VOCAB_FILES_NAMES
		A_			:    Tuple   					=       PRETRAINED_VOCAB_FILES_MAP
		A_			:    int   					=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		A_			:    List[str]   					=       ["""input_ids""", """attention_mask""", """token_type_ids"""]







		def __init__(      self	:		Union[str, Any]						,  _A	:		Union[str, Any]						,  _A	:		int						,  _A	:		Optional[Any]="replace"						,  _A	:		Optional[int]="[CLS]"						,  _A	:		Optional[Any]="[SEP]"						,  _A	:		Optional[int]="[SEP]"						,  _A	:		int="[CLS]"						,  _A	:		str="[UNK]"						,  _A	:		Union[str, Any]="[PAD]"						,  _A	:		Union[str, Any]="[MASK]"						,  _A	:		Optional[Any]=False						,  _A	:		int=False						,  **_A	:		Any						,  )						->				Optional[int]:
			__magic_name__ :					int  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else bos_token
			__magic_name__ :					Tuple  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else eos_token
			__magic_name__ :					List[str]  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else sep_token
			__magic_name__ :					Optional[int]  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else cls_token
			__magic_name__ :					List[str]  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else unk_token
			__magic_name__ :					str  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else pad_token

			# Mask token behave like a normal word, i.e. include the space before it
			__magic_name__ :					Optional[int]  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else mask_token

			super().__init__(
			    errors=_A						,  bos_token=_A						,  eos_token=_A						,  unk_token=_A						,  sep_token=_A						,  cls_token=_A						,  pad_token=_A						,  mask_token=_A						,  add_prefix_space=_A						,  add_bos_token=_A						,  **_A						,  )
			__magic_name__ :					Optional[int]  			=  add_bos_token

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

			# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
			__magic_name__ :					Union[str, Any]  			=  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      __lowerCAmelCase	(      self	:		str    )						->				List[Any]:
			return len(self.encoder    )







		def      __lowerCAmelCase	(      self	:		Tuple    )						->				Any:
			return dict(self.encoder						,  **self.added_tokens_encoder    )







		def      __lowerCAmelCase	(      self	:		Any						,  _A	:		Union[str, Any]    )						->				str:
			if token in self.cache:
				return self.cache[token]
			__magic_name__ :					Tuple  			=  tuple(_A    )
			__magic_name__ :					List[Any]  			=  get_pairs(_A    )

			if not pairs:
				return token

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

					if word[i] == first and i < len(_A    ) - 1 and word[i + 1] == second:
						new_word.append(first + second    )
						i += 2
					else:
						new_word.append(word[i]    )
						i += 1
				__magic_name__ :					Union[str, Any]  			=  tuple(_A    )
				__magic_name__ :					int  			=  new_word
				if len(_A    ) == 1:
					break
				else:
					__magic_name__ :					str  			=  get_pairs(_A    )
			__magic_name__ :					Optional[Any]  			=  ' '.join(_A    )
			__magic_name__ :					int  			=  word
			return word







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







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

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







		def      __lowerCAmelCase	(      self	:		Any						,  _A	:		List[int]						,  _A	:		Optional[List[int]] = None    )						->				List[int]:
			__magic_name__ :					Optional[Any]  			=  [self.sep_token_id]
			__magic_name__ :					Tuple  			=  [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	:		Optional[Any]						,  _A	:		Optional[int]    )						->				Any:
			__magic_name__ :					str  			=  []
			for token in re.findall(self.pat						,  _A    ):
				__magic_name__ :					Union[str, Any]  			=  ''.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(_A    ).split(' '    )    )
			return bpe_tokens







		def      __lowerCAmelCase	(      self	:		Dict						,  _A	:		Optional[Any]    )						->				str:
			return self.encoder.get(_A						,  self.encoder.get(self.unk_token    )    )







		def      __lowerCAmelCase	(      self	:		str						,  _A	:		Dict    )						->				List[str]:
			return self.decoder.get(_A    )







		def      __lowerCAmelCase	(      self	:		str						,  _A	:		Dict    )						->				List[str]:
			__magic_name__ :					int  			=  ''.join(_A    )
			__magic_name__ :					List[Any]  			=  bytearray([self.byte_decoder[c] for c in text]    ).decode('utf-8'						,  errors=self.errors    )
			return text







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

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

			__magic_name__ :					Any  			=  0
			with open(_A						,  '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!'    )
						__magic_name__ :					List[str]  			=  token_index
					writer.write(' '.join(_A    ) + '\n'    )
					index += 1

			return vocab_file, merge_file







		def      __lowerCAmelCase	(      self	:		Tuple						,  _A	:		Optional[Any]						,  _A	:		Union[str, Any]=False						,  **_A	:		Optional[int]    )						->				Dict:
			__magic_name__ :					Any  			=  kwargs.pop('add_prefix_space'						,  self.add_prefix_space    )
			if (is_split_into_words or add_prefix_space) and (len(_A    ) > 0 and not text[0].isspace()):
				__magic_name__ :					List[Any]  			=  ' ' + text
			return (text, kwargs)







		def      __lowerCAmelCase	(      self	:		List[Any]						,  _A	:		"Conversation"    )						->				List[int]:
			__magic_name__ :					List[str]  			=  []
			for is_user, text in conversation.iter_texts():
				input_ids.extend(self.encode(_A						,  add_special_tokens=_A    ) + [self.eos_token_id]    )
			if len(_A    ) > self.model_max_length:
				__magic_name__ :					Optional[Any]  			=  input_ids[-self.model_max_length :]
			return input_ids



'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase   :List[Any]								=    logging.get_logger(__name__)

lowerCAmelCase   :Dict								=    {
    '''uw-madison/yoso-4096''': '''https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json''',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}
class _lowerCamelCase (		lowercase__							):



		'''simple docstring'''







		A_			:    Optional[Any]   					=       """yoso"""







		def __init__(      self	:		Any						,  _A	:		List[Any]=50265						,  _A	:		Any=768						,  _A	:		List[str]=12						,  _A	:		Dict=12						,  _A	:		Union[str, Any]=3072						,  _A	:		List[Any]="gelu"						,  _A	:		Dict=0.1						,  _A	:		Union[str, Any]=0.1						,  _A	:		Union[str, Any]=4096						,  _A	:		Dict=1						,  _A	:		Tuple=0.02						,  _A	:		Any=1E-12						,  _A	:		Optional[int]="absolute"						,  _A	:		Tuple=True						,  _A	:		Any=9						,  _A	:		Tuple=64						,  _A	:		str=None						,  _A	:		Dict=True						,  _A	:		str=True						,  _A	:		int=1						,  _A	:		Optional[int]=0						,  _A	:		Tuple=2						,  **_A	:		Optional[Any]						,  )						->				Any:
			super().__init__(pad_token_id=_A						,  bos_token_id=_A						,  eos_token_id=_A						,  **_A    )

			__magic_name__ :					List[Any]  			=  vocab_size
			__magic_name__ :					int  			=  max_position_embeddings
			__magic_name__ :					int  			=  hidden_size
			__magic_name__ :					Any  			=  num_hidden_layers
			__magic_name__ :					List[str]  			=  num_attention_heads
			__magic_name__ :					str  			=  intermediate_size
			__magic_name__ :					Any  			=  hidden_act
			__magic_name__ :					Union[str, Any]  			=  hidden_dropout_prob
			__magic_name__ :					str  			=  attention_probs_dropout_prob
			__magic_name__ :					int  			=  initializer_range
			__magic_name__ :					List[Any]  			=  type_vocab_size
			__magic_name__ :					Tuple  			=  layer_norm_eps
			__magic_name__ :					Tuple  			=  position_embedding_type
			__magic_name__ :					Optional[Any]  			=  use_expectation
			__magic_name__ :					Union[str, Any]  			=  hash_code_len
			__magic_name__ :					int  			=  num_hash
			__magic_name__ :					List[Any]  			=  conv_window
			__magic_name__ :					Optional[Any]  			=  use_fast_hash
			__magic_name__ :					int  			=  lsh_backward