






"""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

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""": 5_12,
    """microsoft/deberta-large""": 5_12,
    """microsoft/deberta-xlarge""": 5_12,
    """microsoft/deberta-base-mnli""": 5_12,
    """microsoft/deberta-large-mnli""": 5_12,
    """microsoft/deberta-xlarge-mnli""": 5_12,
}

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






def 							A(    ):
       """simple docstring"""





       lowercase__:							Dict         =     (
           list(range(ord("!"						)		,  ord("~"						) + 1						)						) + list(range(ord("¡"						)		,  ord("¬"						) + 1						)						) + list(range(ord("®"						)		,  ord("ÿ"						) + 1						)						)
       )
       lowercase__:							int         =     bs[:]
       lowercase__:							Union[str, Any]         =     0
       for b in range(2**8						):
              if b not in bs:
                     bs.append(snake_case_						)
                     cs.append(2**8 + n						)
                     n += 1
       lowercase__:							Optional[Any]         =     [chr(snake_case_						) for n in cs]
       return dict(zip(snake_case_		,  snake_case_						)						)






def 							A(    snake_case_						):
       """simple docstring"""





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







class 						_a  (		lowercase_       ):





   '''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					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_="replace"					, UpperCAmelCase_="[CLS]"					, UpperCAmelCase_="[SEP]"					, UpperCAmelCase_="[SEP]"					, UpperCAmelCase_="[CLS]"					, UpperCAmelCase_="[UNK]"					, UpperCAmelCase_="[PAD]"					, UpperCAmelCase_="[MASK]"					, UpperCAmelCase_=False					, UpperCAmelCase_=False					, **UpperCAmelCase_					, )			->   Dict:




          '''simple docstring'''




          lowercase__:							List[str]         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else bos_token
          lowercase__:							Optional[int]         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else eos_token
          lowercase__:							int         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else sep_token
          lowercase__:							Optional[Any]         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else cls_token
          lowercase__:							List[Any]         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else unk_token
          lowercase__:							Tuple         =     AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_					, UpperCAmelCase_) else pad_token

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

          super().__init__(
              errors=UpperCAmelCase_					, bos_token=UpperCAmelCase_					, eos_token=UpperCAmelCase_					, unk_token=UpperCAmelCase_					, sep_token=UpperCAmelCase_					, cls_token=UpperCAmelCase_					, pad_token=UpperCAmelCase_					, mask_token=UpperCAmelCase_					, add_prefix_space=UpperCAmelCase_					, add_bos_token=UpperCAmelCase_					, **UpperCAmelCase_					, )
          lowercase__:							int         =     add_bos_token

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

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          lowercase__:							List[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 __lowercase							(       self)			->   List[str]:




          '''simple docstring'''




          return len(self.encoder)





   def __lowercase							(       self)			->   int:




          '''simple docstring'''




          return dict(self.encoder					, **self.added_tokens_encoder)





   def __lowercase							(       self					, UpperCAmelCase_)			->   List[Any]:




          '''simple docstring'''




          if token in self.cache:
                 return self.cache[token]
          lowercase__:							str         =     tuple(UpperCAmelCase_)
          lowercase__:							List[Any]         =     get_pairs(UpperCAmelCase_)

          if not pairs:
                 return token

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

                        if word[i] == first and i < len(UpperCAmelCase_) - 1 and word[i + 1] == second:
                               new_word.append(first + second)
                               i += 2
                        else:
                               new_word.append(word[i])
                               i += 1
                 lowercase__:							List[Any]         =     tuple(UpperCAmelCase_)
                 lowercase__:							List[Any]         =     new_word
                 if len(UpperCAmelCase_) == 1:
                        break
                 else:
                        lowercase__:							Optional[Any]         =     get_pairs(UpperCAmelCase_)
          lowercase__:							List[str]         =     " ".join(UpperCAmelCase_)
          lowercase__:							Dict         =     word
          return word





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_ = None)			->   List[int]:




          '''simple docstring'''




          if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          lowercase__:							List[str]         =     [self.cls_token_id]
          lowercase__:							int         =     [self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_ = None					, UpperCAmelCase_ = False)			->   List[int]:




          '''simple docstring'''




          if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=UpperCAmelCase_					, token_ids_a=UpperCAmelCase_					, already_has_special_tokens=UpperCAmelCase_)

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





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_ = None)			->   List[int]:




          '''simple docstring'''




          lowercase__:							Dict         =     [self.sep_token_id]
          lowercase__:							Optional[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 __lowercase							(       self					, UpperCAmelCase_)			->   List[Any]:




          '''simple docstring'''




          lowercase__:							List[Any]         =     []
          for token in re.findall(self.pat					, UpperCAmelCase_):
                 lowercase__:							int         =     "".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(UpperCAmelCase_).split(" "))
          return bpe_tokens





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




          '''simple docstring'''




          return self.encoder.get(UpperCAmelCase_					, self.encoder.get(self.unk_token))





   def __lowercase							(       self					, UpperCAmelCase_)			->   int:




          '''simple docstring'''




          return self.decoder.get(UpperCAmelCase_)





   def __lowercase							(       self					, UpperCAmelCase_)			->   Optional[Any]:




          '''simple docstring'''




          lowercase__:							int         =     "".join(UpperCAmelCase_)
          lowercase__:							Any         =     bytearray([self.byte_decoder[c] for c in text]).decode("utf-8"					, errors=self.errors)
          return text





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_ = None)			->   Tuple[str]:




          '''simple docstring'''




          if not os.path.isdir(UpperCAmelCase_):
                 logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
                 return
          lowercase__:							List[str]         =     os.path.join(
              UpperCAmelCase_					, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])
          lowercase__:							Union[str, Any]         =     os.path.join(
              UpperCAmelCase_					, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"])

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

          lowercase__:							Any         =     0
          with open(UpperCAmelCase_					, "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 UpperCAmelCase_: 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!")
                               lowercase__:							int         =     token_index
                        writer.write(" ".join(UpperCAmelCase_) + "\n")
                        index += 1

          return vocab_file, merge_file





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_=False					, **UpperCAmelCase_)			->   Optional[Any]:




          '''simple docstring'''




          lowercase__:							Optional[int]         =     kwargs.pop("add_prefix_space"					, self.add_prefix_space)
          if (is_split_into_words or add_prefix_space) and (len(UpperCAmelCase_) > 0 and not text[0].isspace()):
                 lowercase__:							Tuple         =     " " + text
          return (text, kwargs)





   def __lowercase							(       self					, UpperCAmelCase_)			->   List[int]:




          '''simple docstring'''




          lowercase__:							Tuple         =     []
          for is_user, text in conversation.iter_texts():
                 input_ids.extend(self.encode(UpperCAmelCase_					, add_special_tokens=UpperCAmelCase_) + [self.eos_token_id])
          if len(UpperCAmelCase_) > self.model_max_length:
                 lowercase__:							Union[str, Any]         =     input_ids[-self.model_max_length :]
          return input_ids














'''simple docstring'''







import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
  import torch

  from transformers import CamembertModel




@require_torch
@require_sentencepiece
@require_tokenizers
class 					__UpperCAmelCase (		unittest.TestCase	):

      '''simple docstring'''





      @slow
      def 							lowerCamelCase     (					self						):
             UpperCAmelCase__	:   Optional[int]												=	CamembertModel.from_pretrained('''camembert-base'''						)
             model.to(_UpperCAmelCase						)

             UpperCAmelCase__	:   Optional[int]												=	torch.tensor(
                 [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]]  ,		device=_UpperCAmelCase  ,		dtype=torch.long  ,		)  # J'aime le camembert !
             with torch.no_grad():
                    UpperCAmelCase__	:   Tuple												=	model(_UpperCAmelCase						)['''last_hidden_state''']
             UpperCAmelCase__	:   List[str]												=	torch.Size((1, 10, 768)						)
             self.assertEqual(output.shape  ,		_UpperCAmelCase						)
             # compare the actual values for a slice.
             UpperCAmelCase__	:   List[Any]												=	torch.tensor(
                 [[[-0.02_54, 0.02_35, 0.10_27], [0.06_06, -0.18_11, -0.04_18], [-0.15_61, -0.11_27, 0.26_87]]]  ,		device=_UpperCAmelCase  ,		dtype=torch.float  ,		)
             # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
             # camembert.eval()
             # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

             self.assertTrue(torch.allclose(output[:, :3, :3]  ,		_UpperCAmelCase  ,		atol=1E-4						)						)