






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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation


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

a	: Tuple      =				{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

a	: str      =				{
    "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"
        ),
    },
}

a	: Optional[Any]      =				{
    "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,
}

a	: Dict      =				{
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}
class 					a					(				a__     ):



      """simple docstring"""


      a						:				List[Any]							 =			VOCAB_FILES_NAMES
      a						:				int							 =			PRETRAINED_VOCAB_FILES_MAP
      a						:				Dict							 =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a						:				List[Any]							 =			["input_ids", "attention_mask", "token_type_ids"]
      a						:				int							 =			DebertaTokenizer
      def __init__(   self      :    Union[str, Any]	,   __lowercase      :    Union[str, Any]=None	,   __lowercase      :    Tuple=None	,   __lowercase      :    Optional[int]=None	,   __lowercase      :    int="replace"	,   __lowercase      :    str="[CLS]"	,   __lowercase      :    List[str]="[SEP]"	,   __lowercase      :    List[str]="[SEP]"	,   __lowercase      :    Optional[Any]="[CLS]"	,   __lowercase      :    List[Any]="[UNK]"	,   __lowercase      :    Union[str, Any]="[PAD]"	,   __lowercase      :    List[str]="[MASK]"	,   __lowercase      :    str=False	,   **__lowercase      :    List[str]	,   )							->   Union[str, Any]:
        super().__init__(
            SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_	,   tokenizer_file=SCREAMING_SNAKE_CASE_	,   errors=SCREAMING_SNAKE_CASE_	,   bos_token=SCREAMING_SNAKE_CASE_	,   eos_token=SCREAMING_SNAKE_CASE_	,   unk_token=SCREAMING_SNAKE_CASE_	,   sep_token=SCREAMING_SNAKE_CASE_	,   cls_token=SCREAMING_SNAKE_CASE_	,   pad_token=SCREAMING_SNAKE_CASE_	,   mask_token=SCREAMING_SNAKE_CASE_	,   add_prefix_space=SCREAMING_SNAKE_CASE_	,   **SCREAMING_SNAKE_CASE_	,   )
        __UpperCAmelCase							:			Optional[Any]     =						kwargs.pop("""add_bos_token"""	,   SCREAMING_SNAKE_CASE_      )

        __UpperCAmelCase							:			Any     =						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()      )
        if pre_tok_state.get("""add_prefix_space"""	,   SCREAMING_SNAKE_CASE_      ) != add_prefix_space:
          __UpperCAmelCase							:			str     =						getattr(SCREAMING_SNAKE_CASE_	,   pre_tok_state.pop("""type"""      )      )
          __UpperCAmelCase							:			List[str]     =						add_prefix_space
          __UpperCAmelCase							:			int     =						pre_tok_class(**SCREAMING_SNAKE_CASE_      )

        __UpperCAmelCase							:			str     =						add_prefix_space
      @property
      def 			UpperCAmelCase   (   self      :    Dict      )							->   str:
        if self._mask_token is None:
          if self.verbose:
            logger.error("""Using mask_token, but it is not set yet."""      )
          return None
        return str(self._mask_token      )
      @mask_token.setter
      def 			UpperCAmelCase   (   self      :    Optional[int]	,   __lowercase      :    str      )							->   Optional[Any]:
        __UpperCAmelCase							:			List[Any]     =						AddedToken(SCREAMING_SNAKE_CASE_	,   lstrip=SCREAMING_SNAKE_CASE_	,   rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_	,   SCREAMING_SNAKE_CASE_      ) else value
        __UpperCAmelCase							:			Optional[Any]     =						value
      def 			UpperCAmelCase   (   self      :    Any	,   __lowercase      :    List[str]	,   __lowercase      :    Optional[Any] = None      )							->   List[int]:
        if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        __UpperCAmelCase							:			Dict     =						[self.cls_token_id]
        __UpperCAmelCase							:			Optional[int]     =						[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep
      def 			UpperCAmelCase   (   self      :    Optional[Any]	,   __lowercase      :    List[Any]	,   __lowercase      :    List[Any] = None      )							->   List[int]:
        __UpperCAmelCase							:			Dict     =						[self.sep_token_id]
        __UpperCAmelCase							:			int     =						[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      :    Any	,   *__lowercase      :    str	,   **__lowercase      :    Any      )							->   BatchEncoding:
        __UpperCAmelCase							:			Optional[int]     =						kwargs.get("""is_split_into_words"""	,   SCREAMING_SNAKE_CASE_      )
        assert self.add_prefix_space or not is_split_into_words, (
            f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
            "to use it with pretokenized inputs."
        )

        return super()._batch_encode_plus(*SCREAMING_SNAKE_CASE_	,   **SCREAMING_SNAKE_CASE_      )
      def 			UpperCAmelCase   (   self      :    str	,   *__lowercase      :    List[str]	,   **__lowercase      :    Optional[Any]      )							->   BatchEncoding:
        __UpperCAmelCase							:			List[str]     =						kwargs.get("""is_split_into_words"""	,   SCREAMING_SNAKE_CASE_      )

        assert self.add_prefix_space or not is_split_into_words, (
            f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
            "to use it with pretokenized inputs."
        )

        return super()._encode_plus(*SCREAMING_SNAKE_CASE_	,   **SCREAMING_SNAKE_CASE_      )
      def 			UpperCAmelCase   (   self      :    Optional[int]	,   __lowercase      :    Optional[int]	,   __lowercase      :    str = None      )							->   Tuple[str]:
        __UpperCAmelCase							:			Tuple     =						self._tokenizer.model.save(SCREAMING_SNAKE_CASE_	,   name=SCREAMING_SNAKE_CASE_      )
        return tuple(SCREAMING_SNAKE_CASE_      )




      def 			UpperCAmelCase   (   self      :    int	,   __lowercase      :    Optional[int]      )							->   List[int]:
        __UpperCAmelCase							:			List[Any]     =						[]
        for is_user, text in conversation.iter_texts():
          input_ids.extend(self.encode(SCREAMING_SNAKE_CASE_	,   add_special_tokens=SCREAMING_SNAKE_CASE_      ) + [self.eos_token_id]      )

        if len(SCREAMING_SNAKE_CASE_      ) > self.model_max_length:
          __UpperCAmelCase							:			List[str]     =						input_ids[-self.model_max_length :]
        return input_ids










# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from pathlib import Path

from .config_args import default_config_file, load_config_from_file
from .config_utils import SubcommandHelpFormatter


a	: Union[str, Any]      =				"Update an existing config file with the latest defaults while maintaining the old configuration."






def        lowerCamelCase__   (					__lowerCamelCase    :  str	):
  __UpperCAmelCase							:			Optional[Any]     =						args.config_file
  if config_file is None and Path(__lowerCamelCase	).exists():
    __UpperCAmelCase							:			int     =						default_config_file
  elif not Path(__lowerCamelCase	).exists():
    raise ValueError(f"""The passed config file located at {config_file} doesn't exist."""	)
  __UpperCAmelCase							:			Tuple     =						load_config_from_file(__lowerCamelCase	)

  if config_file.endswith(""".json"""	):
    config.to_json_file(__lowerCamelCase	)
  else:
    config.to_yaml_file(__lowerCamelCase	)
  return config_file






def        lowerCamelCase__   (					__lowerCamelCase    :  Dict						,	__lowerCamelCase    :  List[str]	):
  __UpperCAmelCase							:			List[str]     =						parser.add_parser("""update"""						,	parents=__lowerCamelCase						,	help=__lowerCamelCase						,	formatter_class=__lowerCamelCase	)
  parser.add_argument(
      """--config_file"""						,	default=__lowerCamelCase						,	help=(
          """The path to the config file to update. Will default to a file named default_config.yaml in the cache """
          """location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have """
          """such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed """
          """with 'huggingface'."""
      )						,	)

  parser.set_defaults(func=__lowerCamelCase	)
  return parser







def        lowerCamelCase__   (					__lowerCamelCase    :  Optional[int]	):
  __UpperCAmelCase							:			Optional[Any]     =						update_config(__lowerCamelCase	)
  print(f"""Sucessfully updated the configuration file at {config_file}."""	)


