'''simple docstring'''




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


_lowercase		:					Tuple													=		logging.get_logger(__name__)

_lowercase		:					List[Any]													=		{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_lowercase		:					Union[str, 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"
        ),
    },
}

_lowercase		:					Union[str, 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,
}

_lowercase		:					Optional[Any]													=		{
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}





class        __magic_name__		(       _UpperCAmelCase):
			UpperCamelCase__							=			VOCAB_FILES_NAMES
			UpperCamelCase__							=			PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__							=			['''input_ids''', '''attention_mask''', '''token_type_ids''']
			UpperCamelCase__							=			DebertaTokenizer







			def __init__(      self							:    Optional[Any]							,     lowercase_							:    Any=None							,     lowercase_							:    Union[str, Any]=None							,     lowercase_							:    Optional[Any]=None							,     lowercase_							:    Any="replace"							,     lowercase_							:    Optional[int]="[CLS]"							,     lowercase_							:    int="[SEP]"							,     lowercase_							:    Optional[int]="[SEP]"							,     lowercase_							:    Optional[Any]="[CLS]"							,     lowercase_							:    List[Any]="[UNK]"							,     lowercase_							:    List[str]="[PAD]"							,     lowercase_							:    Tuple="[MASK]"							,     lowercase_							:    List[str]=False							,     **lowercase_							:    int							,     ):
										super().__init__(
										    lowercase_							,     lowercase_							,     tokenizer_file=lowercase_							,     errors=lowercase_							,     bos_token=lowercase_							,     eos_token=lowercase_							,     unk_token=lowercase_							,     sep_token=lowercase_							,     cls_token=lowercase_							,     pad_token=lowercase_							,     mask_token=lowercase_							,     add_prefix_space=lowercase_							,     **lowercase_							,     )
										lowercase_   :     List[Any]									=			kwargs.pop("""add_bos_token"""							,     lowercase_       )

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

										lowercase_   :     Optional[int]									=			add_prefix_space







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    Tuple       ):
										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       SCREAMING_SNAKE_CASE_	(      self							:    List[Any]							,     lowercase_							:    Any       ):
										lowercase_   :     Any									=			AddedToken(lowercase_							,     lstrip=lowercase_							,     rstrip=lowercase_       ) if isinstance(lowercase_							,     lowercase_       ) else value
										lowercase_   :     Union[str, Any]									=			value







			def       SCREAMING_SNAKE_CASE_	(      self							:    Any							,     lowercase_							:    List[int]							,     lowercase_							:    Optional[List[int]] = None       ):
										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_   :     Tuple									=			[self.sep_token_id]
										return cls + token_ids_a + sep + token_ids_a + sep







			def       SCREAMING_SNAKE_CASE_	(      self							:    Optional[Any]							,     lowercase_							:    List[int]							,     lowercase_							:    Optional[List[int]] = None       ):
										lowercase_   :     Union[str, Any]									=			[self.sep_token_id]
										lowercase_   :     Optional[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       SCREAMING_SNAKE_CASE_	(      self							:    Optional[int]							,     *lowercase_							:    Optional[int]							,     **lowercase_							:    Optional[int]       ):
										lowercase_   :     str									=			kwargs.get("""is_split_into_words"""							,     lowercase_       )
										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(*lowercase_							,     **lowercase_       )







			def       SCREAMING_SNAKE_CASE_	(      self							:    Dict							,     *lowercase_							:    Tuple							,     **lowercase_							:    int       ):
										lowercase_   :     List[Any]									=			kwargs.get("""is_split_into_words"""							,     lowercase_       )

										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(*lowercase_							,     **lowercase_       )







			def       SCREAMING_SNAKE_CASE_	(      self							:    Tuple							,     lowercase_							:    str							,     lowercase_							:    Optional[str] = None       ):
										lowercase_   :     Dict									=			self._tokenizer.model.save(lowercase_							,     name=lowercase_       )
										return tuple(lowercase_       )







			def       SCREAMING_SNAKE_CASE_	(      self							:    str							,     lowercase_							:    "Conversation"       ):
										lowercase_   :     Union[str, Any]									=			[]
										for is_user, text in conversation.iter_texts():
																	input_ids.extend(self.encode(lowercase_							,     add_special_tokens=lowercase_       ) + [self.eos_token_id]       )

										if len(lowercase_       ) > self.model_max_length:
																	lowercase_   :     Optional[int]									=			input_ids[-self.model_max_length :]
										return input_ids






'''simple docstring'''




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments




def 				lowerCamelCase      ( )     -> List[Any]:
							lowercase_   :     Tuple									=			HfArgumentParser(UpperCAmelCase__					)
							try:
														lowercase_   :     List[Any]									=			parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowercase_   :     int									=			"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
														lowercase_   :     Any									=			""" """.join(str(UpperCAmelCase__					).split(""" """					)[:-1]					)
														lowercase_   :     Optional[Any]									=			""""""
														lowercase_   :     List[str]									=			eval(str(UpperCAmelCase__					).split(""" """					)[-1]					)
														lowercase_   :     Dict									=			[]
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]					)
																					else:
																												wrong_args.append(UpperCAmelCase__					)
														if len(UpperCAmelCase__					) > 0:
																					lowercase_   :     Dict									=			full_error_msg + begin_error_msg + str(UpperCAmelCase__					)
														raise ValueError(UpperCAmelCase__					)

							lowercase_   :     Optional[int]									=			PyTorchBenchmark(args=UpperCAmelCase__					)
							benchmark.run()


if __name__ == "__main__":
						main()





