

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


a_      =     logging.get_logger(__name__)


a_      =     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all MVP models at https://huggingface.co/models?filter=mvp
a_      =     {
    'vocab_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json',
    },
    'added_tokens.json': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json',
    },
    'merges_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json',
    },
}

a_      =     {
    'RUCAIBox/mvp': 1024,
}






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     =VOCAB_FILES_NAMES
			lowerCamelCase__							     =PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__							     =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__							     =['input_ids', 'attention_mask']
			lowerCamelCase__							     =MvpTokenizer
			def __init__(      self				:			int   ,   a				:			List[str]=None   ,   a				:			List[str]=None   ,   a				:			List[str]=None   ,   a				:			int="replace"   ,   a				:			Tuple="<s>"   ,   a				:			List[Any]="</s>"   ,   a				:			int="</s>"   ,   a				:			Optional[Any]="<s>"   ,   a				:			int="<unk>"   ,   a				:			int="<pad>"   ,   a				:			List[Any]="<mask>"   ,   a				:			Union[str, Any]=False   ,   a				:			str=True   ,   **a				:			Optional[int]   ,   )				->							int:

				"""simple docstring"""

				super().__init__(
				    a   ,   a   ,   tokenizer_file=a   ,   errors=a   ,   bos_token=a   ,   eos_token=a   ,   sep_token=a   ,   cls_token=a   ,   unk_token=a   ,   pad_token=a   ,   mask_token=a   ,   add_prefix_space=a   ,   trim_offsets=a   ,   **a   ,   )

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

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							add_prefix_space

				# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
				SCREAMING_SNAKE_CASE :   List[str]					  =							"post_processor"
				SCREAMING_SNAKE_CASE :   Optional[Any]					  =							getattr(self.backend_tokenizer   ,   a   ,   a						)
				if tokenizer_component_instance:
					SCREAMING_SNAKE_CASE :   Any					  =							json.loads(tokenizer_component_instance.__getstate__()						)

					# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
					if "sep" in state:
						SCREAMING_SNAKE_CASE :   str					  =							tuple(state["sep"]						)
					if "cls" in state:
						SCREAMING_SNAKE_CASE :   Optional[int]					  =							tuple(state["cls"]						)

					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							False

					if state.get("add_prefix_space"   ,   a						) != add_prefix_space:
						SCREAMING_SNAKE_CASE :   List[str]					  =							add_prefix_space
						SCREAMING_SNAKE_CASE :   Optional[int]					  =							True

					if state.get("trim_offsets"   ,   a						) != trim_offsets:
						SCREAMING_SNAKE_CASE :   str					  =							trim_offsets
						SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							True

					if changes_to_apply:
						SCREAMING_SNAKE_CASE :   Tuple					  =							getattr(a   ,   state.pop("type"						)						)
						SCREAMING_SNAKE_CASE :   Tuple					  =							component_class(**a						)
						setattr(self.backend_tokenizer   ,   a   ,   a						)
			@property
			def 				__UpperCamelCase			(      self				:			Tuple						)				->							str:

				"""simple docstring"""

				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				:			str   ,   a				:			Tuple						)				->							Optional[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   int					  =							AddedToken(a   ,   lstrip=a   ,   rstrip=a						) if isinstance(a   ,   a						) else value
				SCREAMING_SNAKE_CASE :   str					  =							value
			def 				__UpperCamelCase			(      self				:			Tuple   ,   *a				:			List[Any]   ,   **a				:			List[str]						)				->							BatchEncoding:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							kwargs.get("is_split_into_words"   ,   a						)

				if is_split_into_words and not self.add_prefix_space:
					raise ValueError(
					    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
					    "to use it with pretokenized inputs."						)

				return super()._batch_encode_plus(*a   ,   **a						)
			def 				__UpperCamelCase			(      self				:			List[Any]   ,   *a				:			Union[str, Any]   ,   **a				:			Dict						)				->							BatchEncoding:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Tuple					  =							kwargs.get("is_split_into_words"   ,   a						)

				if is_split_into_words and not self.add_prefix_space:
					raise ValueError(
					    F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
					    "to use it with pretokenized inputs."						)

				return super()._encode_plus(*a   ,   **a						)
			def 				__UpperCamelCase			(      self				:			int   ,   a				:			str   ,   a				:			Optional[str] = None						)				->							Tuple[str]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[str]					  =							self._tokenizer.model.save(a   ,   name=a						)
				return tuple(a						)
			def 				__UpperCamelCase			(      self				:			str   ,   a				:			str   ,   a				:			Optional[Any]=None						)				->							Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[Any]					  =							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
				if token_ids_a is None:
					return output

				return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






			def 				__UpperCamelCase			(      self				:			Optional[int]   ,   a				:			List[int]   ,   a				:			Optional[List[int]] = None						)				->							List[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   str					  =							[self.sep_token_id]
				SCREAMING_SNAKE_CASE :   Union[str, 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 + sep + token_ids_a + sep						) * [0]


def 			lowerCamelCase__			(       _a):
	if not isinstance(_a				,      _a):
		SCREAMING_SNAKE_CASE :   Tuple					  =							f"Input value of [number={number}] must be an integer"
		raise TypeError(_a)
	if number < 0:
		return False
	SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							number * number
	while number > 0:
		if number % 10 != number_square % 10:
			return False
		number //= 10
		number_square //= 10
	return True


if __name__ == "__main__":
			import doctest

			doctest.testmod()