






"""simple docstring"""
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer


lowerCamelCase_					=      logging.get_logger(__name__)

lowerCamelCase_					=      {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase_					=      [
    'small',
    'small-base',
    'medium',
    'medium-base',
    'intermediate',
    'intermediate-base',
    'large',
    'large-base',
    'xlarge',
    'xlarge-base',
]

lowerCamelCase_					=      {
    'vocab_file': {
        'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/vocab.txt',
        'funnel-transformer/small-base': 'https://huggingface.co/funnel-transformer/small-base/resolve/main/vocab.txt',
        'funnel-transformer/medium': 'https://huggingface.co/funnel-transformer/medium/resolve/main/vocab.txt',
        'funnel-transformer/medium-base': (
            'https://huggingface.co/funnel-transformer/medium-base/resolve/main/vocab.txt'
        ),
        'funnel-transformer/intermediate': (
            'https://huggingface.co/funnel-transformer/intermediate/resolve/main/vocab.txt'
        ),
        'funnel-transformer/intermediate-base': (
            'https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/vocab.txt'
        ),
        'funnel-transformer/large': 'https://huggingface.co/funnel-transformer/large/resolve/main/vocab.txt',
        'funnel-transformer/large-base': 'https://huggingface.co/funnel-transformer/large-base/resolve/main/vocab.txt',
        'funnel-transformer/xlarge': 'https://huggingface.co/funnel-transformer/xlarge/resolve/main/vocab.txt',
        'funnel-transformer/xlarge-base': (
            'https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/tokenizer.json',
        'funnel-transformer/small-base': (
            'https://huggingface.co/funnel-transformer/small-base/resolve/main/tokenizer.json'
        ),
        'funnel-transformer/medium': 'https://huggingface.co/funnel-transformer/medium/resolve/main/tokenizer.json',
        'funnel-transformer/medium-base': (
            'https://huggingface.co/funnel-transformer/medium-base/resolve/main/tokenizer.json'
        ),
        'funnel-transformer/intermediate': (
            'https://huggingface.co/funnel-transformer/intermediate/resolve/main/tokenizer.json'
        ),
        'funnel-transformer/intermediate-base': (
            'https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/tokenizer.json'
        ),
        'funnel-transformer/large': 'https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer.json',
        'funnel-transformer/large-base': (
            'https://huggingface.co/funnel-transformer/large-base/resolve/main/tokenizer.json'
        ),
        'funnel-transformer/xlarge': 'https://huggingface.co/funnel-transformer/xlarge/resolve/main/tokenizer.json',
        'funnel-transformer/xlarge-base': (
            'https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/tokenizer.json'
        ),
    },
}
lowerCamelCase_					=      {f'funnel-transformer/{name}': 512 for name in _model_names}
lowerCamelCase_					=      {f'funnel-transformer/{name}': {'do_lower_case': True} for name in _model_names}







class 			UpperCamelCase_       (__UpperCAmelCase     ):
	__magic_name__	      =				VOCAB_FILES_NAMES
	__magic_name__	      =				PRETRAINED_VOCAB_FILES_MAP
	__magic_name__	      =				PRETRAINED_INIT_CONFIGURATION
	__magic_name__	      =				FunnelTokenizer
	__magic_name__	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__magic_name__	      =				2





	def __init__(      self					: Dict	,	lowerCAmelCase_					: Dict=None	,	lowerCAmelCase_					: str=None	,	lowerCAmelCase_					: Union[str, Any]=True	,	lowerCAmelCase_					: List[str]="<unk>"	,	lowerCAmelCase_					: int="<sep>"	,	lowerCAmelCase_					: Any="<pad>"	,	lowerCAmelCase_					: Any="<cls>"	,	lowerCAmelCase_					: Optional[Any]="<mask>"	,	lowerCAmelCase_					: Optional[Any]="<s>"	,	lowerCAmelCase_					: Any="</s>"	,	lowerCAmelCase_					: int=True	,	lowerCAmelCase_					: Optional[Any]=True	,	lowerCAmelCase_					: Optional[int]=None	,	lowerCAmelCase_					: List[str]="##"	,	**lowerCAmelCase_					: List[Any]	,	)						->			Any:
				super().__init__(
				    lowerCamelCase__	,	tokenizer_file=lowerCamelCase__	,	do_lower_case=lowerCamelCase__	,	unk_token=lowerCamelCase__	,	sep_token=lowerCamelCase__	,	pad_token=lowerCamelCase__	,	cls_token=lowerCamelCase__	,	mask_token=lowerCamelCase__	,	bos_token=lowerCamelCase__	,	eos_token=lowerCamelCase__	,	clean_text=lowerCamelCase__	,	tokenize_chinese_chars=lowerCamelCase__	,	strip_accents=lowerCamelCase__	,	wordpieces_prefix=lowerCamelCase__	,	**lowerCamelCase__	,	)

				UpperCAmelCase_     : List[str]			     =					json.loads(self.backend_tokenizer.normalizer.__getstate__()						)
				if (
				    normalizer_state.get("lowercase"	,	lowerCamelCase__						) != do_lower_case
				    or normalizer_state.get("strip_accents"	,	lowerCamelCase__						) != strip_accents
				    or normalizer_state.get("handle_chinese_chars"	,	lowerCamelCase__						) != tokenize_chinese_chars
				):
							UpperCAmelCase_     : Any			     =					getattr(lowerCamelCase__	,	normalizer_state.pop("type"						)						)
							UpperCAmelCase_     : Any			     =					do_lower_case
							UpperCAmelCase_     : str			     =					strip_accents
							UpperCAmelCase_     : Dict			     =					tokenize_chinese_chars
							UpperCAmelCase_     : List[str]			     =					normalizer_class(**lowerCamelCase__						)

				UpperCAmelCase_     : Tuple			     =					do_lower_case





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[int]	,	lowerCAmelCase_					: Tuple	,	lowerCAmelCase_					: Optional[int]=None						)						->			Any:
				UpperCAmelCase_     : Tuple			     =					[self.cls_token_id] + token_ids_a + [self.sep_token_id]

				if token_ids_a:
							output += token_ids_a + [self.sep_token_id]

				return output





	def      _SCREAMING_SNAKE_CASE      (      self					: str	,	lowerCAmelCase_					: List[int]	,	lowerCAmelCase_					: Optional[List[int]] = None						)						->			Union[str, Any]:
				UpperCAmelCase_     : Dict			     =					[self.sep_token_id]
				UpperCAmelCase_     : Optional[int]			     =					[self.cls_token_id]
				if token_ids_a is None:
							return len(cls						) * [self.cls_token_type_id] + len(token_ids_a + sep						) * [0]
				return len(cls						) * [self.cls_token_type_id] + len(token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]	,	lowerCAmelCase_					: str	,	lowerCAmelCase_					: Optional[str] = None						)						->			str:
				UpperCAmelCase_     : Optional[Any]			     =					self._tokenizer.model.save(lowerCamelCase__	,	name=lowerCamelCase__						)
				return tuple(lowerCamelCase__						)




"""simple docstring"""






from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				snake_case       :




					"""simple docstring"""

					snake_case__				    = 42
					snake_case__				    = None
					snake_case__				    = None






lowerCAmelCase__  :  Union[str, Any]						     =	namedtuple('CoinsDistribResult', 'moves excess')



def   a_						(					lowerCamelCase       ):

				if root is None:
								return 0

				# Validation
				def count_nodes(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_nodes(node.left       ) + count_nodes(node.right       ) + 1

				def count_coins(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_coins(node.left       ) + count_coins(node.right       ) + node.data

				if count_nodes(lowerCamelCase       ) != count_coins(lowerCamelCase       ):
								raise ValueError('The nodes number should be same as the number of coins'       )

				# Main calculation
				def get_distrib(lowerCamelCase       ) -> CoinsDistribResult:

								if node is None:
												return CoinsDistribResult(0					,			1       )

								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.left       )
								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.right       )

								UpperCAmelCase__             =							1 - left_distrib_excess
								UpperCAmelCase__             =							1 - right_distrib_excess

								UpperCAmelCase__             =							(
								    left_distrib_moves
								    + right_distrib_moves
								    + abs(lowerCamelCase       )
								    + abs(lowerCamelCase       )
								)
								UpperCAmelCase__             =							node.data - coins_to_left - coins_to_right

								return CoinsDistribResult(lowerCamelCase					,			lowerCamelCase       )

				return get_distrib(lowerCamelCase       )[0]


if __name__ == "__main__":
						import doctest

						doctest.testmod()



