


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


SCREAMING_SNAKE_CASE		:List[str]     						=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:List[Any]     						=   {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE		:Any     						=   [
    '''small''',
    '''small-base''',
    '''medium''',
    '''medium-base''',
    '''intermediate''',
    '''intermediate-base''',
    '''large''',
    '''large-base''',
    '''xlarge''',
    '''xlarge-base''',
]

SCREAMING_SNAKE_CASE		:Optional[int]     						=   {
    '''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'''
        ),
    },
}
SCREAMING_SNAKE_CASE		:str     						=   {F'''funnel-transformer/{name}''': 5_12 for name in _model_names}
SCREAMING_SNAKE_CASE		:Tuple     						=   {F'''funnel-transformer/{name}''': {'''do_lower_case''': True} for name in _model_names}


class 			__lowerCAmelCase   (       lowerCamelCase_    ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE									=				VOCAB_FILES_NAMES
  _SCREAMING_SNAKE_CASE									=				PRETRAINED_VOCAB_FILES_MAP
  _SCREAMING_SNAKE_CASE									=				PRETRAINED_INIT_CONFIGURATION
  _SCREAMING_SNAKE_CASE									=				FunnelTokenizer
  _SCREAMING_SNAKE_CASE									=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _SCREAMING_SNAKE_CASE									=				2



  def __init__(   self				:				str			, _lowerCAmelCase				:				Any=None			, _lowerCAmelCase				:				Optional[int]=None			, _lowerCAmelCase				:				Union[str, Any]=True			, _lowerCAmelCase				:				Dict="<unk>"			, _lowerCAmelCase				:				Tuple="<sep>"			, _lowerCAmelCase				:				List[str]="<pad>"			, _lowerCAmelCase				:				Any="<cls>"			, _lowerCAmelCase				:				str="<mask>"			, _lowerCAmelCase				:				Optional[Any]="<s>"			, _lowerCAmelCase				:				Tuple="</s>"			, _lowerCAmelCase				:				Any=True			, _lowerCAmelCase				:				List[str]=True			, _lowerCAmelCase				:				Any=None			, _lowerCAmelCase				:				Dict="##"			, **_lowerCAmelCase				:				List[Any]			, )      ->       Tuple:




     """simple docstring"""
     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__			, )

     snake_case_    			=    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
     ):
        snake_case_    			=    getattr(lowerCAmelCase__			, normalizer_state.pop("type"     )     )
        snake_case_    			=    do_lower_case
        snake_case_    			=    strip_accents
        snake_case_    			=    tokenize_chinese_chars
        snake_case_    			=    normalizer_class(**lowerCAmelCase__     )

     snake_case_    			=    do_lower_case



  def     lowerCAmelCase__     (   self				:				Union[str, Any]			, _lowerCAmelCase				:				Dict			, _lowerCAmelCase				:				Any=None     )      ->       Optional[Any]:




     """simple docstring"""
     snake_case_    			=    [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     lowerCAmelCase__     (   self				:				int			, _lowerCAmelCase				:				str			, _lowerCAmelCase				:				Union[str, Any] = None     )      ->       List[int]:




     """simple docstring"""
     snake_case_    			=    [self.sep_token_id]
     snake_case_    			=    [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     lowerCAmelCase__     (   self				:				List[str]			, _lowerCAmelCase				:				Optional[Any]			, _lowerCAmelCase				:				List[str] = None     )      ->       Tuple[str]:




     """simple docstring"""
     snake_case_    			=    self._tokenizer.model.save(lowerCAmelCase__			, name=lowerCAmelCase__     )
     return tuple(lowerCAmelCase__     )








"""simple docstring"""




from math import isclose, sqrt


def     lowercase			(SCREAMING_SNAKE_CASE_		:				float ,			SCREAMING_SNAKE_CASE_		:				float ,			SCREAMING_SNAKE_CASE_		:				float  )   ->						tuple[float, float, float]:
						SCREAMING_SNAKE_CASE													=					point_y / 4 / point_x
						SCREAMING_SNAKE_CASE													=					2 * normal_gradient / (1 + normal_gradient * normal_gradient)
						SCREAMING_SNAKE_CASE													=					(1 - normal_gradient * normal_gradient) / (
						    1 + normal_gradient * normal_gradient
						)
						SCREAMING_SNAKE_CASE													=					(sa - ca * incoming_gradient) / (ca + sa * incoming_gradient)

						# to find the next point, solve the simultaeneous equations:
						# y^2 + 4x^2 = 100
						# y - b = m * (x - a)
						# ==> A x^2 + B x + C = 0
						SCREAMING_SNAKE_CASE													=					outgoing_gradient**2 + 4
						SCREAMING_SNAKE_CASE													=					2 * outgoing_gradient * (point_y - outgoing_gradient * point_x)
						SCREAMING_SNAKE_CASE													=					(point_y - outgoing_gradient * point_x) ** 2 - 1_00

						SCREAMING_SNAKE_CASE													=					(
						    -linear_term - sqrt(linear_term**2 - 4 * quadratic_term * constant_term  )
						) / (2 * quadratic_term)
						SCREAMING_SNAKE_CASE													=					(
						    -linear_term + sqrt(linear_term**2 - 4 * quadratic_term * constant_term  )
						) / (2 * quadratic_term)

						# two solutions, one of which is our input point
						SCREAMING_SNAKE_CASE													=					x_minus if isclose(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_  ) else x_plus
						SCREAMING_SNAKE_CASE													=					point_y + outgoing_gradient * (next_x - point_x)

						return next_x, next_y, outgoing_gradient


def     lowercase			(SCREAMING_SNAKE_CASE_		:				float = 1.4 ,			SCREAMING_SNAKE_CASE_		:				float = -9.6  )   ->						int:
						SCREAMING_SNAKE_CASE													=					0
						SCREAMING_SNAKE_CASE													=					first_x_coord
						SCREAMING_SNAKE_CASE													=					first_y_coord
						SCREAMING_SNAKE_CASE													=					(10.1 - point_y) / (0.0 - point_x)

						while not (-0.01 <= point_x <= 0.01 and point_y > 0):
												SCREAMING_SNAKE_CASE							,				SCREAMING_SNAKE_CASE							,				SCREAMING_SNAKE_CASE													=					next_point(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_  )
												num_reflections += 1

						return num_reflections


if __name__ == "__main__":
	print(f'''{solution() = }''')


