




def 							_UpperCAmelCase     (UpperCamelCase_       :       Any				):
				'''simple docstring'''


				if len(lowercase_				) == 0 or not all(len(lowercase_				) == 2 for pair in coordinates				):
								raise ValueError("""The program cannot work out a fitting polynomial."""				)

				if len({tuple(lowercase_				) for pair in coordinates}				) != len(lowercase_				):
								raise ValueError("""The program cannot work out a fitting polynomial."""				)

				_lowerCAmelCase			:			Optional[int]        =					{x for x, _ in coordinates}
				if len(lowercase_				) == 1:
								return F"x={coordinates[0][0]}"

				if len(lowercase_				) != len(lowercase_				):
								raise ValueError("""The program cannot work out a fitting polynomial."""				)

				_lowerCAmelCase			:			List[Any]        =					len(lowercase_				)

				_lowerCAmelCase			:			Optional[Any]        =					0
				_lowerCAmelCase			:			Tuple        =					[]
				# put the x and x to the power values in a matrix
				while count_of_line < x:
								_lowerCAmelCase			:			Optional[Any]        =					0
								_lowerCAmelCase			:			Dict        =					coordinates[count_of_line][0]
								_lowerCAmelCase			:			Tuple        =					[]
								while count_in_line < x:
												count_line.append(a ** (x - (count_in_line + 1))				)
												count_in_line += 1
								matrix.append(lowercase_				)
								count_of_line += 1

				_lowerCAmelCase			:			Union[str, Any]        =					0
				# put the y values into a vector
				_lowerCAmelCase			:			List[str]        =					[]
				while count_of_line < x:
								vector.append(coordinates[count_of_line][1]				)
								count_of_line += 1

				_lowerCAmelCase			:			List[str]        =					0

				while count < x:
								_lowerCAmelCase			:			Optional[int]        =					0
								while zahlen < x:
												if count == zahlen:
																zahlen += 1
												if zahlen == x:
																break
												_lowerCAmelCase			:			List[Any]        =					matrix[zahlen][count] / matrix[count][count]
												for counting_columns, item in enumerate(matrix[count]				):
																# manipulating all the values in the matrix
																matrix[zahlen][counting_columns] -= item * bruch
												# manipulating the values in the vector
												vector[zahlen] -= vector[count] * bruch
												zahlen += 1
								count += 1

				_lowerCAmelCase			:			Union[str, Any]        =					0
				# make solutions
				_lowerCAmelCase			:			int        =					[]
				while count < x:
								solution.append(str(vector[count] / matrix[count][count]				)				)
								count += 1

				_lowerCAmelCase			:			str        =					0
				_lowerCAmelCase			:			Tuple        =					"""f(x)="""

				while count < x:
								_lowerCAmelCase			:			int        =					solution[count].split("""E"""				)
								if len(lowercase_				) > 1:
												_lowerCAmelCase			:			List[str]        =					F"{remove_e[0]}*10^{remove_e[1]}"
								solved += F"x^{x - (count + 1)}*{solution[count]}"
								if count + 1 != x:
												solved += "+"
								count += 1

				return solved


if __name__ == "__main__":
	print(points_to_polynomial([]))
	print(points_to_polynomial([[]]))
	print(points_to_polynomial([[1, 0], [2, 0], [3, 0]]))
	print(points_to_polynomial([[1, 1], [2, 1], [3, 1]]))
	print(points_to_polynomial([[1, 3], [2, 3], [3, 3]]))
	print(points_to_polynomial([[1, 1], [2, 2], [3, 3]]))
	print(points_to_polynomial([[1, 1], [2, 4], [3, 9]]))
	print(points_to_polynomial([[1, 3], [2, 6], [3, 1_1]]))
	print(points_to_polynomial([[1, -3], [2, -6], [3, -1_1]]))
	print(points_to_polynomial([[1, 5], [2, 2], [3, 9]]))







import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
 from .tokenization_deberta_va import DebertaVaTokenizer
else:
 a_      						=   None

a_      						=   logging.get_logger(__name__)

a_      						=   {"vocab_file": "spm.model", "tokenizer_file": "tokenizer.json"}

a_      						=   {
    "vocab_file": {
        "microsoft/deberta-v2-xlarge": "https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xxlarge": "https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model"
        ),
        "microsoft/deberta-v2-xxlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model"
        ),
    }
}

a_      						=   {
    "microsoft/deberta-v2-xlarge": 512,
    "microsoft/deberta-v2-xxlarge": 512,
    "microsoft/deberta-v2-xlarge-mnli": 512,
    "microsoft/deberta-v2-xxlarge-mnli": 512,
}

a_      						=   {
    "microsoft/deberta-v2-xlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xlarge-mnli": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge-mnli": {"do_lower_case": False},
}

class        _lowerCamelCase  (	_SCREAMING_SNAKE_CASE      ):

      """simple docstring"""

      lowerCAmelCase__	:       int			=    VOCAB_FILES_NAMES
      lowerCAmelCase__	:       Any			=    PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__	:       Optional[Any]			=    PRETRAINED_INIT_CONFIGURATION
      lowerCAmelCase__	:       int			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__	:       Dict			=    DebertaVaTokenizer







      def __init__(   self    :       int       ,				snake_case    :       int=None       ,				snake_case    :       Optional[int]=None       ,				snake_case    :       Any=False       ,				snake_case    :       Optional[int]=False       ,				snake_case    :       Dict="[CLS]"       ,				snake_case    :       Any="[SEP]"       ,				snake_case    :       Union[str, Any]="[UNK]"       ,				snake_case    :       List[Any]="[SEP]"       ,				snake_case    :       Union[str, Any]="[PAD]"       ,				snake_case    :       Tuple="[CLS]"       ,				snake_case    :       Dict="[MASK]"       ,				**snake_case    :       int       ,				):
          super().__init__(
              snake_case       ,				tokenizer_file=snake_case       ,				do_lower_case=snake_case       ,				bos_token=snake_case       ,				eos_token=snake_case       ,				unk_token=snake_case       ,				sep_token=snake_case       ,				pad_token=snake_case       ,				cls_token=snake_case       ,				mask_token=snake_case       ,				split_by_punct=snake_case       ,				**snake_case       ,				)

          __UpperCamelCase     						=  do_lower_case
          __UpperCamelCase     						=  split_by_punct
          __UpperCamelCase     						=  vocab_file
          __UpperCamelCase     						=  False if not self.vocab_file else True







      def 					snake_case		(   self    :       Optional[int]       ,				snake_case    :       int       ,				snake_case    :       Tuple=None ):

          if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          __UpperCamelCase     						=  [self.cls_token_id]
          __UpperCamelCase     						=  [self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep







      def 					snake_case		(   self    :       Any       ,				snake_case    :       Union[str, Any]       ,				snake_case    :       Optional[Any]=None       ,				snake_case    :       Union[str, Any]=False ):

          if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=snake_case       ,				token_ids_a=snake_case       ,				already_has_special_tokens=snake_case )

          if token_ids_a is not None:
              return [1] + ([0] * len(snake_case )) + [1] + ([0] * len(snake_case )) + [1]
          return [1] + ([0] * len(snake_case )) + [1]







      def 					snake_case		(   self    :       Optional[int]       ,				snake_case    :       Optional[int]       ,				snake_case    :       Optional[Any]=None ):
          __UpperCamelCase     						=  [self.sep_token_id]
          __UpperCamelCase     						=  [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 					snake_case		(   self    :       List[str]       ,				snake_case    :       str       ,				snake_case    :       Optional[str] = None ):
          if not self.can_save_slow_tokenizer:
              raise ValueError(
                  '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                  '''tokenizer.''' )

          if not os.path.isdir(snake_case ):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory" )
              return
          __UpperCamelCase     						=  os.path.join(
              snake_case       ,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

          if os.path.abspath(self.vocab_file ) != os.path.abspath(snake_case ):
              copyfile(self.vocab_file       ,				snake_case )

          return (out_vocab_file,)






