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_bart import BartTokenizer


UpperCamelCase__											=					logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
UpperCamelCase__											=					{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

UpperCamelCase__											=					{
    'facebook/bart-base': 1_0_2_4,
    'facebook/bart-large': 1_0_2_4,
    'facebook/bart-large-mnli': 1_0_2_4,
    'facebook/bart-large-cnn': 1_0_2_4,
    'facebook/bart-large-xsum': 1_0_2_4,
    'yjernite/bart_eli5': 1_0_2_4,
}





class      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : int      =			VOCAB_FILES_NAMES
   __UpperCAmelCase : List[Any]      =			PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase : str      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase : Union[str, Any]      =			['input_ids', 'attention_mask']
   __UpperCAmelCase : Dict      =			BartTokenizer


   def __init__(self     :						List[Any]       ,  __UpperCAmelCase     :						Tuple=None       ,  __UpperCAmelCase     :						Tuple=None       ,  __UpperCAmelCase     :						List[Any]=None       ,  __UpperCAmelCase     :						int="replace"       ,  __UpperCAmelCase     :						Tuple="<s>"       ,  __UpperCAmelCase     :						int="</s>"       ,  __UpperCAmelCase     :						Dict="</s>"       ,  __UpperCAmelCase     :						Any="<s>"       ,  __UpperCAmelCase     :						List[Any]="<unk>"       ,  __UpperCAmelCase     :						str="<pad>"       ,  __UpperCAmelCase     :						Tuple="<mask>"       ,  __UpperCAmelCase     :						Any=False       ,  __UpperCAmelCase     :						Optional[Any]=True       ,  **__UpperCAmelCase     :						Tuple       ,  )						->				str:
         """simple docstring"""



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

         UpperCAmelCase__								=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
         if pre_tok_state.get("add_prefix_space"       ,  __UpperCAmelCase		) != add_prefix_space:
               UpperCAmelCase__								=  getattr(__UpperCAmelCase       ,  pre_tok_state.pop("type"		)		)
               UpperCAmelCase__								=  add_prefix_space
               UpperCAmelCase__								=  pre_tok_class(**__UpperCAmelCase		)

         UpperCAmelCase__								=  add_prefix_space

         # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
         UpperCAmelCase__								=  "post_processor"
         UpperCAmelCase__								=  getattr(self.backend_tokenizer       ,  __UpperCAmelCase       ,  __UpperCAmelCase		)
         if tokenizer_component_instance:
               UpperCAmelCase__								=  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:
                     UpperCAmelCase__								=  tuple(state["sep"]		)
               if "cls" in state:
                     UpperCAmelCase__								=  tuple(state["cls"]		)

               UpperCAmelCase__								=  False

               if state.get("add_prefix_space"       ,  __UpperCAmelCase		) != add_prefix_space:
                     UpperCAmelCase__								=  add_prefix_space
                     UpperCAmelCase__								=  True

               if state.get("trim_offsets"       ,  __UpperCAmelCase		) != trim_offsets:
                     UpperCAmelCase__								=  trim_offsets
                     UpperCAmelCase__								=  True

               if changes_to_apply:
                     UpperCAmelCase__								=  getattr(__UpperCAmelCase       ,  state.pop("type"		)		)
                     UpperCAmelCase__								=  component_class(**__UpperCAmelCase		)
                     setattr(self.backend_tokenizer       ,  __UpperCAmelCase       ,  __UpperCAmelCase		)


   @property
   def 			lowercase_      (self     :						Any		)						->				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 			lowercase_      (self     :						Union[str, Any]       ,  __UpperCAmelCase     :						Dict		)						->				List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  AddedToken(__UpperCAmelCase       ,  lstrip=__UpperCAmelCase       ,  rstrip=__UpperCAmelCase		) if isinstance(__UpperCAmelCase       ,  __UpperCAmelCase		) else value
         UpperCAmelCase__								=  value


   def 			lowercase_      (self     :						List[Any]       ,  *__UpperCAmelCase     :						Optional[Any]       ,  **__UpperCAmelCase     :						List[str]		)						->				BatchEncoding:
         """simple docstring"""



         UpperCAmelCase__								=  kwargs.get("is_split_into_words"       ,  __UpperCAmelCase		)

         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(*__UpperCAmelCase       ,  **__UpperCAmelCase		)


   def 			lowercase_      (self     :						Any       ,  *__UpperCAmelCase     :						Tuple       ,  **__UpperCAmelCase     :						List[Any]		)						->				BatchEncoding:
         """simple docstring"""



         UpperCAmelCase__								=  kwargs.get("is_split_into_words"       ,  __UpperCAmelCase		)

         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(*__UpperCAmelCase       ,  **__UpperCAmelCase		)


   def 			lowercase_      (self     :						List[str]       ,  __UpperCAmelCase     :						str       ,  __UpperCAmelCase     :						Optional[str] = None		)						->				Tuple[str]:
         """simple docstring"""



         UpperCAmelCase__								=  self._tokenizer.model.save(__UpperCAmelCase       ,  name=__UpperCAmelCase		)
         return tuple(__UpperCAmelCase		)


   def 			lowercase_      (self     :						str       ,  __UpperCAmelCase     :						Any       ,  __UpperCAmelCase     :						Union[str, Any]=None		)						->				int:
         """simple docstring"""



         UpperCAmelCase__								=  [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 			lowercase_      (self     :						int       ,  __UpperCAmelCase     :						List[int]       ,  __UpperCAmelCase     :						Optional[List[int]] = None		)						->				List[int]:
         """simple docstring"""



         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 + sep + token_ids_a + sep		) * [0]




from __future__ import annotations

from scipy.special import comb  # type: ignore





class      A							:


   def __init__(self     :						List[Any]       ,  __UpperCAmelCase     :						list[tuple[float, float]]		)						->				List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  list_of_points
         # Degree determines the flexibility of the curve.
         # Degree = 1 will produce a straight line.
         UpperCAmelCase__								=  len(__UpperCAmelCase		) - 1


   def 			lowercase_      (self     :						int       ,  __UpperCAmelCase     :						float		)						->				list[float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."
         UpperCAmelCase__								=  []
         for i in range(len(self.list_of_points		)		):
               # basis function for each i
               output_values.append(
                   comb(self.degree       ,  __UpperCAmelCase		) * ((1 - t) ** (self.degree - i)) * (t**i)		)
         # the basis must sum up to 1 for it to produce a valid Bezier curve.
         assert round(sum(__UpperCAmelCase		)       ,  5		) == 1
         return output_values


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						float		)						->				tuple[float, float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."

         UpperCAmelCase__								=  self.basis_function(__UpperCAmelCase		)
         UpperCAmelCase__								=  0.0
         UpperCAmelCase__								=  0.0
         for i in range(len(self.list_of_points		)		):
               # For all points, sum up the product of i-th basis function and i-th point.
               x += basis_function[i] * self.list_of_points[i][0]
               y += basis_function[i] * self.list_of_points[i][1]
         return (x, y)





   def 			lowercase_      (self     :						Optional[int]       ,  __UpperCAmelCase     :						float = 0.01		)						->				Optional[int]:
         """simple docstring"""



         from matplotlib import pyplot as plt  # type: ignore

         UpperCAmelCase__								=  []  # x coordinates of points to plot
         UpperCAmelCase__								=  []  # y coordinates of points to plot

         UpperCAmelCase__								=  0.0
         while t <= 1:
               UpperCAmelCase__								=  self.bezier_curve_function(__UpperCAmelCase		)
               to_plot_x.append(value[0]		)
               to_plot_y.append(value[1]		)
               t += step_size

         UpperCAmelCase__								=  [i[0] for i in self.list_of_points]
         UpperCAmelCase__								=  [i[1] for i in self.list_of_points]

         plt.plot(
             __UpperCAmelCase       ,  __UpperCAmelCase       ,  color="blue"       ,  label="Curve of Degree " + str(self.degree		)       ,  )
         plt.scatter(__UpperCAmelCase       ,  __UpperCAmelCase       ,  color="red"       ,  label="Control Points"		)
         plt.legend()
         plt.show()


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
      BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
      BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3



