
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE				:str									=							'▁'

SCREAMING_SNAKE_CASE				:Any									=							{'vocab_file': 'spiece.model'}

SCREAMING_SNAKE_CASE				:List[str]									=							{
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'}
}

SCREAMING_SNAKE_CASE				:int									=							{
    'google/pegasus-xsum': 512,
}


SCREAMING_SNAKE_CASE				:Tuple									=							logging.get_logger(__name__)





class 				UpperCAmelCase (    __SCREAMING_SNAKE_CASE    ):




	'''simple docstring'''





	snake_case_          =	VOCAB_FILES_NAMES

	snake_case_          =	VOCAB_FILES_NAMES
	snake_case_          =	PRETRAINED_VOCAB_FILES_MAP
	snake_case_          =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case_          =	["input_ids", "attention_mask"]






	def __init__(			self   :					Tuple				,A   :					Union[str, Any]				,A   :					List[str]="<pad>"				,A   :					Dict="</s>"				,A   :					Union[str, Any]="<unk>"				,A   :					List[str]="<mask_2>"				,A   :					Optional[int]="<mask_1>"				,A   :					Union[str, Any]=None				,A   :					Optional[Any]=1_03				,A   :					Optional[Dict[str, Any]] = None				,**A   :					Dict				,):
					__A       =					offset
					if additional_special_tokens is not None:
									if not isinstance(A				,A					):
													raise TypeError(
													    f'''additional_special_tokens should be of type {type(A					)}, but is'''
													    f''' {type(A					)}'''					)

									__A       =					(
									    ([mask_token_sent] + additional_special_tokens)
									    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
									    else additional_special_tokens
									)
									# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
									additional_special_tokens_extended += [
									    f'''<unk_{i}>''' for i in range(len(A					)				,self.offset - 1					)
									]

									if len(set(A					)					) != len(A					):
													raise ValueError(
													    "Please make sure that the provided additional_special_tokens do not contain an incorrectly"
													    f''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'''					)
									__A       =					additional_special_tokens_extended
					else:
									__A       =					[mask_token_sent] if mask_token_sent is not None else []
									additional_special_tokens += [f'''<unk_{i}>''' for i in range(2				,self.offset					)]

					__A       =					{} if sp_model_kwargs is None else sp_model_kwargs

					super().__init__(
					    eos_token=A				,unk_token=A				,mask_token=A				,pad_token=A				,mask_token_sent=A				,offset=A				,additional_special_tokens=A				,sp_model_kwargs=self.sp_model_kwargs				,**A				,)
					__A       =					mask_token_sent
					__A       =					vocab_file
					__A       =					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
					self.sp_model.Load(A					)

					# add special tokens to encoder dict
					__A       =					{
					    0: self.pad_token,
					    1: self.eos_token,
					}

					if self.mask_token_sent is not None:
									self.encoder.update(
									    {
									        2: self.mask_token_sent,
									        3: self.mask_token,
									    }					)

					if self.offset > 0:
									# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
									# mask_token_sent is already added to list -> so start at 1
									self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1				,self.offset - 1					)}					)

					__A       =					{v: k for k, v in self.encoder.items()}






	@property
	def 							UpperCamelCase_    (			self   :					Optional[Any]					):
					return len(self.sp_model					) + self.offset






	def 							UpperCamelCase_    (			self   :					Dict					):
					__A       =					{self.convert_ids_to_tokens(A					): i for i in range(self.vocab_size					)}
					vocab.update(self.added_tokens_encoder					)
					return vocab






	def __getstate__(			self   :					Tuple					):
					__A       =					self.__dict__.copy()
					__A       =					None
					return state






	def __setstate__(			self   :					int				,A   :					Optional[int]					):
					__A       =					d

					# for backward compatibility
					if not hasattr(self				,"sp_model_kwargs"					):
									__A       =					{}

					__A       =					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
					self.sp_model.Load(self.vocab_file					)






	def 							UpperCamelCase_    (			self   :					int				,A   :					str					):
					return self.sp_model.encode(A				,out_type=A					)






	def 							UpperCamelCase_    (			self   :					Optional[int]				,A   :					str					):
					if token in self.decoder:
									return self.decoder[token]
					elif token in self.added_tokens_decoder:
									return self.added_tokens_decoder[token]
					__A       =					self.sp_model.piece_to_id(A					)
					return sp_id + self.offset






	def 							UpperCamelCase_    (			self   :					int				,A   :					int					):
					if index in self.encoder:
									return self.encoder[index]
					elif index in self.added_tokens_encoder:
									return self.added_tokens_encoder[index]
					else:
									__A       =					self.sp_model.IdToPiece(index - self.offset					)
					return token






	def 							UpperCamelCase_    (			self   :					Optional[int]				,A   :					str					):
					__A       =					[]
					__A       =					""
					for token in tokens:
									# make sure that special tokens are not decoded using sentencepiece model
									if token in self.all_special_tokens:
													out_string += self.sp_model.decode(A					) + token
													__A       =					[]
									else:
													current_sub_tokens.append(A					)
					out_string += self.sp_model.decode(A					)
					return out_string.strip()






	def 							UpperCamelCase_    (			self   :					Union[str, Any]				,A   :					Optional[Any]=False					):
					return 1






	def 							UpperCamelCase_    (			self   :					Optional[Any]				,A   :					int					):
					__A       =					set(self.all_special_ids					)  # call it once instead of inside list comp
					all_special_ids.remove(self.unk_token_id					)  # <unk> is only sometimes special

					return [1 if x in all_special_ids else 0 for x in seq]






	def 							UpperCamelCase_    (			self   :					Optional[Any]				,A   :					List				,A   :					Optional[List] = None				,A   :					bool = False					):
					if already_has_special_tokens:
									return self._special_token_mask(A					)
					elif token_ids_a is None:
									return self._special_token_mask(A					) + [1]
					else:
									return self._special_token_mask(token_ids_a + token_ids_a					) + [1]






	def 							UpperCamelCase_    (			self   :					List[str]				,A   :					Any				,A   :					Union[str, Any]=None					):
					if token_ids_a is None:
									return token_ids_a + [self.eos_token_id]
					# We don't expect to process pairs, but leave the pair logic for API consistency
					return token_ids_a + token_ids_a + [self.eos_token_id]







	def 							UpperCamelCase_    (			self   :					Tuple				,A   :					str				,A   :					Optional[str] = None					):
					if not os.path.isdir(A					):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
									return
					__A       =					os.path.join(
					    A				,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)

					if os.path.abspath(self.vocab_file					) != os.path.abspath(A					) and os.path.isfile(self.vocab_file					):
									copyfile(self.vocab_file				,A					)
					elif not os.path.isfile(self.vocab_file					):
									with open(A				,"wb"					) as fi:
													__A       =					self.sp_model.serialized_model_proto()
													fi.write(A					)

					return (out_vocab_file,)







from __future__ import annotations

from scipy.special import comb  # type: ignore







class       __A							:




      """simple docstring"""







      def __init__(		self   ,				a__):



             """simple docstring"""





             _lowerCamelCase				:  str						=		list_of_points
             # Degree determines the flexibility of the curve.
             # Degree = 1 will produce a straight line.
             _lowerCamelCase				:  List[Any]						=		len(a__) - 1


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





             assert 0 <= t <= 1, "Time t must be between 0 and 1."
             _lowerCamelCase				:  list[float]						=		[]
             for i in range(len(self.list_of_points)):
                    # basis function for each i
                    output_values.append(
                        comb(self.degree   ,				a__) * ((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(a__)   ,				5) == 1
             return output_values


      def 					__snake_case      (		self   ,				a__):



             """simple docstring"""





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

             _lowerCamelCase				:  Any						=		self.basis_function(a__)
             _lowerCamelCase				:  List[Any]						=		0.0
             _lowerCamelCase				:  List[Any]						=		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 					__snake_case      (		self   ,				a__ = 0.01):



             """simple docstring"""





             from matplotlib import pyplot as plt  # type: ignore

             _lowerCamelCase				:  list[float]						=		[]  # x coordinates of points to plot
             _lowerCamelCase				:  list[float]						=		[]  # y coordinates of points to plot

             _lowerCamelCase				:  List[Any]						=		0.0
             while t <= 1:
                    _lowerCamelCase				:  Tuple						=		self.bezier_curve_function(a__)
                    to_plot_x.append(value[0])
                    to_plot_y.append(value[1])
                    t += step_size

             _lowerCamelCase				:  List[Any]						=		[i[0] for i in self.list_of_points]
             _lowerCamelCase				:  Union[str, Any]						=		[i[1] for i in self.list_of_points]

             plt.plot(
                 a__   ,				a__   ,				color='''blue'''   ,				label='''Curve of Degree ''' + str(self.degree)   ,				)
             plt.scatter(a__   ,				a__   ,				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

