

"""simple docstring"""




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


A_							:	str      =       logging.get_logger(__name__)

A_							:	Dict      =       {'vocab_file': 'spiece.model'}

A_							:	Optional[int]      =       {
    'vocab_file': {
        'bert_for_seq_generation': (
            'https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'
        ),
    }
}

A_							:	Dict      =       {'bert_for_seq_generation': 512}





class       lowerCamelCase  (_UpperCamelCase	):
			lowerCamelCase__      :						Any    						=							VOCAB_FILES_NAMES
			lowerCamelCase__      :						Union[str, Any]    						=							PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__      :						int    						=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__      :						List[int]    						=							[]
			lowerCamelCase__      :						Optional[Any]    						=							["""input_ids""", """attention_mask"""]

			def __init__(    self :  List[Any]			, __UpperCAmelCase :  Tuple			, __UpperCAmelCase :  str="<s>"			, __UpperCAmelCase :  Optional[int]="</s>"			, __UpperCAmelCase :  int="<unk>"			, __UpperCAmelCase :  List[str]="<pad>"			, __UpperCAmelCase :  Union[str, Any]="<::::>"			, __UpperCAmelCase :  Optional[Dict[str, Any]] = None			, **__UpperCAmelCase :  List[str]			, )      ->			None:
						SCREAMING_SNAKE_CASE__									=					{} if sp_model_kwargs is None else sp_model_kwargs

						# Add extra_ids to the special token list
						super().__init__(
						    bos_token=__lowerCamelCase			, eos_token=__lowerCamelCase			, unk_token=__lowerCamelCase			, pad_token=__lowerCamelCase			, sep_token=__lowerCamelCase			, sp_model_kwargs=self.sp_model_kwargs			, **__lowerCamelCase			, )

						SCREAMING_SNAKE_CASE__									=					vocab_file

						SCREAMING_SNAKE_CASE__									=					spm.SentencePieceProcessor(**self.sp_model_kwargs				)
						self.sp_model.Load(__lowerCamelCase				)

			@property
			def     SCREAMING_SNAKE_CASE (    self :  Dict				)      ->			Dict:
						return self.sp_model.get_piece_size()

			def     SCREAMING_SNAKE_CASE (    self :  Tuple				)      ->			Optional[int]:
						SCREAMING_SNAKE_CASE__									=					{self.convert_ids_to_tokens(__lowerCamelCase				): i for i in range(self.vocab_size				)}
						vocab.update(self.added_tokens_encoder				)
						return vocab

			def __getstate__(    self :  Dict				)      ->			Optional[Any]:
						SCREAMING_SNAKE_CASE__									=					self.__dict__.copy()
						SCREAMING_SNAKE_CASE__									=					None
						return state

			def __setstate__(    self :  Optional[Any]			, __UpperCAmelCase :  Dict				)      ->			Optional[Any]:
						SCREAMING_SNAKE_CASE__									=					d

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

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

			def     SCREAMING_SNAKE_CASE (    self :  Union[str, Any]			, __UpperCAmelCase :  str				)      ->			List[str]:
						return self.sp_model.encode(__lowerCamelCase			, out_type=__lowerCamelCase				)

			def     SCREAMING_SNAKE_CASE (    self :  str			, __UpperCAmelCase :  Union[str, Any]				)      ->			int:
						return self.sp_model.piece_to_id(__lowerCamelCase				)

			def     SCREAMING_SNAKE_CASE (    self :  Tuple			, __UpperCAmelCase :  List[str]				)      ->			Any:
						SCREAMING_SNAKE_CASE__									=					self.sp_model.IdToPiece(__lowerCamelCase				)
						return token

			def     SCREAMING_SNAKE_CASE (    self :  Any			, __UpperCAmelCase :  Dict				)      ->			Any:
						SCREAMING_SNAKE_CASE__									=					[]
						SCREAMING_SNAKE_CASE__									=					""""""
						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(__lowerCamelCase				) + token
												SCREAMING_SNAKE_CASE__									=					[]
									else:
												current_sub_tokens.append(__lowerCamelCase				)
						out_string += self.sp_model.decode(__lowerCamelCase				)
						return out_string.strip()





			def     SCREAMING_SNAKE_CASE (    self :  Dict			, __UpperCAmelCase :  str			, __UpperCAmelCase :  Optional[str] = None				)      ->			Tuple[str]:
						if not os.path.isdir(__lowerCamelCase				):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""				)
									return
						SCREAMING_SNAKE_CASE__									=					os.path.join(
						    __lowerCamelCase			, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

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

						return (out_vocab_file,)








from __future__ import annotations

from scipy.special import comb  # type: ignore




class     snake_case__							:
				"""simple docstring"""



				def __init__(      self				:     Any					,      __lowerCamelCase				:     list[tuple[float, float]]							)					->     Tuple:
							a    =			list_of_points
							# Degree determines the flexibility of the curve.
							# Degree = 1 will produce a straight line.
							a    =			len(__lowerCamelCase							) - 1





				def 							__UpperCAmelCase							(      self				:     Union[str, Any]					,      __lowerCamelCase				:     float							)					->     list[float]:
							assert 0 <= t <= 1, "Time t must be between 0 and 1."
							a    =			[]
							for i in range(len(self.list_of_points							)							):
										# basis function for each i
										output_values.append(
										    comb(self.degree					,      __lowerCamelCase							) * ((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(__lowerCamelCase							)					,      5							) == 1
							return output_values





				def 							__UpperCAmelCase							(      self				:     Optional[Any]					,      __lowerCamelCase				:     float							)					->     tuple[float, float]:
							assert 0 <= t <= 1, "Time t must be between 0 and 1."

							a    =			self.basis_function(__lowerCamelCase							)
							a    =			0.0
							a    =			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 							__UpperCAmelCase							(      self				:     Optional[Any]					,      __lowerCamelCase				:     float = 0.01							)					->     List[str]:
							from matplotlib import pyplot as plt  # type: ignore

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

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

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

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






