



"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


__SCREAMING_SNAKE_CASE  :						Tuple    							=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE  :						Optional[int]    							=      {'''vocab_file''': '''spiece.model'''}

__SCREAMING_SNAKE_CASE  :						Tuple    							=      {
    '''vocab_file''': {
        '''TsinghuaAI/CPM-Generate''': '''https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model''',
    }
}


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					def __init__(    self				,       lowerCamelCase__				,       lowerCamelCase__=False				,       lowerCamelCase__=True				,       lowerCamelCase__=False				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="<unk>"				,       lowerCamelCase__="<sep>"				,       lowerCamelCase__="<pad>"				,       lowerCamelCase__="<cls>"				,       lowerCamelCase__="<mask>"				,       lowerCamelCase__=["<eop>", "<eod>"]				,       lowerCamelCase__ = None				,       **lowerCamelCase__				,       ):
									_lowerCamelCase        =				AddedToken(lowerCamelCase__				,       lstrip=lowerCamelCase__				,       rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__				,       lowerCamelCase__   ) else mask_token

									_lowerCamelCase        =				{} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    do_lower_case=lowerCamelCase__				,       remove_space=lowerCamelCase__				,       keep_accents=lowerCamelCase__				,       bos_token=lowerCamelCase__				,       eos_token=lowerCamelCase__				,       unk_token=lowerCamelCase__				,       sep_token=lowerCamelCase__				,       pad_token=lowerCamelCase__				,       cls_token=lowerCamelCase__				,       mask_token=lowerCamelCase__				,       additional_special_tokens=lowerCamelCase__				,       sp_model_kwargs=self.sp_model_kwargs				,       **lowerCamelCase__				,       )

									_lowerCamelCase        =				3

									_lowerCamelCase        =				do_lower_case
									_lowerCamelCase        =				remove_space
									_lowerCamelCase        =				keep_accents
									_lowerCamelCase        =				vocab_file

									_lowerCamelCase        =				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
									self.sp_model.Load(lowerCamelCase__   )

									try:
													import jieba
									except ModuleNotFoundError as error:
													raise error.__class__(
													    '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
													    '''See https://pypi.org/project/jieba/ for installation.'''   )
									_lowerCamelCase        =				jieba
									_lowerCamelCase        =				str.maketrans(''' \n'''				,       '''\u2582\u2583'''   )

					@property
					# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
					def 			snake_case__      (    self   ):
									return len(self.sp_model   )

					def 			snake_case__      (    self   ):
									_lowerCamelCase        =				{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   ):
									_lowerCamelCase        =				self.__dict__.copy()
									_lowerCamelCase        =				None
									return state

					def __setstate__(    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				d

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

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

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									if self.remove_space:
													_lowerCamelCase        =				''' '''.join(inputs.strip().split()   )
									else:
													_lowerCamelCase        =				inputs
									_lowerCamelCase        =				outputs.replace('''``'''				,       '''"'''   ).replace('''\'\''''				,       '''"'''   )

									if not self.keep_accents:
													_lowerCamelCase        =				unicodedata.normalize('''NFKD'''				,       lowerCamelCase__   )
													_lowerCamelCase        =				''''''.join([c for c in outputs if not unicodedata.combining(lowerCamelCase__   )]   )
									if self.do_lower_case:
													_lowerCamelCase        =				outputs.lower()

									return outputs

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				self.preprocess_text(lowerCamelCase__   )
									_lowerCamelCase        =				self.sp_model.encode(lowerCamelCase__				,       out_type=lowerCamelCase__   )
									_lowerCamelCase        =				[]
									for piece in pieces:
													if len(lowerCamelCase__   ) > 1 and piece[-1] == str(''','''   ) and piece[-2].isdigit():
																	_lowerCamelCase        =				self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCamelCase__				,       ''''''   )   )
																	if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																					if len(cur_pieces[0]   ) == 1:
																									_lowerCamelCase        =				cur_pieces[1:]
																					else:
																									_lowerCamelCase        =				cur_pieces[0][1:]
																	cur_pieces.append(piece[-1]   )
																	new_pieces.extend(lowerCamelCase__   )
													else:
																	new_pieces.append(lowerCamelCase__   )

									return new_pieces

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									return self.sp_model.PieceToId(lowerCamelCase__   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									return self.sp_model.IdToPiece(lowerCamelCase__   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				''''''.join(lowerCamelCase__   ).replace(lowerCamelCase__				,       ''' '''   ).strip()
									return out_string

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				[self.sep_token_id]
									_lowerCamelCase        =				[self.cls_token_id]
									if token_ids_a is None:
													return token_ids_a + sep + cls
									return token_ids_a + sep + token_ids_a + sep + cls

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None				,       lowerCamelCase__ = False   ):

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

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

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				[self.sep_token_id]
									_lowerCamelCase        =				[2]

									if token_ids_a is None:
													return len(token_ids_a + sep   ) * [0] + cls_segment_id
									return len(token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1] + cls_segment_id

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									if not os.path.isdir(lowerCamelCase__   ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
													return
									_lowerCamelCase        =				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:
																	_lowerCamelCase        =				self.sp_model.serialized_model_proto()
																	fi.write(lowerCamelCase__   )

									return (out_vocab_file,)





					def 			snake_case__      (    self				,       *lowerCamelCase__				,       **lowerCamelCase__   ):
									_lowerCamelCase        =				super()._decode(*lowerCamelCase__				,       **lowerCamelCase__   )
									_lowerCamelCase        =				text.replace(''' '''				,       ''''''   ).replace('''\u2582'''				,       ''' '''   ).replace('''\u2583'''				,       '''\n'''   )
									return text





"""simple docstring"""
from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
__SCREAMING_SNAKE_CASE  :						List[str]    							=      numpy.array([0, 0])
__SCREAMING_SNAKE_CASE  :						Optional[Any]    							=      numpy.array([0.5, 0.866_0254])
__SCREAMING_SNAKE_CASE  :						Tuple    							=      numpy.array([1, 0])
__SCREAMING_SNAKE_CASE  :						List[Any]    							=      [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]



def        lowerCAmelCase_(   lowercase_     :							list[numpy.ndarray]						,   lowercase_     :							int							)	->       list[numpy.ndarray]:
				_lowerCamelCase        =				initial_vectors
				for _ in range(lowercase_							):
								_lowerCamelCase        =				iteration_step(lowercase_							)
				return vectors



def        lowerCAmelCase_(   lowercase_     :							list[numpy.ndarray]							)	->       list[numpy.ndarray]:
				_lowerCamelCase        =				[]
				for i, start_vector in enumerate(vectors[:-1]							):
								_lowerCamelCase        =				vectors[i + 1]
								new_vectors.append(lowercase_							)
								_lowerCamelCase        =				end_vector - start_vector
								new_vectors.append(start_vector + difference_vector / 3							)
								new_vectors.append(
								    start_vector + difference_vector / 3 + rotate(difference_vector / 3						,   60							)							)
								new_vectors.append(start_vector + difference_vector * 2 / 3							)
				new_vectors.append(vectors[-1]							)
				return new_vectors



def        lowerCAmelCase_(   lowercase_     :							numpy.ndarray						,   lowercase_     :							float							)	->       numpy.ndarray:
				_lowerCamelCase        =				numpy.radians(lowercase_							)
				_lowerCamelCase  ,     _lowerCamelCase        =				numpy.cos(lowercase_							), numpy.sin(lowercase_							)
				_lowerCamelCase        =				numpy.array(((c, -s), (s, c))							)
				return numpy.dot(lowercase_						,   lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							list[numpy.ndarray]							)	->       None:
				_lowerCamelCase        =				plt.gca()
				axes.set_aspect('''equal'''							)

				# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
				# y-coordinates as inputs, which are constructed from the vector-list using
				# zip()
				_lowerCamelCase  ,     _lowerCamelCase        =				zip(*lowercase_							)
				plt.plot(lowercase_						,   lowercase_							)
				plt.show()


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			__SCREAMING_SNAKE_CASE  :						str    							=      iterate(INITIAL_VECTORS, 5)
			plot(processed_vectors)
