




'''simple docstring'''







import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A     =get_tests_dir('fixtures/test_sentencepiece.model')


@require_sentencepiece
@require_tokenizers
class 			_a  (	__a							,							unittest.TestCase ):
       __a				:     int   				=					XGLMTokenizer
       __a				:     Any   				=					XGLMTokenizerFast
       __a				:     Any   				=					True
       __a				:     Tuple   				=					True
       def     A      (	self						:	Optional[int]				):



           '''simple docstring'''

           super().setUp()

           # We have a SentencePiece fixture for testing
           UpperCAmelCase			       =		XGLMTokenizer(lowercase   ,				keep_accents=lowercase				)
           tokenizer.save_pretrained(self.tmpdirname				)
       def     A      (	self						:	Any				):



           '''simple docstring'''

           UpperCAmelCase			       =		'''<pad>'''
           UpperCAmelCase			       =		1

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase				)   ,				lowercase				)
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase				)   ,				lowercase				)
       def     A      (	self						:	str				):



           '''simple docstring'''

           UpperCAmelCase			       =		list(self.get_tokenizer().get_vocab().keys()				)

           self.assertEqual(vocab_keys[0]   ,				'''<s>'''				)
           self.assertEqual(vocab_keys[1]   ,				'''<pad>'''				)
           self.assertEqual(len(lowercase				)   ,				1_008				)
       def     A      (	self						:	str				):



           '''simple docstring'''

           self.assertEqual(self.get_tokenizer().vocab_size   ,				1_008				)
       def     A      (	self						:	List[str]				):



           '''simple docstring'''

           UpperCAmelCase			       =		XGLMTokenizer(lowercase   ,				keep_accents=lowercase				)

           UpperCAmelCase			       =		tokenizer.tokenize('''This is a test'''				)
           self.assertListEqual(lowercase   ,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']				)

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(lowercase				)   ,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,				)

           UpperCAmelCase			       =		tokenizer.tokenize('''I was born in 92000, and this is falsé.'''				)
           self.assertListEqual(
               lowercase   ,				[
                   SPIECE_UNDERLINE + '''I''',
                   SPIECE_UNDERLINE + '''was''',
                   SPIECE_UNDERLINE + '''b''',
                   '''or''',
                   '''n''',
                   SPIECE_UNDERLINE + '''in''',
                   SPIECE_UNDERLINE + '''''',
                   '''9''',
                   '''2''',
                   '''0''',
                   '''0''',
                   '''0''',
                   ''',''',
                   SPIECE_UNDERLINE + '''and''',
                   SPIECE_UNDERLINE + '''this''',
                   SPIECE_UNDERLINE + '''is''',
                   SPIECE_UNDERLINE + '''f''',
                   '''al''',
                   '''s''',
                   '''é''',
                   '''.''',
               ]   ,				)
           UpperCAmelCase			       =		tokenizer.convert_tokens_to_ids(lowercase				)
           self.assertListEqual(
               lowercase   ,				[
                   value + tokenizer.fairseq_offset
                   for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
               ]   ,				)

           UpperCAmelCase			       =		tokenizer.convert_ids_to_tokens(lowercase				)
           self.assertListEqual(
               lowercase   ,				[
                   SPIECE_UNDERLINE + '''I''',
                   SPIECE_UNDERLINE + '''was''',
                   SPIECE_UNDERLINE + '''b''',
                   '''or''',
                   '''n''',
                   SPIECE_UNDERLINE + '''in''',
                   SPIECE_UNDERLINE + '''''',
                   '''<unk>''',
                   '''2''',
                   '''0''',
                   '''0''',
                   '''0''',
                   ''',''',
                   SPIECE_UNDERLINE + '''and''',
                   SPIECE_UNDERLINE + '''this''',
                   SPIECE_UNDERLINE + '''is''',
                   SPIECE_UNDERLINE + '''f''',
                   '''al''',
                   '''s''',
                   '''<unk>''',
                   '''.''',
               ]   ,				)
       @cached_property
       def     A      (	self						:	Any				):



           '''simple docstring'''

           return XGLMTokenizer.from_pretrained('''facebook/xglm-564M'''				)
       def     A      (	self						:	str				):



           '''simple docstring'''

           with tempfile.NamedTemporaryFile() as f:
               shutil.copyfile(lowercase   ,				f.name				)
               UpperCAmelCase			       =		XGLMTokenizer(f.name   ,				keep_accents=lowercase				)
               UpperCAmelCase			       =		pickle.dumps(lowercase				)
           pickle.loads(lowercase				)
       def     A      (	self						:	List[str]				):



           '''simple docstring'''

           if not self.test_rust_tokenizer:
               return

           UpperCAmelCase			       =		self.get_tokenizer()
           UpperCAmelCase			       =		self.get_rust_tokenizer()

           UpperCAmelCase			       =		'''I was born in 92000, and this is falsé.'''

           UpperCAmelCase			       =		tokenizer.tokenize(lowercase				)
           UpperCAmelCase			       =		rust_tokenizer.tokenize(lowercase				)
           self.assertListEqual(lowercase   ,				lowercase				)

           UpperCAmelCase			       =		tokenizer.encode(lowercase   ,				add_special_tokens=lowercase				)
           UpperCAmelCase			       =		rust_tokenizer.encode(lowercase   ,				add_special_tokens=lowercase				)
           self.assertListEqual(lowercase   ,				lowercase				)

           UpperCAmelCase			       =		self.get_rust_tokenizer()
           UpperCAmelCase			       =		tokenizer.encode(lowercase				)
           UpperCAmelCase			       =		rust_tokenizer.encode(lowercase				)
           self.assertListEqual(lowercase   ,				lowercase				)
       @slow
       def     A      (	self						:	List[Any]				):



           '''simple docstring'''

           UpperCAmelCase			       =		'''Hello World!'''
           UpperCAmelCase			       =		[2, 31_227, 4_447, 35]

           self.assertListEqual(lowercase   ,				self.big_tokenizer.encode(lowercase				)				)
       @slow
       def     A      (	self						:	int				):



           '''simple docstring'''

           UpperCAmelCase			       =		(
               '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
               ''' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'''
           )
           # fmt: off
           UpperCAmelCase			       =		[2, 1_018, 67, 11, 1_988, 2_617, 5_631, 278, 11, 3_407, 48, 71_630, 28_085, 4, 3_234, 157, 13, 6, 5, 6, 4, 3_526, 768, 15, 659, 57, 298, 3_983, 864, 129, 21, 6, 5, 13_675, 377, 652, 7_580, 10_341, 155, 2_817, 422, 1_666, 7, 1_674, 53, 113, 202_277, 17_892, 33, 60, 87, 4, 3_234, 157, 61, 2_667, 52_376, 19, 88, 23, 735]
           # fmt: on

           self.assertListEqual(lowercase   ,				self.big_tokenizer.encode(lowercase				)				)







       @slow
       def     A      (	self						:	List[str]				):



           '''simple docstring'''

           UpperCAmelCase			       =		{
               '''input_ids''': [[2, 108_825, 1_163, 15, 88_010, 473, 15_898, 157, 13_672, 1_857, 312, 8, 238_021, 1_163, 53, 13_672, 1_857, 312, 8, 53_283, 182_396, 8, 18_566, 16, 36_733, 4_101, 8, 230, 244_017, 122_553, 7, 15, 132_597, 4, 293, 12_511, 7_610, 4, 3_414, 132_597, 9, 4, 32_361, 362, 4, 734, 28_512, 32_569, 18, 4, 32_361, 26_096, 14_982, 73, 18_715, 21_433, 235_261, 15, 492, 12_427, 16, 53, 18_715, 21_433, 65_454, 15, 23_659, 563, 16, 278, 597, 2_843, 595, 7_931, 182_396, 64_186, 22, 886, 595, 132_981, 53, 25_540, 3_449, 43_982, 39_901, 5_951, 878, 330, 4, 27_694, 80_269, 312, 53, 6_517, 11_780, 611, 20_408, 5], [2, 6, 132_597, 67, 42_897, 33, 592, 8, 163_729, 25_540, 361, 136_997, 109_514, 173_230, 7, 501, 60, 102_913, 196, 5_631, 235, 63_243, 473, 6, 231_757, 74, 5_277, 7_905, 53, 3_095, 37_317, 22, 454, 183_874, 5], [2, 268, 31_298, 46_530, 6, 132_935, 43_831, 7, 597, 32, 24, 3_688, 9_865, 5]],
               '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
           }  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=lowercase   ,				model_name='''facebook/xglm-564M'''   ,				padding=lowercase   ,				)









'''simple docstring'''






from __future__ import annotations

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

# initial triangle of Koch snowflake
UpperCamelCase__:   Tuple								=			numpy.array([0, 0])
UpperCamelCase__:   Union[str, Any]								=			numpy.array([0.5, 0.8660254])
UpperCamelCase__:   Dict								=			numpy.array([1, 0])
UpperCamelCase__:   int								=			[VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]


def  snake_case_     (					_lowerCAmelCase  :						list[numpy.ndarray]   ,      _lowerCAmelCase  :						int  )      ->   list[numpy.ndarray]:
							UpperCAmelCase :       Union[str, Any] 							=		initial_vectors
							for _ in range(_lowerCAmelCase  ):
														UpperCAmelCase :       Union[str, Any] 							=		iteration_step(_lowerCAmelCase  )
							return vectors


def  snake_case_     (					_lowerCAmelCase  :						list[numpy.ndarray]  )      ->   list[numpy.ndarray]:
							UpperCAmelCase :       Tuple 							=		[]
							for i, start_vector in enumerate(vectors[:-1]  ):
														UpperCAmelCase :       List[str] 							=		vectors[i + 1]
														new_vectors.append(_lowerCAmelCase  )
														UpperCAmelCase :       Optional[Any] 							=		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  snake_case_     (					_lowerCAmelCase  :						numpy.ndarray   ,      _lowerCAmelCase  :						float  )      ->   numpy.ndarray:
							UpperCAmelCase :       List[str] 							=		numpy.radians(_lowerCAmelCase  )
							UpperCAmelCase							,		UpperCAmelCase :       Tuple 							=		numpy.cos(_lowerCAmelCase  ), numpy.sin(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		numpy.array(((c, -s), (s, c))  )
							return numpy.dot(_lowerCAmelCase   ,      _lowerCAmelCase  )


def  snake_case_     (					_lowerCAmelCase  :						list[numpy.ndarray]  )      ->   None:
							UpperCAmelCase :       List[Any] 							=		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()
							UpperCAmelCase							,		UpperCAmelCase :       str 							=		zip(*_lowerCAmelCase  )
							plt.plot(_lowerCAmelCase   ,      _lowerCAmelCase  )
							plt.show()


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						UpperCamelCase__:   List[Any]								=			iterate(INITIAL_VECTORS, 5)
						plot(processed_vectors)





