





'''simple docstring'''






import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


snake_case_     =	"""▁"""

snake_case_     =	get_tests_dir("""fixtures/test_sentencepiece.model""")


@require_sentencepiece
class   _lowercase						(							a		,					unittest.TestCase				):
   _UpperCamelCase       		=   BertGenerationTokenizer
   _UpperCamelCase       		=   False
   _UpperCamelCase       		=   True


   def 					snake_case				( self					):
       super().setUp()

       A       :       Tuple							=						BertGenerationTokenizer(_UpperCAmelCase    ,   keep_accents=_UpperCAmelCase					)
       tokenizer.save_pretrained(self.tmpdirname					)


   def 					snake_case				( self					):
       A       :       str							=						'''<s>'''
       A       :       Tuple							=						1

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCAmelCase					)    ,   _UpperCAmelCase					)
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCAmelCase					)    ,   _UpperCAmelCase					)


   def 					snake_case				( self					):
       A       :       int							=						list(self.get_tokenizer().get_vocab().keys()					)

       self.assertEqual(vocab_keys[0]    ,   '''<unk>'''					)
       self.assertEqual(vocab_keys[1]    ,   '''<s>'''					)
       self.assertEqual(vocab_keys[-1]    ,   '''<pad>'''					)
       self.assertEqual(len(_UpperCAmelCase					)    ,   1_002					)


   def 					snake_case				( self					):
       self.assertEqual(self.get_tokenizer().vocab_size    ,   1_000					)


   def 					snake_case				( self					):
       A       :       Optional[Any]							=						BertGenerationTokenizer(_UpperCAmelCase    ,   keep_accents=_UpperCAmelCase					)

       A       :       List[Any]							=						tokenizer.tokenize('''This is a test'''					)
       self.assertListEqual(_UpperCAmelCase    ,   ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']					)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(_UpperCAmelCase					)    ,   [285, 46, 10, 170, 382]    ,   )

       A       :       List[str]							=						tokenizer.tokenize('''I was born in 92000, and this is falsé.'''					)
       self.assertListEqual(
           _UpperCAmelCase    ,   [
               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''',
               '''.''',
           ]    ,   )
       A       :       Union[str, Any]							=						tokenizer.convert_tokens_to_ids(_UpperCAmelCase					)
       self.assertListEqual(
           _UpperCAmelCase    ,   [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]    ,   )

       A       :       Optional[Any]							=						tokenizer.convert_ids_to_tokens(_UpperCAmelCase					)
       self.assertListEqual(
           _UpperCAmelCase    ,   [
               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 					snake_case				( self					):
       return BertGenerationTokenizer.from_pretrained('''google/bert_for_seq_generation_L-24_bbc_encoder'''					)


   @slow
   def 					snake_case				( self					):
       A       :       Optional[Any]							=						'''Hello World!'''
       A       :       List[Any]							=						[18_536, 2_260, 101]

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


   @slow
   def 					snake_case				( self					):
       A       :       Any							=						(
           '''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'''
       )
       A       :       str							=						[
           871,
           419,
           358,
           946,
           991,
           2_521,
           452,
           358,
           1_357,
           387,
           7_751,
           3_536,
           112,
           985,
           456,
           126,
           865,
           938,
           5_400,
           5_734,
           458,
           1_368,
           467,
           786,
           2_462,
           5_246,
           1_159,
           633,
           865,
           4_519,
           457,
           582,
           852,
           2_557,
           427,
           916,
           508,
           405,
           34_324,
           497,
           391,
           408,
           11_342,
           1_244,
           385,
           100,
           938,
           985,
           456,
           574,
           362,
           12_597,
           3_200,
           3_129,
           1_172,
       ]

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


   @require_torch
   @slow
   def 					snake_case				( self					):
       import torch

       from transformers import BertGenerationConfig, BertGenerationEncoder

       # Build sequence
       A       :       List[Any]							=						list(self.big_tokenizer.get_vocab().keys()					)[:10]
       A       :       int							=						''' '''.join(_UpperCAmelCase					)
       A       :       Any							=						self.big_tokenizer.encode_plus(_UpperCAmelCase    ,   return_tensors='''pt'''    ,   return_token_type_ids=_UpperCAmelCase					)
       A       :       Optional[int]							=						self.big_tokenizer.batch_encode_plus(
           [sequence + ''' ''' + sequence]    ,   return_tensors='''pt'''    ,   return_token_type_ids=_UpperCAmelCase					)

       A       :       Dict							=						BertGenerationConfig()
       A       :       List[Any]							=						BertGenerationEncoder(_UpperCAmelCase					)

       assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

       with torch.no_grad():
           model(**_UpperCAmelCase					)
           model(**_UpperCAmelCase					)


   @slow
   def 					snake_case				( self					):
       # fmt: off
       A       :       Optional[Any]							=						{'''input_ids''': [[39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114], [448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=_UpperCAmelCase    ,   model_name='''google/bert_for_seq_generation_L-24_bbc_encoder'''    ,   revision='''c817d1fd1be2ffa69431227a1fe320544943d4db'''    ,   )







'''simple docstring'''






from math import pi
def 							_lowerCamelCase(  UpperCamelCase__    : int    ,       UpperCamelCase__    : int		)		->  float:
    return 2 * pi * radius * (angle / 360)


if __name__ == "__main__":
     print(arc_length(90, 10))
