






'''simple docstring'''



import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE								=	get_tests_dir('fixtures/test_sentencepiece.model')
@require_sentencepiece
@require_tokenizers
class UpperCAmelCase_					(    UpperCamelCase_				,       unittest.TestCase				):




      """simple docstring"""




      UpperCamelCase_								=			ReformerTokenizer
      UpperCamelCase_								=			ReformerTokenizerFast
      UpperCamelCase_								=			True
      UpperCamelCase_								=			False
      UpperCamelCase_								=			True






      def 				A__      ( self			:		Dict		)  ->  List[str]:


       '''simple docstring'''

       super().setUp()

       lowercase					:   List[Any]				  =ReformerTokenizer(_a     ,      keep_accents=_a		)
       tokenizer.save_pretrained(self.tmpdirname		)






      def 				A__      ( self			:		List[str]		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   str				  ="""<s>"""
       lowercase					:   Optional[int]				  =1

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






      def 				A__      ( self			:		Optional[Any]		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   Optional[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]     ,      '''j'''		)
       self.assertEqual(len(_a		)     ,      1000		)






      def 				A__      ( self			:		Any		)  ->  Any:


       '''simple docstring'''

       self.assertEqual(self.get_tokenizer().vocab_size     ,      1000		)






      def 				A__      ( self			:		Any		)  ->  Optional[int]:


       '''simple docstring'''

       if not self.test_rust_tokenizer:
        return

       lowercase					:   List[str]				  =self.get_tokenizer()
       lowercase					:   Optional[Any]				  =self.get_rust_tokenizer()

       lowercase					:   int				  ="""I was born in 92000, and this is falsé."""

       lowercase					:   List[str]				  =tokenizer.tokenize(_a		)
       lowercase					:   Any				  =rust_tokenizer.tokenize(_a		)
       self.assertListEqual(_a     ,      _a		)

       lowercase					:   List[Any]				  =tokenizer.encode(_a     ,      add_special_tokens=_a		)
       lowercase					:   Union[str, Any]				  =rust_tokenizer.encode(_a     ,      add_special_tokens=_a		)
       self.assertListEqual(_a     ,      _a		)

       lowercase					:   str				  =self.get_rust_tokenizer()
       lowercase					:   List[str]				  =tokenizer.encode(_a		)
       lowercase					:   Any				  =rust_tokenizer.encode(_a		)
       self.assertListEqual(_a     ,      _a		)






      def 				A__      ( self			:		Union[str, Any]     ,      UpperCAmelCase			:		int=15		)  ->  Union[str, Any]:


       '''simple docstring'''

       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'		):
         lowercase					:   Dict				  =self.rust_tokenizer_class.from_pretrained(_a     ,      **_a		)

         # Simple input
         lowercase					:   List[Any]				  ="""This is a simple input"""
         lowercase					:   Optional[Any]				  =["""This is a simple input 1""", """This is a simple input 2"""]
         lowercase					:   int				  =("""This is a simple input""", """This is a pair""")
         lowercase					:   Dict				  =[
             ("""This is a simple input 1""", """This is a simple input 2"""),
             ("""This is a simple pair 1""", """This is a simple pair 2"""),
         ]

         # Simple input tests
         self.assertRaises(_a     ,      tokenizer_r.encode     ,      _a     ,      max_length=_a     ,      padding='''max_length'''		)

         # Simple input
         self.assertRaises(_a     ,      tokenizer_r.encode_plus     ,      _a     ,      max_length=_a     ,      padding='''max_length'''		)

         # Simple input
         self.assertRaises(
             _a     ,      tokenizer_r.batch_encode_plus     ,      _a     ,      max_length=_a     ,      padding='''max_length'''     ,      )

         # Pair input
         self.assertRaises(_a     ,      tokenizer_r.encode     ,      _a     ,      max_length=_a     ,      padding='''max_length'''		)

         # Pair input
         self.assertRaises(_a     ,      tokenizer_r.encode_plus     ,      _a     ,      max_length=_a     ,      padding='''max_length'''		)

         # Pair input
         self.assertRaises(
             _a     ,      tokenizer_r.batch_encode_plus     ,      _a     ,      max_length=_a     ,      padding='''max_length'''     ,      )






      def 				A__      ( self			:		Optional[int]		)  ->  Optional[Any]:


       '''simple docstring'''

       pass






      def 				A__      ( self			:		Optional[Any]		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   List[Any]				  =ReformerTokenizer(_a     ,      keep_accents=_a		)

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

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

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

       lowercase					:   Union[str, Any]				  =tokenizer.convert_ids_to_tokens(_a		)
       self.assertListEqual(
           _a     ,      [
               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			:		Dict		)  ->  Optional[Any]:


       '''simple docstring'''

       return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''		)






      @slow
      def 				A__      ( self			:		Any		)  ->  Tuple:


       '''simple docstring'''

       lowercase					:   Any				  ="""Hello World!"""
       lowercase					:   List[str]				  =[126, 32, 262, 152, 38, 72, 287]

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






      @slow
      def 				A__      ( self			:		str		)  ->  Union[str, Any]:


       '''simple docstring'''

       lowercase					:   int				  =(
           """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"""
       )
       lowercase					:   int				  =[
           108,
           265,
           24,
           111,
           4,
           258,
           156,
           35,
           28,
           275,
           3,
           259,
           297,
           260,
           84,
           4,
           35,
           110,
           44,
           8,
           259,
           91,
           268,
           21,
           11,
           209,
           274,
           109,
           266,
           277,
           117,
           86,
           93,
           315,
           258,
           278,
           258,
           277,
           258,
           0,
           258,
           288,
           258,
           319,
           258,
           0,
           258,
           0,
           258,
           0,
           258,
           0,
           258,
           287,
           258,
           315,
           258,
           289,
           258,
           278,
           99,
           269,
           266,
           262,
           8,
           259,
           241,
           4,
           217,
           230,
           268,
           266,
           55,
           168,
           106,
           75,
           193,
           266,
           223,
           27,
           49,
           26,
           282,
           25,
           264,
           299,
           19,
           26,
           0,
           258,
           277,
           117,
           86,
           93,
           176,
           183,
           270,
           11,
           262,
           42,
           61,
           265,
       ]

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






      @require_torch
      @slow
      def 				A__      ( self			:		str		)  ->  Tuple:


       '''simple docstring'''

       import torch

       from transformers import ReformerConfig, ReformerModel

       # Build sequence
       lowercase					:   Dict				  =list(self.big_tokenizer.get_vocab().keys()		)[:10]
       lowercase					:   List[Any]				  =""" """.join(_a		)
       lowercase					:   str				  =self.big_tokenizer.encode_plus(_a     ,      return_tensors='''pt'''		)
       lowercase					:   Tuple				  =self.big_tokenizer.batch_encode_plus([sequence, sequence]     ,      return_tensors='''pt'''		)

       lowercase					:   Optional[int]				  =ReformerConfig()
       # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
       lowercase					:   Any				  =encoded_sequence["""input_ids"""].shape
       lowercase					:   Any				  =ReformerModel(_a		)

       # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
       assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

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






      @slow
      def 				A__      ( self			:		Optional[int]		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   Optional[int]				  ={"""input_ids""": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], """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]]}  # noqa: E501
       # fmt: on

       # This tokenizer does not know some characters like ")".
       # That is the reason why we use very simple texts here.
       # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
       lowercase					:   Tuple				  =[
           """This is a very simple sentence.""",
           """The quick brown fox jumps over the lazy dog.""",
       ]

       self.tokenizer_integration_test_util(
           expected_encoding=_a     ,      model_name='''google/reformer-crime-and-punishment'''     ,      revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a'''     ,      padding=_a     ,      sequences=_a     ,      )











'''simple docstring'''



from __future__ import annotations

SCREAMING_SNAKE_CASE						=	8.988E9  # units = N * m^s * C^-2


def 							lowercase_				(    __A :       float					,      __A :       float					,      __A :       float					,      __A :       float			)       ->      dict[str, float]:



 """simple docstring"""




 lowercase					:   Dict				  =abs(chargea * chargea			)

 if (force, chargea, chargea, distance).count(0			) != 1:
  raise ValueError('''One and only one argument must be 0'''			)
 if distance < 0:
  raise ValueError('''Distance cannot be negative'''			)
 if force == 0:
  lowercase					:   Union[str, Any]				  =COULOMBS_CONSTANT * charge_product / (distance**2)
  return {"force": force}
 elif chargea == 0:
  lowercase					:   int				  =abs(__A			) * (distance**2) / (COULOMBS_CONSTANT * chargea)
  return {"charge1": chargea}
 elif chargea == 0:
  lowercase					:   int				  =abs(__A			) * (distance**2) / (COULOMBS_CONSTANT * chargea)
  return {"charge2": chargea}
 elif distance == 0:
  lowercase					:   Tuple				  =(COULOMBS_CONSTANT * charge_product / abs(__A			)) ** 0.5
  return {"distance": distance}
 raise ValueError('''Exactly one argument must be 0'''			)


if __name__ == "__main__":
      import doctest

      doctest.testmod()



