

import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 						__magic_name__			(							lowerCamelCase__		,       unittest.TestCase							):

   '''simple docstring'''




   lowerCamelCase__ :	Tuple    =   GPTaTokenizer
   lowerCamelCase__ :	Union[str, Any]    =   GPTaTokenizerFast
   lowerCamelCase__ :	Dict    =   True
   lowerCamelCase__ :	str    =   {'add_prefix_space': True}
   lowerCamelCase__ :	Tuple    =   False



   def  _UpperCAmelCase (				self       )							->    Optional[int]:






     """simple docstring"""






     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     a__  =[
         '''l''',
         '''o''',
         '''w''',
         '''e''',
         '''r''',
         '''s''',
         '''t''',
         '''i''',
         '''d''',
         '''n''',
         '''\u0120''',
         '''\u0120l''',
         '''\u0120n''',
         '''\u0120lo''',
         '''\u0120low''',
         '''er''',
         '''\u0120lowest''',
         '''\u0120newer''',
         '''\u0120wider''',
         '''<unk>''',
         '''<|endoftext|>''',
     ]
     a__  =dict(zip(lowercase_,    range(len(lowercase_       )       )       )       )
     a__  =['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
     a__  ={'''unk_token''': '''<unk>'''}

     a__  =os.path.join(self.tmpdirname,    VOCAB_FILES_NAMES['''vocab_file''']       )
     a__  =os.path.join(self.tmpdirname,    VOCAB_FILES_NAMES['''merges_file''']       )
     with open(self.vocab_file,    '''w''',    encoding='''utf-8'''       ) as fp:
       fp.write(json.dumps(lowercase_       ) + '''\n'''       )
     with open(self.merges_file,    '''w''',    encoding='''utf-8'''       ) as fp:
       fp.write('''\n'''.join(lowercase_       )       )



   def  _UpperCAmelCase (				self,    **lowercase_       )							->    Dict:






     """simple docstring"""






     kwargs.update(self.special_tokens_map       )
     return GPTaTokenizer.from_pretrained(self.tmpdirname,    **lowercase_       )



   def  _UpperCAmelCase (				self,    **lowercase_       )							->    List[str]:






     """simple docstring"""






     kwargs.update(self.special_tokens_map       )
     return GPTaTokenizerFast.from_pretrained(self.tmpdirname,    **lowercase_       )



   def  _UpperCAmelCase (				self,    lowercase_       )							->    List[Any]:






     """simple docstring"""






     a__  ='''lower newer'''
     a__  ='''lower newer'''
     return input_text, output_text



   def  _UpperCAmelCase (				self       )							->    Any:






     """simple docstring"""






     a__  =GPTaTokenizer(self.vocab_file,    self.merges_file,    **self.special_tokens_map       )
     a__  ='''lower newer'''
     a__  =['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
     a__  =tokenizer.tokenize(lowercase_,    add_prefix_space=lowercase_       )
     self.assertListEqual(lowercase_,    lowercase_       )

     a__  =tokens + [tokenizer.unk_token]
     a__  =[14, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_       ),    lowercase_       )



   def  _UpperCAmelCase (				self       )							->    Dict:






     """simple docstring"""






     if not self.test_rust_tokenizer:
       return

     a__  =self.get_tokenizer()
     a__  =self.get_rust_tokenizer(add_prefix_space=lowercase_       )

     a__  ='''lower newer'''

     # Testing tokenization
     a__  =tokenizer.tokenize(lowercase_,    add_prefix_space=lowercase_       )
     a__  =rust_tokenizer.tokenize(lowercase_       )
     self.assertListEqual(lowercase_,    lowercase_       )

     # Testing conversion to ids without special tokens
     a__  =tokenizer.encode(lowercase_,    add_special_tokens=lowercase_,    add_prefix_space=lowercase_       )
     a__  =rust_tokenizer.encode(lowercase_,    add_special_tokens=lowercase_       )
     self.assertListEqual(lowercase_,    lowercase_       )

     # Testing conversion to ids with special tokens
     a__  =self.get_rust_tokenizer(add_prefix_space=lowercase_       )
     a__  =tokenizer.encode(lowercase_,    add_prefix_space=lowercase_       )
     a__  =rust_tokenizer.encode(lowercase_       )
     self.assertListEqual(lowercase_,    lowercase_       )

     # Testing the unknown token
     a__  =tokens + [rust_tokenizer.unk_token]
     a__  =[14, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowercase_       ),    lowercase_       )



   def  _UpperCAmelCase (				self,    *lowercase_,    **lowercase_       )							->    Optional[int]:






     """simple docstring"""






     pass



   def  _UpperCAmelCase (				self,    lowercase_=15       )							->    Any:






     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
         a__  =self.rust_tokenizer_class.from_pretrained(lowercase_,    **lowercase_       )

         # Simple input
         a__  ='''This is a simple input'''
         a__  =['''This is a simple input 1''', '''This is a simple input 2''']
         a__  =('''This is a simple input''', '''This is a pair''')
         a__  =[
             ('''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(lowercase_,    tokenizer_r.encode,    lowercase_,    max_length=lowercase_,    padding='''max_length'''       )

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

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

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

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

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



   def  _UpperCAmelCase (				self       )							->    List[Any]:






     """simple docstring"""






     a__  =GPTaTokenizer.from_pretrained(self.tmpdirname,    pad_token='''<pad>'''       )

     # Simple input
     a__  ='''This is a simple input'''
     a__  =['''This is a simple input looooooooong''', '''This is a simple input''']
     a__  =('''This is a simple input''', '''This is a pair''')
     a__  =[
         ('''This is a simple input loooooong''', '''This is a simple input'''),
         ('''This is a simple pair loooooong''', '''This is a simple pair'''),
     ]

     a__  =tokenizer.pad_token_id

     a__  =tokenizer(lowercase_,    padding='''max_length''',    max_length=30,    return_tensors='''np'''       )
     a__  =tokenizer(lowercase_,    padding=lowercase_,    truncate=lowercase_,    return_tensors='''np'''       )
     a__  =tokenizer(*lowercase_,    padding='''max_length''',    max_length=60,    return_tensors='''np'''       )
     a__  =tokenizer(lowercase_,    padding=lowercase_,    truncate=lowercase_,    return_tensors='''np'''       )

     # s
     # test single string max_length padding
     self.assertEqual(out_s['''input_ids'''].shape[-1],    30       )
     self.assertTrue(pad_token_id in out_s['''input_ids''']       )
     self.assertTrue(0 in out_s['''attention_mask''']       )

     # s2
     # test automatic padding
     self.assertEqual(out_sa['''input_ids'''].shape[-1],    33       )
     # long slice doesn't have padding
     self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]       )
     self.assertFalse(0 in out_sa['''attention_mask'''][0]       )
     # short slice does have padding
     self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]       )
     self.assertTrue(0 in out_sa['''attention_mask'''][1]       )

     # p
     # test single pair max_length padding
     self.assertEqual(out_p['''input_ids'''].shape[-1],    60       )
     self.assertTrue(pad_token_id in out_p['''input_ids''']       )
     self.assertTrue(0 in out_p['''attention_mask''']       )

     # p2
     # test automatic padding pair
     self.assertEqual(out_pa['''input_ids'''].shape[-1],    52       )
     # long slice pair doesn't have padding
     self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]       )
     self.assertFalse(0 in out_pa['''attention_mask'''][0]       )
     # short slice pair does have padding
     self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]       )
     self.assertTrue(0 in out_pa['''attention_mask'''][1]       )



   def  _UpperCAmelCase (				self       )							->    Optional[int]:






     """simple docstring"""






     a__  ='''$$$'''
     a__  =GPTaTokenizer.from_pretrained(self.tmpdirname,    bos_token=lowercase_,    add_bos_token=lowercase_       )

     a__  ='''This is a simple input'''
     a__  =['''This is a simple input 1''', '''This is a simple input 2''']

     a__  =tokenizer.bos_token_id

     a__  =tokenizer(lowercase_       )
     a__  =tokenizer(lowercase_       )

     self.assertEqual(out_s.input_ids[0],    lowercase_       )
     self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids       )       )

     a__  =tokenizer.decode(out_s.input_ids       )
     a__  =tokenizer.batch_decode(out_sa.input_ids       )

     self.assertEqual(decode_s.split()[0],    lowercase_       )
     self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa       )       )



   def  _UpperCAmelCase (				self       )							->    List[str]:






     """simple docstring"""






     pass



   def  _UpperCAmelCase (				self       )							->    Optional[int]:






     """simple docstring"""






     a__  =[self.get_tokenizer(do_lower_case=lowercase_,    add_bos_token=lowercase_       )]
     for tokenizer in tokenizers:
       with self.subTest(F"""{tokenizer.__class__.__name__}"""       ):
         a__  ='''Encode this.'''
         a__  ='''This one too please.'''
         a__  =tokenizer.encode(lowercase_,    add_special_tokens=lowercase_       )
         encoded_sequence += tokenizer.encode(lowercase_,    add_special_tokens=lowercase_       )
         a__  =tokenizer.encode_plus(
             lowercase_,    lowercase_,    add_special_tokens=lowercase_,    return_special_tokens_mask=lowercase_,    )
         a__  =encoded_sequence_dict['''input_ids''']
         a__  =encoded_sequence_dict['''special_tokens_mask''']
         self.assertEqual(len(lowercase_       ),    len(lowercase_       )       )

         a__  =[
             (x if not special_tokens_mask[i] else None) for i, x in enumerate(lowercase_       )
         ]
         a__  =[x for x in filtered_sequence if x is not None]
         self.assertEqual(lowercase_,    lowercase_       )







@require_tokenizers
class 						__magic_name__			(							unittest.TestCase							):

   '''simple docstring'''




   def  _UpperCAmelCase (				self       )							->    Any:






     """simple docstring"""






     a__  =AutoTokenizer.from_pretrained('''facebook/opt-350m''',    from_slow=lowercase_       )
     a__  ='''A photo of a cat'''

     a__  =tokenizer.encode(
         lowercase_,    )
     self.assertEqual(lowercase_,    [2, 250, 1345, 9, 10, 4758]       )
     tokenizer.save_pretrained('''test_opt'''       )

     a__  =AutoTokenizer.from_pretrained('''./test_opt'''       )
     a__  =tokenizer.encode(
         lowercase_,    )
     self.assertEqual(lowercase_,    [2, 250, 1345, 9, 10, 4758]       )



   def  _UpperCAmelCase (				self       )							->    Optional[Any]:






     """simple docstring"""






     a__  =AutoTokenizer.from_pretrained('''facebook/opt-350m''',    use_slow=lowercase_       )
     a__  ='''A photo of a cat'''

     a__  =tokenizer.encode(
         lowercase_,    )
     # Same as above
     self.assertEqual(lowercase_,    [2, 250, 1345, 9, 10, 4758]       )



   @unittest.skip('''This test is failing because of a bug in the fast tokenizer'''       )
   def  _UpperCAmelCase (				self       )							->    int:






     """simple docstring"""






     a__  =AutoTokenizer.from_pretrained('''facebook/opt-350m''',    from_slow=lowercase_       )

     a__  ='''bos'''
     a__  =tokenizer.get_vocab()['''bos''']

     a__  ='''A photo of a cat'''
     a__  =tokenizer.encode(
         lowercase_,    )
     # We changed the bos token
     self.assertEqual(lowercase_,    [31957, 250, 1345, 9, 10, 4758]       )
     tokenizer.save_pretrained('''./tok'''       )
     a__  =AutoTokenizer.from_pretrained('''./tok'''       )
     self.assertTrue(tokenizer.is_fast       )
     a__  =tokenizer.encode(
         lowercase_,    )
     self.assertEqual(lowercase_,    [31957, 250, 1345, 9, 10, 4758]       )



from __future__ import annotations




def 			UpperCAmelCase__				(			_A      : float	,      _A      : float	,      _A      : float	,      ):





  '''simple docstring'''







  if (stress, tangential_force, area).count(0							) != 1:
    raise ValueError('''You cannot supply more or less than 2 values'''							)
  elif stress < 0:
    raise ValueError('''Stress cannot be negative'''							)
  elif tangential_force < 0:
    raise ValueError('''Tangential Force cannot be negative'''							)
  elif area < 0:
    raise ValueError('''Area cannot be negative'''							)
  elif stress == 0:
    return (
        "stress",
        tangential_force / area,
    )
  elif tangential_force == 0:
    return (
        "tangential_force",
        stress * area,
    )
  else:
    return (
        "area",
        tangential_force / stress,
    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
