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 		_lowercase						(					snake_case_						,      unittest.TestCase       ):
 lowercase				     =   GPTaTokenizer
 lowercase				     =   GPTaTokenizerFast
 lowercase				     =   True
 lowercase				     =   {'add_prefix_space': True}
 lowercase				     =   False

 def 						SCREAMING_SNAKE_CASE__   ( self	:							int			)   ->						List[Any]:

  """simple docstring"""





  super().setUp()

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

  UpperCamelCase_					:						Dict =					os.path.join(self.tmpdirname   ,      VOCAB_FILES_NAMES['vocab_file']			)
  UpperCamelCase_					:						List[str] =					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(snake_case			) + '\n'			)
  with open(self.merges_file   ,      'w'   ,      encoding='utf-8'			) as fp:
   fp.write('\n'.join(snake_case			)			)

 def 						SCREAMING_SNAKE_CASE__   ( self	:							Optional[int]   ,      **snake_case	:							Union[str, Any]			)   ->						Union[str, Any]:

  """simple docstring"""





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

 def 						SCREAMING_SNAKE_CASE__   ( self	:							List[str]   ,      **snake_case	:							str			)   ->						Tuple:

  """simple docstring"""





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

 def 						SCREAMING_SNAKE_CASE__   ( self	:							Optional[int]   ,      snake_case	:							Optional[int]			)   ->						int:

  """simple docstring"""





  UpperCamelCase_					:						int =					'lower newer'
  UpperCamelCase_					:						Any =					'lower newer'
  return input_text, output_text

 def 						SCREAMING_SNAKE_CASE__   ( self	:							int			)   ->						str:

  """simple docstring"""





  UpperCamelCase_					:						str =					GPTaTokenizer(self.vocab_file   ,      self.merges_file   ,      **self.special_tokens_map			)
  UpperCamelCase_					:						Optional[Any] =					'lower newer'
  UpperCamelCase_					:						List[str] =					['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
  UpperCamelCase_					:						List[Any] =					tokenizer.tokenize(snake_case   ,      add_prefix_space=snake_case			)
  self.assertListEqual(snake_case   ,      snake_case			)

  UpperCamelCase_					:						Tuple =					tokens + [tokenizer.unk_token]
  UpperCamelCase_					:						Optional[Any] =					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
  self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case			)   ,      snake_case			)

 def 						SCREAMING_SNAKE_CASE__   ( self	:							Tuple			)   ->						Optional[Any]:

  """simple docstring"""





  if not self.test_rust_tokenizer:
   return

  UpperCamelCase_					:						Optional[int] =					self.get_tokenizer()
  UpperCamelCase_					:						Any =					self.get_rust_tokenizer(add_prefix_space=snake_case			)

  UpperCamelCase_					:						Optional[Any] =					'lower newer'

  # Testing tokenization
  UpperCamelCase_					:						Optional[int] =					tokenizer.tokenize(snake_case   ,      add_prefix_space=snake_case			)
  UpperCamelCase_					:						Optional[int] =					rust_tokenizer.tokenize(snake_case			)
  self.assertListEqual(snake_case   ,      snake_case			)

  # Testing conversion to ids without special tokens
  UpperCamelCase_					:						Dict =					tokenizer.encode(snake_case   ,      add_special_tokens=snake_case   ,      add_prefix_space=snake_case			)
  UpperCamelCase_					:						Dict =					rust_tokenizer.encode(snake_case   ,      add_special_tokens=snake_case			)
  self.assertListEqual(snake_case   ,      snake_case			)

  # Testing conversion to ids with special tokens
  UpperCamelCase_					:						Optional[int] =					self.get_rust_tokenizer(add_prefix_space=snake_case			)
  UpperCamelCase_					:						int =					tokenizer.encode(snake_case   ,      add_prefix_space=snake_case			)
  UpperCamelCase_					:						Union[str, Any] =					rust_tokenizer.encode(snake_case			)
  self.assertListEqual(snake_case   ,      snake_case			)

  # Testing the unknown token
  UpperCamelCase_					:						Optional[int] =					tokens + [rust_tokenizer.unk_token]
  UpperCamelCase_					:						Dict =					[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
  self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(snake_case			)   ,      snake_case			)

 def 						SCREAMING_SNAKE_CASE__   ( self	:							List[str]   ,      *snake_case	:							int   ,      **snake_case	:							Optional[int]			)   ->						Union[str, Any]:

  """simple docstring"""





  pass

 def 						SCREAMING_SNAKE_CASE__   ( self	:							Optional[Any]   ,      snake_case	:							str=1_5			)   ->						List[str]:

  """simple docstring"""





  for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
   with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"			):
    UpperCamelCase_					:						str =					self.rust_tokenizer_class.from_pretrained(snake_case   ,      **snake_case			)

    # Simple input
    UpperCamelCase_					:						Optional[int] =					'This is a simple input'
    UpperCamelCase_					:						Tuple =					['This is a simple input 1', 'This is a simple input 2']
    UpperCamelCase_					:						Optional[Any] =					('This is a simple input', 'This is a pair')
    UpperCamelCase_					:						int =					[
        ('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(snake_case   ,      tokenizer_r.encode   ,      snake_case   ,      max_length=snake_case   ,      padding='max_length'			)

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

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

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

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

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

 def 						SCREAMING_SNAKE_CASE__   ( self	:							int			)   ->						Union[str, Any]:

  """simple docstring"""





  UpperCamelCase_					:						Dict =					GPTaTokenizer.from_pretrained(self.tmpdirname   ,      pad_token='<pad>'			)

  # Simple input
  UpperCamelCase_					:						Tuple =					'This is a simple input'
  UpperCamelCase_					:						List[str] =					['This is a simple input looooooooong', 'This is a simple input']
  UpperCamelCase_					:						str =					('This is a simple input', 'This is a pair')
  UpperCamelCase_					:						Union[str, Any] =					[
      ('This is a simple input loooooong', 'This is a simple input'),
      ('This is a simple pair loooooong', 'This is a simple pair'),
  ]

  UpperCamelCase_					:						Any =					tokenizer.pad_token_id

  UpperCamelCase_					:						List[Any] =					tokenizer(snake_case   ,      padding='max_length'   ,      max_length=3_0   ,      return_tensors='np'			)
  UpperCamelCase_					:						List[Any] =					tokenizer(snake_case   ,      padding=snake_case   ,      truncate=snake_case   ,      return_tensors='np'			)
  UpperCamelCase_					:						List[str] =					tokenizer(*snake_case   ,      padding='max_length'   ,      max_length=6_0   ,      return_tensors='np'			)
  UpperCamelCase_					:						str =					tokenizer(snake_case   ,      padding=snake_case   ,      truncate=snake_case   ,      return_tensors='np'			)

  # s
  # test single string max_length padding
  self.assertEqual(out_s['input_ids'].shape[-1]   ,      3_0			)
  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]   ,      3_3			)
  # 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]   ,      6_0			)
  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]   ,      5_2			)
  # 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 						SCREAMING_SNAKE_CASE__   ( self	:							int			)   ->						List[Any]:

  """simple docstring"""





  UpperCamelCase_					:						Optional[int] =					'$$$'
  UpperCamelCase_					:						Any =					GPTaTokenizer.from_pretrained(self.tmpdirname   ,      bos_token=snake_case   ,      add_bos_token=snake_case			)

  UpperCamelCase_					:						int =					'This is a simple input'
  UpperCamelCase_					:						str =					['This is a simple input 1', 'This is a simple input 2']

  UpperCamelCase_					:						Union[str, Any] =					tokenizer.bos_token_id

  UpperCamelCase_					:						List[Any] =					tokenizer(snake_case			)
  UpperCamelCase_					:						List[str] =					tokenizer(snake_case			)

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

  UpperCamelCase_					:						str =					tokenizer.decode(out_s.input_ids			)
  UpperCamelCase_					:						Dict =					tokenizer.batch_decode(out_sa.input_ids			)

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

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

  """simple docstring"""





  pass


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

  """simple docstring"""





  UpperCamelCase_					:						Tuple =					[self.get_tokenizer(do_lower_case=snake_case   ,      add_bos_token=snake_case			)]
  for tokenizer in tokenizers:
   with self.subTest(f"{tokenizer.__class__.__name__}"			):
    UpperCamelCase_					:						Optional[int] =					'Encode this.'
    UpperCamelCase_					:						Optional[int] =					'This one too please.'
    UpperCamelCase_					:						Tuple =					tokenizer.encode(snake_case   ,      add_special_tokens=snake_case			)
    encoded_sequence += tokenizer.encode(snake_case   ,      add_special_tokens=snake_case			)
    UpperCamelCase_					:						Dict =					tokenizer.encode_plus(
        snake_case   ,      snake_case   ,      add_special_tokens=snake_case   ,      return_special_tokens_mask=snake_case   ,      )
    UpperCamelCase_					:						List[Any] =					encoded_sequence_dict['input_ids']
    UpperCamelCase_					:						List[Any] =					encoded_sequence_dict['special_tokens_mask']
    self.assertEqual(len(snake_case			)   ,      len(snake_case			)			)

    UpperCamelCase_					:						Optional[int] =					[
        (x if not special_tokens_mask[i] else None) for i, x in enumerate(snake_case			)
    ]
    UpperCamelCase_					:						Optional[int] =					[x for x in filtered_sequence if x is not None]
    self.assertEqual(snake_case   ,      snake_case			)





@require_tokenizers
class 		_lowercase						(					unittest.TestCase       ):

 def 						SCREAMING_SNAKE_CASE__   ( self	:							Union[str, Any]			)   ->						Optional[Any]:

  """simple docstring"""





  UpperCamelCase_					:						Optional[int] =					AutoTokenizer.from_pretrained('facebook/opt-350m'   ,      from_slow=snake_case			)
  UpperCamelCase_					:						Dict =					'A photo of a cat'

  UpperCamelCase_					:						Tuple =					tokenizer.encode(
      snake_case   ,      )
  self.assertEqual(snake_case   ,      [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]			)
  tokenizer.save_pretrained('test_opt'			)

  UpperCamelCase_					:						int =					AutoTokenizer.from_pretrained('./test_opt'			)
  UpperCamelCase_					:						Union[str, Any] =					tokenizer.encode(
      snake_case   ,      )
  self.assertEqual(snake_case   ,      [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]			)

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

  """simple docstring"""





  UpperCamelCase_					:						Dict =					AutoTokenizer.from_pretrained('facebook/opt-350m'   ,      use_slow=snake_case			)
  UpperCamelCase_					:						Union[str, Any] =					'A photo of a cat'

  UpperCamelCase_					:						Optional[int] =					tokenizer.encode(
      snake_case   ,      )
  # Same as above
  self.assertEqual(snake_case   ,      [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]			)


 @unittest.skip('This test is failing because of a bug in the fast tokenizer'			)
 def 						SCREAMING_SNAKE_CASE__   ( self	:							str			)   ->						Union[str, Any]:

  """simple docstring"""





  UpperCamelCase_					:						List[Any] =					AutoTokenizer.from_pretrained('facebook/opt-350m'   ,      from_slow=snake_case			)

  UpperCamelCase_					:						Union[str, Any] =					'bos'
  UpperCamelCase_					:						Optional[int] =					tokenizer.get_vocab()['bos']

  UpperCamelCase_					:						Dict =					'A photo of a cat'
  UpperCamelCase_					:						Dict =					tokenizer.encode(
      snake_case   ,      )
  # We changed the bos token
  self.assertEqual(snake_case   ,      [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]			)
  tokenizer.save_pretrained('./tok'			)
  UpperCamelCase_					:						Dict =					AutoTokenizer.from_pretrained('./tok'			)
  self.assertTrue(tokenizer.is_fast			)
  UpperCamelCase_					:						int =					tokenizer.encode(
      snake_case   ,      )
  self.assertEqual(snake_case   ,      [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]			)




def    __lowercase     (						lowerCamelCase					:     str  ,  lowerCamelCase					:     str	):

 def get_matched_characters(lowerCamelCase					:     str  ,  lowerCamelCase					:     str	) -> str:
  UpperCamelCase_					:						Tuple =					[]
  UpperCamelCase_					:						List[Any] =					min(len(_stra	)  ,  len(_stra	)	) // 2
  for i, l in enumerate(_stra	):
   UpperCamelCase_					:						int =					int(max(0  ,  i - limit	)	)
   UpperCamelCase_					:						Dict =					int(min(i + limit + 1  ,  len(_stra	)	)	)
   if l in _stra[left:right]:
    matched.append(lowerCamelCase	)
    UpperCamelCase_					:						Dict =					F"{_stra[0:_stra.index(lowerCamelCase	)]} {_stra[_stra.index(lowerCamelCase	) + 1:]}"

  return "".join(lowerCamelCase	)

 # matching characters
 UpperCamelCase_					:						str =					get_matched_characters(lowerCamelCase  ,  lowerCamelCase	)
 UpperCamelCase_					:						str =					get_matched_characters(lowerCamelCase  ,  lowerCamelCase	)
 UpperCamelCase_					:						Union[str, Any] =					len(lowerCamelCase	)

 # transposition
 UpperCamelCase_					:						int =					(
     len([(ca, ca) for ca, ca in zip(lowerCamelCase  ,  lowerCamelCase	) if ca != ca]	) // 2
 )

 if not match_count:
  UpperCamelCase_					:						Union[str, Any] =					0.0
 else:
  UpperCamelCase_					:						str =					(
      1
      / 3
      * (
          match_count / len(lowerCamelCase	)
          + match_count / len(lowerCamelCase	)
          + (match_count - transpositions) / match_count
      )
  )

 # common prefix up to 4 characters
 UpperCamelCase_					:						Dict =					0
 for ca, ca in zip(stra[:4]  ,  stra[:4]	):
  if ca == ca:
   prefix_len += 1
  else:
   break

 return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(jaro_winkler('hello', 'world'))



