



import json
import os
import unittest

from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors

@require_tokenizers
class        _A			(      snake_case_ ,unittest.TestCase       ):
       UpperCamelCase__    :       int		   =		BartTokenizer
       UpperCamelCase__    :       Tuple		   =		BartTokenizerFast
       UpperCamelCase__    :       Optional[Any]		   =		True
       UpperCamelCase__    :       Any		   =		filter_roberta_detectors



       def 						_lowerCamelCase     (						self				:	Union[str, Any]):


           '''simple docstring'''

           super().setUp()
           __a					=							[
               'l',
               'o',
               'w',
               'e',
               'r',
               's',
               't',
               'i',
               'd',
               'n',
               '\u0120',
               '\u0120l',
               '\u0120n',
               '\u0120lo',
               '\u0120low',
               'er',
               '\u0120lowest',
               '\u0120newer',
               '\u0120wider',
               '<unk>',
           ]
           __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 						_lowerCamelCase     (						self				:	int	,						**__SCREAMING_SNAKE_CASE				:	Tuple):


           '''simple docstring'''

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



       def 						_lowerCamelCase     (						self				:	Optional[int]	,						**__SCREAMING_SNAKE_CASE				:	int):


           '''simple docstring'''

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



       def 						_lowerCamelCase     (						self				:	int	,						__SCREAMING_SNAKE_CASE				:	Any):


           '''simple docstring'''

           return "lower newer", "lower newer"



       @cached_property
       def 						_lowerCamelCase     (						self				:	Optional[int]):


           '''simple docstring'''

           return BartTokenizer.from_pretrained('''facebook/bart-large''')



       @cached_property
       def 						_lowerCamelCase     (						self				:	Optional[int]):


           '''simple docstring'''

           return BartTokenizerFast.from_pretrained('''facebook/bart-large''')



       @require_torch
       def 						_lowerCamelCase     (						self				:	Optional[int]):


           '''simple docstring'''

           __a					=							['A long paragraph for summarization.', 'Another paragraph for summarization.']
           __a					=							[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

           for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               __a					=							tokenizer(lowercase_	,						max_length=len(lowercase_)	,						padding=lowercase_	,						return_tensors='''pt''')
               self.assertIsInstance(lowercase_	,						lowercase_)

               self.assertEqual((2, 9)	,						batch.input_ids.shape)
               self.assertEqual((2, 9)	,						batch.attention_mask.shape)
               __a					=							batch.input_ids.tolist()[0]
               self.assertListEqual(lowercase_	,						lowercase_)
               # Test that special tokens are reset



       @require_torch
       def 						_lowerCamelCase     (						self				:	str):


           '''simple docstring'''

           __a					=							['A long paragraph for summarization.', 'Another paragraph for summarization.']
           for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               __a					=							tokenizer(lowercase_	,						padding=lowercase_	,						return_tensors='''pt''')
               # check if input_ids are returned and no labels
               self.assertIn('''input_ids'''	,						lowercase_)
               self.assertIn('''attention_mask'''	,						lowercase_)
               self.assertNotIn('''labels'''	,						lowercase_)
               self.assertNotIn('''decoder_attention_mask'''	,						lowercase_)



       @require_torch
       def 						_lowerCamelCase     (						self				:	List[str]):


           '''simple docstring'''

           __a					=							[
               'Summary of the text.',
               'Another summary.',
           ]
           for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               __a					=							tokenizer(text_target=lowercase_	,						max_length=32	,						padding='''max_length'''	,						return_tensors='''pt''')
               self.assertEqual(32	,						targets['''input_ids'''].shape[1])



       @require_torch
       def 						_lowerCamelCase     (						self				:	Optional[int]):


           '''simple docstring'''

           for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               __a					=							tokenizer(
                   ['''I am a small frog''' * 1_024, '''I am a small frog''']	,						padding=lowercase_	,						truncation=lowercase_	,						return_tensors='''pt''')
               self.assertIsInstance(lowercase_	,						lowercase_)
               self.assertEqual(batch.input_ids.shape	,						(2, 1_024))



       @require_torch
       def 						_lowerCamelCase     (						self				:	Union[str, Any]):


           '''simple docstring'''

           __a					=							['A long paragraph for summarization.']
           __a					=							[
               'Summary of the text.',
           ]
           for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
               __a					=							tokenizer(lowercase_	,						return_tensors='''pt''')
               __a					=							tokenizer(text_target=lowercase_	,						return_tensors='''pt''')
               __a					=							inputs['input_ids']
               __a					=							targets['input_ids']
               self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
               self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
               self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
               self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())



       def 						_lowerCamelCase     (						self				:	Optional[int]):


           '''simple docstring'''

           pass





       def 						_lowerCamelCase     (						self				:	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_)
                   __a					=							self.tokenizer_class.from_pretrained(lowercase_	,						**lowercase_)
                   __a					=							'A, <mask> AllenNLP sentence.'
                   __a					=							tokenizer_r.encode_plus(lowercase_	,						add_special_tokens=lowercase_	,						return_token_type_ids=lowercase_)
                   __a					=							tokenizer_p.encode_plus(lowercase_	,						add_special_tokens=lowercase_	,						return_token_type_ids=lowercase_)

                   # token_type_ids should put 0 everywhere
                   self.assertEqual(sum(tokens_r['''token_type_ids'''])	,						sum(tokens_p['''token_type_ids''']))

                   # attention_mask should put 1 everywhere, so sum over length should be 1
                   self.assertEqual(
                       sum(tokens_r['''attention_mask''']) / len(tokens_r['''attention_mask'''])	,						sum(tokens_p['''attention_mask''']) / len(tokens_p['''attention_mask'''])	,						)

                   __a					=							tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''])
                   __a					=							tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids'''])

                   # Rust correctly handles the space before the mask while python doesnt
                   self.assertSequenceEqual(tokens_p['''input_ids''']	,						[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2])
                   self.assertSequenceEqual(tokens_r['''input_ids''']	,						[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2])

                   self.assertSequenceEqual(
                       lowercase_	,						['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])
                   self.assertSequenceEqual(
                       lowercase_	,						['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])













"""simple docstring"""


def 					a			(  UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int		)	->		int:
 return len_board * len_board_column * row + column




def 					a			(  UpperCamelCase_				:					list[list[str]]  ,						UpperCamelCase_				:					str  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					int  ,						UpperCamelCase_				:					set[int]  ,						)	->		bool:

 if board[row][column] != word[word_index]:
  return False

 if word_index == len(UpperCamelCase_		) - 1:
  return True

 __A						:							List[str]      =						[(0, 1), (0, -1), (-1, 0), (1, 0)]
 __A						:							Any      =						len(UpperCamelCase_		)
 __A						:							Union[str, Any]      =						len(board[0]		)
 for direction in traverts_directions:
  __A						:							Any      =						row + direction[0]
  __A						:							List[Any]      =						column + direction[1]
  if not (0 <= next_i < len_board and 0 <= next_j < len_board_column):
   continue

  __A						:							Any      =						get_point_key(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)
  if key in visited_points_set:
   continue

  visited_points_set.add(UpperCamelCase_		)
  if exits_word(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						word_index + 1  ,						UpperCamelCase_		):
   return True

  visited_points_set.remove(UpperCamelCase_		)

 return False




def 					a			(  UpperCamelCase_				:					list[list[str]]  ,						UpperCamelCase_				:					str		)	->		bool:
 __A						:							Optional[Any]      =						(
     'The board should be a non empty matrix of single chars strings.'
 )

 __A						:							Dict      =						len(UpperCamelCase_		)
 if not isinstance(UpperCamelCase_  ,						UpperCamelCase_		) or len(UpperCamelCase_		) == 0:
  raise ValueError(UpperCamelCase_		)

 for row in board:
  if not isinstance(UpperCamelCase_  ,						UpperCamelCase_		) or len(UpperCamelCase_		) == 0:
   raise ValueError(UpperCamelCase_		)

  for item in row:
   if not isinstance(UpperCamelCase_  ,						UpperCamelCase_		) or len(UpperCamelCase_		) != 1:
    raise ValueError(UpperCamelCase_		)

    # Validate word
 if not isinstance(UpperCamelCase_  ,						UpperCamelCase_		) or len(UpperCamelCase_		) == 0:
  raise ValueError(
      'The word parameter should be a string of length greater than 0.'		)

 __A						:							List[Any]      =						len(board[0]		)
 for i in range(UpperCamelCase_		):
  for j in range(UpperCamelCase_		):
   if exits_word(
       UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						0  ,						{get_point_key(UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_  ,						UpperCamelCase_		)}		):
    return True

 return False


if __name__ == "__main__":
   import doctest

   doctest.testmod()





