


'''simple docstring'''




import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led 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

@require_tokenizers
class 		UpperCAmelCase_      (  __lowercase       ,	unittest.TestCase		):
     lowerCamelCase				:	str		=     LEDTokenizer
     lowerCamelCase				:	Any		=     LEDTokenizerFast
     lowerCamelCase				:	int		=     True





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    )				->  str:
        super().setUp()
        lowerCAmelCase     =			[
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            '\u0120',
            '\u0120l',
            '\u0120n',
            '\u0120lo',
            '\u0120low',
            'er',
            '\u0120lowest',
            '\u0120newer',
            '\u0120wider',
            '<unk>',
        ]
        lowerCAmelCase     =			dict(zip(UpperCAmelCase__    ,      range(len(UpperCAmelCase__    )    )    )    )
        lowerCAmelCase     =			['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
        lowerCAmelCase     =			{'unk_token': '<unk>'}

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





     def 							__UpperCAmelCase      ( self       :      Dict    ,      **UpperCAmelCase__       :      Optional[Any]    )				->  Dict:
        kwargs.update(self.special_tokens_map    )
        return self.tokenizer_class.from_pretrained(self.tmpdirname    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      **UpperCAmelCase__       :      Optional[int]    )				->  List[str]:
        kwargs.update(self.special_tokens_map    )
        return self.rust_tokenizer_class.from_pretrained(self.tmpdirname    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Any    ,      UpperCAmelCase__       :      Any    )				->  int:
        return "lower newer", "lower newer"





     @cached_property
     def 							__UpperCAmelCase      ( self       :      int    )				->  List[Any]:
        return LEDTokenizer.from_pretrained('allenai/led-base-16384'    )





     @cached_property
     def 							__UpperCAmelCase      ( self       :      List[Any]    )				->  Tuple:
        return LEDTokenizerFast.from_pretrained('allenai/led-base-16384'    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      Any    )				->  Any:
        lowerCAmelCase     =			['A long paragraph for summarization.', 'Another paragraph for summarization.']
        lowerCAmelCase     =			[0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

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

           self.assertEqual((2, 9)    ,      batch.input_ids.shape    )
           self.assertEqual((2, 9)    ,      batch.attention_mask.shape    )
           lowerCAmelCase     =			batch.input_ids.tolist()[0]
           self.assertListEqual(UpperCAmelCase__    ,      UpperCAmelCase__    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      List[Any]    )				->  Optional[int]:
        lowerCAmelCase     =			['A long paragraph for summarization.', 'Another paragraph for summarization.']
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
           lowerCAmelCase     =			tokenizer(UpperCAmelCase__    ,      padding=UpperCAmelCase__    ,      return_tensors='pt'    )
           self.assertIn('input_ids'    ,      UpperCAmelCase__    )
           self.assertIn('attention_mask'    ,      UpperCAmelCase__    )
           self.assertNotIn('labels'    ,      UpperCAmelCase__    )
           self.assertNotIn('decoder_attention_mask'    ,      UpperCAmelCase__    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  Optional[int]:
        lowerCAmelCase     =			[
            'Summary of the text.',
            'Another summary.',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
           lowerCAmelCase     =			tokenizer(text_target=UpperCAmelCase__    ,      max_length=3_2    ,      padding='max_length'    ,      return_tensors='pt'    )
           self.assertEqual(3_2    ,      targets['input_ids'].shape[1]    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      Any    )				->  Any:
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
           lowerCAmelCase     =			tokenizer(
               ['I am a small frog' * 1_0_2_4, 'I am a small frog']    ,      padding=UpperCAmelCase__    ,      truncation=UpperCAmelCase__    ,      return_tensors='pt'    )
           self.assertIsInstance(UpperCAmelCase__    ,      UpperCAmelCase__    )
           self.assertEqual(batch.input_ids.shape    ,      (2, 5_1_2_2)    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      str    )				->  List[Any]:
        lowerCAmelCase     =			['A long paragraph for summarization.']
        lowerCAmelCase     =			[
            'Summary of the text.',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
           lowerCAmelCase     =			tokenizer(UpperCAmelCase__    ,      return_tensors='pt'    )
           lowerCAmelCase     =			tokenizer(text_target=UpperCAmelCase__    ,      return_tensors='pt'    )
           lowerCAmelCase     =			inputs['input_ids']
           lowerCAmelCase     =			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()    )





     @require_torch
     def 							__UpperCAmelCase      ( self       :      Dict    )				->  Optional[int]:
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
           lowerCAmelCase     =			['Summary of the text.', 'Another summary.']
           lowerCAmelCase     =			[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

           lowerCAmelCase     =			tokenizer(UpperCAmelCase__    ,      padding=UpperCAmelCase__    )
           lowerCAmelCase     =			[[0] * len(UpperCAmelCase__    ) for x in encoded_output['input_ids']]
           lowerCAmelCase     =			tokenizer.pad(UpperCAmelCase__    )
           self.assertSequenceEqual(outputs['global_attention_mask']    ,      UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      str    )				->  Optional[int]:
        pass





     def 							__UpperCAmelCase      ( self       :      str    )				->  Tuple:
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
              lowerCAmelCase     =			self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__    ,      **UpperCAmelCase__    )
              lowerCAmelCase     =			self.tokenizer_class.from_pretrained(UpperCAmelCase__    ,      **UpperCAmelCase__    )
              lowerCAmelCase     =			'A, <mask> AllenNLP sentence.'
              lowerCAmelCase     =			tokenizer_r.encode_plus(UpperCAmelCase__    ,      add_special_tokens=UpperCAmelCase__    ,      return_token_type_ids=UpperCAmelCase__    )
              lowerCAmelCase     =			tokenizer_p.encode_plus(UpperCAmelCase__    ,      add_special_tokens=UpperCAmelCase__    ,      return_token_type_ids=UpperCAmelCase__    )
              self.assertEqual(sum(tokens_r['token_type_ids']    )    ,      sum(tokens_p['token_type_ids']    )    )
              self.assertEqual(
                  sum(tokens_r['attention_mask']    ) / len(tokens_r['attention_mask']    )    ,      sum(tokens_p['attention_mask']    ) / len(tokens_p['attention_mask']    )    ,      )

              lowerCAmelCase     =			tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']    )
              lowerCAmelCase     =			tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']    )
              self.assertSequenceEqual(tokens_p['input_ids']    ,      [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]    )
              self.assertSequenceEqual(tokens_r['input_ids']    ,      [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]    )

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









"""simple docstring"""



def   __lowerCAmelCase						(						lowercase  :  int )	->						bool:


    """simple docstring"""





    if p < 2:
        raise ValueError("p should not be less than 2!" )
    elif p == 2:
        return True

    snake_case    :      Dict      					=    4
    snake_case    :      str      					=    (1 << p) - 1
    for _ in range(p - 2 ):
        snake_case    :      Any      					=    ((s * s) - 2) % m
    return s == 0


if __name__ == "__main__":
  print(lucas_lehmer_test(7))
  print(lucas_lehmer_test(11))





