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


snake_case__				= get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class  UpperCamelCase				( __lowercase   ,  unittest.TestCase ):

     '''simple docstring'''

     A_										=  ReformerTokenizer
     A_										=  ReformerTokenizerFast
     A_										=  True
     A_										=  False
     A_										=  True



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






           """simple docstring"""
           super().setUp()

           _lowerCamelCase			    =				ReformerTokenizer(A_				,				keep_accents=A_						)
           tokenizer.save_pretrained(self.tmpdirname						)



     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           _lowerCamelCase			    =				'''<s>'''
           _lowerCamelCase			    =				1

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



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






           """simple docstring"""
           _lowerCamelCase			    =				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_						)				,				10_00						)



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






           """simple docstring"""
           self.assertEqual(self.get_tokenizer().vocab_size				,				10_00						)



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






           """simple docstring"""
           if not self.test_rust_tokenizer:
                 return

           _lowerCamelCase			    =				self.get_tokenizer()
           _lowerCamelCase			    =				self.get_rust_tokenizer()

           _lowerCamelCase			    =				'''I was born in 92000, and this is falsé.'''

           _lowerCamelCase			    =				tokenizer.tokenize(A_						)
           _lowerCamelCase			    =				rust_tokenizer.tokenize(A_						)
           self.assertListEqual(A_				,				A_						)

           _lowerCamelCase			    =				tokenizer.encode(A_				,				add_special_tokens=A_						)
           _lowerCamelCase			    =				rust_tokenizer.encode(A_				,				add_special_tokens=A_						)
           self.assertListEqual(A_				,				A_						)

           _lowerCamelCase			    =				self.get_rust_tokenizer()
           _lowerCamelCase			    =				tokenizer.encode(A_						)
           _lowerCamelCase			    =				rust_tokenizer.encode(A_						)
           self.assertListEqual(A_				,				A_						)



     def 		UpperCamelCase_						(					self				,				A_=15						) ->				Any:






           """simple docstring"""
           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(A_				,				**A_						)

                       # Simple input
                       _lowerCamelCase			    =				'''This is a simple input'''
                       _lowerCamelCase			    =				['''This is a simple input 1''', '''This is a simple input 2''']
                       _lowerCamelCase			    =				('''This is a simple input''', '''This is a pair''')
                       _lowerCamelCase			    =				[
                           ('''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 		UpperCamelCase_						(					self						) ->				Optional[Any]:






           """simple docstring"""
           pass



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






           """simple docstring"""
           _lowerCamelCase			    =				ReformerTokenizer(A_				,				keep_accents=A_						)

           _lowerCamelCase			    =				tokenizer.tokenize('''This is a test'''						)
           self.assertListEqual(A_				,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']						)

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(A_						)				,				[2_85, 46, 10, 1_70, 3_82]				,				)

           _lowerCamelCase			    =				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''',
                   '''.''',
               ]				,				)
           _lowerCamelCase			    =				tokenizer.convert_tokens_to_ids(A_						)
           self.assertListEqual(
               A_				,				[8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]				,				)

           _lowerCamelCase			    =				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 		UpperCamelCase_						(					self						) ->				Optional[Any]:






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



     @slow
     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           _lowerCamelCase			    =				'''Hello World!'''
           _lowerCamelCase			    =				[1_26, 32, 2_62, 1_52, 38, 72, 2_87]

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



     @slow
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           _lowerCamelCase			    =				(
               '''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'''
           )
           _lowerCamelCase			    =				[
               1_08,
               2_65,
               24,
               1_11,
               4,
               2_58,
               1_56,
               35,
               28,
               2_75,
               3,
               2_59,
               2_97,
               2_60,
               84,
               4,
               35,
               1_10,
               44,
               8,
               2_59,
               91,
               2_68,
               21,
               11,
               2_09,
               2_74,
               1_09,
               2_66,
               2_77,
               1_17,
               86,
               93,
               3_15,
               2_58,
               2_78,
               2_58,
               2_77,
               2_58,
               0,
               2_58,
               2_88,
               2_58,
               3_19,
               2_58,
               0,
               2_58,
               0,
               2_58,
               0,
               2_58,
               0,
               2_58,
               2_87,
               2_58,
               3_15,
               2_58,
               2_89,
               2_58,
               2_78,
               99,
               2_69,
               2_66,
               2_62,
               8,
               2_59,
               2_41,
               4,
               2_17,
               2_30,
               2_68,
               2_66,
               55,
               1_68,
               1_06,
               75,
               1_93,
               2_66,
               2_23,
               27,
               49,
               26,
               2_82,
               25,
               2_64,
               2_99,
               19,
               26,
               0,
               2_58,
               2_77,
               1_17,
               86,
               93,
               1_76,
               1_83,
               2_70,
               11,
               2_62,
               42,
               61,
               2_65,
           ]

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



     @require_torch
     @slow
     def 		UpperCamelCase_						(					self						) ->				Tuple:






           """simple docstring"""
           import torch

           from transformers import ReformerConfig, ReformerModel

           # Build sequence
           _lowerCamelCase			    =				list(self.big_tokenizer.get_vocab().keys()						)[:10]
           _lowerCamelCase			    =				''' '''.join(A_						)
           _lowerCamelCase			    =				self.big_tokenizer.encode_plus(A_				,				return_tensors='''pt'''						)
           _lowerCamelCase			    =				self.big_tokenizer.batch_encode_plus([sequence, sequence]				,				return_tensors='''pt'''						)

           _lowerCamelCase			    =				ReformerConfig()
           # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
           _lowerCamelCase			    =				encoded_sequence['''input_ids'''].shape
           _lowerCamelCase			    =				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 		UpperCamelCase_						(					self						) ->				Optional[int]:






           """simple docstring"""
           # fmt: off
           _lowerCamelCase			    =				{'''input_ids''': [[1_08, 2_65, 24, 1_11, 4, 2_58, 1_56, 7, 51, 2_79, 58, 7, 76, 25, 69, 2_78], [1_40, 2_43, 2_64, 1_34, 17, 2_67, 77, 2_63, 22, 2_62, 2_97, 2_58, 3_04, 1_77, 2_79, 2_66, 14, 89, 13, 35, 2_61, 2_99, 2_72, 1_37, 2_75, 2_78]], '''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
           _lowerCamelCase			    =				[
               '''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_				,				)
import argparse
import json
import subprocess
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase		)						->    int:



      '''simple docstring'''

      _lowerCamelCase			    =				[]

      _lowerCamelCase			    =				(
          F'curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'
          ''' https://api.github.com/repos/huggingface/transformers/actions/runners'''
      )
      _lowerCamelCase			    =				subprocess.run(__UpperCAmelCase ,						shell=__UpperCAmelCase ,						stdout=subprocess.PIPE		)
      _lowerCamelCase			    =				output.stdout.decode('''utf-8'''		)
      _lowerCamelCase			    =				json.loads(__UpperCAmelCase		)

      _lowerCamelCase			    =				status['''runners''']
      for runner in runners:
            if runner["name"] in target_runners:
                  if runner["status"] == "offline":
                        offline_runners.append(__UpperCAmelCase		)

    # save the result so we can report them on Slack
      with open('''offline_runners.txt''' ,						'''w'''		) as fp:
            fp.write(json.dumps(__UpperCAmelCase		)		)

      if len(__UpperCAmelCase		) > 0:
            _lowerCamelCase			    =				'''\n'''.join([x['''name'''] for x in offline_runners]		)
            raise ValueError(F'The following runners are offline:\n{failed}'		)


if __name__ == "__main__":
     def       __magic_name__(  __UpperCAmelCase		)						->    str:



           '''simple docstring'''

           return values.split(''','''		)

     snake_case__				= argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '--target_runners',
         default=None,
         type=list_str,
         required=True,
         help='Comma-separated list of runners to check status.',
     )

     parser.add_argument(
         '--token', default=None, type=str, required=True, help='A token that has actions:read permission.'
     )
     snake_case__				= parser.parse_args()




     get_runner_status(args.target_runners, args.token)