


'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


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




@require_sentencepiece
@require_tokenizers
class 			lowerCamelCase_   (	__a     ,       unittest.TestCase      ):
      lowerCAmelCase__		     =     XLMRobertaTokenizer
      lowerCAmelCase__		     =     XLMRobertaTokenizerFast
      lowerCAmelCase__		     =     True
      lowerCAmelCase__		     =     True






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          super().setUp()

          # We have a SentencePiece fixture for testing
          UpperCAmelCase__			:		Optional[Any]													=				XLMRobertaTokenizer(_A						,						keep_accents=_A )
          tokenizer.save_pretrained(self.tmpdirname )






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				'''<pad>'''
          UpperCAmelCase__			:		List[Any]													=				1

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






      def lowercase_							(					self				:    Dict ):


          '''simple docstring'''


          UpperCAmelCase__			:		List[Any]													=				list(self.get_tokenizer().get_vocab().keys() )

          self.assertEqual(vocab_keys[0]						,						'''<s>''' )
          self.assertEqual(vocab_keys[1]						,						'''<pad>''' )
          self.assertEqual(vocab_keys[-1]						,						'''<mask>''' )
          self.assertEqual(len(_A )						,						1_002 )






      def lowercase_							(					self				:    int ):


          '''simple docstring'''


          self.assertEqual(self.get_tokenizer().vocab_size						,						1_002 )






      def lowercase_							(					self				:    Optional[int] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Any													=				XLMRobertaTokenizer(_A						,						keep_accents=_A )

          UpperCAmelCase__			:		Union[str, Any]													=				tokenizer.tokenize('''This is a test''' )
          self.assertListEqual(_A						,						['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''] )

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(_A )						,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]						,						)

          UpperCAmelCase__			:		Dict													=				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''',
                  '''.''',
              ]						,						)
          UpperCAmelCase__			:		Optional[int]													=				tokenizer.convert_tokens_to_ids(_A )
          self.assertListEqual(
              _A						,						[
                  value + tokenizer.fairseq_offset
                  for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                  #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
              ]						,						)

          UpperCAmelCase__			:		Tuple													=				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>''',
                  '''.''',
              ]						,						)






      def lowercase_							(					self				:    Any ):


          '''simple docstring'''


          if not self.test_slow_tokenizer:
              # as we don't have a slow version, we can't compare the outputs between slow and fast versions
              return

          UpperCAmelCase__			:		List[str]													=				(self.rust_tokenizer_class, '''hf-internal-testing/tiny-xlm-roberta''', {})
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
                  UpperCAmelCase__			:		Union[str, Any]													=				self.rust_tokenizer_class.from_pretrained(_A						,						**_A )
                  UpperCAmelCase__			:		Union[str, Any]													=				self.tokenizer_class.from_pretrained(_A						,						**_A )

                  UpperCAmelCase__			:		Optional[int]													=				tempfile.mkdtemp()

                  UpperCAmelCase__			:		int													=				tokenizer_r.save_pretrained(_A )
                  UpperCAmelCase__			:		List[str]													=				tokenizer_p.save_pretrained(_A )

                  # Checks it save with the same files + the tokenizer.json file for the fast one
                  self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files ) )
                  UpperCAmelCase__			:		Union[str, Any]													=				tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f )
                  self.assertSequenceEqual(_A						,						_A )

                  # Checks everything loads correctly in the same way
                  UpperCAmelCase__			:		Optional[int]													=				tokenizer_r.from_pretrained(_A )
                  UpperCAmelCase__			:		str													=				tokenizer_p.from_pretrained(_A )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                      self.assertTrue(hasattr(_A						,						_A ) )
                      # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                      # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                  shutil.rmtree(_A )

                  # Save tokenizer rust, legacy_format=True
                  UpperCAmelCase__			:		int													=				tempfile.mkdtemp()

                  UpperCAmelCase__			:		Tuple													=				tokenizer_r.save_pretrained(_A						,						legacy_format=_A )
                  UpperCAmelCase__			:		str													=				tokenizer_p.save_pretrained(_A )

                  # Checks it save with the same files
                  self.assertSequenceEqual(_A						,						_A )

                  # Checks everything loads correctly in the same way
                  UpperCAmelCase__			:		Any													=				tokenizer_r.from_pretrained(_A )
                  UpperCAmelCase__			:		str													=				tokenizer_p.from_pretrained(_A )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                      self.assertTrue(hasattr(_A						,						_A ) )

                  shutil.rmtree(_A )

                  # Save tokenizer rust, legacy_format=False
                  UpperCAmelCase__			:		int													=				tempfile.mkdtemp()

                  UpperCAmelCase__			:		List[Any]													=				tokenizer_r.save_pretrained(_A						,						legacy_format=_A )
                  UpperCAmelCase__			:		List[str]													=				tokenizer_p.save_pretrained(_A )

                  # Checks it saved the tokenizer.json file
                  self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files ) )

                  # Checks everything loads correctly in the same way
                  UpperCAmelCase__			:		Dict													=				tokenizer_r.from_pretrained(_A )
                  UpperCAmelCase__			:		Tuple													=				tokenizer_p.from_pretrained(_A )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                      self.assertTrue(hasattr(_A						,						_A ) )

                  shutil.rmtree(_A )






      @cached_property
      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base''' )






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


          '''simple docstring'''


          with tempfile.NamedTemporaryFile() as f:
              shutil.copyfile(_A						,						f.name )
              UpperCAmelCase__			:		Any													=				XLMRobertaTokenizer(f.name						,						keep_accents=_A )
              UpperCAmelCase__			:		Optional[Any]													=				pickle.dumps(_A )
          pickle.loads(_A )






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          if not self.test_rust_tokenizer:
              return

          UpperCAmelCase__			:		Optional[Any]													=				self.get_tokenizer()
          UpperCAmelCase__			:		Optional[int]													=				self.get_rust_tokenizer()

          UpperCAmelCase__			:		Tuple													=				'''I was born in 92000, and this is falsé.'''

          UpperCAmelCase__			:		Tuple													=				tokenizer.tokenize(_A )
          UpperCAmelCase__			:		Optional[Any]													=				rust_tokenizer.tokenize(_A )
          self.assertListEqual(_A						,						_A )

          UpperCAmelCase__			:		List[str]													=				tokenizer.encode(_A						,						add_special_tokens=_A )
          UpperCAmelCase__			:		Optional[int]													=				rust_tokenizer.encode(_A						,						add_special_tokens=_A )
          self.assertListEqual(_A						,						_A )

          UpperCAmelCase__			:		Tuple													=				self.get_rust_tokenizer()
          UpperCAmelCase__			:		Any													=				tokenizer.encode(_A )
          UpperCAmelCase__			:		Optional[int]													=				rust_tokenizer.encode(_A )
          self.assertListEqual(_A						,						_A )






      @slow
      def lowercase_							(					self				:    Optional[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Dict													=				'''Hello World!'''
          UpperCAmelCase__			:		Dict													=				[0, 35_378, 6_661, 38, 2]
          # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
          # xlmr.eval()
          # xlmr.encode(symbols)

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






      @slow
      def lowercase_							(					self				:    Any ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				(
              '''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'''
          )
          UpperCAmelCase__			:		Any													=				[
              0,
              3_293,
              83,
              10,
              4_552,
              4_989,
              7_986,
              678,
              10,
              5_915,
              111,
              179_459,
              124_850,
              4,
              6_044,
              237,
              12,
              6,
              5,
              6,
              4,
              6_780,
              705,
              15,
              1_388,
              44,
              378,
              10_114,
              711,
              152,
              20,
              6,
              5,
              22_376,
              642,
              1_221,
              15_190,
              34_153,
              450,
              5_608,
              959,
              1_119,
              57_702,
              136,
              186,
              47,
              1_098,
              29_367,
              47,
              # 4426, # What fairseq tokenizes from "<unk>": "_<"
              # 3678, # What fairseq tokenizes from "<unk>": "unk"
              # 2740, # What fairseq tokenizes from "<unk>": ">"
              3,  # What we tokenize from "<unk>": "<unk>"
              6,  # Residue from the tokenization: an extra sentencepiece underline
              4,
              6_044,
              237,
              6_284,
              50_901,
              528,
              31,
              90,
              34,
              927,
              2,
          ]
          # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
          # xlmr.eval()
          # xlmr.encode(symbols)

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






      @slow
      def lowercase_							(					self				:    Optional[int] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Dict													=				{'''input_ids''': [[0, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [0, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 7, 5, 2, 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, 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], [0, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 5, 2, 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, 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, 1, 1, 1, 1, 1, 1, 1]], '''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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
          # fmt: on

          self.tokenizer_integration_test_util(
              expected_encoding=_A						,						model_name='''xlm-roberta-base'''						,						revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''						,						)




'''simple docstring'''
import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
  # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
  # setup instructions, if using on-demand hardware

  # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
  # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
  # Throw an error if user passes both BYO and on-demand cluster args
  # Otherwise, use default values
  UpperCamelCase__    					=      argparse.ArgumentParser()
  parser.add_argument('''--user''', type=str, default='''ubuntu''')
  parser.add_argument('''--host''', type=str, default='''localhost''')
  parser.add_argument('''--key_path''', type=str, default=None)
  parser.add_argument('''--instance''', type=str, default='''V100:1''')
  parser.add_argument('''--provider''', type=str, default='''cheapest''')
  parser.add_argument('''--use_spot''', type=bool, default=False)
  parser.add_argument('''--example''', type=str, default='''pytorch/text-generation/run_generation.py''')
  UpperCamelCase__					,   UpperCamelCase__    					=      parser.parse_known_args()
  if args.host != "localhost":
    if args.instance != "V100:1" or args.provider != "cheapest":
      raise ValueError('''Cannot specify both BYO and on-demand cluster args''')
    UpperCamelCase__    					=      rh.cluster(
        name='''rh-cluster''', ips=[args.host], ssh_creds={'''ssh_user''': args.user, '''ssh_private_key''': args.key_path}
    )
  else:
    UpperCamelCase__    					=      rh.cluster(
        name='''rh-cluster''', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
    )
  UpperCamelCase__    					=      args.example.rsplit('''/''', 1)[0]

  # Set up remote environment
  cluster.install_packages(['''pip:./'''])  # Installs transformers from local source
  # Note transformers is copied into the home directory on the remote machine, so we can install from there
  cluster.run([F"""pip install -r transformers/examples/{example_dir}/requirements.txt"""])
  cluster.run(['''pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117'''])

  # Run example. You can bypass the CLI wrapper and paste your own code here.
  cluster.run([F"""python transformers/examples/{args.example} {' '.join(shlex.quote(arg) for arg in unknown)}"""])

  # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
  # from my_script... import train
  # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
  # launch_train_gpu = rh.function(fn=train,
  #                                system=gpu,
  #                                reqs=reqs,
  #                                name='train_bert_glue')
  #
  # We can pass in arguments just like we would to a function:
  # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
  #                  stream_logs=True)
