'''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
  __a:			str	       =       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""")
  __a       ,      __a:			Optional[Any]	       =       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""")
    __a:			Optional[int]	       =       rh.cluster(
        name="""rh-cluster""", ips=[args.host], ssh_creds={"""ssh_user""": args.user, """ssh_private_key""": args.key_path}
    )
  else:
    __a:			Dict	       =       rh.cluster(
        name="""rh-cluster""", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
    )
  __a:			Optional[Any]	       =       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)


'''simple docstring'''

import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class       UpperCAmelCase  (						a__   ,						unittest.TestCase ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   OpenAIGPTTokenizer
       SCREAMING_SNAKE_CASE 		=   OpenAIGPTTokenizerFast
       SCREAMING_SNAKE_CASE 		=   True
       SCREAMING_SNAKE_CASE 		=   False

       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        lowercase__    :   Optional[Any]						= [
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''w</w>''',
            '''r</w>''',
            '''t</w>''',
            '''lo''',
            '''low''',
            '''er</w>''',
            '''low</w>''',
            '''lowest</w>''',
            '''newer</w>''',
            '''wider</w>''',
            '''<unk>''',
        ]
        lowercase__    :   Optional[int]						= dict(zip(__lowerCAmelCase     ,       range(len(__lowerCAmelCase			)			)			)			)
        lowercase__    :   Union[str, Any]						= ['''#version: 0.2''', '''l o''', '''lo w''', '''e r</w>''', '''''']

        lowercase__    :   Optional[int]						= os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''vocab_file''']			)
        lowercase__    :   Optional[int]						= os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''merges_file''']			)
        with open(self.vocab_file     ,       '''w'''			) as fp:
         fp.write(json.dumps(__lowerCAmelCase			)			)
        with open(self.merges_file     ,       '''w'''			) as fp:
         fp.write('''\n'''.join(__lowerCAmelCase			)			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Dict:
        return "lower newer", "lower newer"

       def _lowerCAmelCase(						self			)  ->  List[Any]:
        lowercase__    :   int						= OpenAIGPTTokenizer(self.vocab_file     ,       self.merges_file			)

        lowercase__    :   List[Any]						= '''lower'''
        lowercase__    :   Any						= ['''low''', '''er</w>''']
        lowercase__    :   Union[str, Any]						= tokenizer.tokenize(__lowerCAmelCase			)
        self.assertListEqual(__lowerCAmelCase     ,       __lowerCAmelCase			)

        lowercase__    :   Tuple						= tokens + ['''<unk>''']
        lowercase__    :   Optional[Any]						= [14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)     ,       __lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase=15			)  ->  Optional[int]:
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""			):
          lowercase__    :   List[str]						= self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase     ,       **__lowerCAmelCase			)

          # Simple input
          lowercase__    :   List[str]						= '''This is a simple input'''
          lowercase__    :   Any						= ['''This is a simple input 1''', '''This is a simple input 2''']
          lowercase__    :   str						= ('''This is a simple input''', '''This is a pair''')
          lowercase__    :   str						= [
              ('''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(__lowerCAmelCase     ,       tokenizer_r.encode     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''			)

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

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

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

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

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


       def _lowerCAmelCase(						self			)  ->  Tuple:
        pass



@require_ftfy
@require_spacy
@require_tokenizers
class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       pass

