code: 
  
  
  import subprocess
  from argparse import ArgumentParser
  from typing import List, Union
  
  from huggingface_hub.hf_api import HfFolder, create_repo, whoami
  from requests.exceptions import HTTPError
  
  from . import BaseTransformersCLICommand
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        @staticmethod
        def        __lowerCamelCase			(							SCREAMING_SNAKE_CASE__		):
              lowercase			:   Dict					   =		parser.add_parser('''login'''							,						help='''Log in using the same credentials as on huggingface.co'''		)
              login_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE__		: LoginCommand(SCREAMING_SNAKE_CASE__		)		)
              lowercase			:   int					   =		parser.add_parser('''whoami'''							,						help='''Find out which huggingface.co account you are logged in as.'''		)
              whoami_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE__		: WhoamiCommand(SCREAMING_SNAKE_CASE__		)		)
              lowercase			:   int					   =		parser.add_parser('''logout'''							,						help='''Log out'''		)
              logout_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE__		: LogoutCommand(SCREAMING_SNAKE_CASE__		)		)
  
              # new system: git-based repo system
              lowercase			:   Union[str, Any]					   =		parser.add_parser(
                  '''repo'''							,						help='''Deprecated: use `huggingface-cli` instead. Commands to interact with your huggingface.co repos.'''							,						)
              lowercase			:   List[str]					   =		repo_parser.add_subparsers(
                  help='''Deprecated: use `huggingface-cli` instead. huggingface.co repos related commands'''		)
              lowercase			:   int					   =		repo_subparsers.add_parser(
                  '''create'''							,						help='''Deprecated: use `huggingface-cli` instead. Create a new repo on huggingface.co'''		)
              repo_create_parser.add_argument(
                  '''name'''							,						type=SCREAMING_SNAKE_CASE__							,						help='''Name for your model\'s repo. Will be namespaced under your username to build the model id.'''							,						)
              repo_create_parser.add_argument('''--organization'''							,						type=SCREAMING_SNAKE_CASE__							,						help='''Optional: organization namespace.'''		)
              repo_create_parser.add_argument('''-y'''							,						'''--yes'''							,						action='''store_true'''							,						help='''Optional: answer Yes to the prompt'''		)
              repo_create_parser.set_defaults(func=lambda SCREAMING_SNAKE_CASE__		: RepoCreateCommand(SCREAMING_SNAKE_CASE__		)		)
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   :
        A				:							Tuple    							=     "\u001b[1m"
        A				:							int    							=     "\u001b[31m"
        A				:							Optional[Any]    							=     "\u001b[90m"
        A				:							Optional[Any]    							=     "\u001b[0m"
  
  
        @classmethod
        def        __lowerCamelCase			(							cls							,						SCREAMING_SNAKE_CASE__		):
              return f"""{cls._bold}{s}{cls._reset}"""
  
  
        @classmethod
        def        __lowerCamelCase			(							cls							,						SCREAMING_SNAKE_CASE__		):
              return f"""{cls._bold}{cls._red}{s}{cls._reset}"""
  
  
  
  
  
  
        @classmethod
        def        __lowerCamelCase			(							cls							,						SCREAMING_SNAKE_CASE__		):
              return f"""{cls._gray}{s}{cls._reset}"""
  
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->str:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Dict					   =		[max(len(str(_UpperCamelCase     )     ) for x in col     ) for col in zip(*_UpperCamelCase,    _UpperCamelCase     )]
        lowercase			:   str					   =		("{{:{}}} " * len(_UpperCamelCase     )).format(*_UpperCamelCase     )
        lowercase			:   Tuple					   =		[]
        lines.append(row_format.format(*_UpperCamelCase     )     )
        lines.append(row_format.format(*['''-''' * w for w in col_widths]     )     )
        for row in rows:
              lines.append(row_format.format(*_UpperCamelCase     )     )
        return "\n".join(_UpperCamelCase     )
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   :
  
  
        def __init__(							self							,						SCREAMING_SNAKE_CASE__		):
              lowercase			:   List[str]					   =		args
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        def        __lowerCamelCase			(							self		):
              print(
                  ANSI.red(
                      '''ERROR! `huggingface-cli login` uses an outdated login mechanism '''
                      '''that is not compatible with the Hugging Face Hub backend anymore. '''
                      '''Please use `huggingface-cli login instead.'''		)		)
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        def        __lowerCamelCase			(							self		):
              print(
                  ANSI.red(
                      '''WARNING! `transformers-cli whoami` is deprecated and will be removed in v5. Please use '''
                      '''`huggingface-cli whoami` instead.'''		)		)
              lowercase			:   Optional[Any]					   =		HfFolder.get_token()
              if token is None:
                    print('''Not logged in'''		)
                    exit()
              try:
                    lowercase			:   Tuple					   =		whoami(SCREAMING_SNAKE_CASE__		)
                    print(SCREAMING_SNAKE_CASE__		)
                    if orgs:
                          print(ANSI.bold('''orgs: '''		)							,						''','''.join(SCREAMING_SNAKE_CASE__		)		)
              except HTTPError as e:
                    print(SCREAMING_SNAKE_CASE__		)
                    print(ANSI.red(e.response.text		)		)
                    exit(1		)
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        def        __lowerCamelCase			(							self		):
              print(
                  ANSI.red(
                      '''ERROR! `transformers-cli logout` uses an outdated logout mechanism '''
                      '''that is not compatible with the Hugging Face Hub backend anymore. '''
                      '''Please use `huggingface-cli logout instead.'''		)		)
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        def        __lowerCamelCase			(							self		):
              print(
                  ANSI.red(
                      '''WARNING! Managing repositories through transformers-cli is deprecated. '''
                      '''Please use `huggingface-cli` instead.'''		)		)
              lowercase			:   Dict					   =		HfFolder.get_token()
              if token is None:
                    print('''Not logged in'''		)
                    exit(1		)
              try:
                    lowercase			:   Optional[int]					   =		subprocess.check_output(['''git''', '''--version''']		).decode('''utf-8'''		)
                    print(ANSI.gray(stdout.strip()		)		)
              except FileNotFoundError:
                    print('''Looks like you do not have git installed, please install.'''		)
  
              try:
                    lowercase			:   Union[str, Any]					   =		subprocess.check_output(['''git-lfs''', '''--version''']		).decode('''utf-8'''		)
                    print(ANSI.gray(stdout.strip()		)		)
              except FileNotFoundError:
                    print(
                        ANSI.red(
                            '''Looks like you do not have git-lfs installed, please install.'''
                            ''' You can install from https://git-lfs.github.com/.'''
                            ''' Then run `git lfs install` (you only have to do this once).'''		)		)
              print(''''''		)
  
              lowercase			:   Any					   =		whoami(SCREAMING_SNAKE_CASE__		)
              lowercase			:   List[str]					   =		self.args.organization if self.args.organization is not None else user
              lowercase			:   Any					   =		f"""{namespace}/{self.args.name}"""
              print(f"""You are about to create {ANSI.bold(SCREAMING_SNAKE_CASE__		)}"""		)
  
              if not self.args.yes:
                    lowercase			:   Optional[int]					   =		input('''Proceed? [Y/n] '''		).lower()
                    if not (choice == "" or choice == "y" or choice == "yes"):
                          print('''Abort'''		)
                          exit()
              try:
                    lowercase			:   List[str]					   =		create_repo(SCREAMING_SNAKE_CASE__							,						name=self.args.name							,						organization=self.args.organization		)
              except HTTPError as e:
                    print(SCREAMING_SNAKE_CASE__		)
                    print(ANSI.red(e.response.text		)		)
                    exit(1		)
              print('''\nYour repo now lives at:'''		)
              print(f"""  {ANSI.bold(SCREAMING_SNAKE_CASE__		)}"""		)
              print('''\nYou can clone it locally with the command below, and commit/push as usual.'''		)
              print(f"""\n  git clone {url}"""		)
              print(''''''		)
  
  
style_context: 
  
  
  import argparse
  import logging
  
  import numpy as np
  import torch
  
  from transformers import AutoModelForCausalLM, AutoTokenizer
  
  
  logging.basicConfig(
      format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''',
      datefmt='''%m/%d/%Y %H:%M:%S''',
      level=logging.INFO,
  )
  __a   				=      logging.getLogger(__name__)
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->Any:
  
  
  
  
  
  
  
        """simple docstring"""
  
        np.random.seed(args.seed     )
        torch.manual_seed(args.seed     )
        if args.n_gpu > 0:
              torch.cuda.manual_seed_all(args.seed     )
  
  
  
  
  def 			__lowercase	(						)    ->List[str]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   List[str]					   =		argparse.ArgumentParser()
        parser.add_argument(
            '''--model_name_or_path''',    default=_UpperCamelCase,    type=_UpperCamelCase,    required=_UpperCamelCase,    )
        parser.add_argument('''--prompt''',    type=_UpperCamelCase,    default=''''''     )
        parser.add_argument('''--length''',    type=_UpperCamelCase,    default=20     )
        parser.add_argument('''--stop_token''',    type=_UpperCamelCase,    default=_UpperCamelCase,    help='''Token at which text generation is stopped'''     )
        parser.add_argument(
            '''--temperature''',    type=_UpperCamelCase,    default=1.0,    help='''temperature of 1.0 has no effect, lower tend toward greedy sampling''',    )
        parser.add_argument(
            '''--repetition_penalty''',    type=_UpperCamelCase,    default=1.0,    help='''primarily useful for CTRL model; in that case, use 1.2'''     )
        parser.add_argument('''--k''',    type=_UpperCamelCase,    default=0     )
        parser.add_argument('''--penalty_alpha''',    type=_UpperCamelCase,    default=0.0     )
        parser.add_argument('''--p''',    type=_UpperCamelCase,    default=0.9     )
  
        parser.add_argument('''--prefix''',    type=_UpperCamelCase,    default='''''',    help='''Text added prior to input.'''     )
        parser.add_argument('''--padding_text''',    type=_UpperCamelCase,    default='''''',    help='''Deprecated, the use of `--prefix` is preferred.'''     )
        parser.add_argument('''--xlm_language''',    type=_UpperCamelCase,    default='''''',    help='''Optional language when used with the XLM model.'''     )
  
        parser.add_argument('''--seed''',    type=_UpperCamelCase,    default=42,    help='''random seed for initialization'''     )
        parser.add_argument('''--no_cuda''',    action='''store_true''',    help='''Avoid using CUDA when available'''     )
        parser.add_argument(
            '''--fp16''',    action='''store_true''',    help='''Whether to use 16-bit (mixed) precision (through NVIDIA apex) instead of 32-bit''',    )
        lowercase			:   Any					   =		parser.parse_args()
  
        lowercase			:   int					   =		torch.device('''cuda''' if torch.cuda.is_available() and not args.no_cuda else '''cpu'''     )
        lowercase			:   List[str]					   =		0 if args.no_cuda else torch.cuda.device_count()
  
        logger.warning(f"""device: {args.device}, n_gpu: {args.n_gpu}, 16-bits training: {args.fpaa}"""     )
  
        set_seed(_UpperCamelCase     )
  
        # Initialize the model and tokenizer
        lowercase			:   Optional[Any]					   =		AutoTokenizer.from_pretrained(args.model_name_or_path     )
        lowercase			:   List[Any]					   =		AutoModelForCausalLM.from_pretrained(args.model_name_or_path     )
  
        # tokenizer = GPT2Tokenizer.from_pretrained(args.model_name_or_path)
        # model = OPTForCausalLM.from_pretrained(args.model_name_or_path)
        model.to(args.device     )
  
        if args.fpaa:
              model.half()
  
        logger.info(_UpperCamelCase     )
        lowercase			:   Union[str, Any]					   =		args.prompt if args.prompt else input('''Model prompt >>> '''     )
  
        lowercase			:   List[Any]					   =		tokenizer(_UpperCamelCase,    return_tensors='''pt''',    add_special_tokens=_UpperCamelCase     )
        lowercase			:   Union[str, Any]					   =		{key: value.to(args.device     ) for key, value in inputs.items()}
  
        lowercase			:   Optional[int]					   =		model.generate(
            **_UpperCamelCase,    max_length=args.length + len(inputs['''input_ids'''][0]     ),    penalty_alpha=args.penalty_alpha,    top_k=args.k,    )
  
        lowercase			:   Union[str, Any]					   =		[]
        for generated_sequence_idx, generated_sequence in enumerate(_UpperCamelCase     ):
              print(f"""=== GENERATED SEQUENCE {generated_sequence_idx + 1} ==="""     )
              lowercase			:   Optional[Any]					   =		generated_sequence.tolist()
  
              # Decode text
              lowercase			:   int					   =		tokenizer.decode(_UpperCamelCase,    clean_up_tokenization_spaces=_UpperCamelCase,    add_special_tokens=_UpperCamelCase     )
  
              # Remove all text after the stop token
              lowercase			:   Optional[int]					   =		text[: text.find(args.stop_token     ) if args.stop_token else None]
  
              # Add the prompt at the beginning of the sequence. Remove the excess text that was used for pre-processing
              lowercase			:   Optional[Any]					   =		(
                  prompt_text + text[len(tokenizer.decode(inputs['''input_ids'''][0],    clean_up_tokenization_spaces=_UpperCamelCase     )     ) :]
              )
  
              generated_sequences.append(_UpperCamelCase     )
              print(_UpperCamelCase     )
  
        return generated_sequences
  
  
  if __name__ == "__main__":
    main()
  
  