




'''simple docstring'''
import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					_UpperCamelCase							=		["""image_processor""", """tokenizer"""]
					_UpperCamelCase							=		"""ViltImageProcessor"""
					_UpperCamelCase							=		("""BertTokenizer""", """BertTokenizerFast""")



					def __init__(	self     :						int      ,       _lowercase     :						int=None      ,       _lowercase     :						List[str]=None      ,       **_lowercase     :						Dict)    ->							Union[str, Any]:
								A_									= None
								if "feature_extractor" in kwargs:
											warnings.warn(
											    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
											    ' instead.'      ,       _lowercase      ,       )
											A_									= kwargs.pop('feature_extractor')

								A_									= image_processor if image_processor is not None else feature_extractor
								if image_processor is None:
											raise ValueError('You need to specify an `image_processor`.')
								if tokenizer is None:
											raise ValueError('You need to specify a `tokenizer`.')

								super().__init__(_lowercase      ,       _lowercase)
								A_									= self.image_processor



					def __call__(	self     :						Optional[int]      ,       _lowercase     :						str      ,       _lowercase     :						Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None      ,       _lowercase     :						bool = True      ,       _lowercase     :						Union[bool, str, PaddingStrategy] = False      ,       _lowercase     :						Union[bool, str, TruncationStrategy] = None      ,       _lowercase     :						Optional[int] = None      ,       _lowercase     :						int = 0      ,       _lowercase     :						Optional[int] = None      ,       _lowercase     :						Optional[bool] = None      ,       _lowercase     :						Optional[bool] = None      ,       _lowercase     :						bool = False      ,       _lowercase     :						bool = False      ,       _lowercase     :						bool = False      ,       _lowercase     :						bool = False      ,       _lowercase     :						bool = True      ,       _lowercase     :						Optional[Union[str, TensorType]] = None      ,       **_lowercase     :						int      ,       )    ->							BatchEncoding:
								A_									= self.tokenizer(
								    text=_lowercase      ,       add_special_tokens=_lowercase      ,       padding=_lowercase      ,       truncation=_lowercase      ,       max_length=_lowercase      ,       stride=_lowercase      ,       pad_to_multiple_of=_lowercase      ,       return_token_type_ids=_lowercase      ,       return_attention_mask=_lowercase      ,       return_overflowing_tokens=_lowercase      ,       return_special_tokens_mask=_lowercase      ,       return_offsets_mapping=_lowercase      ,       return_length=_lowercase      ,       verbose=_lowercase      ,       return_tensors=_lowercase      ,       **_lowercase      ,       )
								# add pixel_values + pixel_mask
								A_									= self.image_processor(_lowercase      ,       return_tensors=_lowercase)
								encoding.update(_lowercase)

								return encoding



					def     __snake_case						(	self     :						Union[str, Any]      ,       *_lowercase     :						Dict      ,       **_lowercase     :						str)    ->							Optional[int]:
								return self.tokenizer.batch_decode(*_lowercase      ,       **_lowercase)



					def     __snake_case						(	self     :						Union[str, Any]      ,       *_lowercase     :						Any      ,       **_lowercase     :						List[Any])    ->							List[Any]:
								return self.tokenizer.decode(*_lowercase      ,       **_lowercase)



					@property
					def     __snake_case						(	self     :						Any)    ->							Optional[int]:
								A_									= self.tokenizer.model_input_names
								A_									= self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))



					@property
					def     __snake_case						(	self     :						Optional[int])    ->							Any:
								warnings.warn(
								    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'      ,       _lowercase      ,       )
								return self.image_processor_class



					@property
					def     __snake_case						(	self     :						Union[str, Any])    ->							Optional[Any]:
								warnings.warn(
								    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'      ,       _lowercase      ,       )
								return self.image_processor










'''simple docstring'''
from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands





def 			lowerCamelCase(							)		->		int:
			A_									= ArgumentParser('Transformers CLI tool'       ,usage='transformers-cli <command> [<args>]'     )
			A_									= parser.add_subparsers(help='transformers-cli command helpers'     )

			# Register commands
			ConvertCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			DownloadCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			EnvironmentCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			RunCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			ServeCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			UserCommands.register_subcommand(SCREAMING_SNAKE_CASE_     )
			AddNewModelCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			AddNewModelLikeCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )
			LfsCommands.register_subcommand(SCREAMING_SNAKE_CASE_     )
			PTtoTFCommand.register_subcommand(SCREAMING_SNAKE_CASE_     )

			# Let's go
			A_									= parser.parse_args()

			if not hasattr(SCREAMING_SNAKE_CASE_       ,'func'     ):
						parser.print_help()
						exit(1     )

			# Run
			A_									= args.func(SCREAMING_SNAKE_CASE_     )
			service.run()


if __name__ == "__main__":
							main()




