
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


__A				={'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__A				={
    '''vocab_file''': {
        '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''unc-nlp/lxmert-base-uncased''': (
            '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

__A				={
    '''unc-nlp/lxmert-base-uncased''': 5_1_2,
}

__A				={
    '''unc-nlp/lxmert-base-uncased''': {'''do_lower_case''': True},
}




class     _SCREAMING_SNAKE_CASE     (      snake_case_						):
	lowerCAmelCase__         = VOCAB_FILES_NAMES
	lowerCAmelCase__         = PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase__         = PRETRAINED_INIT_CONFIGURATION
	lowerCAmelCase__         = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase__         = LxmertTokenizer



	def __init__(    self						,  lowercase=None						,  lowercase=None						,  lowercase=True						,  lowercase="[UNK]"						,  lowercase="[SEP]"						,  lowercase="[PAD]"						,  lowercase="[CLS]"						,  lowercase="[MASK]"						,  lowercase=True						,  lowercase=None						,  **lowercase						,  )				->       Dict:
					super().__init__(
					    lowercase						,  tokenizer_file=lowercase						,  do_lower_case=lowercase						,  unk_token=lowercase						,  sep_token=lowercase						,  pad_token=lowercase						,  cls_token=lowercase						,  mask_token=lowercase						,  tokenize_chinese_chars=lowercase						,  strip_accents=lowercase						,  **lowercase						,  )

					lowerCamelCase_						=			json.loads(self.backend_tokenizer.normalizer.__getstate__() )
					if (
					    normalizer_state.get("lowercase"						,  lowercase ) != do_lower_case
					    or normalizer_state.get("strip_accents"						,  lowercase ) != strip_accents
					    or normalizer_state.get("handle_chinese_chars"						,  lowercase ) != tokenize_chinese_chars
					):
									lowerCamelCase_						=			getattr(lowercase						,  normalizer_state.pop("type" ) )
									lowerCamelCase_						=			do_lower_case
									lowerCamelCase_						=			strip_accents
									lowerCamelCase_						=			tokenize_chinese_chars
									lowerCamelCase_						=			normalizer_class(**lowercase )

					lowerCamelCase_						=			do_lower_case



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase=None )				->       Union[str, Any]:
					lowerCamelCase_						=			[self.cls_token_id] + token_ids_a + [self.sep_token_id]

					if token_ids_a:
									output += token_ids_a + [self.sep_token_id]

					return output



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase = None )				->       List[int]:
					lowerCamelCase_						=			[self.sep_token_id]
					lowerCamelCase_						=			[self.cls_token_id]
					if token_ids_a is None:
									return len(cls + token_ids_a + sep ) * [0]
					return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase = None )				->       Tuple[str]:
					lowerCamelCase_						=			self._tokenizer.model.save(lowercase						,  name=lowercase )
					return tuple(lowercase )





from argparse import ArgumentParser

from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.utils.logging import set_verbosity_info
def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	Tuple      )							->      Tuple:





    '''simple docstring'''






    return {key.lstrip('-'      ): value for key, value in zip(unknown_args[::2]    ,			unknown_args[1::2]      )}
def 						_snake_case(    )							->      Dict:





    '''simple docstring'''






    A__          =   ArgumentParser(
        'HuggingFace Datasets CLI tool'    ,			usage='datasets-cli <command> [<args>]'    ,			allow_abbrev=SCREAMING_SNAKE_CASE__      )
    A__          =   parser.add_subparsers(help='datasets-cli command helpers'      )
    set_verbosity_info()

    # Register commands
    ConvertCommand.register_subcommand(SCREAMING_SNAKE_CASE__      )
    EnvironmentCommand.register_subcommand(SCREAMING_SNAKE_CASE__      )
    TestCommand.register_subcommand(SCREAMING_SNAKE_CASE__      )
    RunBeamCommand.register_subcommand(SCREAMING_SNAKE_CASE__      )
    DummyDataCommand.register_subcommand(SCREAMING_SNAKE_CASE__      )

    # Parse args
    A__      ,						A__          =   parser.parse_known_args()
    if not hasattr(SCREAMING_SNAKE_CASE__    ,			'func'      ):
        parser.print_help()
        exit(1      )
    A__          =   parse_unknown_args(SCREAMING_SNAKE_CASE__      )

    # Run
    A__          =   args.func(SCREAMING_SNAKE_CASE__    ,			**SCREAMING_SNAKE_CASE__      )
    service.run()


if __name__ == "__main__":
     main()

