


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_xglm import XGLMTokenizer
else:
       __lowerCamelCase   	=  None


__lowerCamelCase   	=  logging.get_logger(__name__)

__lowerCamelCase   	=  {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCamelCase   	=  {
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json''',
    },
}

__lowerCamelCase   	=  {
    '''facebook/xglm-564M''': 2048,
}


class 	a__						(    lowerCAmelCase_     ):
       lowerCamelCase__:  Optional[int]				     =  VOCAB_FILES_NAMES
       lowerCamelCase__:  Dict				     =  PRETRAINED_VOCAB_FILES_MAP
       lowerCamelCase__:  Dict				     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCamelCase__:  Optional[Any]				     =  ["""input_ids""", """attention_mask"""]
       lowerCamelCase__:  Dict				     =  XGLMTokenizer

       def __init__( self   :  int   ,				lowerCamelCase_   :  Optional[Any]=None   ,				lowerCamelCase_   :  Any=None   ,				lowerCamelCase_   :  Dict="<s>"   ,				lowerCamelCase_   :  Dict="</s>"   ,				lowerCamelCase_   :  Any="</s>"   ,				lowerCamelCase_   :  List[str]="<s>"   ,				lowerCamelCase_   :  Optional[Any]="<unk>"   ,				lowerCamelCase_   :  Dict="<pad>"   ,				**lowerCamelCase_   :  Tuple   ,				):
            # Compatibility with the original tokenizer
            a_     :  Union[str, Any]				      =     7
            a_     :  List[str]				      =     [F'''<madeupword{i}>''' for i in range(self.num_madeup_words     )]

            a_     :  Tuple				      =     kwargs.get("""additional_special_tokens"""   ,				[]     )
            kwargs["additional_special_tokens"] += [
                word for word in madeup_words if word not in kwargs["additional_special_tokens"]
            ]

            super().__init__(
                lowerCamelCase_   ,				tokenizer_file=lowerCamelCase_   ,				bos_token=lowerCamelCase_   ,				eos_token=lowerCamelCase_   ,				sep_token=lowerCamelCase_   ,				cls_token=lowerCamelCase_   ,				unk_token=lowerCamelCase_   ,				pad_token=lowerCamelCase_   ,				**lowerCamelCase_   ,				)

            a_     :  int				      =     vocab_file
            a_     :  Optional[int]				      =     False if not self.vocab_file else True

       def     UpperCAmelCase( self   :  List[Any]   ,				lowerCamelCase_   :  List[int]   ,				lowerCamelCase_   :  Optional[List[int]] = None     ):

            if token_ids_a is None:
                 return [self.sep_token_id] + token_ids_a
            a_     :  Union[str, Any]				      =     [self.sep_token_id]
            return sep + token_ids_a + sep + sep + token_ids_a

       def     UpperCAmelCase( self   :  str   ,				lowerCamelCase_   :  List[int]   ,				lowerCamelCase_   :  Optional[List[int]] = None     ):
            a_     :  List[str]				      =     [self.sep_token_id]

            if token_ids_a is None:
                 return len(sep + token_ids_a     ) * [0]
            return len(sep + token_ids_a + sep + sep + token_ids_a     ) * [0]

       def     UpperCAmelCase( self   :  Any   ,				lowerCamelCase_   :  str   ,				lowerCamelCase_   :  Optional[str] = None     ):
            if not self.can_save_slow_tokenizer:
                 raise ValueError(
                     """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                     """tokenizer."""     )

            if not os.path.isdir(lowerCamelCase_     ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''     )
                 return
            a_     :  Optional[Any]				      =     os.path.join(
                lowerCamelCase_   ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]     )

            if os.path.abspath(self.vocab_file     ) != os.path.abspath(lowerCamelCase_     ):
                 copyfile(self.vocab_file   ,				lowerCamelCase_     )

            return (out_vocab_file,)








from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase__  =			logging.get_logger(__name__)

UpperCAmelCase__  =			{
    "dandelin/vilt-b32-mlm": "https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"
}







class      __lowerCAmelCase       (     A		):
			UpperCamelCase     =	'''vilt'''



			def __init__(		self  :    List[Any]					,						A  :    Dict=3_05_22					,						A  :    Union[str, Any]=2					,						A  :    Tuple=2					,						A  :    List[Any]=40					,						A  :    Optional[int]=7_68					,						A  :    Any=12					,						A  :    Optional[int]=12					,						A  :    Optional[Any]=30_72					,						A  :    Optional[Any]="gelu"					,						A  :    str=0.0					,						A  :    Any=0.0					,						A  :    Union[str, Any]=0.0_2					,						A  :    Union[str, Any]=1E-12					,						A  :    Optional[Any]=3_84					,						A  :    Dict=32					,						A  :    int=3					,						A  :    int=True					,						A  :    Union[str, Any]=-1					,						A  :    int=False					,						A  :    int=-1					,						**A  :    Tuple					,						)  ->       Dict:



						"""simple docstring"""






						super().__init__(tie_word_embeddings=A					,						**A)

						_UpperCAmelCase									=  vocab_size
						_UpperCAmelCase									=  type_vocab_size
						_UpperCAmelCase									=  modality_type_vocab_size
						_UpperCAmelCase									=  max_position_embeddings

						_UpperCAmelCase									=  hidden_size
						_UpperCAmelCase									=  num_hidden_layers
						_UpperCAmelCase									=  num_attention_heads
						_UpperCAmelCase									=  intermediate_size
						_UpperCAmelCase									=  hidden_act
						_UpperCAmelCase									=  hidden_dropout_prob
						_UpperCAmelCase									=  attention_probs_dropout_prob
						_UpperCAmelCase									=  initializer_range
						_UpperCAmelCase									=  layer_norm_eps

						_UpperCAmelCase									=  image_size
						_UpperCAmelCase									=  patch_size
						_UpperCAmelCase									=  num_channels
						_UpperCAmelCase									=  qkv_bias
						_UpperCAmelCase									=  max_image_length
						_UpperCAmelCase									=  num_images
