


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:
       lowercase_           =	None


lowercase_           =	logging.get_logger(__name__)

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

lowercase_           =	{
    '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',
    },
}

lowercase_           =	{
    'facebook/xglm-564M': 2_0_4_8,
}


class        A_					(       __UpperCamelCase    ):




      '''simple docstring'''


      __snake_case					       =   VOCAB_FILES_NAMES
      __snake_case					       =   PRETRAINED_VOCAB_FILES_MAP
      __snake_case					       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __snake_case					       =   ["""input_ids""", """attention_mask"""]
      __snake_case					       =   XGLMTokenizer




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

       __lowerCamelCase		:							List[str]							=						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__(
           a						,      tokenizer_file=a						,      bos_token=a						,      eos_token=a						,      sep_token=a						,      cls_token=a						,      unk_token=a						,      pad_token=a						,      **a						,      )

       __lowerCamelCase		:							Dict							=						vocab_file
       __lowerCamelCase		:							int							=						False if not self.vocab_file else True




      def      _snake_case	(				self:       List[str]						,      a:       List[int]						,      a:       Optional[List[int]] = None				):

       if token_ids_a is None:
        return [self.sep_token_id] + token_ids_a
       __lowerCamelCase		:							Any							=						[self.sep_token_id]
       return sep + token_ids_a + sep + sep + token_ids_a




      def      _snake_case	(				self:       Union[str, Any]						,      a:       List[int]						,      a:       Optional[List[int]] = None				):
       __lowerCamelCase		:							Optional[int]							=						[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      _snake_case	(				self:       Union[str, Any]						,      a:       str						,      a:       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(a				):
        logger.error(F'Vocabulary path ({save_directory}) should be a directory.'				)
        return
       __lowerCamelCase		:							str							=						os.path.join(
           a						,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

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

       return (out_vocab_file,)





from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


lowercase_           =	datasets.utils.logging.get_logger(__name__)


class        A_					(       folder_based_builder.FolderBasedBuilderConfig    ):




      '''simple docstring'''


      __snake_case					       =   None
      __snake_case					       =   None



class        A_					(       folder_based_builder.FolderBasedBuilder    ):




      '''simple docstring'''


      __snake_case					       =   datasets.Image()
      __snake_case					       =   """image"""
      __snake_case					       =   ImageFolderConfig
      __snake_case					       =   42  # definition at the bottom of the script
      __snake_case					       =   ImageClassification(image_column="""image"""					,      label_column="""label"""    )



lowercase_           =	[
    '.blp',
    '.bmp',
    '.dib',
    '.bufr',
    '.cur',
    '.pcx',
    '.dcx',
    '.dds',
    '.ps',
    '.eps',
    '.fit',
    '.fits',
    '.fli',
    '.flc',
    '.ftc',
    '.ftu',
    '.gbr',
    '.gif',
    '.grib',
    '.h5',
    '.hdf',
    '.png',
    '.apng',
    '.jp2',
    '.j2k',
    '.jpc',
    '.jpf',
    '.jpx',
    '.j2c',
    '.icns',
    '.ico',
    '.im',
    '.iim',
    '.tif',
    '.tiff',
    '.jfif',
    '.jpe',
    '.jpg',
    '.jpeg',
    '.mpg',
    '.mpeg',
    '.msp',
    '.pcd',
    '.pxr',
    '.pbm',
    '.pgm',
    '.ppm',
    '.pnm',
    '.psd',
    '.bw',
    '.rgb',
    '.rgba',
    '.sgi',
    '.ras',
    '.tga',
    '.icb',
    '.vda',
    '.vst',
    '.webp',
    '.wmf',
    '.emf',
    '.xbm',
    '.xpm',
]
lowercase_           =	IMAGE_EXTENSIONS

