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

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


if is_sentencepiece_available():
   from .tokenization_fnet import FNetTokenizer
else:
   __lowerCamelCase      :			Union[str, Any]							       =		None

__lowerCamelCase      :			Optional[Any]							       =		logging.get_logger(__name__)
__lowerCamelCase      :			int							       =		{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCamelCase      :			List[Any]							       =		{
    '''vocab_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/spiece.model''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json''',
    },
}

__lowerCamelCase      :			Optional[int]							       =		{
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

__lowerCamelCase      :			Dict							       =		'''▁'''







class __snake_case    (						lowerCamelCase_		):
   lowerCAmelCase_														=							VOCAB_FILES_NAMES
   lowerCAmelCase_														=							PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase_														=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase_														=							["input_ids", "token_type_ids"]
   lowerCAmelCase_														=							FNetTokenizer




   def __init__(   self      :    Any	,     _lowercase      :    Optional[Any]=None	,     _lowercase      :    Optional[Any]=None	,     _lowercase      :    int=False	,     _lowercase      :    Tuple=True	,     _lowercase      :    Tuple=True	,     _lowercase      :    Dict="<unk>"	,     _lowercase      :    int="[SEP]"	,     _lowercase      :    Optional[int]="<pad>"	,     _lowercase      :    List[str]="[CLS]"	,     _lowercase      :    Dict="[MASK]"	,     **_lowercase      :    Optional[int]	,     ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				(
         AddedToken(_lowercase	,     lstrip=_lowercase	,     rstrip=_lowercase	,     normalized=_lowercase				)
         if isinstance(_lowercase	,     _lowercase				)
         else mask_token
     )

     super().__init__(
         _lowercase	,     tokenizer_file=_lowercase	,     do_lower_case=_lowercase	,     remove_space=_lowercase	,     keep_accents=_lowercase	,     unk_token=_lowercase	,     sep_token=_lowercase	,     pad_token=_lowercase	,     cls_token=_lowercase	,     mask_token=_lowercase	,     **_lowercase	,     )

     SCREAMING_SNAKE_CASE__      							=				do_lower_case
     SCREAMING_SNAKE_CASE__      							=				remove_space
     SCREAMING_SNAKE_CASE__      							=				keep_accents
     SCREAMING_SNAKE_CASE__      							=				vocab_file
     SCREAMING_SNAKE_CASE__      							=				False if not self.vocab_file else True




   def      __a						(   self      :    List[str]	,     _lowercase      :    List[int]	,     _lowercase      :    Optional[List[int]] = None				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				[self.sep_token_id]
     SCREAMING_SNAKE_CASE__      							=				[self.cls_token_id]
     if token_ids_a is None:
       return cls + token_ids_a + sep
     return cls + token_ids_a + sep + token_ids_a + sep




   def      __a						(   self      :    Optional[int]	,     _lowercase      :    List[int]	,     _lowercase      :    Optional[List[int]] = None				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				[self.sep_token_id]
     SCREAMING_SNAKE_CASE__      							=				[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      __a						(   self      :    int	,     _lowercase      :    str	,     _lowercase      :    Optional[str] = None				):



     """simple docstring"""






     if not os.path.isdir(_lowercase				):
       logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
       return
     SCREAMING_SNAKE_CASE__      							=				os.path.join(
         _lowercase	,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

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

     return (out_vocab_file,)

import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
   __lowerCamelCase      :			Optional[Any]							       =		{
       '''linear''': PIL.Image.Resampling.BILINEAR,
       '''bilinear''': PIL.Image.Resampling.BILINEAR,
       '''bicubic''': PIL.Image.Resampling.BICUBIC,
       '''lanczos''': PIL.Image.Resampling.LANCZOS,
       '''nearest''': PIL.Image.Resampling.NEAREST,
   }
else:
   __lowerCamelCase      :			int							       =		{
       '''linear''': PIL.Image.LINEAR,
       '''bilinear''': PIL.Image.BILINEAR,
       '''bicubic''': PIL.Image.BICUBIC,
       '''lanczos''': PIL.Image.LANCZOS,
       '''nearest''': PIL.Image.NEAREST,
   }



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				(images / 2 + 0.5).clamp(0			,					1     )
  SCREAMING_SNAKE_CASE__      							=				images.cpu().permute(0			,					2			,					3			,					1     ).float().numpy()
  SCREAMING_SNAKE_CASE__      							=				numpy_to_pil(__UpperCamelCase     )
  return images






def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> int:







  """simple docstring"""





  if images.ndim == 3:
    SCREAMING_SNAKE_CASE__      							=				images[None, ...]
  SCREAMING_SNAKE_CASE__      							=				(images * 2_55).round().astype("""uint8"""     )
  if images.shape[-1] == 1:
    # special case for grayscale (single channel) images
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(image.squeeze()			,					mode="""L"""     ) for image in images]
  else:
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(__UpperCamelCase     ) for image in images]

  return pil_images
