
"""simple docstring"""





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:
				_a :    List[Any]														=		None

_a :    Union[str, Any]														=		logging.get_logger(__name__)
_a :    Any														=		{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

_a :    Tuple														=		{
    '''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''',
    },
}

_a :    Tuple														=		{
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

_a :    Optional[Any]														=		'''▁'''






class    _UpperCAmelCase(   SCREAMING_SNAKE_CASE__     ):
		lowercase__      =				VOCAB_FILES_NAMES
		lowercase__      =				PRETRAINED_VOCAB_FILES_MAP
		lowercase__      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase__      =				['input_ids', 'token_type_ids']
		lowercase__      =				FNetTokenizer



		def __init__( self    ,		__a=None    ,		__a=None    ,		__a=False    ,		__a=True    ,		__a=True    ,		__a="<unk>"    ,		__a="[SEP]"    ,		__a="<pad>"    ,		__a="[CLS]"    ,		__a="[MASK]"    ,		**__a    ,		)	->	Union[str, Any]:






							'''simple docstring'''
							# Mask token behave like a normal word, i.e. include the space before it and
							# is included in the raw text, there should be a match in a non-normalized sentence.
							_UpperCamelCase										=  (
							    AddedToken(_SCREAMING_SNAKE_CASE    ,		lstrip=_SCREAMING_SNAKE_CASE    ,		rstrip=_SCREAMING_SNAKE_CASE    ,		normalized=_SCREAMING_SNAKE_CASE)
							    if isinstance(_SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE)
							    else mask_token
							)

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

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



		def 						UpperCAmelCase							( self    ,		__a    ,		__a = None)	->	List[int]:






							'''simple docstring'''
							_UpperCamelCase										=  [self.sep_token_id]
							_UpperCamelCase										=  [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 						UpperCAmelCase							( self    ,		__a    ,		__a = None)	->	List[int]:






							'''simple docstring'''
							_UpperCamelCase										=  [self.sep_token_id]
							_UpperCamelCase										=  [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 						UpperCAmelCase							( self    ,		__a    ,		__a = None)	->	Tuple[str]:






							'''simple docstring'''
							if not os.path.isdir(_SCREAMING_SNAKE_CASE):
												logger.error(F'''Vocabulary path ({save_directory}) should be a directory''')
												return
							_UpperCamelCase										=  os.path.join(
							    _SCREAMING_SNAKE_CASE    ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

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

							return (out_vocab_file,)








"""simple docstring"""





from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
				from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline






