
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		: str								=     None

A		: Dict								=     logging.get_logger(__name__)
A		: Any								=     {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

A		: Union[str, 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''',
    },
}

A		: Union[str, Any]								=     {
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

A		: Union[str, Any]								=     '''▁'''



class    a_ (			_a    ):
			a	:			List[str]					   =							VOCAB_FILES_NAMES
			a	:			Tuple					   =							PRETRAINED_VOCAB_FILES_MAP
			a	:			Optional[int]					   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			a	:			Optional[int]					   =							['''input_ids''', '''token_type_ids''']
			a	:			Union[str, Any]					   =							FNetTokenizer






			def __init__(      self				,			__UpperCamelCase=None				,			__UpperCamelCase=None				,			__UpperCamelCase=False				,			__UpperCamelCase=True				,			__UpperCamelCase=True				,			__UpperCamelCase="<unk>"				,			__UpperCamelCase="[SEP]"				,			__UpperCamelCase="<pad>"				,			__UpperCamelCase="[CLS]"				,			__UpperCamelCase="[MASK]"				,			**__UpperCamelCase				,			):
									# 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.
									_lowercase					       =					(
									    AddedToken(__UpperCamelCase				,			lstrip=__UpperCamelCase				,			rstrip=__UpperCamelCase				,			normalized=__UpperCamelCase  )
									    if isinstance(__UpperCamelCase				,			__UpperCamelCase  )
									    else mask_token
									)

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

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






			def    UpperCamelCase_				(      self				,			__UpperCamelCase				,			__UpperCamelCase = None  ):
									_lowercase					       =					[self.sep_token_id]
									_lowercase					       =					[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				,			__UpperCamelCase				,			__UpperCamelCase = None  ):
									_lowercase					       =					[self.sep_token_id]
									_lowercase					       =					[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				,			__UpperCamelCase				,			__UpperCamelCase = None  ):
									if not os.path.isdir(__UpperCamelCase  ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
															return
									_lowercase					       =					os.path.join(
									    __UpperCamelCase				,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

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

									return (out_vocab_file,)

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A		: Dict								=     {
    '''configuration_x_clip''': [
        '''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XCLIPConfig''',
        '''XCLIPTextConfig''',
        '''XCLIPVisionConfig''',
    ],
    '''processing_x_clip''': ['''XCLIPProcessor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A		: Optional[Any]								=     [
		    '''XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''XCLIPModel''',
		    '''XCLIPPreTrainedModel''',
		    '''XCLIPTextModel''',
		    '''XCLIPVisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_x_clip import (
		    XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    XCLIPConfig,
		    XCLIPTextConfig,
		    XCLIPVisionConfig,
		)
		from .processing_x_clip import XCLIPProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_x_clip import (
				    XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    XCLIPModel,
				    XCLIPPreTrainedModel,
				    XCLIPTextModel,
				    XCLIPVisionModel,
				)

else:
		import sys

		A		: List[str]								=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)