
"""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:
					lowerCamelCase__ :       Optional[Any]						     =			None

lowerCamelCase__ :       Optional[int]						     =			logging.get_logger(__name__)
lowerCamelCase__ :       Union[str, Any]						     =			{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase__ :       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__ :       Tuple						     =			{
    "google/fnet-base": 512,
    "google/fnet-large": 512,
}

lowerCamelCase__ :       List[Any]						     =			"▁"




class 				lowercase__(				_UpperCAmelCase   ):
	'''simple docstring'''

	UpperCamelCase				=  VOCAB_FILES_NAMES
	UpperCamelCase				=  PRETRAINED_VOCAB_FILES_MAP
	UpperCamelCase				=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	UpperCamelCase				=  ["""input_ids""", """token_type_ids"""]
	UpperCamelCase				=  FNetTokenizer





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







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= (
			    AddedToken(lowerCamelCase_		, lstrip=lowerCamelCase_		, rstrip=lowerCamelCase_		, normalized=lowerCamelCase_					)
			    if isinstance(lowerCamelCase_		, lowerCamelCase_					)
			    else mask_token
			)

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

			SCREAMING_SNAKE_CASE       :     List[Any]				= do_lower_case
			SCREAMING_SNAKE_CASE       :     int				= remove_space
			SCREAMING_SNAKE_CASE       :     Dict				= keep_accents
			SCREAMING_SNAKE_CASE       :     int				= vocab_file
			SCREAMING_SNAKE_CASE       :     List[Any]				= False if not self.vocab_file else True





	def   __lowerCAmelCase (						self    :str		, lowerCamelCase_    :List[int]		, lowerCamelCase_    :Optional[List[int]] = None					)							->			List[int]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Optional[Any]				= [self.sep_token_id]
			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= [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   __lowerCAmelCase (						self    :Any		, lowerCamelCase_    :List[int]		, lowerCamelCase_    :Optional[List[int]] = None					)							->			List[int]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Tuple				= [self.sep_token_id]
			SCREAMING_SNAKE_CASE       :     int				= [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   __lowerCAmelCase (						self    :Any		, lowerCamelCase_    :str		, lowerCamelCase_    :Optional[str] = None					)							->			Tuple[str]:







			'''simple docstring'''




			if not os.path.isdir(lowerCamelCase_					):
					logger.error(f"Vocabulary path ({save_directory}) should be a directory"					)
					return
			SCREAMING_SNAKE_CASE       :     Dict				= 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,)







"""simple docstring"""






import os
import sys

lowerCamelCase__ :       List[Any]						     =			os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowerCamelCase__ :       str						     =			[
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]





@add_start_docstrings(AutoConfig.__doc__     )
def __A						(   *a_ :							Any		,		**a_ :							Union[str, Any]     )->							Dict:




		'''simple docstring'''






		return AutoConfig.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoTokenizer.__doc__     )
def __A						(   *a_ :							str		,		**a_ :							Union[str, Any]     )->							Union[str, Any]:




		'''simple docstring'''






		return AutoTokenizer.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoModel.__doc__     )
def __A						(   *a_ :							List[str]		,		**a_ :							int     )->							Dict:




		'''simple docstring'''






		return AutoModel.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoModelForCausalLM.__doc__     )
def __A						(   *a_ :							Any		,		**a_ :							Tuple     )->							Dict:




		'''simple docstring'''






		return AutoModelForCausalLM.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoModelForMaskedLM.__doc__     )
def __A						(   *a_ :							Dict		,		**a_ :							Optional[Any]     )->							Optional[int]:




		'''simple docstring'''






		return AutoModelForMaskedLM.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoModelForSequenceClassification.__doc__     )
def __A						(   *a_ :							Optional[int]		,		**a_ :							str     )->							Optional[int]:




		'''simple docstring'''






		return AutoModelForSequenceClassification.from_pretrained(*a_		,		**a_     )





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__     )
def __A						(   *a_ :							List[str]		,		**a_ :							int     )->							List[Any]:




		'''simple docstring'''






		return AutoModelForQuestionAnswering.from_pretrained(*a_		,		**a_     )





