


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


__lowerCAmelCase	: Any  				={
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}
class        _lowercase      (			lowercase__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		"""albert"""


				def __init__(       self			:Optional[int]			,			lowerCAmelCase__			:Optional[Any]=30_000			,			lowerCAmelCase__			:List[Any]=128			,			lowerCAmelCase__			:List[str]=4_096			,			lowerCAmelCase__			:Tuple=12			,			lowerCAmelCase__			:str=1			,			lowerCAmelCase__			:List[Any]=64			,			lowerCAmelCase__			:Any=16_384			,			lowerCAmelCase__			:Any=1			,			lowerCAmelCase__			:List[Any]="gelu_new"			,			lowerCAmelCase__			:Union[str, Any]=0			,			lowerCAmelCase__			:Union[str, Any]=0			,			lowerCAmelCase__			:Tuple=512			,			lowerCAmelCase__			:Dict=2			,			lowerCAmelCase__			:Dict=0.02			,			lowerCAmelCase__			:Optional[int]=1E-1_2			,			lowerCAmelCase__			:Union[str, Any]=0.1			,			lowerCAmelCase__			:List[Any]="absolute"			,			lowerCAmelCase__			:int=0			,			lowerCAmelCase__			:Optional[int]=2			,			lowerCAmelCase__			:List[str]=3			,			**lowerCAmelCase__			:List[Any]			,			)		->			List[Any]:
										super().__init__(pad_token_id=lowercase_			,			bos_token_id=lowercase_			,			eos_token_id=lowercase_			,			**lowercase_	)

										__SCREAMING_SNAKE_CASE						:     int					=		vocab_size
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		embedding_size
										__SCREAMING_SNAKE_CASE						:     List[str]					=		hidden_size
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		num_hidden_layers
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		num_hidden_groups
										__SCREAMING_SNAKE_CASE						:     Dict					=		num_attention_heads
										__SCREAMING_SNAKE_CASE						:     Any					=		inner_group_num
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		hidden_act
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		intermediate_size
										__SCREAMING_SNAKE_CASE						:     List[str]					=		hidden_dropout_prob
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		attention_probs_dropout_prob
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		max_position_embeddings
										__SCREAMING_SNAKE_CASE						:     Any					=		type_vocab_size
										__SCREAMING_SNAKE_CASE						:     List[str]					=		initializer_range
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		layer_norm_eps
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		classifier_dropout_prob
										__SCREAMING_SNAKE_CASE						:     Tuple					=		position_embedding_type




class        _lowercase      (			lowercase__       ):






				'''simple docstring'''



				@property
				def 		__magic_name__(       self			:Optional[Any]	)		->			Any:
										if self.task == "multiple-choice":
																__SCREAMING_SNAKE_CASE						:     int					=		{0: "batch", 1: "choice", 2: "sequence"}
										else:
																__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		{0: "batch", 1: "sequence"}
										return OrderedDict(
										    [
										        ('''input_ids''', dynamic_axis),
										        ('''attention_mask''', dynamic_axis),
										        ('''token_type_ids''', dynamic_axis),
										    ]	)


"""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		       =							None

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

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

_a		       =							'▁'


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						List[str]       =		VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__			:						Tuple       =		PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__			:						Any       =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__			:						Union[str, Any]       =		["""input_ids""", """token_type_ids"""]
  SCREAMING_SNAKE_CASE__			:						Tuple       =		FNetTokenizer







  def __init__(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=False				,   lowercase_=True				,   lowercase_=True				,   lowercase_="<unk>"				,   lowercase_="[SEP]"				,   lowercase_="<pad>"				,   lowercase_="[CLS]"				,   lowercase_="[MASK]"				,   **lowercase_				,   ):

     """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_					:					int			     =    (
         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_				,   )

     UpperCAmelCase_					:					Any			     =    do_lower_case
     UpperCAmelCase_					:					Tuple			     =    remove_space
     UpperCAmelCase_					:					str			     =    keep_accents
     UpperCAmelCase_					:					Any			     =    vocab_file
     UpperCAmelCase_					:					List[Any]			     =    False if not self.vocab_file else True







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Tuple			     =    [self.sep_token_id]
     UpperCAmelCase_					:					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        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Any			     =    [self.sep_token_id]
     UpperCAmelCase_					:					Any			     =    [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				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     if not os.path.isdir(lowercase_  ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""  )
        return
     UpperCAmelCase_					:					List[str]			     =    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,)


