


"""simple docstring"""





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
 from ...onnx.config import PatchingSpec
 from ...tokenization_utils_base import PreTrainedTokenizerBase


snake_case__						:   Optional[int]			 = logging.get_logger(__name__)

snake_case__						:   List[Any]			 = {
    '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096''': '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096-finetuned-triviaqa''': (
        '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'''
    ),
    '''allenai/longformer-base-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
    '''allenai/longformer-large-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
}



class 						snake_case_(				a__	):
     __UpperCamelCase     =    '''longformer'''






     def __init__(		self     :    Optional[int]    , UpperCamelCase_     :    Union[List[int], int] = 5_1_2    , UpperCamelCase_     :    int = 2    , UpperCamelCase_     :    int = 1    , UpperCamelCase_     :    int = 0    , UpperCamelCase_     :    int = 2    , UpperCamelCase_     :    int = 3_0_5_2_2    , UpperCamelCase_     :    int = 7_6_8    , UpperCamelCase_     :    int = 1_2    , UpperCamelCase_     :    int = 1_2    , UpperCamelCase_     :    int = 3_0_7_2    , UpperCamelCase_     :    str = "gelu"    , UpperCamelCase_     :    float = 0.1    , UpperCamelCase_     :    float = 0.1    , UpperCamelCase_     :    int = 5_1_2    , UpperCamelCase_     :    int = 2    , UpperCamelCase_     :    float = 0.02    , UpperCamelCase_     :    float = 1E-12    , UpperCamelCase_     :    bool = False    , **UpperCamelCase_     :    List[Any]    , ):
           super().__init__(pad_token_id=UpperCamelCase_    , **UpperCamelCase_ )

           lowerCAmelCase    :		Union[str, Any]				=      attention_window
           lowerCAmelCase    :		List[str]				=      sep_token_id
           lowerCAmelCase    :		Tuple				=      bos_token_id
           lowerCAmelCase    :		str				=      eos_token_id
           lowerCAmelCase    :		Any				=      vocab_size
           lowerCAmelCase    :		Union[str, Any]				=      hidden_size
           lowerCAmelCase    :		str				=      num_hidden_layers
           lowerCAmelCase    :		Any				=      num_attention_heads
           lowerCAmelCase    :		List[str]				=      hidden_act
           lowerCAmelCase    :		Dict				=      intermediate_size
           lowerCAmelCase    :		Optional[int]				=      hidden_dropout_prob
           lowerCAmelCase    :		Any				=      attention_probs_dropout_prob
           lowerCAmelCase    :		Union[str, Any]				=      max_position_embeddings
           lowerCAmelCase    :		List[str]				=      type_vocab_size
           lowerCAmelCase    :		int				=      initializer_range
           lowerCAmelCase    :		List[Any]				=      layer_norm_eps
           lowerCAmelCase    :		Tuple				=      onnx_export



class 						snake_case_(				a__	):






     def __init__(		self     :    Union[str, Any]    , UpperCamelCase_     :    "PretrainedConfig"    , UpperCamelCase_     :    str = "default"    , UpperCamelCase_     :    "List[PatchingSpec]" = None ):
           super().__init__(UpperCamelCase_    , UpperCamelCase_    , UpperCamelCase_ )
           lowerCAmelCase    :		int				=      True






     @property
     def    lowerCamelCase__   (		self     :    Optional[Any] ):
           if self.task == "multiple-choice":
                 lowerCAmelCase    :		Tuple				=      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
                 lowerCAmelCase    :		List[str]				=      {0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
                   ('''global_attention_mask''', dynamic_axis),
               ] )






     @property
     def    lowerCamelCase__   (		self     :    str ):
           lowerCAmelCase    :		Optional[int]				=      super().outputs
           if self.task == "default":
                 lowerCAmelCase    :		List[str]				=      {0: '''batch'''}
           return outputs






     @property
     def    lowerCamelCase__   (		self     :    List[Any] ):
           return 1E-4






     @property
     def    lowerCamelCase__   (		self     :    Any ):
           # needs to be >= 14 to support tril operator
           return max(super().default_onnx_opset    , 1_4 )






     def    lowerCamelCase__   (		self     :    int    , UpperCamelCase_     :    "PreTrainedTokenizerBase"    , UpperCamelCase_     :    int = -1    , UpperCamelCase_     :    int = -1    , UpperCamelCase_     :    bool = False    , UpperCamelCase_     :    Optional[TensorType] = None    , ):
           lowerCAmelCase    :		Optional[int]				=      super().generate_dummy_inputs(
               preprocessor=UpperCamelCase_    , batch_size=UpperCamelCase_    , seq_length=UpperCamelCase_    , is_pair=UpperCamelCase_    , framework=UpperCamelCase_ )
           import torch

           # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
           # makes the export fail randomly
           lowerCAmelCase    :		Optional[int]				=      torch.zeros_like(inputs['''input_ids'''] )
           # make every second token global
           lowerCAmelCase    :		Union[str, Any]				=      1

           return inputs






"""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:
 snake_case__						:   str			 = None

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

snake_case__						:   Dict			 = {
    '''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''',
    },
}

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

snake_case__						:   Dict			 = '''▁'''



class 						snake_case_(				a__	):
     __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     :    Union[str, Any]    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Any=False    , UpperCamelCase_     :    Any=True    , UpperCamelCase_     :    Dict=True    , UpperCamelCase_     :    Tuple="<unk>"    , UpperCamelCase_     :    List[str]="[SEP]"    , UpperCamelCase_     :    List[Any]="<pad>"    , UpperCamelCase_     :    Union[str, Any]="[CLS]"    , UpperCamelCase_     :    int="[MASK]"    , **UpperCamelCase_     :    Optional[Any]    , ):
           # 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.
           lowerCAmelCase    :		int				=      (
               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_    , )

           lowerCAmelCase    :		Optional[int]				=      do_lower_case
           lowerCAmelCase    :		str				=      remove_space
           lowerCAmelCase    :		Any				=      keep_accents
           lowerCAmelCase    :		int				=      vocab_file
           lowerCAmelCase    :		List[str]				=      False if not self.vocab_file else True






     def    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		Optional[int]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[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     :    List[str]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		List[str]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[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    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    str    , UpperCamelCase_     :    Optional[str] = None ):
           if not os.path.isdir(UpperCamelCase_ ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
                 return
           lowerCAmelCase    :		str				=      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,)


