

"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase										=		logging.get_logger(__name__)

__lowerCamelCase										=		{
    'facebook/data2vec-text-base': 'https://huggingface.co/data2vec/resolve/main/config.json',
}
class        _lowercase					(     __lowercase     ):
     _lowerCamelCase     =       '''data2vec-text'''







     def __init__(      self ,						UpperCamelCase_=3_0522 ,						UpperCamelCase_=768 ,						UpperCamelCase_=12 ,						UpperCamelCase_=12 ,						UpperCamelCase_=3072 ,						UpperCamelCase_="gelu" ,						UpperCamelCase_=0.1 ,						UpperCamelCase_=0.1 ,						UpperCamelCase_=512 ,						UpperCamelCase_=2 ,						UpperCamelCase_=0.0_2 ,						UpperCamelCase_=1E-1_2 ,						UpperCamelCase_=1 ,						UpperCamelCase_=0 ,						UpperCamelCase_=2 ,						UpperCamelCase_="absolute" ,						UpperCamelCase_=True ,						UpperCamelCase_=None ,						**UpperCamelCase_ ,						):
      super().__init__(pad_token_id=__a ,						bos_token_id=__a ,						eos_token_id=__a ,						**__a       )

      __magic_name__     =      vocab_size
      __magic_name__     =      hidden_size
      __magic_name__     =      num_hidden_layers
      __magic_name__     =      num_attention_heads
      __magic_name__     =      hidden_act
      __magic_name__     =      intermediate_size
      __magic_name__     =      hidden_dropout_prob
      __magic_name__     =      attention_probs_dropout_prob
      __magic_name__     =      max_position_embeddings
      __magic_name__     =      type_vocab_size
      __magic_name__     =      initializer_range
      __magic_name__     =      layer_norm_eps
      __magic_name__     =      position_embedding_type
      __magic_name__     =      use_cache
      __magic_name__     =      classifier_dropout


class        _lowercase					(     __lowercase     ):







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








"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase										=		logging.get_logger(__name__)

__lowerCamelCase										=		{
    "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
    "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/config.json"
    # See all FNet models at https://huggingface.co/models?filter=fnet
}
class        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       '''fnet'''







     def __init__(      self ,						UpperCamelCase_=3_2000 ,						UpperCamelCase_=768 ,						UpperCamelCase_=12 ,						UpperCamelCase_=3072 ,						UpperCamelCase_="gelu_new" ,						UpperCamelCase_=0.1 ,						UpperCamelCase_=512 ,						UpperCamelCase_=4 ,						UpperCamelCase_=0.0_2 ,						UpperCamelCase_=1E-1_2 ,						UpperCamelCase_=False ,						UpperCamelCase_=512 ,						UpperCamelCase_=3 ,						UpperCamelCase_=1 ,						UpperCamelCase_=2 ,						**UpperCamelCase_ ,						):
      super().__init__(pad_token_id=UpperCamelCase_ ,						bos_token_id=UpperCamelCase_ ,						eos_token_id=UpperCamelCase_ ,						**UpperCamelCase_       )

      __magic_name__     =      vocab_size
      __magic_name__     =      max_position_embeddings
      __magic_name__     =      hidden_size
      __magic_name__     =      num_hidden_layers
      __magic_name__     =      intermediate_size
      __magic_name__     =      hidden_act
      __magic_name__     =      hidden_dropout_prob
      __magic_name__     =      initializer_range
      __magic_name__     =      type_vocab_size
      __magic_name__     =      layer_norm_eps
      __magic_name__     =      use_tpu_fourier_optimizations
      __magic_name__     =      tpu_short_seq_length

