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


UpperCamelCase__    							= logging.get_logger(__name__)

UpperCamelCase__    							= {
    '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 					A							(    UpperCAmelCase_					):
   __UpperCAmelCase			:			Any              =      'fnet'


   def __init__(self					:						List[str]	,  __UpperCAmelCase					:						Union[str, Any]=3_2_0_0_0	,  __UpperCAmelCase					:						Optional[Any]=7_6_8	,  __UpperCAmelCase					:						Any=1_2	,  __UpperCAmelCase					:						Union[str, Any]=3_0_7_2	,  __UpperCAmelCase					:						str="gelu_new"	,  __UpperCAmelCase					:						Dict=0.1	,  __UpperCAmelCase					:						Tuple=5_1_2	,  __UpperCAmelCase					:						List[str]=4	,  __UpperCAmelCase					:						Optional[Any]=0.02	,  __UpperCAmelCase					:						Optional[int]=1E-12	,  __UpperCAmelCase					:						Any=False	,  __UpperCAmelCase					:						Optional[Any]=5_1_2	,  __UpperCAmelCase					:						int=3	,  __UpperCAmelCase					:						List[Any]=1	,  __UpperCAmelCase					:						Any=2	,  **__UpperCAmelCase					:						Any	,  )						->    str:
         """simple docstring"""



         super().__init__(pad_token_id=__UpperCAmelCase	,  bos_token_id=__UpperCAmelCase	,  eos_token_id=__UpperCAmelCase	,  **__UpperCAmelCase		)

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




from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__    							= {'tokenization_bertweet': ['BertweetTokenizer']}


if TYPE_CHECKING:
      from .tokenization_bertweet import BertweetTokenizer

else:
      import sys

      UpperCamelCase__    							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



