






"""simple docstring"""


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


lowercase_				     =     logging.get_logger(__name__)

lowercase_				     =     {
    '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 					snake_case		(							_lowerCAmelCase						):


   '''simple docstring'''

   A_						:	Dict						 = "fnet"


   def __init__(	self :     str,       _lowerCamelCase :     Any=3_20_00,       _lowerCamelCase :     int=7_68,       _lowerCamelCase :     List[str]=12,       _lowerCamelCase :     Union[str, Any]=30_72,       _lowerCamelCase :     Union[str, Any]="gelu_new",       _lowerCamelCase :     Optional[int]=0.1,       _lowerCamelCase :     int=5_12,       _lowerCamelCase :     Dict=4,       _lowerCamelCase :     List[Any]=0.02,       _lowerCamelCase :     Any=1e-12,       _lowerCamelCase :     Dict=False,       _lowerCamelCase :     Union[str, Any]=5_12,       _lowerCamelCase :     Optional[Any]=3,       _lowerCamelCase :     str=1,       _lowerCamelCase :     Dict=2,       **_lowerCamelCase :     Any,       ):

     '''simple docstring'''
     super().__init__(pad_token_id=_lowerCamelCase,       bos_token_id=_lowerCamelCase,       eos_token_id=_lowerCamelCase,       **_lowerCamelCase  )

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












"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowercase_				     =     logging.get_logger(__name__)


class 					snake_case		(							_lowerCAmelCase						):


   '''simple docstring'''

   def __init__(	self :     Optional[int],       *_lowerCamelCase :     Union[str, Any],       **_lowerCamelCase :     Dict  ):

     '''simple docstring'''
     warnings.warn(
         '''The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use SegformerImageProcessor instead.''',       _lowerCamelCase,       )
     super().__init__(*_lowerCamelCase,       **_lowerCamelCase  )




