'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


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

_A			:      int					      =				{
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}







class 				_lowercase     (				UpperCAmelCase__			):


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE     :       Union[str, Any]      	=					"""data2vec-text"""
 def __init__(      self   :	Any      ,       SCREAMING_SNAKE_CASE__   :	int=3_05_22      ,       SCREAMING_SNAKE_CASE__   :	Union[str, Any]=7_68      ,       SCREAMING_SNAKE_CASE__   :	List[Any]=12      ,       SCREAMING_SNAKE_CASE__   :	Dict=12      ,       SCREAMING_SNAKE_CASE__   :	Tuple=30_72      ,       SCREAMING_SNAKE_CASE__   :	Tuple="gelu"      ,       SCREAMING_SNAKE_CASE__   :	str=0.1      ,       SCREAMING_SNAKE_CASE__   :	Union[str, Any]=0.1      ,       SCREAMING_SNAKE_CASE__   :	Dict=5_12      ,       SCREAMING_SNAKE_CASE__   :	Tuple=2      ,       SCREAMING_SNAKE_CASE__   :	List[Any]=0.0_2      ,       SCREAMING_SNAKE_CASE__   :	Tuple=1e-1_2      ,       SCREAMING_SNAKE_CASE__   :	Dict=1      ,       SCREAMING_SNAKE_CASE__   :	Optional[int]=0      ,       SCREAMING_SNAKE_CASE__   :	Any=2      ,       SCREAMING_SNAKE_CASE__   :	Optional[Any]="absolute"      ,       SCREAMING_SNAKE_CASE__   :	Dict=True      ,       SCREAMING_SNAKE_CASE__   :	Dict=None      ,       **SCREAMING_SNAKE_CASE__   :	Optional[Any]      ,       )  ->    int:
  super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__      ,       bos_token_id=SCREAMING_SNAKE_CASE__      ,       eos_token_id=SCREAMING_SNAKE_CASE__      ,       **SCREAMING_SNAKE_CASE__							)

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







class 				_lowercase     (				UpperCAmelCase__			):


 '''simple docstring'''






 @property
 def a					(      self   :	List[Any]							)  ->    Mapping[str, Mapping[int, str]]:
  if self.task == "multiple-choice":
   __lowerCAmelCase											=						{0: """batch""", 1: """choice""", 2: """sequence"""}
  else:
   __lowerCAmelCase											=						{0: """batch""", 1: """sequence"""}
  return OrderedDict(
      [
          ("""input_ids""", dynamic_axis),
          ("""attention_mask""", dynamic_axis),
      ]							)







'''simple docstring'''

import warnings

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


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







class 				_lowercase     (				UpperCAmelCase__			):


 '''simple docstring'''






 def __init__(      self   :	Dict      ,       *SCREAMING_SNAKE_CASE__   :	Optional[int]      ,       **SCREAMING_SNAKE_CASE__   :	List[str]							)  ->    None:
  warnings.warn(
      """The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
      """ Please use SegformerImageProcessor instead."""      ,       SCREAMING_SNAKE_CASE__      ,       )
  super().__init__(*SCREAMING_SNAKE_CASE__      ,       **SCREAMING_SNAKE_CASE__							)






