



"""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 	__snake_case	(     _lowercase):
  snake_case__    :       int        =						"data2vec-text"




  def __init__(			self					:						Optional[Any]						, __lowerCAmelCase					:						Optional[int]=3_0_5_2_2						, __lowerCAmelCase					:						str=7_6_8						, __lowerCAmelCase					:						int=1_2						, __lowerCAmelCase					:						Dict=1_2						, __lowerCAmelCase					:						Union[str, Any]=3_0_7_2						, __lowerCAmelCase					:						Optional[Any]="gelu"						, __lowerCAmelCase					:						Union[str, Any]=0.1						, __lowerCAmelCase					:						List[Any]=0.1						, __lowerCAmelCase					:						Optional[int]=5_1_2						, __lowerCAmelCase					:						Any=2						, __lowerCAmelCase					:						Any=0.02						, __lowerCAmelCase					:						Any=1E-12						, __lowerCAmelCase					:						int=1						, __lowerCAmelCase					:						str=0						, __lowerCAmelCase					:						Tuple=2						, __lowerCAmelCase					:						Optional[Any]="absolute"						, __lowerCAmelCase					:						Any=True						, __lowerCAmelCase					:						Optional[int]=None						, **__lowerCAmelCase					:						str						, ):






         """simple docstring"""






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

         _lowerCamelCase						:    Optional[int]         =			vocab_size
         _lowerCamelCase						:    Tuple         =			hidden_size
         _lowerCamelCase						:    Tuple         =			num_hidden_layers
         _lowerCamelCase						:    Any         =			num_attention_heads
         _lowerCamelCase						:    Union[str, Any]         =			hidden_act
         _lowerCamelCase						:    Any         =			intermediate_size
         _lowerCamelCase						:    Dict         =			hidden_dropout_prob
         _lowerCamelCase						:    Any         =			attention_probs_dropout_prob
         _lowerCamelCase						:    str         =			max_position_embeddings
         _lowerCamelCase						:    Tuple         =			type_vocab_size
         _lowerCamelCase						:    Optional[int]         =			initializer_range
         _lowerCamelCase						:    List[str]         =			layer_norm_eps
         _lowerCamelCase						:    Optional[int]         =			position_embedding_type
         _lowerCamelCase						:    Union[str, Any]         =			use_cache
         _lowerCamelCase						:    str         =			classifier_dropout






class 	__snake_case	(     _lowercase):




  @property
  def 						SCREAMING_SNAKE_CASE    (			self					:						int		):






         """simple docstring"""






         if self.task == "multiple-choice":
                _lowerCamelCase						:    Union[str, Any]         =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
                _lowerCamelCase						:    Tuple         =			{0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ]		)







"""simple docstring"""






from torch import nn






class 	__snake_case	(     nn.Module):




  def __init__(			self					:						Optional[Any]						, __lowerCAmelCase					:						Dict						, __lowerCAmelCase					:						str		):






         """simple docstring"""






         super().__init__()
         _lowerCamelCase						:    List[str]         =			class_size
         _lowerCamelCase						:    List[str]         =			embed_size
         # self.mlp1 = nn.Linear(embed_size, embed_size)
         # self.mlp2 = (nn.Linear(embed_size, class_size))
         _lowerCamelCase						:    Optional[int]         =			nn.Linear(__lowerCAmelCase						, __lowerCAmelCase		)




  def 						SCREAMING_SNAKE_CASE    (			self					:						List[Any]						, __lowerCAmelCase					:						Tuple		):






         """simple docstring"""






         _lowerCamelCase						:    Optional[Any]         =			self.mlp(__lowerCAmelCase		)
         return logits


