



'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__          =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__          =  {
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}


class 					snake_case			(UpperCamelCase ):
       lowerCAmelCase__	:int     =       "data2vec-text"



       def __init__(					self  ,UpperCAmelCase_=30_522  ,UpperCAmelCase_=768  ,UpperCAmelCase_=12  ,UpperCAmelCase_=12  ,UpperCAmelCase_=3_072  ,UpperCAmelCase_="gelu"  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=512  ,UpperCAmelCase_=2  ,UpperCAmelCase_=0.02  ,UpperCAmelCase_=1E-1_2  ,UpperCAmelCase_=1  ,UpperCAmelCase_=0  ,UpperCAmelCase_=2  ,UpperCAmelCase_="absolute"  ,UpperCAmelCase_=True  ,UpperCAmelCase_=None  ,**UpperCAmelCase_  ,)	->				List[Any]:
           super().__init__(pad_token_id=UpperCAmelCase_  ,bos_token_id=UpperCAmelCase_  ,eos_token_id=UpperCAmelCase_  ,**UpperCAmelCase_   )

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





class 					snake_case			(UpperCamelCase ):



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









'''simple docstring'''





from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin


class 					snake_case			(UpperCamelCase		,   UpperCamelCase ):



       @register_to_config
       def __init__(					self  ,UpperCAmelCase_ = 768  ,)	->				List[Any]:
           super().__init__()

           lowercase__									=    nn.Parameter(torch.zeros(1  ,UpperCAmelCase_   )   )
           lowercase__									=    nn.Parameter(torch.ones(1  ,UpperCAmelCase_   )   )



       def 				_a   (					self  ,UpperCAmelCase_ = None  ,UpperCAmelCase_ = None  ,)	->				Any:
           lowercase__									=    nn.Parameter(self.mean.to(UpperCAmelCase_   ).to(UpperCAmelCase_   )   )
           lowercase__									=    nn.Parameter(self.std.to(UpperCAmelCase_   ).to(UpperCAmelCase_   )   )
           return self



       def 				_a   (					self  ,UpperCAmelCase_   )	->				Tuple:
           lowercase__									=    (embeds - self.mean) * 1.0 / self.std
           return embeds







       def 				_a   (					self  ,UpperCAmelCase_   )	->				List[str]:
           lowercase__									=    (embeds * self.std) + self.mean
           return embeds




