





'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__lowerCAmelCase				:      Any						      =logging.get_logger(__name__)

__lowerCAmelCase				:      List[Any]						      ={
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}






class   UpperCAmelCase      (			UpperCamelCase__     ,			UpperCamelCase__							):
 __lowercase  						=							"""bit"""
 __lowercase  						=							["""preactivation""", """bottleneck"""]
 __lowercase  						=							["""SAME""", """VALID"""]
 def __init__(							self :List[str]		,			lowercase_ :Optional[Any]=3		,			lowercase_ :str=64		,			lowercase_ :List[str]=[2_56, 5_12, 10_24, 20_48]		,			lowercase_ :Union[str, Any]=[3, 4, 6, 3]		,			lowercase_ :Union[str, Any]="preactivation"		,			lowercase_ :int="relu"		,			lowercase_ :Tuple=None		,			lowercase_ :List[str]=32		,			lowercase_ :List[Any]=0.0		,			lowercase_ :Tuple=False		,			lowercase_ :Tuple=32		,			lowercase_ :List[Any]=1		,			lowercase_ :List[Any]=None		,			lowercase_ :Optional[Any]=None		,			**lowercase_ :Optional[int]		,			)->				Dict:
     super().__init__(**lowercase_				)
     if layer_type not in self.layer_types:
         raise ValueError(F"layer_type={layer_type} is not one of {','.join(self.layer_types				)}"				)
     if global_padding is not None:
         if global_padding.upper() in self.supported_padding:
             A__							=     global_padding.upper()
         else:
             raise ValueError(F"Padding strategy {global_padding} not supported"				)
     A__							=     num_channels
     A__							=     embedding_size
     A__							=     hidden_sizes
     A__							=     depths
     A__							=     layer_type
     A__							=     hidden_act
     A__							=     global_padding
     A__							=     num_groups
     A__							=     drop_path_rate
     A__							=     embedding_dynamic_padding
     A__							=     output_stride
     A__							=     width_factor

     A__							=     ["stem"] + [F"stage{idx}" for idx in range(1		,			len(lowercase_				) + 1				)]
     A__,      A__							=     get_aligned_output_features_output_indices(
         out_features=lowercase_		,			out_indices=lowercase_		,			stage_names=self.stage_names				)










'''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   UpperCAmelCase      (			UpperCamelCase__     ,			UpperCamelCase__							):
 @register_to_config
 def __init__(							self :List[str]		,			lowercase_ :int = 7_68		,			)->				str:
     super().__init__()

     A__							=     nn.Parameter(torch.zeros(1		,			lowercase_				)				)
     A__							=     nn.Parameter(torch.ones(1		,			lowercase_				)				)
 def 	UpperCAmelCase_				(							self :List[Any]		,			lowercase_ :Optional[Union[str, torch.device]] = None		,			lowercase_ :Optional[torch.dtype] = None		,			)->				Tuple:
     A__							=     nn.Parameter(self.mean.to(lowercase_				).to(lowercase_				)				)
     A__							=     nn.Parameter(self.std.to(lowercase_				).to(lowercase_				)				)
     return self
 def 	UpperCAmelCase_				(							self :Optional[int]		,			lowercase_ :str				)->				Union[str, Any]:
     A__							=     (embeds - self.mean) * 1.0 / self.std
     return embeds



 def 	UpperCAmelCase_				(							self :Any		,			lowercase_ :List[Any]				)->				Tuple:
     A__							=     (embeds * self.std) + self.mean
     return embeds



