




from collections import OrderedDict
from typing import Mapping

from packaging import version

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


lowerCamelCase				:		Any     =   logging.get_logger(__name__)

lowerCamelCase				:		Tuple     =   {
    "facebook/levit-128S": "https://huggingface.co/facebook/levit-128S/resolve/main/config.json",
    # See all LeViT models at https://huggingface.co/models?filter=levit
}







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						'''levit'''

 def __init__(				self					:  Optional[Any]						,							A_					:  Union[str, Any]=224						,							A_					:  Optional[Any]=3						,							A_					:  int=3						,							A_					:  int=2						,							A_					:  Any=1						,							A_					:  Any=16						,							A_					:  Dict=[128, 256, 384]						,							A_					:  List[str]=[4, 8, 12]						,							A_					:  Union[str, Any]=[4, 4, 4]						,							A_					:  Any=[16, 16, 16]						,							A_					:  str=0						,							A_					:  int=[2, 2, 2]						,							A_					:  List[Any]=[2, 2, 2]						,							A_					:  Any=0.02						,							**A_					:  Optional[int]						,							)   ->	Dict:

       """simple docstring"""






       super().__init__(**A_  )
       lowerCamelCase_		     =    image_size
       lowerCamelCase_		     =    num_channels
       lowerCamelCase_		     =    kernel_size
       lowerCamelCase_		     =    stride
       lowerCamelCase_		     =    padding
       lowerCamelCase_		     =    hidden_sizes
       lowerCamelCase_		     =    num_attention_heads
       lowerCamelCase_		     =    depths
       lowerCamelCase_		     =    key_dim
       lowerCamelCase_		     =    drop_path_rate
       lowerCamelCase_		     =    patch_size
       lowerCamelCase_		     =    attention_ratio
       lowerCamelCase_		     =    mlp_ratio
       lowerCamelCase_		     =    initializer_range
       lowerCamelCase_		     =    [
           ['Subsample', key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
           ['Subsample', key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
       ]







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						version.parse('''1.11'''   )

 @property
 def 				a__ (				self					:  int  )   ->	Mapping[str, Mapping[int, str]]:

       """simple docstring"""






       return OrderedDict(
           [
               ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
           ]  )





 @property
 def 				a__ (				self					:  Tuple  )   ->	float:

       """simple docstring"""






       return 1E-4









import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


lowerCamelCase				:		Union[str, Any]     =   logging.get_logger(__name__)







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 def __init__(				self					:  int						,							*A_					:  str						,							**A_					:  Optional[int]  )   ->	None:

       """simple docstring"""






       warnings.warn(
           'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
           ' use GLPNImageProcessor instead.'						,							A_						,							)
       super().__init__(*A_						,							**A_  )



