
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase__						       =      logging.get_logger(__name__)

lowercase__						       =      {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}






class 	snake_case__       (      __SCREAMING_SNAKE_CASE    ,					__SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		lowerCamelCase     							=						"""bit"""
		lowerCamelCase     							=						["""preactivation""", """bottleneck"""]
		lowerCamelCase     							=						["""SAME""", """VALID"""]



		def __init__(      self				:			int  ,	UpperCamelCase__				:			Dict=3  ,	UpperCamelCase__				:			Optional[int]=64  ,	UpperCamelCase__				:			int=[256, 512, 1024, 2048]  ,	UpperCamelCase__				:			int=[3, 4, 6, 3]  ,	UpperCamelCase__				:			List[Any]="preactivation"  ,	UpperCamelCase__				:			Union[str, Any]="relu"  ,	UpperCamelCase__				:			Dict=None  ,	UpperCamelCase__				:			int=32  ,	UpperCamelCase__				:			Union[str, Any]=0.0  ,	UpperCamelCase__				:			Union[str, Any]=False  ,	UpperCamelCase__				:			Union[str, Any]=32  ,	UpperCamelCase__				:			Optional[int]=1  ,	UpperCamelCase__				:			Optional[int]=None  ,	UpperCamelCase__				:			int=None  ,	**UpperCamelCase__				:			Tuple  ,	)						->			Union[str, Any]:






				"""simple docstring"""







				super().__init__(**UpperCamelCase__      )
				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:
								snake_case  :       List[Any]     			=						global_padding.upper()
						else:
								raise ValueError(f'Padding strategy {global_padding} not supported'      )
				snake_case  :       Union[str, Any]     			=						num_channels
				snake_case  :       Optional[Any]     			=						embedding_size
				snake_case  :       Tuple     			=						hidden_sizes
				snake_case  :       Union[str, Any]     			=						depths
				snake_case  :       str     			=						layer_type
				snake_case  :       str     			=						hidden_act
				snake_case  :       Union[str, Any]     			=						global_padding
				snake_case  :       Optional[int]     			=						num_groups
				snake_case  :       Any     			=						drop_path_rate
				snake_case  :       Union[str, Any]     			=						embedding_dynamic_padding
				snake_case  :       Union[str, Any]     			=						output_stride
				snake_case  :       str     			=						width_factor

				snake_case  :       List[str]     			=						['''stem'''] + [f'stage{idx}' for idx in range(1  ,	len(UpperCamelCase__      ) + 1      )]
				snake_case			,snake_case  :       Union[str, Any]     			=						get_aligned_output_features_output_indices(
				    out_features=UpperCamelCase__  ,	out_indices=UpperCamelCase__  ,	stage_names=self.stage_names      )




'''simple docstring'''
import warnings

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


lowercase__						       =      logging.get_logger(__name__)






class 	snake_case__       (      __SCREAMING_SNAKE_CASE					):







		"""simple docstring"""

		def __init__(      self				:			Optional[Any]  ,	*UpperCamelCase__				:			Optional[Any]  ,	**UpperCamelCase__				:			str      )						->			None:






				"""simple docstring"""







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


