
import warnings
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_  :	Union[str, Any] 				=					logging.get_logger(__name__)

lowerCamelCase_  :	Tuple 				=					{
    """nvidia/segformer-b0-finetuned-ade-512-512""": (
        """https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"""
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  Dict    =	"""segformer"""

			def __init__(    self	:    str  ,		snake_case_	:    Optional[int]=3  ,		snake_case_	:    Any=4  ,		snake_case_	:    Union[str, Any]=[2, 2, 2, 2]  ,		snake_case_	:    List[str]=[8, 4, 2, 1]  ,		snake_case_	:    Tuple=[32, 64, 160, 256]  ,		snake_case_	:    List[Any]=[7, 3, 3, 3]  ,		snake_case_	:    Dict=[4, 2, 2, 2]  ,		snake_case_	:    Union[str, Any]=[1, 2, 5, 8]  ,		snake_case_	:    Union[str, Any]=[4, 4, 4, 4]  ,		snake_case_	:    Any="gelu"  ,		snake_case_	:    Any=0.0  ,		snake_case_	:    Tuple=0.0  ,		snake_case_	:    List[Any]=0.1  ,		snake_case_	:    str=0.02  ,		snake_case_	:    int=0.1  ,		snake_case_	:    Optional[Any]=1e-6  ,		snake_case_	:    List[Any]=256  ,		snake_case_	:    Union[str, Any]=255  ,		**snake_case_	:    List[Any]  ,		):
							super().__init__(**snake_case_ )

							if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
											warnings.warn(
											    """Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"""
											    """ removed, as the behaviour will default to that of reshape_last_stage = True."""  ,		snake_case_  ,		)

							UpperCamelCase_:							List[Any]		=  num_channels
							UpperCamelCase_:							Union[str, Any]		=  num_encoder_blocks
							UpperCamelCase_:							Any		=  depths
							UpperCamelCase_:							Optional[Any]		=  sr_ratios
							UpperCamelCase_:							str		=  hidden_sizes
							UpperCamelCase_:							List[str]		=  patch_sizes
							UpperCamelCase_:							str		=  strides
							UpperCamelCase_:							Any		=  mlp_ratios
							UpperCamelCase_:							Any		=  num_attention_heads
							UpperCamelCase_:							Optional[int]		=  hidden_act
							UpperCamelCase_:							List[Any]		=  hidden_dropout_prob
							UpperCamelCase_:							List[Any]		=  attention_probs_dropout_prob
							UpperCamelCase_:							str		=  classifier_dropout_prob
							UpperCamelCase_:							int		=  initializer_range
							UpperCamelCase_:							Union[str, Any]		=  drop_path_rate
							UpperCamelCase_:							Tuple		=  layer_norm_eps
							UpperCamelCase_:							Dict		=  decoder_hidden_size
							UpperCamelCase_:							Optional[int]		=  kwargs.get("""reshape_last_stage"""  ,		snake_case_ )
							UpperCamelCase_:							Dict		=  semantic_loss_ignore_index




class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  int    =	version.parse("""1.11"""					)

			@property
			def  lowerCAmelCase__		(    self	:    int ):
							return OrderedDict(
							    [
							        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
							    ] )

			@property
			def  lowerCAmelCase__		(    self	:    str ):
							return 1e-4




			@property
			def  lowerCAmelCase__		(    self	:    str ):
							return 12








def     A__   (  lowerCamelCase  )					->		list:
				return [
				    txt[:a] + txt[a].upper() + txt[a + 1 :]
				    for a in range(len(lowerCamelCase  )  )
				    if txt[a].isalpha()
				]


if __name__ == "__main__":
							__import__("""doctest""").testmod()






