




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


__UpperCamelCase   :			int          = logging.get_logger(__name__)

__UpperCamelCase   :			Optional[int]          = {
    "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 						__lowerCAmelCase      (      SCREAMING_SNAKE_CASE__					):
							UpperCamelCase__   	=    '''segformer'''
							def __init__(		self		:int						, __magic_name__		:Optional[int]=3						, __magic_name__		:Optional[Any]=4						, __magic_name__		:Optional[int]=[2, 2, 2, 2]						, __magic_name__		:Union[str, Any]=[8, 4, 2, 1]						, __magic_name__		:Optional[int]=[32, 64, 160, 256]						, __magic_name__		:int=[7, 3, 3, 3]						, __magic_name__		:int=[4, 2, 2, 2]						, __magic_name__		:Tuple=[1, 2, 5, 8]						, __magic_name__		:Any=[4, 4, 4, 4]						, __magic_name__		:Any="gelu"						, __magic_name__		:Optional[Any]=0.0						, __magic_name__		:Optional[int]=0.0						, __magic_name__		:str=0.1						, __magic_name__		:int=0.02						, __magic_name__		:int=0.1						, __magic_name__		:int=1E-6						, __magic_name__		:Tuple=256						, __magic_name__		:int=255						, **__magic_name__		:Union[str, Any]						, ):







								'''simple docstring'''







								super().__init__(**_lowercase							)

								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."""						, _lowercase						, )

								a									=				num_channels
								a									=				num_encoder_blocks
								a									=				depths
								a									=				sr_ratios
								a									=				hidden_sizes
								a									=				patch_sizes
								a									=				strides
								a									=				mlp_ratios
								a									=				num_attention_heads
								a									=				hidden_act
								a									=				hidden_dropout_prob
								a									=				attention_probs_dropout_prob
								a									=				classifier_dropout_prob
								a									=				initializer_range
								a									=				drop_path_rate
								a									=				layer_norm_eps
								a									=				decoder_hidden_size
								a									=				kwargs.get("""reshape_last_stage"""						, _lowercase							)
								a									=				semantic_loss_ignore_index







class 						__lowerCAmelCase      (      SCREAMING_SNAKE_CASE__					):
							UpperCamelCase__   	=    version.parse('''1.11'''					)
							@property
							def  lowerCamelCase__				(		self		:Tuple							):







								'''simple docstring'''







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







								'''simple docstring'''







								return 1E-4





							@property
							def  lowerCamelCase__				(		self		:str							):







								'''simple docstring'''







								return 12






"""simple docstring"""







import math
import sys

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int ):
						"""simple docstring"""






						if number != int(lowerCamelCase_ ):
												raise ValueError("the value of input must be a natural number" )
						if number < 0:
												raise ValueError("the value of input must not be a negative number" )
						if number == 0:
												return 1
						snake_case   :			List[str]						    = [-1] * (number + 1)
						snake_case   :			str						    = 0
						for i in range(1     ,		number + 1 ):
												snake_case   :			Tuple						    = sys.maxsize
												snake_case   :			Optional[Any]						    = int(math.sqrt(lowerCamelCase_ ) )
												for j in range(1     ,		root + 1 ):
																		snake_case   :			List[str]						    = 1 + answers[i - (j**2)]
																		snake_case   :			List[str]						    = min(lowerCamelCase_     ,		lowerCamelCase_ )
												snake_case   :			Dict						    = answer
						return answers[number]


if __name__ == "__main__":
			import doctest

			doctest.testmod()



