




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase ):
				__magic_name__						:						Tuple										=word.split()

				def justify(lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase ) -> str:
								__magic_name__						:						Optional[Any]										=max_width - width
								__magic_name__						:						Optional[Any]										=len(lowerCamelCase )
								if len(lowerCamelCase ) == 1:
												# if there is only word in line
												# just insert overall_spaces_count for the remainder of line
												return line[0] + " " * overall_spaces_count
								else:
												__magic_name__						:						List[Any]										=words_count - 1
												# num_spaces_between_words_list[i] : tells you to insert
												# num_spaces_between_words_list[i] spaces
												# after word on line[i]
												__magic_name__						:						Any										=spaces_to_insert_between_words * [
												    overall_spaces_count // spaces_to_insert_between_words
												]
												__magic_name__						:						Tuple										=(
												    overall_spaces_count % spaces_to_insert_between_words
												)
												# distribute spaces via round robin to the left words
												for i in range(lowerCamelCase ):
																num_spaces_between_words_list[i] += 1
												__magic_name__						:						Dict										=[]
												for i in range(lowerCamelCase ):
																# add the word
																aligned_words_list.append(line[i] )
																# add the spaces to insert
																aligned_words_list.append(num_spaces_between_words_list[i] * """ """ )
												# just add the last word to the sentence
												aligned_words_list.append(line[-1] )
												# join the aligned words list to form a justified line
												return "".join(lowerCamelCase )

				__magic_name__						:						Union[str, Any]										=[]
				__magic_name__						:						list[str]										=[]
				__magic_name__						:						Any										=0
				for word in words:
								if width + len(lowerCamelCase ) + len(lowerCamelCase ) <= max_width:
												# keep adding words until we can fill out max_width
												# width = sum of length of all words (without overall_spaces_count)
												# len(word) = length of current word
												# len(line) = number of overall_spaces_count to insert between words
												line.append(lowerCamelCase )
												width += len(lowerCamelCase )
								else:
												# justify the line and add it to result
												answer.append(justify(lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase ) )
												# reset new line and new width
												__magic_name__					,			__magic_name__						:						int										=[word], len(lowerCamelCase )
				__magic_name__						:						Optional[int]										=max_width - width - len(lowerCamelCase )
				answer.append(""" """.join(lowerCamelCase ) + (remaining_spaces + 1) * """ """ )
				return answer


if __name__ == "__main__":
							from doctest import testmod

							testmod()










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_		:					Any          =  logging.get_logger(__name__)

UpperCAmelCase_		:					List[str]          =  {
    "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 		__A   (      UpperCamelCase__      ):
						UpperCamelCase      =       """segformer"""

						def __init__(		self :List[str]     ,			__snake_case :str=3     ,			__snake_case :Optional[Any]=4     ,			__snake_case :List[Any]=[2, 2, 2, 2]     ,			__snake_case :Dict=[8, 4, 2, 1]     ,			__snake_case :Optional[int]=[32, 64, 1_60, 2_56]     ,			__snake_case :Union[str, Any]=[7, 3, 3, 3]     ,			__snake_case :Optional[Any]=[4, 2, 2, 2]     ,			__snake_case :Tuple=[1, 2, 5, 8]     ,			__snake_case :List[Any]=[4, 4, 4, 4]     ,			__snake_case :Optional[Any]="gelu"     ,			__snake_case :Tuple=0.0     ,			__snake_case :Dict=0.0     ,			__snake_case :Optional[int]=0.1     ,			__snake_case :Optional[int]=0.02     ,			__snake_case :Tuple=0.1     ,			__snake_case :Union[str, Any]=1E-6     ,			__snake_case :int=2_56     ,			__snake_case :Optional[int]=2_55     ,			**__snake_case :Dict     ,			):
										'''simple docstring'''

										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     ,			)

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




class 		__A   (      UpperCamelCase__      ):
						UpperCamelCase      =       version.parse("""1.11"""      )

						@property
						def      A__    (		self :List[str]			):
										'''simple docstring'''

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

						@property
						def      A__    (		self :Any			):
										'''simple docstring'''

										return 1E-4


						@property
						def      A__    (		self :int			):
										'''simple docstring'''

										return 12




