






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     current_set.copy()
				for row_index, row in enumerate(lowerCamelCase_							):
								lowercase__  					=     row[0]
								for column_index, column in enumerate(lowerCamelCase_							):
												if magnitude == 0:
																lowercase__  					=     column
																continue
												lowercase__  					=     column / magnitude
    # Subtract to cancel term
				lowercase__  					=     current_set[0]
				lowercase__  					=     [first_row]
				lowercase__  					=     current_set[1::]
				for row in current_set:
								lowercase__  					=     []
								# If first term is 0, it is already in form we want, so we preserve it
								if row[0] == 0:
												final_set.append(lowerCamelCase_							)
												continue
								for column_index in range(len(lowerCamelCase_							)							):
												temp_row.append(first_row[column_index] - row[column_index]							)
								final_set.append(lowerCamelCase_							)
				# Create next recursion iteration set
				if len(final_set[0]							) != 3:
								lowercase__  					=     final_set[0]
								lowercase__  					=     []
								lowercase__  					=     []
								for row in final_set[1::]:
												current_first_column.append(row[0]							)
												next_iteration.append(row[1::]							)
								lowercase__  					=     simplify(lowerCamelCase_							)
								for i in range(len(lowerCamelCase_							)							):
												resultant[i].insert(0						,  current_first_column[i]							)
								resultant.insert(0						,  lowerCamelCase_							)
								lowercase__  					=     resultant
				return final_set






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if len(lowerCamelCase_							) == 0:
								raise IndexError('''solve_simultaneous() requires n lists of length n+1'''							)
				lowercase__  					=     len(lowerCamelCase_							) + 1
				if any(len(lowerCamelCase_							) != _length for item in equations							):
								raise IndexError('''solve_simultaneous() requires n lists of length n+1'''							)
				for row in equations:
								if any(not isinstance(lowerCamelCase_						,  (int, float)							) for column in row							):
												raise ValueError('''solve_simultaneous() requires lists of integers'''							)
				if len(lowerCamelCase_							) == 1:
								return [equations[0][-1] / equations[0][0]]
				lowercase__  					=     equations.copy()
				if any(0 in row for row in data_set							):
								lowercase__  					=     data_set.copy()
								lowercase__  					=     []
								for row_index, row in enumerate(lowerCamelCase_							):
												if 0 not in row:
																lowercase__  					=     data_set.pop(lowerCamelCase_							)
																break
								if not full_row:
												raise ValueError('''solve_simultaneous() requires at least 1 full equation'''							)
								data_set.insert(0						,  lowerCamelCase_							)
				lowercase__  					=     data_set.copy()
				lowercase__  					=     simplify(lowerCamelCase_							)
				lowercase__  					=     simplified[::-1]
				lowercase__  					=     []
				for row in simplified:
								lowercase__  					=     row[-1]
								if not solutions:
												if row[-2] == 0:
																solutions.append(0							)
																continue
												solutions.append(current_solution / row[-2]							)
												continue
								lowercase__  					=     row.copy()[: len(lowerCamelCase_							) - 1 :]
								while temp_row[0] == 0:
												temp_row.pop(0							)
								if len(lowerCamelCase_							) == 0:
												solutions.append(0							)
												continue
								lowercase__  					=     temp_row[1::]
								lowercase__  					=     temp_row[::-1]
								for column_index, column in enumerate(lowerCamelCase_							):
												current_solution -= column * solutions[column_index]
								solutions.append(lowerCamelCase_							)
				lowercase__  					=     []
				for item in solutions:
								final.append(float(round(lowerCamelCase_						,  5							)							)							)
				return final[::-1]


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							A__      :     Any       =					[
							    [2, 1, 1, 1, 1, 4],
							    [1, 2, 1, 1, 1, 5],
							    [1, 1, 2, 1, 1, 6],
							    [1, 1, 1, 2, 1, 7],
							    [1, 1, 1, 1, 2, 8],
							]
							print(solve_simultaneous(eq))
							print(solve_simultaneous([[4, 2]]))












import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


A__      :     Tuple       =					logging.get_logger(__name__)
class  _UpperCAmelCase   (			A__      ):

				"""simple docstring"""




				lowercase__											=			"""upernet"""




				def __init__(	self		:       Dict,    lowerCamelCase		:       Union[str, Any]=None,    lowerCamelCase		:       str=512,    lowerCamelCase		:       Optional[Any]=0.02,    lowerCamelCase		:       Optional[Any]=[1, 2, 3, 6],    lowerCamelCase		:       Optional[int]=True,    lowerCamelCase		:       Tuple=0.4,    lowerCamelCase		:       Optional[int]=384,    lowerCamelCase		:       Optional[int]=256,    lowerCamelCase		:       Dict=1,    lowerCamelCase		:       str=False,    lowerCamelCase		:       List[str]=255,    **lowerCamelCase		:       List[Any],    ):

								'''simple docstring'''
								super().__init__(**lowerCamelCase    )

								if backbone_config is None:
												logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''    )
												lowercase__  					=     CONFIG_MAPPING['''resnet'''](out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']    )
								elif isinstance(lowerCamelCase,    lowerCamelCase    ):
												lowercase__  					=     backbone_config.get('''model_type'''    )
												lowercase__  					=     CONFIG_MAPPING[backbone_model_type]
												lowercase__  					=     config_class.from_dict(lowerCamelCase    )

								lowercase__  					=     backbone_config
								lowercase__  					=     hidden_size
								lowercase__  					=     initializer_range
								lowercase__  					=     pool_scales
								lowercase__  					=     use_auxiliary_head
								lowercase__  					=     auxiliary_loss_weight
								lowercase__  					=     auxiliary_in_channels
								lowercase__  					=     auxiliary_channels
								lowercase__  					=     auxiliary_num_convs
								lowercase__  					=     auxiliary_concat_input
								lowercase__  					=     loss_ignore_index




				def 							lowercase__  (	self		:       str    ):

								'''simple docstring'''
								lowercase__  					=     copy.deepcopy(self.__dict__    )
								lowercase__  					=     self.backbone_config.to_dict()
								lowercase__  					=     self.__class__.model_type
								return output




