


"""simple docstring"""







# using dfs for finding eulerian path traversal


def      lowercase			(				A_  ,   A_  ,   A_  ,   A_=None       )->      Dict:
  '''simple docstring'''







  a						:		Tuple      							=			(path or []) + [u]
  for v in graph[u]:
    if visited_edge[u][v] is False:
      a							,		a						:		Optional[Any]      							=			True, True
      a						:		List[str]      							=			dfs(A_  ,   A_  ,   A_  ,   A_       )
  return path


def      lowercase			(				A_  ,   A_       )->      Optional[int]:
  '''simple docstring'''







  a						:		Any      							=			0
  a						:		Dict      							=			-1
  for i in range(A_       ):
    if i not in graph.keys():
      continue
    if len(graph[i]       ) % 2 == 1:
      odd_degree_nodes += 1
      a						:		str      							=			i
  if odd_degree_nodes == 0:
    return 1, odd_node
  if odd_degree_nodes == 2:
    return 2, odd_node
  return 3, odd_node


def      lowercase			(				A_  ,   A_       )->      int:
  '''simple docstring'''







  a						:		Tuple      							=			[[False for _ in range(max_node + 1       )] for _ in range(max_node + 1       )]
  a							,		a						:		Optional[Any]      							=			check_circuit_or_path(A_  ,   A_       )
  if check == 3:
    print("graph is not Eulerian"       )
    print("no path"       )
    return
  a						:		Any      							=			1
  if check == 2:
    a						:		List[Any]      							=			odd_node
    print("graph has a Euler path"       )
  if check == 1:
    print("graph has a Euler cycle"       )
  a						:		Optional[Any]      							=			dfs(A_  ,   A_  ,   A_       )
  print(A_       )


def      lowercase			(				)->      Tuple:
  '''simple docstring'''







  a						:		Optional[Any]      							=			{1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
  a						:		Union[str, Any]      							=			{1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
  a						:		str      							=			{1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
  a						:		Dict      							=			{1: [2, 3], 2: [1, 3], 3: [1, 2]}
  a						:		Dict      							=			{
      1: [],
      2: []
      # all degree is zero
  }
  a						:		int      							=			10
  check_euler(A_  ,   A_       )
  check_euler(A_  ,   A_       )
  check_euler(A_  ,   A_       )
  check_euler(A_  ,   A_       )
  check_euler(A_  ,   A_       )


if __name__ == "__main__":
 main()











from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A__  :  Union[str, Any]								=					logging.get_logger(__name__)

A__  :  Tuple								=					{
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}



class 				__snake_case						(     UpperCamelCase_						):
							_a			      = '''xlm-roberta-xl'''




							def __init__(       self     :       int				,				A_     :       List[str]=2_5_0_8_8_0				,				A_     :       List[str]=2_5_6_0				,				A_     :       Optional[int]=3_6				,				A_     :       List[Any]=3_2				,				A_     :       Optional[int]=1_0_2_4_0				,				A_     :       Dict="gelu"				,				A_     :       int=0.1				,				A_     :       Optional[Any]=0.1				,				A_     :       int=5_1_4				,				A_     :       Any=1				,				A_     :       Optional[Any]=0.02				,				A_     :       str=1e-05				,				A_     :       Dict=1				,				A_     :       Any=0				,				A_     :       Tuple=2				,				A_     :       str="absolute"				,				A_     :       str=True				,				A_     :       List[str]=None				,				**A_     :       Dict				,				):
									super().__init__(pad_token_id=A_				,				bos_token_id=A_				,				eos_token_id=A_				,				**A_)
									lowerCAmelCase_			:     Tuple									= vocab_size
									lowerCAmelCase_			:     List[str]									= hidden_size
									lowerCAmelCase_			:     int									= num_hidden_layers
									lowerCAmelCase_			:     int									= num_attention_heads
									lowerCAmelCase_			:     Dict									= hidden_act
									lowerCAmelCase_			:     int									= intermediate_size
									lowerCAmelCase_			:     Tuple									= hidden_dropout_prob
									lowerCAmelCase_			:     Optional[Any]									= attention_probs_dropout_prob
									lowerCAmelCase_			:     Union[str, Any]									= max_position_embeddings
									lowerCAmelCase_			:     Dict									= type_vocab_size
									lowerCAmelCase_			:     str									= initializer_range
									lowerCAmelCase_			:     str									= layer_norm_eps
									lowerCAmelCase_			:     Optional[Any]									= position_embedding_type
									lowerCAmelCase_			:     Optional[Any]									= use_cache
									lowerCAmelCase_			:     List[str]									= classifier_dropout





class 				__snake_case						(     UpperCamelCase_						):




							@property
							def    UpperCAmelCase__			(       self     :       List[str]):
									if self.task == "multiple-choice":
											lowerCAmelCase_			:     Union[str, Any]									= {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
											lowerCAmelCase_			:     List[Any]									= {0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									    ])





