

from typing import List, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__							=			logging.get_logger(__name__)

lowerCAmelCase__							=			{
    "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/config.json",
    # See all LED models at https://huggingface.co/models?filter=led
}






class     __magic_name__     (							_snake_case     ):
 UpperCAmelCase				     =    """led"""
 UpperCAmelCase				     =    {
     """num_attention_heads""": """encoder_attention_heads""",
     """hidden_size""": """d_model""",
     """attention_probs_dropout_prob""": """attention_dropout""",
     """initializer_range""": """init_std""",
 }


 def __init__(    self		:			List[str]      ,    lowerCAmelCase__		:			str=5_0_2_6_5      ,    lowerCAmelCase__		:			List[Any]=1_6_3_8_4      ,    lowerCAmelCase__		:			Tuple=1_0_2_4      ,    lowerCAmelCase__		:			Optional[int]=1_2      ,    lowerCAmelCase__		:			int=4_0_9_6      ,    lowerCAmelCase__		:			Union[str, Any]=1_6      ,    lowerCAmelCase__		:			Any=1_2      ,    lowerCAmelCase__		:			Union[str, Any]=4_0_9_6      ,    lowerCAmelCase__		:			List[str]=1_6      ,    lowerCAmelCase__		:			List[str]=0.0      ,    lowerCAmelCase__		:			Optional[int]=0.0      ,    lowerCAmelCase__		:			str=True      ,    lowerCAmelCase__		:			Dict=True      ,    lowerCAmelCase__		:			Any="gelu"      ,    lowerCAmelCase__		:			Optional[Any]=1_0_2_4      ,    lowerCAmelCase__		:			str=0.1      ,    lowerCAmelCase__		:			List[Any]=0.0      ,    lowerCAmelCase__		:			List[Any]=0.0      ,    lowerCAmelCase__		:			int=0.02      ,    lowerCAmelCase__		:			Optional[int]=2      ,    lowerCAmelCase__		:			List[str]=0.0      ,    lowerCAmelCase__		:			int=1      ,    lowerCAmelCase__		:			str=0      ,    lowerCAmelCase__		:			str=2      ,    lowerCAmelCase__		:			Union[List[int], int] = 5_1_2      ,    **lowerCAmelCase__		:			Dict      ,    )     ->   Dict:
   UpperCAmelCase          =	vocab_size
   UpperCAmelCase          =	max_encoder_position_embeddings
   UpperCAmelCase          =	max_decoder_position_embeddings
   UpperCAmelCase          =	d_model
   UpperCAmelCase          =	encoder_ffn_dim
   UpperCAmelCase          =	encoder_layers
   UpperCAmelCase          =	encoder_attention_heads
   UpperCAmelCase          =	decoder_ffn_dim
   UpperCAmelCase          =	decoder_layers
   UpperCAmelCase          =	decoder_attention_heads
   UpperCAmelCase          =	dropout
   UpperCAmelCase          =	attention_dropout
   UpperCAmelCase          =	activation_dropout
   UpperCAmelCase          =	activation_function
   UpperCAmelCase          =	init_std
   UpperCAmelCase          =	encoder_layerdrop
   UpperCAmelCase          =	decoder_layerdrop
   UpperCAmelCase          =	classifier_dropout
   UpperCAmelCase          =	use_cache
   UpperCAmelCase          =	encoder_layers
   UpperCAmelCase          =	attention_window

   super().__init__(
       pad_token_id=lowerCAmelCase__      ,    bos_token_id=lowerCAmelCase__      ,    eos_token_id=lowerCAmelCase__      ,    is_encoder_decoder=lowerCAmelCase__      ,    decoder_start_token_id=lowerCAmelCase__      ,    **lowerCAmelCase__      ,    )






lowerCAmelCase__							=			float("inf")






class     __magic_name__     :


 def __init__(    self		:			List[str]      ,    lowerCAmelCase__		:			Dict     )     ->   List[Any]:
   UpperCAmelCase          =	[0] * n
   UpperCAmelCase          =	[0] * n
   UpperCAmelCase          =	[0] * n
   UpperCAmelCase          =	[[] for _ in range(lowerCAmelCase__     )]


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			Tuple      ,    lowerCAmelCase__		:			Dict      ,    lowerCAmelCase__		:			str      ,    lowerCAmelCase__		:			Optional[Any]=0     )     ->   Any:
   self.adj[a].append([b, len(self.adj[b]     ), c, 0]     )
   self.adj[b].append([a, len(self.adj[a]     ) - 1, rcap, 0]     )


 def _UpperCamelCase						(    self		:			List[str]      ,    lowerCAmelCase__		:			Union[str, Any]      ,    lowerCAmelCase__		:			List[Any]      ,    lowerCAmelCase__		:			Any     )     ->   List[str]:
   if vertex == sink or not flow:
     return flow

   for i in range(self.ptr[vertex]      ,    len(self.adj[vertex]     )     ):
     UpperCAmelCase          =	self.adj[vertex][i]
     if self.lvl[e[0]] == self.lvl[vertex] + 1:
       UpperCAmelCase          =	self.depth_first_search(e[0]      ,    lowerCAmelCase__      ,    min(lowerCAmelCase__      ,    e[2] - e[3]     )     )
       if p:
         self.adj[vertex][i][3] += p
         self.adj[e[0]][e[1]][3] -= p
         return p
     UpperCAmelCase          =	self.ptr[vertex] + 1
   return 0


 def _UpperCamelCase						(    self		:			str      ,    lowerCAmelCase__		:			str      ,    lowerCAmelCase__		:			Tuple     )     ->   int:
   UpperCAmelCase   ,						UpperCAmelCase          =	0, source
   for l in range(3_1     ):  # noqa: E741  l = 30 maybe faster for random data
     while True:
       UpperCAmelCase   ,						UpperCAmelCase          =	[0] * len(self.q     ), [0] * len(self.q     )
       UpperCAmelCase   ,						UpperCAmelCase   ,						UpperCAmelCase          =	0, 1, 1
       while qi < qe and not self.lvl[sink]:
         UpperCAmelCase          =	self.q[qi]
         qi += 1
         for e in self.adj[v]:
           if not self.lvl[e[0]] and (e[2] - e[3]) >> (3_0 - l):
             UpperCAmelCase          =	e[0]
             qe += 1
             UpperCAmelCase          =	self.lvl[v] + 1

       UpperCAmelCase          =	self.depth_first_search(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__     )
       while p:
         flow += p
         UpperCAmelCase          =	self.depth_first_search(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__     )

       if not self.lvl[sink]:
         break

   return flow
lowerCAmelCase__							=			Dinic(10)
lowerCAmelCase__							=			0
lowerCAmelCase__							=			9
for vertex in range(1, 5):
      graph.add_edge(source, vertex, 1)
for vertex in range(5, 9):
      graph.add_edge(vertex, sink, 1)
for vertex in range(1, 5):
      graph.add_edge(vertex, vertex + 4, 1)

# Now we can know that is the maximum flow(source -> sink)
print(graph.max_flow(source, sink))



