




_lowerCamelCase					:     List[Any]					  =  float("inf")
class 				__snake_case     :



				def __init__(					self					:						str						,		_UpperCAmelCase					:						int					)     ->			Any:





								'''simple docstring'''




								_lowerCAmelCase			:			List[str]        =					[0] * n
								_lowerCAmelCase			:			Optional[Any]        =					[0] * n
								_lowerCAmelCase			:			Dict        =					[0] * n
								_lowerCAmelCase			:			Tuple        =					[[] for _ in range(_UpperCAmelCase					)]



				def 					SCREAMING_SNAKE_CASE				(					self					:						List[str]						,		_UpperCAmelCase					:						List[str]						,		_UpperCAmelCase					:						Optional[int]						,		_UpperCAmelCase					:						Dict						,		_UpperCAmelCase					:						int=0					)     ->			Union[str, Any]:





								'''simple docstring'''




								self.adj[a].append([b, len(self.adj[b]					), c, 0]					)
								self.adj[b].append([a, len(self.adj[a]					) - 1, rcap, 0]					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						int						,		_UpperCAmelCase					:						str						,		_UpperCAmelCase					:						int						,		_UpperCAmelCase					:						Union[str, Any]					)     ->			Union[str, Any]:





								'''simple docstring'''




								if vertex == sink or not flow:
												return flow

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



				def 					SCREAMING_SNAKE_CASE				(					self					:						List[Any]						,		_UpperCAmelCase					:						Any						,		_UpperCAmelCase					:						str					)     ->			List[Any]:





								'''simple docstring'''




								_lowerCAmelCase    ,			_lowerCAmelCase			:			Optional[Any]        =					0, source
								for l in range(31					):  # noqa: E741  l = 30 maybe faster for random data
												while True:
																_lowerCAmelCase    ,			_lowerCAmelCase			:			str        =					[0] * len(self.q					), [0] * len(self.q					)
																_lowerCAmelCase    ,			_lowerCAmelCase    ,			_lowerCAmelCase			:			Tuple        =					0, 1, 1
																while qi < qe and not self.lvl[sink]:
																				_lowerCAmelCase			:			Any        =					self.q[qi]
																				qi += 1
																				for e in self.adj[v]:
																								if not self.lvl[e[0]] and (e[2] - e[3]) >> (30 - l):
																												_lowerCAmelCase			:			str        =					e[0]
																												qe += 1
																												_lowerCAmelCase			:			Any        =					self.lvl[v] + 1

																_lowerCAmelCase			:			Union[str, Any]        =					self.depth_first_search(_UpperCAmelCase						,		_UpperCAmelCase						,		_UpperCAmelCase					)
																while p:
																				flow += p
																				_lowerCAmelCase			:			Optional[Any]        =					self.depth_first_search(_UpperCAmelCase						,		_UpperCAmelCase						,		_UpperCAmelCase					)

																if not self.lvl[sink]:
																				break

								return flow
_lowerCamelCase					:     str					  =  Dinic(1_0)
_lowerCamelCase					:     int					  =  0
_lowerCamelCase					:     str					  =  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))







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


_lowerCamelCase					:     Optional[Any]					  =  logging.get_logger(__name__)

_lowerCamelCase					:     str					  =  {
    "google/reformer-crime-and-punishment": (
        "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json"
    ),
    "google/reformer-enwik8": "https://huggingface.co/google/reformer-enwik8/resolve/main/config.json",
}
class 				__snake_case     (_a						):
				lowerCAmelCase__			=   "reformer"
				lowerCAmelCase__			=   ["past_buckets_states"]
				lowerCAmelCase__			=   {}



				def __init__(					self					:						Optional[int]						,		_UpperCAmelCase					:						str=64						,		_UpperCAmelCase					:						Tuple=["local", "lsh", "local", "lsh", "local", "lsh"]						,		_UpperCAmelCase					:						Optional[int]=1.0						,		_UpperCAmelCase					:						str=True						,		_UpperCAmelCase					:						List[Any]=[64, 64]						,		_UpperCAmelCase					:						str=[64, 192]						,		_UpperCAmelCase					:						List[Any]=0						,		_UpperCAmelCase					:						Optional[Any]=2						,		_UpperCAmelCase					:						Dict=512						,		_UpperCAmelCase					:						Optional[int]=None						,		_UpperCAmelCase					:						Tuple="relu"						,		_UpperCAmelCase					:						Tuple=0.05						,		_UpperCAmelCase					:						int=256						,		_UpperCAmelCase					:						List[str]=0.02						,		_UpperCAmelCase					:						Any=False						,		_UpperCAmelCase					:						Any=1E-12						,		_UpperCAmelCase					:						List[Any]=1						,		_UpperCAmelCase					:						Optional[Any]=0						,		_UpperCAmelCase					:						Union[str, Any]=0.05						,		_UpperCAmelCase					:						int=64						,		_UpperCAmelCase					:						List[str]=64						,		_UpperCAmelCase					:						Any=0.0						,		_UpperCAmelCase					:						Any=1						,		_UpperCAmelCase					:						Optional[Any]=0						,		_UpperCAmelCase					:						Union[str, Any]=4096						,		_UpperCAmelCase					:						Dict=12						,		_UpperCAmelCase					:						int=None						,		_UpperCAmelCase					:						List[Any]=1						,		_UpperCAmelCase					:						Union[str, Any]=0						,		_UpperCAmelCase					:						Any=320						,		_UpperCAmelCase					:						Any=False						,		_UpperCAmelCase					:						List[str]=True						,		_UpperCAmelCase					:						Optional[int]=None						,		**_UpperCAmelCase					:						Tuple						,		)     ->			List[str]:





								'''simple docstring'''




								_lowerCAmelCase			:			Union[str, Any]        =					hash_seed
								_lowerCAmelCase			:			int        =					vocab_size
								_lowerCAmelCase			:			Optional[Any]        =					attention_head_size
								_lowerCAmelCase			:			Dict        =					hidden_size
								_lowerCAmelCase			:			Union[str, Any]        =					num_attention_heads
								_lowerCAmelCase			:			int        =					num_hashes
								_lowerCAmelCase			:			Union[str, Any]        =					len(_UpperCAmelCase					)
								_lowerCAmelCase			:			int        =					tuple(_UpperCAmelCase					) if isinstance(_UpperCAmelCase						,		_UpperCAmelCase					) else num_buckets
								_lowerCAmelCase			:			Union[str, Any]        =					lsh_attn_chunk_length
								_lowerCAmelCase			:			List[str]        =					local_attn_chunk_length
								_lowerCAmelCase			:			int        =					lsh_num_chunks_after
								_lowerCAmelCase			:			Union[str, Any]        =					lsh_num_chunks_before
								_lowerCAmelCase			:			str        =					local_num_chunks_after
								_lowerCAmelCase			:			Dict        =					local_num_chunks_before
								_lowerCAmelCase			:			Any        =					hidden_act
								_lowerCAmelCase			:			List[str]        =					feed_forward_size
								_lowerCAmelCase			:			str        =					hidden_dropout_prob
								_lowerCAmelCase			:			Any        =					lsh_attention_probs_dropout_prob
								_lowerCAmelCase			:			Dict        =					local_attention_probs_dropout_prob
								_lowerCAmelCase			:			Tuple        =					max_position_embeddings
								_lowerCAmelCase			:			Any        =					initializer_range
								_lowerCAmelCase			:			List[str]        =					layer_norm_eps
								_lowerCAmelCase			:			Dict        =					axial_pos_embds
								_lowerCAmelCase			:			Union[str, Any]        =					tuple(_UpperCAmelCase					)
								_lowerCAmelCase			:			int        =					tuple(_UpperCAmelCase					)
								_lowerCAmelCase			:			List[str]        =					axial_norm_std
								_lowerCAmelCase			:			List[str]        =					chunk_size_lm_head
								_lowerCAmelCase			:			int        =					attn_layers
								_lowerCAmelCase			:			List[Any]        =					use_cache
								_lowerCAmelCase			:			Optional[int]        =					classifier_dropout
								super().__init__(
								    pad_token_id=_UpperCAmelCase						,		eos_token_id=_UpperCAmelCase						,		is_decoder=_UpperCAmelCase						,		tie_word_embeddings=_UpperCAmelCase						,		**_UpperCAmelCase						,		)

