__SCREAMING_SNAKE_CASE						:    List[Any]     = float('inf')



class    lowercase_    :



							def __init__(						self      ,				lowercase_				):
													_snake_case						:     List[str]				=    [0] * n
													_snake_case						:     Optional[Any]				=    [0] * n
													_snake_case						:     Dict				=    [0] * n
													_snake_case						:     Tuple				=    [[] for _ in range(_UpperCAmelCase				)]



							def        UpperCamelCase       (						self      ,				lowercase_      ,				lowercase_      ,				lowercase_      ,				lowercase_=0				):
													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      ,				lowercase_      ,				lowercase_      ,				lowercase_				):




													if vertex == sink or not flow:
																			return flow

													for i in range(self.ptr[vertex]      ,				len(self.adj[vertex]				)				):
																			_snake_case						:     Optional[int]				=    self.adj[vertex][i]
																			if self.lvl[e[0]] == self.lvl[vertex] + 1:
																									_snake_case						:     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
																			_snake_case						:     Dict				=    self.ptr[vertex] + 1
													return 0



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

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

																									if not self.lvl[sink]:
																															break

													return flow




__SCREAMING_SNAKE_CASE						:    str     = Dinic(1_0)
__SCREAMING_SNAKE_CASE						:    int     = 0
__SCREAMING_SNAKE_CASE						:    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 collections import OrderedDict
from typing import Mapping

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


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

_lowerCamelCase					:     Optional[int]					  =  {
    "squeezebert/squeezebert-uncased": (
        "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"
    ),
    "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json",
    "squeezebert/squeezebert-mnli-headless": (
        "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"
    ),
}
class 				__snake_case     (_a						):
				lowerCAmelCase__			=   SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
				lowerCAmelCase__			=   "squeezebert"



				def __init__(					self					:						Optional[int]						,		_UpperCAmelCase					:						Tuple=3_0522						,		_UpperCAmelCase					:						str=768						,		_UpperCAmelCase					:						int=12						,		_UpperCAmelCase					:						Tuple=12						,		_UpperCAmelCase					:						Tuple=3072						,		_UpperCAmelCase					:						Union[str, Any]="gelu"						,		_UpperCAmelCase					:						Union[str, Any]=0.1						,		_UpperCAmelCase					:						List[Any]=0.1						,		_UpperCAmelCase					:						List[Any]=512						,		_UpperCAmelCase					:						Tuple=2						,		_UpperCAmelCase					:						Optional[Any]=0.02						,		_UpperCAmelCase					:						Any=1E-12						,		_UpperCAmelCase					:						Optional[Any]=0						,		_UpperCAmelCase					:						Union[str, Any]=768						,		_UpperCAmelCase					:						Any=4						,		_UpperCAmelCase					:						Any=4						,		_UpperCAmelCase					:						Optional[int]=4						,		_UpperCAmelCase					:						str=1						,		_UpperCAmelCase					:						Union[str, Any]=4						,		_UpperCAmelCase					:						List[str]=4						,		**_UpperCAmelCase					:						int						,		)     ->			Any:





								'''simple docstring'''




								super().__init__(pad_token_id=_UpperCAmelCase						,		**_UpperCAmelCase					)

								_lowerCAmelCase			:			Optional[Any]        =					vocab_size
								_lowerCAmelCase			:			Optional[Any]        =					hidden_size
								_lowerCAmelCase			:			Tuple        =					num_hidden_layers
								_lowerCAmelCase			:			int        =					num_attention_heads
								_lowerCAmelCase			:			List[Any]        =					hidden_act
								_lowerCAmelCase			:			List[Any]        =					intermediate_size
								_lowerCAmelCase			:			List[str]        =					hidden_dropout_prob
								_lowerCAmelCase			:			Any        =					attention_probs_dropout_prob
								_lowerCAmelCase			:			str        =					max_position_embeddings
								_lowerCAmelCase			:			int        =					type_vocab_size
								_lowerCAmelCase			:			str        =					initializer_range
								_lowerCAmelCase			:			int        =					layer_norm_eps
								_lowerCAmelCase			:			int        =					embedding_size
								_lowerCAmelCase			:			Optional[int]        =					q_groups
								_lowerCAmelCase			:			List[Any]        =					k_groups
								_lowerCAmelCase			:			List[Any]        =					v_groups
								_lowerCAmelCase			:			Dict        =					post_attention_groups
								_lowerCAmelCase			:			Optional[Any]        =					intermediate_groups
								_lowerCAmelCase			:			str        =					output_groups






class 				__snake_case     (_a						):



				@property
				def 					SCREAMING_SNAKE_CASE				(					self					:						Union[str, Any]					)     ->			Mapping[str, Mapping[int, str]]:





								'''simple docstring'''




								if self.task == "multiple-choice":
												_lowerCAmelCase			:			Optional[int]        =					{0: """batch""", 1: """choice""", 2: """sequence"""}
								else:
												_lowerCAmelCase			:			int        =					{0: """batch""", 1: """sequence"""}
								return OrderedDict(
								    [
								        ("""input_ids""", dynamic_axis),
								        ("""attention_mask""", dynamic_axis),
								        ("""token_type_ids""", dynamic_axis),
								    ]					)

