'''simple docstring'''




class 	lowerCamelCase_	:
      '''simple docstring'''

      def __init__(       self						:				Tuple						,					A						:				Any						,					A						:				str						,					A						:				Union[str, Any]       ):
             _UpperCAmelCase     :  Optional[int]							      =    None
             _UpperCAmelCase     :  Optional[int]							      =    None
             _UpperCAmelCase     :  Any							      =    graph

             self._normalize_graph(A						,					A       )
             _UpperCAmelCase     :  List[str]							      =    len(A       )
             _UpperCAmelCase     :  Tuple							      =    None




      def      _A	(       self						:				Any						,					A						:				List[Any]						,					A						:				str       ):
             if sources is int:
                    _UpperCAmelCase     :  List[Any]							      =    [sources]
             if sinks is int:
                    _UpperCAmelCase     :  List[Any]							      =    [sinks]

             if len(A       ) == 0 or len(A       ) == 0:
                    return

             _UpperCAmelCase     :  str							      =    sources[0]
             _UpperCAmelCase     :  Union[str, Any]							      =    sinks[0]

             # make fake vertex if there are more
             # than one source or sink
             if len(A       ) > 1 or len(A       ) > 1:
                    _UpperCAmelCase     :  Dict							      =    0
                    for i in sources:
                           max_input_flow += sum(self.graph[i]       )

                    _UpperCAmelCase     :  str							      =    len(self.graph       ) + 1
                    for room in self.graph:
                           room.insert(0						,					0       )
                    self.graph.insert(0						,					[0] * size       )
                    for i in sources:
                           _UpperCAmelCase     :  Optional[Any]							      =    max_input_flow
                    _UpperCAmelCase     :  List[str]							      =    0

                    _UpperCAmelCase     :  str							      =    len(self.graph       ) + 1
                    for room in self.graph:
                           room.append(0       )
                    self.graph.append([0] * size       )
                    for i in sinks:
                           _UpperCAmelCase     :  Dict							      =    max_input_flow
                    _UpperCAmelCase     :  List[Any]							      =    size - 1




      def      _A	(       self						:				Union[str, Any]       ):
             if self.maximum_flow_algorithm is None:
                    raise Exception("You need to set maximum flow algorithm before."       )
             if self.source_index is None or self.sink_index is None:
                    return 0

             self.maximum_flow_algorithm.execute()
             return self.maximum_flow_algorithm.getMaximumFlow()





      def      _A	(       self						:				Tuple						,					A						:				Dict       ):
             _UpperCAmelCase     :  str							      =    algorithm(self       )

class 	lowerCamelCase_	:
      '''simple docstring'''

      def __init__(       self						:				Any						,					A						:				str       ):
             _UpperCAmelCase     :  Optional[int]							      =    flow_network
             _UpperCAmelCase     :  Any							      =    flow_network.verticesCount
             _UpperCAmelCase     :  List[str]							      =    flow_network.sourceIndex
             _UpperCAmelCase     :  Union[str, Any]							      =    flow_network.sinkIndex
             # it's just a reference, so you shouldn't change
             # it in your algorithms, use deep copy before doing that
             _UpperCAmelCase     :  Any							      =    flow_network.graph
             _UpperCAmelCase     :  Union[str, Any]							      =    False




      def      _A	(       self						:				List[str]       ):
             if not self.executed:
                    self._algorithm()
                    _UpperCAmelCase     :  int							      =    True





      def      _A	(       self						:				List[Any]       ):
             pass

class 	lowerCamelCase_	(snake_case__    ):
      '''simple docstring'''

      def __init__(       self						:				Optional[int]						,					A						:				Union[str, Any]       ):
             super().__init__(A       )
             # use this to save your result
             _UpperCAmelCase     :  Any							      =    -1





      def      _A	(       self						:				Union[str, Any]       ):
             if not self.executed:
                    raise Exception("You should execute algorithm before using its result!"       )

             return self.maximum_flow

class 	lowerCamelCase_	(snake_case__    ):
      '''simple docstring'''

      def __init__(       self						:				Tuple						,					A						:				int       ):
             super().__init__(A       )

             _UpperCAmelCase     :  List[str]							      =    [[0] * self.verticies_count for i in range(self.verticies_count       )]

             _UpperCAmelCase     :  Union[str, Any]							      =    [0] * self.verticies_count
             _UpperCAmelCase     :  int							      =    [0] * self.verticies_count




      def      _A	(       self						:				Dict       ):
             _UpperCAmelCase     :  Dict							      =    self.verticies_count

             # push some substance to graph
             for nextvertex_index, bandwidth in enumerate(self.graph[self.source_index]       ):
                    self.preflow[self.source_index][nextvertex_index] += bandwidth
                    self.preflow[nextvertex_index][self.source_index] -= bandwidth
                    self.excesses[nextvertex_index] += bandwidth

             # Relabel-to-front selection rule
             _UpperCAmelCase     :  Optional[int]							      =    [
                 i
                 for i in range(self.verticies_count       )
                 if i != self.source_index and i != self.sink_index
             ]

             # move through list
             _UpperCAmelCase     :  Any							      =    0
             while i < len(A       ):
                    _UpperCAmelCase     :  int							      =    vertices_list[i]
                    _UpperCAmelCase     :  int							      =    self.heights[vertex_index]
                    self.process_vertex(A       )
                    if self.heights[vertex_index] > previous_height:
                           # if it was relabeled, swap elements
                           # and start from 0 index
                           vertices_list.insert(0						,					vertices_list.pop(A       )       )
                           _UpperCAmelCase     :  Union[str, Any]							      =    0
                    else:
                           i += 1

             _UpperCAmelCase     :  List[Any]							      =    sum(self.preflow[self.source_index]       )




      def      _A	(       self						:				Union[str, Any]						,					A						:				str       ):
             while self.excesses[vertex_index] > 0:
                    for neighbour_index in range(self.verticies_count       ):
                           # if it's neighbour and current vertex is higher
                           if (
                               self.graph[vertex_index][neighbour_index]
                               - self.preflow[vertex_index][neighbour_index]
                               > 0
                               and self.heights[vertex_index] > self.heights[neighbour_index]
                           ):
                                  self.push(A						,					A       )

                    self.relabel(A       )




      def      _A	(       self						:				int						,					A						:				Dict						,					A						:				List[str]       ):
             _UpperCAmelCase     :  int							      =    min(
                 self.excesses[from_index]						,					self.graph[from_index][to_index] - self.preflow[from_index][to_index]						,					)
             self.preflow[from_index][to_index] += preflow_delta
             self.preflow[to_index][from_index] -= preflow_delta
             self.excesses[from_index] -= preflow_delta
             self.excesses[to_index] += preflow_delta





      def      _A	(       self						:				Optional[int]						,					A						:				Union[str, Any]       ):
             _UpperCAmelCase     :  str							      =    None
             for to_index in range(self.verticies_count       ):
                    if (
                        self.graph[vertex_index][to_index]
                        - self.preflow[vertex_index][to_index]
                        > 0
                    ) and (min_height is None or self.heights[to_index] < min_height):
                           _UpperCAmelCase     :  Tuple							      =    self.heights[to_index]

             if min_height is not None:
                    _UpperCAmelCase     :  Optional[Any]							      =    min_height + 1


if __name__ == "__main__":
  __SCREAMING_SNAKE_CASE       :     Optional[int]     =  [0]
  __SCREAMING_SNAKE_CASE       :     Union[str, Any]     =  [3]
  # graph = [
  #     [0, 0, 4, 6, 0, 0],
  #     [0, 0, 5, 2, 0, 0],
  #     [0, 0, 0, 0, 4, 4],
  #     [0, 0, 0, 0, 6, 6],
  #     [0, 0, 0, 0, 0, 0],
  #     [0, 0, 0, 0, 0, 0],
  # ]
  __SCREAMING_SNAKE_CASE       :     List[Any]     =  [[0, 7, 0, 0], [0, 0, 6, 0], [0, 0, 0, 8], [9, 0, 0, 0]]

  # prepare our network
  __SCREAMING_SNAKE_CASE       :     Union[str, Any]     =  FlowNetwork(graph, entrances, exits)
  # set algorithm
  flow_network.set_maximum_flow_algorithm(PushRelabelExecutor)
  # and calculate
  __SCREAMING_SNAKE_CASE       :     Optional[Any]     =  flow_network.find_maximum_flow()

  print(F'maximum flow is {maximum_flow}')







from typing import Dict, List, Optional

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_A     =			logging.get_logger(__name__)


_A     =			{
    '''nielsr/canine-s''': 2_048,
}

# Unicode defines 1,114,112 total “codepoints”
_A     =			1_114_112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
_A     =			0

_A     =			0xe0_00
_A     =			0xe0_01
_A     =			0xe0_02
_A     =			0xe0_03
_A     =			0xe0_04

# Maps special codepoints to human-readable names.
_A     =			{
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
_A     =			{name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}


class  A		(  __UpperCAmelCase     ):
		__snake_case									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



		def __init__(     self,	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=chr(UpperCamelCase__   ),	UpperCamelCase__=False,	UpperCamelCase__=2048,	**UpperCamelCase__,	):







								"""simple docstring"""



								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else bos_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else eos_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else sep_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else cls_token
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								lowerCAmelCase_      			=  AddedToken(UpperCamelCase__,	lstrip=UpperCamelCase__,	rstrip=UpperCamelCase__   ) if isinstance(UpperCamelCase__,	UpperCamelCase__   ) else mask_token

								super().__init__(
								    bos_token=UpperCamelCase__,	eos_token=UpperCamelCase__,	sep_token=UpperCamelCase__,	cls_token=UpperCamelCase__,	pad_token=UpperCamelCase__,	mask_token=UpperCamelCase__,	add_prefix_space=UpperCamelCase__,	model_max_length=UpperCamelCase__,	**UpperCamelCase__,	)

								# Creates a mapping for looking up the IDs of special symbols.
								lowerCAmelCase_      			=  {}
								for codepoint, name in SPECIAL_CODEPOINTS.items():
														lowerCAmelCase_      			=  codepoint

								# Creates a mapping for looking up the string forms of special symbol IDs.
								lowerCAmelCase_      			=  {
								    codepoint: name for name, codepoint in self._special_codepoints.items()
								}

								lowerCAmelCase_      			=  UNICODE_VOCAB_SIZE
								lowerCAmelCase_      			=  len(self._special_codepoints   )



		@property
		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								return self._unicode_vocab_size



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return list(UpperCamelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								try:
														return ord(UpperCamelCase__   )
								except TypeError:
														raise ValueError(f"invalid token: '{token}'"   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								try:
														if index in SPECIAL_CODEPOINTS:
																				return SPECIAL_CODEPOINTS[index]
														return chr(UpperCamelCase__   )
								except TypeError:
														raise ValueError(f"invalid id: {index}"   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return "".join(UpperCamelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [self.cls_token_id]

								lowerCAmelCase_      			=  cls + token_ids_a + sep
								if token_ids_a is not None:
														result += token_ids_a + sep
								return result



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None,	UpperCamelCase__ = False   ):







								"""simple docstring"""



								if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=UpperCamelCase__,	token_ids_a=UpperCamelCase__,	already_has_special_tokens=UpperCamelCase__   )

								lowerCAmelCase_      			=  [1] + ([0] * len(UpperCamelCase__   )) + [1]
								if token_ids_a is not None:
														result += ([0] * len(UpperCamelCase__   )) + [1]
								return result



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [self.cls_token_id]

								lowerCAmelCase_      			=  len(cls + token_ids_a + sep   ) * [0]
								if token_ids_a is not None:
														result += len(token_ids_a + sep   ) * [1]
								return result







		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								return ()




