'''simple docstring'''

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


UpperCAmelCase__						:Tuple          =			logging.get_logger(__name__)

UpperCAmelCase__						:Any          =			{}







class 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):
       snake_case__    :     Union[str, Any]   		=			'llama'
       snake_case__    :     Tuple   		=			['past_key_values']




       def __init__(					self      : Dict	,    A__      : int=32000	,    A__      : Optional[int]=4096	,    A__      : List[str]=11008	,    A__      : str=32	,    A__      : str=32	,    A__      : List[str]=None	,    A__      : Optional[int]="silu"	,    A__      : int=2048	,    A__      : List[str]=0.02	,    A__      : List[Any]=1e-6	,    A__      : List[Any]=True	,    A__      : List[str]=0	,    A__      : str=1	,    A__      : List[Any]=2	,    A__      : Optional[Any]=1	,    A__      : Union[str, Any]=False	,    A__      : Tuple=None	,    **A__      : List[Any]	,    ):


            """simple docstring"""







            __lowerCamelCase						:       int				   =				vocab_size
            __lowerCamelCase						:       Dict				   =				max_position_embeddings
            __lowerCamelCase						:       List[str]				   =				hidden_size
            __lowerCamelCase						:       str				   =				intermediate_size
            __lowerCamelCase						:       Any				   =				num_hidden_layers
            __lowerCamelCase						:       List[Any]				   =				num_attention_heads

            # for backward compatibility
            if num_key_value_heads is None:
                 __lowerCamelCase						:       Tuple				   =				num_attention_heads

            __lowerCamelCase						:       int				   =				num_key_value_heads
            __lowerCamelCase						:       Union[str, Any]				   =				hidden_act
            __lowerCamelCase						:       str				   =				initializer_range
            __lowerCamelCase						:       List[str]				   =				rms_norm_eps
            __lowerCamelCase						:       Dict				   =				pretraining_tp
            __lowerCamelCase						:       List[Any]				   =				use_cache
            __lowerCamelCase						:       int				   =				rope_scaling
            self._rope_scaling_validation()

            super().__init__(
                pad_token_id=A__	,    bos_token_id=A__	,    eos_token_id=A__	,    tie_word_embeddings=A__	,    **A__	,    )




       def 					a_					(					self      : int					):


            """simple docstring"""







            if self.rope_scaling is None:
                 return

            if not isinstance(self.rope_scaling	,    A__					) or len(self.rope_scaling					) != 2:
                 raise ValueError(
                     """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
                     f"got {self.rope_scaling}"					)
            __lowerCamelCase						:       Union[str, Any]				   =				self.rope_scaling.get("""type"""	,    A__					)
            __lowerCamelCase						:       Union[str, Any]				   =				self.rope_scaling.get("""factor"""	,    A__					)
            if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
                 raise ValueError(
                     f"`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"					)
            if rope_scaling_factor is None or not isinstance(A__	,    A__					) or rope_scaling_factor <= 1.0:
                 raise ValueError(f"`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"					)











'''simple docstring'''

def     __lowercase  (_lowercase,						_lowercase,						_lowercase,						_lowercase     )   ->     Union[str, Any]:


     """simple docstring"""
     # Return True if there is node that has not iterated.
     __lowerCamelCase						:       Optional[Any]				   =				[False] * len(_lowercase     )
     __lowerCamelCase						:       Dict				   =				[]
     queue.append(_lowercase     )
     __lowerCamelCase						:       Optional[int]				   =				True

     while queue:
          __lowerCamelCase						:       Optional[Any]				   =				queue.pop(0     )
          for ind in range(len(graph[u]     )     ):
               if visited[ind] is False and graph[u][ind] > 0:
                    queue.append(_lowercase     )
                    __lowerCamelCase						:       List[str]				   =				True
                    __lowerCamelCase						:       str				   =				u

     return visited[t]
def     __lowercase  (_lowercase,						_lowercase,						_lowercase     )   ->     Optional[Any]:


     """simple docstring"""
     # This array is filled by BFS and to store path
     __lowerCamelCase						:       Any				   =				[-1] * (len(_lowercase     ))
     __lowerCamelCase						:       Optional[int]				   =				0
     while bfs(_lowercase,						_lowercase,						_lowercase,						_lowercase     ):
          __lowerCamelCase						:       List[Any]				   =				float("""Inf"""     )
          __lowerCamelCase						:       Union[str, Any]				   =				sink

          while s != source:
               # Find the minimum value in select path
               __lowerCamelCase						:       Optional[int]				   =				min(_lowercase,						graph[parent[s]][s]     )
               __lowerCamelCase						:       Union[str, Any]				   =				parent[s]

          max_flow += path_flow
          __lowerCamelCase						:       str				   =				sink

          while v != source:
               __lowerCamelCase						:       List[Any]				   =				parent[v]
               graph[u][v] -= path_flow
               graph[v][u] += path_flow
               __lowerCamelCase						:       Dict				   =				parent[v]
     return max_flow


UpperCAmelCase__						:str          =			[
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

UpperCAmelCase__       ,				UpperCAmelCase__						:Optional[Any]          =			0, 5
print(ford_fulkerson(graph, source, sink))



