
'''simple docstring'''

import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


__snake_case:  Union[str, Any]								=			["small", "medium", "large"]

__snake_case:  Optional[Any]								=			"lm_head.decoder.weight"
__snake_case:  str								=			"lm_head.weight"






def 	_snake_case						(      A_       :    str     ,		A_       :    str   ):
  """simple docstring"""







  a_      :	Tuple      =							torch.load(A_   )
  a_      :	Dict      =							d.pop(A_   )
  os.makedirs(A_     ,		exist_ok=A_   )
  torch.save(A_     ,		os.path.join(A_     ,		A_   )   )


if __name__ == "__main__":
    __snake_case:  List[str]								=			argparse.ArgumentParser()
    parser.add_argument("--dialogpt_path", default=".", type=str)
    __snake_case:  int								=			parser.parse_args()
    for MODEL in DIALOGPT_MODELS:
        __snake_case:  List[str]								=			os.path.join(args.dialogpt_path, F"""{MODEL}_ft.pkl""")
        __snake_case:  Union[str, Any]								=			F"""./DialoGPT-{MODEL}"""
        convert_dialogpt_checkpoint(
            checkpoint_path,
            pytorch_dump_folder_path,
        )




'''simple docstring'''

def 	_snake_case						(      A_       :    int     ,		A_       :    Optional[Any]     ,		A_       :    Optional[int]     ,		A_       :    Dict   ):
  """simple docstring"""







  a_      :	Optional[int]      =							[False] * len(A_   )
  a_      :	List[str]      =							[]
  queue.append(A_   )
  a_      :	Union[str, Any]      =							True

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

  return visited[t]






def 	_snake_case						(      A_       :    Union[str, Any]     ,		A_       :    Union[str, Any]     ,		A_       :    List[Any]   ):
  """simple docstring"""







  a_      :	Dict      =							[-1] * (len(A_   ))
  a_      :	List[str]      =							0
  while bfs(A_     ,		A_     ,		A_     ,		A_   ):
    a_      :	Any      =							float("""Inf"""   )
    a_      :	Any      =							sink

    while s != source:
      # Find the minimum value in select path
      a_      :	Any      =							min(A_     ,		graph[parent[s]][s]   )
      a_      :	List[Any]      =							parent[s]

    max_flow += path_flow
    a_      :	Tuple      =							sink

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


__snake_case:  List[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],
]

__snake_case							,__snake_case:  int								=			0, 5




print(ford_fulkerson(graph, source, sink))


