



def 						a__	(						_UpperCamelCase	:       Union[str, Any]       ,_UpperCamelCase	:       Optional[Any]							):
   print('''\nThe shortest path matrix using Floyd Warshall algorithm\n'''							)
   for i in range(__a							):
      for j in range(__a							):
         if dist[i][j] != float('''inf'''							):
            print(int(dist[i][j]							)       ,end='''\t'''							)
         else:
            print('''INF'''       ,end='''\t'''							)
      print()





def 						a__	(						_UpperCamelCase	:       int       ,_UpperCamelCase	:       Optional[Any]							):
   __lowerCamelCase  							=			[[float('''inf'''							) for _ in range(__a							)] for _ in range(__a							)]

   for i in range(__a							):
      for j in range(__a							):
         __lowerCamelCase  							=			graph[i][j]

         # check vertex k against all other vertices (i, j)
   for k in range(__a							):
      # looping through rows of graph array
      for i in range(__a							):
         # looping through columns of graph array
         for j in range(__a							):
            if (
                dist[i][k] != float('''inf'''							)
                and dist[k][j] != float('''inf'''							)
                and dist[i][k] + dist[k][j] < dist[i][j]
            ):
               __lowerCamelCase  							=			dist[i][k] + dist[k][j]

   _print_dist(__a       ,__a							)
   return dist, v


if __name__ == "__main__":
  a_								=    int(input("""Enter number of vertices: """))
  a_								=    int(input("""Enter number of edges: """))

  a_								=    [[float("""inf""") for i in range(v)] for j in range(v)]

  for i in range(v):
    a_								=    0.0

    # src and dst are indices that must be within the array size graph[e][v]
    # failure to follow this will result in an error
  for i in range(e):
    print("""\nEdge """, i + 1)
    a_								=    int(input("""Enter source:"""))
    a_								=    int(input("""Enter destination:"""))
    a_								=    float(input("""Enter weight:"""))
    a_								=    weight

  floyd_warshall(graph, v)

  # Example Input
  # Enter number of vertices: 3
  # Enter number of edges: 2

  # # generated graph from vertex and edge inputs
  # [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
  # [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

  # specify source, destination and weight for edge #1
  # Edge  1
  # Enter source:1
  # Enter destination:2
  # Enter weight:2

  # specify source, destination and weight for edge #2
  # Edge  2
  # Enter source:2
  # Enter destination:1
  # Enter weight:1

  # # Expected Output from the vertice, edge and src, dst, weight inputs!!
  # 0		INF	INF
  # INF	0	2
  # INF	1	0









import operator as op


a__				=		'''scaler.pt'''
a__				=		'''pytorch_model'''
a__				=		'''random_states'''
a__				=		'''optimizer'''
a__				=		'''scheduler'''
a__				=		'''pytorch_model.bin'''
a__				=		'''pytorch_model.bin.index.json'''
a__				=		'''model.safetensors'''
a__				=		'''model.safetensors.index.json'''
a__				=		'''1.10.2'''
a__				=		'''py38'''
a__				=		'''4.17.0'''
a__				=		['''ml.p3.16xlarge''', '''ml.p3dn.24xlarge''', '''ml.p4dn.24xlarge''']
a__				=		['''FULL_SHARD''', '''SHARD_GRAD_OP''', '''NO_SHARD''', '''HYBRID_SHARD''', '''HYBRID_SHARD_ZERO2''']
a__				=		['''TRANSFORMER_BASED_WRAP''', '''SIZE_BASED_WRAP''', '''NO_WRAP''']
a__				=		['''BACKWARD_PRE''', '''BACKWARD_POST''', '''NO_PREFETCH''']
a__				=		['''FULL_STATE_DICT''', '''LOCAL_STATE_DICT''', '''SHARDED_STATE_DICT''']
a__				=		'''2.0.1'''
a__				=		['''pdsh''', '''standard''', '''openmpi''', '''mvapich''']
a__				=		['''default''', '''reduce-overhead''', '''max-autotune''']

a__				=		{'''>''': op.gt, '''>=''': op.ge, '''==''': op.eq, '''!=''': op.ne, '''<=''': op.le, '''<''': op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
a__				=		[
    '''nnodes''',
    '''nproc_per_node''',
    '''rdzv_backend''',
    '''rdzv_endpoint''',
    '''rdzv_id''',
    '''rdzv_conf''',
    '''standalone''',
    '''max_restarts''',
    '''monitor_interval''',
    '''start_method''',
    '''role''',
    '''module''',
    '''m''',
    '''no_python''',
    '''run_path''',
    '''log_dir''',
    '''r''',
    '''redirects''',
    '''t''',
    '''tee''',
    '''node_rank''',
    '''master_addr''',
    '''master_port''',
]

a__				=		['''DEEPSPEED''', '''MULTI_GPU''', '''FSDP''', '''MEGATRON_LM''']
a__				=		['''DEEPSPEED''', '''MULTI_XPU''', '''FSDP''']



