EiQ.SSKJr SSKrSSKJrJr \\\\R4r S/r S\ S\R4Sjr S \ \ \ 4S\ \R\R44S jrS \\ S\\R4S jr\(aSS KJr O\r"SS\5rg))UnionN)_is_tensorpipe_available constantsTensorPipeRpcBackendOptionsdevicereturnc[R"U5nURS:wa[SURS35eU$)NcudazA`set_devices` expect a list of CUDA devices, but got device type .)torchrtype ValueError)rs Z/home/mande/repo/quber/.venv/lib/python3.13/site-packages/torch/distributed/rpc/options.py _to_devicersE \\& !F {{f !;;-q *   M device_mapc 0n0nUR5HSup4[R"U5[R"U5pCXB;a[SUSX$SU35eXAU'X2U'MU U$)Nz9`device_map` only supports 1-to-1 mapping, trying to map  and  to )itemsr rr)rfull_device_map reverse_mapkvs r_to_device_maprs9;O46K  "||A Q1 !!"5(8QCA A# rdevicesc4[[[U55$N)listmaprrs r_to_device_listr#)s J( ))r) _TensorPipeRpcBackendOptionsBasec^\rSrSrSr\R \R\RSSSSS.S\ S\ S\ S\ \ \ \ \ 44S-S \\ S-S \S-S \S-4U4S jjjrS \ S\ \ \ 44U4SjjrS \\ 4SjrSrU=r$)r4a The backend options for :class:`~torch.distributed.rpc.TensorPipeAgent`, derived from :class:`~torch.distributed.rpc.RpcBackendOptions`. Args: num_worker_threads (int, optional): The number of threads in the thread-pool used by :class:`~torch.distributed.rpc.TensorPipeAgent` to execute requests (default: 16). rpc_timeout (float, optional): The default timeout, in seconds, for RPC requests (default: 60 seconds). If the RPC has not completed in this timeframe, an exception indicating so will be raised. Callers can override this timeout for individual RPCs in :meth:`~torch.distributed.rpc.rpc_sync` and :meth:`~torch.distributed.rpc.rpc_async` if necessary. init_method (str, optional): The URL to initialize the distributed store used for rendezvous. It takes any value accepted for the same argument of :meth:`~torch.distributed.init_process_group` (default: ``env://``). device_maps (Dict[str, Dict], optional): Device placement mappings from this worker to the callee. Key is the callee worker name and value the dictionary (``Dict`` of ``int``, ``str``, or ``torch.device``) that maps this worker's devices to the callee worker's devices. (default: ``None``) devices (List[int, str, or ``torch.device``], optional): all local CUDA devices used by RPC agent. By Default, it will be initialized to all local devices from its own ``device_maps`` and corresponding devices from its peers' ``device_maps``. When processing CUDA RPC requests, the agent will properly synchronize CUDA streams for all devices in this ``List``. N)num_worker_threads rpc_timeout init_method device_mapsr _transports _channelsr'r(r)r*rr+r,c >Uc0O.UR5VV s0sHupU[U 5_M sn nn Uc/O [U5n [T U]UUUUUU U 5 gs sn nfr)rrr#super__init__) selfr'r(r)r*rr+r,rrfull_device_mapsfull_device_list __class__s rr/$TensorPipeRpcBackendOptions.__init__Vsy" 3>3D3D3FG3F41!^A&&3FG  ")2og6N         HsAtorc >[U5n[TU]nX;aGUR5H3upVXTU;dMXdUU:wdM[ SUSUSXAU35e [TU]X5 g)a Set device mapping between each RPC caller and callee pair. This function can be called multiple times to incrementally add device placement configurations. Args: to (str): Callee name. device_map (Dict of int, str, or torch.device): Device placement mappings from this worker to the callee. This map must be invertible. Example: >>> # xdoctest: +SKIP("distributed") >>> # both workers >>> def add(x, y): >>> print(x) # tensor([1., 1.], device='cuda:1') >>> return x + y, (x + y).to(2) >>> >>> # on worker 0 >>> options = TensorPipeRpcBackendOptions( >>> num_worker_threads=8, >>> device_maps={"worker1": {0: 1}} >>> # maps worker0's cuda:0 to worker1's cuda:1 >>> ) >>> options.set_device_map("worker1", {1: 2}) >>> # maps worker0's cuda:1 to worker1's cuda:2 >>> >>> rpc.init_rpc( >>> "worker0", >>> rank=0, >>> world_size=2, >>> backend=rpc.BackendType.TENSORPIPE, >>> rpc_backend_options=options >>> ) >>> >>> x = torch.ones(2) >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) >>> # The first argument will be moved to cuda:1 on worker1. When >>> # sending the return value back, it will follow the invert of >>> # the device map, and hence will be moved back to cuda:0 and >>> # cuda:1 on worker0 >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') z=`set_device_map` only supports 1-to-1 mapping, trying to map rrN)rr.r*rr_set_device_map)r0r5rrcurr_device_mapsrrr3s rset_device_map*TensorPipeRpcBackendOptions.set_device_mapqsZ)4 7. !'--/,,r6J16M1M$##$#T!E2B2Fq2I1JL0 4rc$[U5Ulg)a* Set local devices used by the TensorPipe RPC agent. When processing CUDA RPC requests, the TensorPipe RPC agent will properly synchronize CUDA streams for all devices in this ``List``. Args: devices (List of int, str, or torch.device): local devices used by the TensorPipe RPC agent. N)r#r)r0rs r set_devices'TensorPipeRpcBackendOptions.set_devicess'w/ rr")__name__ __module__ __qualname____firstlineno____doc__ rpc_contantsDEFAULT_NUM_WORKER_THREADSDEFAULT_RPC_TIMEOUT_SECDEFAULT_INIT_METHODintfloatstrdict DeviceTyper r/r9r<__static_attributes__ __classcell__)r3s@rrr4sH#/"I"I)AA';;FJ+/#'!%       #tJ $:;;rTs A3U\\) * ( )zellZ+, %,, $%"*T*-*$u||2D*J'-$A0"BA0r