g^(hddlmZmZddlZddlmZddlmZee e ejfZ dgZ de dejfd Zd ee e fdeejejffd Zd ee deejfd ZGddeZy))OptionalUnionN) _TensorPipeRpcBackendOptionsBase) constantsTensorPipeRpcBackendOptionsdevicereturnctj|}|jdk7rtd|jd|S)NcudazA`set_devices` expect a list of CUDA devices, but got device type .)torchr type ValueError)r s [/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/distributed/rpc/options.py _to_devicersE \\& !F {{f !;;-q *   M device_mapc i}i}|jD]T\}}tj|tj|}}||vrtd|d||d||||<|||<V|S)Nz9`device_map` only supports 1-to-1 mapping, trying to map  and  to )itemsrr r)rfull_device_map reverse_mapkvs r_to_device_maprs9;O46K  "1||A Q1 !!"5Q(8QCA  A rdevicesc4ttt|SN)listmapr)rs r_to_device_listr#*s J( ))rceZdZdZej ej ejddddddede de de e e e e e ffde ee d e ed e effd Zd e d e e e fffd Zdee fdZxZS)ra' 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 |in,|jD cic]\}} |t| c} }} |gn t|} t ||||||| | ycc} }wr )rrr#super__init__) selfr%r&r'r(rr)r*rrfull_device_mapsfull_device_list __class__s rr-z$TensorPipeRpcBackendOptions.__init__Psu" 3>3D3D3FG41a!^A&&G  ")2og6N         HsAtorc t|}t|}||vrE|jD]2\}}|||vs||||k7st d|d|d|||t|||y)a0 Set device mapping between each RPC caller and callee pair. This function can be called multiple times to incrementally add device placement configurations. Args: to (str): Callee name. device_map (Dict of int, str, or torch.device): Device placement mappings from this worker to the callee. This map must be invertible. Example: >>> # xdoctest: +SKIP("distributed") >>> # both workers >>> def add(x, y): >>> print(x) # tensor([1., 1.], device='cuda:1') >>> return x + y, (x + y).to(2) >>> >>> # on worker 0 >>> options = TensorPipeRpcBackendOptions( >>> num_worker_threads=8, >>> device_maps={"worker1": {0: 1}} >>> # maps worker0's cuda:0 to worker1's cuda:1 >>> ) >>> options.set_device_map("worker1", {1: 2}) >>> # maps worker0's cuda:1 to worker1's cuda:2 >>> >>> rpc.init_rpc( >>> "worker0", >>> rank=0, >>> world_size=2, >>> backend=rpc.BackendType.TENSORPIPE, >>> rpc_backend_options=options >>> ) >>> >>> x = torch.ones(2) >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) >>> # The first argument will be moved to cuda:1 on worker1. When >>> # sending the return value back, it will follow the invert of >>> # the device map, and hence will be moved back to cuda:0 and >>> # cuda:1 on worker0 >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') z=`set_device_map` only supports 1-to-1 mapping, trying to map rrN)rr,r(rr_set_device_map)r.r2rrcurr_device_mapsrrr1s rset_device_mapz*TensorPipeRpcBackendOptions.set_device_mapksZ)4 7. ! !'--/ 1(,,6Fr6J16M1M$##$#T!E2B22Fq2I1JL  O4rc$t||_y)ab 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)r.rs r set_devicesz'TensorPipeRpcBackendOptions.set_devicess'w/ r)__name__ __module__ __qualname____doc__ rpc_contantsDEFAULT_NUM_WORKER_THREADSDEFAULT_RPC_TIMEOUT_SECDEFAULT_INIT_METHODintfloatstrrdict DeviceTyper!r-r6r8 __classcell__)r1s@rrr.sH#/"I"I)AA';;IM.2&*$(       d3Z-C(D#DEF  $z*+ d^ D> 68585$z:7M2N85t 04 #3 0r)typingrrrtorch._C._distributed_rpcrrr=rArCr rE__all__rrDrr!r#rrrrLs" F'3U\\) * ( )zellZ+, %,, $%"*T*-*$u||2D*A0"BA0r