Name	Size	Mode	Actions
_autograd.pyi	2744	0644	editdlrm
_cudnn.pyi	378	0644	editdlrm
_distributed_autograd.pyi	908	0644	editdlrm
_distributed_c10d.pyi	9376	0644	editdlrm
_distributed_rpc.pyi	5630	0644	editdlrm
_distributed_rpc_testing.pyi	1136	0644	editdlrm
_functions.pyi	345	0644	editdlrm
_nn.pyi	2050	0644	editdlrm
_nvtx.pyi	150	0644	editdlrm
_onnx.pyi	646	0644	editdlrm
_VariableFunctions.pyi	141026	0644	editdlrm
__init__.pyi	103906	0644	editdlrm

from typing import Any, Dict, List, Optional, Tuple, Union, overload from datetime import timedelta import enum import torch from . import Future from ._autograd import ProfilerConfig, ProfilerState, ProfilerEvent from ._distributed_c10d import ProcessGroup, Store # This module is defined in torch/csrc/distributed/rpc/init.cpp _DEFAULT_INIT_METHOD: str _DEFAULT_NUM_WORKER_THREADS: int _UNSET_RPC_TIMEOUT: float _DEFAULT_RPC_TIMEOUT_SEC: float class RpcBackendOptions: rpc_timeout: float init_method: str def __init__( self, rpc_timeout: float = _DEFAULT_RPC_TIMEOUT_SEC, init_method: str = _DEFAULT_INIT_METHOD, ): ... class WorkerInfo: def __init__(self, name: str, worker_id: int): ... @property def name(self) -> str: ... @property def id(self) -> int: ... def __eq__(self, other: object) -> bool: ... def __repr__(self) -> str: ... class RpcAgent: def join(self, shutdown: bool = False): ... def sync(self): ... def shutdown(self): ... @overload def get_worker_info(self) -> WorkerInfo: ... @overload def get_worker_info(self, workerName: str) -> WorkerInfo: ... def get_worker_infos(self) -> List[WorkerInfo]: ... def _get_device_map(self, dst: WorkerInfo) -> Dict[torch.device, torch.device]: ... def get_debug_info(self) -> Dict[str, str]: ... def get_metrics(self) -> Dict[str, str]: ... class PyRRef: def __init__(self, value: Any, type_hint: Any = None): ... def is_owner(self) -> bool: ... def confirmed_by_owner(self) -> bool: ... def owner(self) -> WorkerInfo: ... def owner_name(self) -> str: ... def to_here(self, timeout: float = _UNSET_RPC_TIMEOUT) -> Any: ... def local_value(self) -> Any: ... def rpc_sync(self, timeout: float = _UNSET_RPC_TIMEOUT) -> Any: ... def rpc_async(self, timeout: float = _UNSET_RPC_TIMEOUT) -> Any: ... def remote(self, timeout: float = _UNSET_RPC_TIMEOUT) -> Any: ... def _serialize(self) -> Tuple: ... @staticmethod def _deserialize(tp: Tuple) -> 'PyRRef': ... def _get_type(self) -> Any: ... def _get_future(self) -> Future: ... def _get_profiling_future(self) -> Future: ... def _set_profiling_future(self, profilingFuture: Future): ... def __repr__(self) -> str: ... ... class _TensorPipeRpcBackendOptionsBase(RpcBackendOptions): num_worker_threads: int device_maps: Dict[str, Dict[torch.device, torch.device]] def __init__( self, num_worker_threads: int, _transports: Optional[List], _channels: Optional[List], rpc_timeout: float = _DEFAULT_RPC_TIMEOUT_SEC, init_method: str = _DEFAULT_INIT_METHOD, device_maps: Dict[str, Dict[torch.device, torch.device]] = dict(), devices: List[torch.device] = list()): ... def _set_device_map(self, to: str, device_map: Dict[torch.device, torch.device]): ... class TensorPipeAgent(RpcAgent): def __init__( self, store: Store, name: str, worker_id: int, world_size: int, pg: ProcessGroup, opts: _TensorPipeRpcBackendOptionsBase, reverse_device_maps: Dict[str, Dict[torch.device, torch.device]], devices: List[torch.device], ): ... def join(self): ... def shutdown(self): ... @overload def get_worker_info(self) -> WorkerInfo: ... @overload def get_worker_info(self, workerName: str) -> WorkerInfo: ... @overload def get_worker_info(self, id: int) -> WorkerInfo: ... def get_worker_infos(self) -> List[WorkerInfo]: ... def _get_device_map(self, dst: WorkerInfo) -> Dict[torch.device, torch.device]: ... def _is_current_rpc_agent_set() -> bool: ... def _get_current_rpc_agent()-> RpcAgent: ... def _set_and_start_rpc_agent(agent: RpcAgent): ... def _reset_current_rpc_agent(): ... def _delete_all_user_and_unforked_owner_rrefs(timeout: timedelta = ...): ... def _destroy_rref_context(ignoreRRefLeak: bool): ... def _rref_context_get_debug_info() -> Dict[str, str]: ... def _cleanup_python_rpc_handler(): ... def _invoke_rpc_builtin( dst: WorkerInfo, opName: str, rpcTimeoutSeconds: float, *args: Any, **kwargs: Any ): ... def _invoke_rpc_python_udf( dst: WorkerInfo, pickledPythonUDF: str, tensors: List[torch.Tensor], rpcTimeoutSeconds: float, isAsyncExecution: bool ): ... def _invoke_rpc_torchscript( dstWorkerName: str, qualifiedNameStr: str, argsTuple: Tuple, kwargsDict: Dict, rpcTimeoutSeconds: float, isAsyncExecution: bool, ): ... def _invoke_remote_builtin( dst: WorkerInfo, opName: str, rpcTimeoutSeconds: float, *args: Any, **kwargs: Any ): ... def _invoke_remote_python_udf( dst: WorkerInfo, pickledPythonUDF: str, tensors: List[torch.Tensor], rpcTimeoutSeconds: float, isAsyncExecution: bool, ): ... def _invoke_remote_torchscript( dstWorkerName: WorkerInfo, qualifiedNameStr: str, rpcTimeoutSeconds: float, isAsyncExecution: bool, *args: Any, **kwargs: Any ): ... def get_rpc_timeout() -> float: ... def enable_gil_profiling(flag: bool): ... def _set_rpc_timeout(rpcTimeoutSeconds: float): ... class RemoteProfilerManager: @staticmethod def set_current_profiling_key(key: str): ... def _enable_server_process_global_profiler(new_config: ProfilerConfig): ... def _disable_server_process_global_profiler() -> List[List[List[ProfilerEvent]]]: ... def _set_profiler_node_id(default_node_id: int): ... def _enable_jit_rref_pickle(): ... def _disable_jit_rref_pickle(): ...