#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. import sys import uuid from dataclasses import dataclass, field from typing import Any, Callable, Dict, List, Optional, Tuple, Union import torch.distributed.elastic.rendezvous.registry as rdzv_registry from torch.distributed.elastic import events, metrics from torch.distributed.elastic.agent.server.api import WorkerSpec from torch.distributed.elastic.agent.server.local_elastic_agent import LocalElasticAgent from torch.distributed.elastic.multiprocessing import DefaultLogsSpecs, LogsSpecs, SignalException from torch.distributed.elastic.multiprocessing.errors import ChildFailedError from torch.distributed.elastic.rendezvous import RendezvousParameters from torch.distributed.elastic.rendezvous.utils import parse_rendezvous_endpoint from torch.distributed.elastic.utils.logging import get_logger __all__ = ['LaunchConfig', 'elastic_launch', 'launch_agent'] logger = get_logger(__name__) @dataclass class LaunchConfig: """ Creates a rendezvous config. Args: min_nodes: Minimum amount of nodes that the user function will be launched on. Elastic agent ensures that the user function start only when the min_nodes amount enters the rendezvous. max_nodes: Maximum amount of nodes that the user function will be launched on. nproc_per_node: On each node the elastic agent will launch this amount of workers that will execute user defined function. rdzv_backend: rdzv_backend to use in the rendezvous (zeus-adapter, etcd). rdzv_endpoint: The endpoint of the rdzv sync. storage. rdzv_configs: Key, value pair that specifies rendezvous specific configuration. rdzv_timeout: Legacy argument that specifies timeout for the rendezvous. It is going to be removed in future versions, see the note below. The default timeout is 900 seconds. run_id: The unique run id of the job (if not passed a unique one will be deduced from run environment - flow workflow id in flow - or auto generated). role: User defined role of the worker (defaults to "trainer"). max_restarts: The maximum amount of restarts that elastic agent will conduct on workers before failure. monitor_interval: The interval in seconds that is used by the elastic_agent as a period of monitoring workers. start_method: The method is used by the elastic agent to start the workers (spawn, fork, forkserver). metrics_cfg: configuration to initialize metrics. local_addr: address of the local node if any. If not set, a lookup on the local machine's FQDN will be performed. local_ranks_filter: ranks for which to show logs in console. If not set, show from all. ..note: `rdzv_timeout` is a legacy argument that will be removed in future. Set the timeout via `rdzv_configs['timeout']` """ min_nodes: int max_nodes: int nproc_per_node: int logs_specs: Optional[LogsSpecs] = None run_id: str = "" role: str = "default_role" rdzv_endpoint: str = "" rdzv_backend: str = "etcd" rdzv_configs: Dict[str, Any] = field(default_factory=dict) rdzv_timeout: int = -1 max_restarts: int = 3 monitor_interval: float = 30 start_method: str = "spawn" log_line_prefix_template: Optional[str] = None metrics_cfg: Dict[str, str] = field(default_factory=dict) local_addr: Optional[str] = None def __post_init__(self): default_timeout = 900 if self.rdzv_timeout != -1: self.rdzv_configs["timeout"] = self.rdzv_timeout elif "timeout" not in self.rdzv_configs: self.rdzv_configs["timeout"] = default_timeout # Post-processing to enable refactoring to introduce logs_specs due to non-torchrun API usage if self.logs_specs is None: self.logs_specs = DefaultLogsSpecs() class elastic_launch: """ Launches an torchelastic agent on the container that invoked the entrypoint. 1. Pass the ``entrypoint`` arguments as non ``kwargs`` (e.g. no named parameters)/ ``entrypoint`` can be a function or a command. 2. The return value is a map of each worker's output mapped by their respective global rank. Usage :: def worker_fn(foo): # ... def main(): # entrypoint is a function. outputs = elastic_launch(LaunchConfig, worker_fn)(foo) # return rank 0's output return outputs[0] # entrypoint is a command and ``script.py`` is the python module. outputs = elastic_launch(LaunchConfig, "script.py")(args) outputs = elastic_launch(LaunchConfig, "python")("script.py") """ def __init__( self, config: LaunchConfig, entrypoint: Union[Callable, str, None], ): self._config = config self._entrypoint = entrypoint def __call__(self, *args): return launch_agent(self._config, self._entrypoint, list(args)) def _get_entrypoint_name( entrypoint: Union[Callable, str, None], args: List[Any] ) -> str: """Retrieve entrypoint name with the rule: 1. If entrypoint is a function, use ``entrypoint.__qualname__``. 2. If entrypoint is a string, check its value: 2.1 if entrypoint equals to ``sys.executable`` (like "python"), use the first element from ``args`` which does not start with hifen letter (for example, "-u" will be skipped). 2.2 otherwise, use ``entrypoint`` value. 3. Otherwise, return empty string. """ if isinstance(entrypoint, Callable): # type: ignore[arg-type] return entrypoint.__name__ # type: ignore[union-attr] elif isinstance(entrypoint, str): if entrypoint == sys.executable: return next((arg for arg in args if arg[0] != "-"), "") else: return entrypoint else: return "" def _get_addr_and_port( rdzv_parameters: RendezvousParameters, ) -> Tuple[Optional[str], Optional[int]]: if rdzv_parameters.backend != "static": return (None, None) endpoint = rdzv_parameters.endpoint endpoint = endpoint.strip() if not endpoint: raise ValueError( "Endpoint is missing in endpoint. Try to add --master-addr and --master-port" ) master_addr, master_port = parse_rendezvous_endpoint(endpoint, default_port=-1) if master_port == -1: raise ValueError( f"port is missing in endpoint: {endpoint}. Try to specify --master-port" ) return (master_addr, master_port) def launch_agent( config: LaunchConfig, entrypoint: Union[Callable, str, None], args: List[Any], ) -> Dict[int, Any]: if not config.run_id: run_id = str(uuid.uuid4().int) logger.warning("config has no run_id, generated a random run_id: %s", run_id) config.run_id = run_id entrypoint_name = _get_entrypoint_name(entrypoint, args) logger.info( "Starting elastic_operator with launch configs:\n" " entrypoint : %(entrypoint)s\n" " min_nodes : %(min_nodes)s\n" " max_nodes : %(max_nodes)s\n" " nproc_per_node : %(nproc_per_node)s\n" " run_id : %(run_id)s\n" " rdzv_backend : %(rdzv_backend)s\n" " rdzv_endpoint : %(rdzv_endpoint)s\n" " rdzv_configs : %(rdzv_configs)s\n" " max_restarts : %(max_restarts)s\n" " monitor_interval : %(monitor_interval)s\n" " log_dir : %(log_dir)s\n" " metrics_cfg : %(metrics_cfg)s\n", { "entrypoint": entrypoint_name, "min_nodes": config.min_nodes, "max_nodes": config.max_nodes, "nproc_per_node": config.nproc_per_node, "run_id": config.run_id, "rdzv_backend": config.rdzv_backend, "rdzv_endpoint": config.rdzv_endpoint, "rdzv_configs": config.rdzv_configs, "max_restarts": config.max_restarts, "monitor_interval": config.monitor_interval, "log_dir": config.logs_specs.root_log_dir, # type: ignore[union-attr] "metrics_cfg": config.metrics_cfg } ) rdzv_parameters = RendezvousParameters( backend=config.rdzv_backend, endpoint=config.rdzv_endpoint, run_id=config.run_id, min_nodes=config.min_nodes, max_nodes=config.max_nodes, local_addr=config.local_addr, **config.rdzv_configs, ) master_addr, master_port = _get_addr_and_port(rdzv_parameters) spec = WorkerSpec( role=config.role, local_world_size=config.nproc_per_node, entrypoint=entrypoint, args=tuple(args), rdzv_handler=rdzv_registry.get_rendezvous_handler(rdzv_parameters), max_restarts=config.max_restarts, monitor_interval=config.monitor_interval, master_addr=master_addr, master_port=master_port, local_addr=config.local_addr, ) agent = LocalElasticAgent( spec=spec, logs_specs=config.logs_specs, # type: ignore[arg-type] start_method=config.start_method, log_line_prefix_template=config.log_line_prefix_template, ) shutdown_rdzv = True try: metrics.initialize_metrics(metrics.MetricsConfig(config.metrics_cfg)) result = agent.run() # records that agent.run() has succeeded NOT that workers have succeeded events.record(agent.get_event_succeeded()) if result.is_failed(): # ChildFailedError is treated specially by @record # if the error files for the failed children exist # @record will copy the first error (root cause) # to the error file of the launcher process. raise ChildFailedError( name=entrypoint_name, failures=result.failures, ) return result.return_values except ChildFailedError: raise except SignalException: # when the agent dies with a signal do NOT shutdown the rdzv_handler # since this closes the rendezvous on this rdzv_id permanently and # prevents any additional scaling events shutdown_rdzv = False events.record(agent.get_event_failed()) raise except Exception: events.record(agent.get_event_failed()) raise finally: if shutdown_rdzv: spec.rdzv_handler.shutdown()