o ci @sUddlZddlZddlmZddlmZmZmZddlZddl m Z ddl m Z ddl mZmZeeZdaeeeefed<eZdeeeffd d Zd ed ed efddZeGdddeZGdddeZdS)N) dataclass)AnyDictOptional)get_address_and_port) WorkerGroup)Backend BackendConfig_lightgbm_network_paramsreturncCsPttstdiWdStWdS1s!wYdS)zGReturns the network parameters to enable LightGBM distributed training.a`ray.train.lightgbm.get_network_params` was called outside the context of a `ray.train.lightgbm.LightGBMTrainer`. The current process has no knowledge of the distributed training worker group, so this method will return an empty dict. Please call this within the training loop of a `ray.train.lightgbm.LightGBMTrainer`. If you are in fact calling this within a `LightGBMTrainer`, this is unexpected: please file a bug report to the Ray Team.N)_lightgbm_network_params_lockr loggerwarningcopyrrM/home/ubuntu/.local/lib/python3.10/site-packages/ray/train/lightgbm/config.pyget_network_paramss $r num_machineslocal_listen_portmachinescCsHttdus Jdt|||daWddS1swYdS)Nz0LightGBM network params are already initialized.rrr)r r dictrrrr_set_network_params(s "rc@seZdZdZeddZdS)LightGBMConfiga Configuration for LightGBM distributed data-parallel training setup. See the LightGBM docs for more information on the "network parameters" that Ray Train sets up for you: https://lightgbm.readthedocs.io/en/latest/Parameters.html#network-parameters cCstS)N)_LightGBMBackend)selfrrr backend_clsCszLightGBMConfig.backend_clsN)__name__ __module__ __qualname____doc__propertyrrrrrr:src@seZdZdedefddZdS)r worker_groupbackend_configcs^t}dd|Dddd|DttfddttDdS)NcSsg|]\}}|qSrr).0_portrrr Msz6_LightGBMBackend.on_training_start..,cSsg|] \}}|d|qS):r)r$node_ipr&rrrr'Osc s"g|] }|t|qSr)execute_single_asyncr)r$rankrrportsr"rrr'Ss )executerjoinlenraygetrange)rr"r#node_ips_and_portsrr-ron_training_startIs   z"_LightGBMBackend.on_training_startN)rrrrrr6rrrrrHs r)logging threading dataclassesrtypingrrrr2ray.train._internal.utilsr ray.train._internal.worker_grouprray.train.backendrr getLoggerrr r str__annotations__Lockr rintrrrrrrrs,