# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # This source code is licensed under the license found in the # LICENSE file in the root directory of this source tree. import logging import os import random import sys import traceback from argparse import ArgumentParser import submitit import torch from hydra import compose, initialize_config_module from hydra.utils import instantiate from iopath.common.file_io import g_pathmgr from omegaconf import OmegaConf from training.utils.train_utils import makedir, register_omegaconf_resolvers os.environ["HYDRA_FULL_ERROR"] = "1" def single_proc_run(local_rank, main_port, cfg, world_size, node_rank, master_addr): """Single GPU process""" os.environ["MASTER_ADDR"] = master_addr os.environ["MASTER_PORT"] = str(main_port) os.environ["RANK"] = str(node_rank * cfg.launcher.gpus_per_node + local_rank) os.environ["LOCAL_RANK"] = str(local_rank) os.environ["WORLD_SIZE"] = str(world_size) try: register_omegaconf_resolvers() except Exception as e: logging.info(e) trainer = instantiate(cfg.trainer, _recursive_=False) trainer.run() def single_node_runner(cfg, main_port: int, node_rank: int = 0, master_addr: str = "localhost"): num_proc = cfg.launcher.gpus_per_node world_size = cfg.launcher.gpus_per_node * cfg.launcher.num_nodes torch.multiprocessing.set_start_method( "spawn" ) # CUDA runtime does not support `fork` if num_proc == 1: # directly call single_proc so we can easily set breakpoints # mp.spawn does not let us set breakpoints single_proc_run(local_rank=0, main_port=main_port, cfg=cfg, world_size=world_size, node_rank=node_rank, master_addr=master_addr) else: mp_runner = torch.multiprocessing.start_processes args = (main_port, cfg, world_size, node_rank, master_addr) mp_runner(single_proc_run, args=args, nprocs=num_proc, start_method="spawn") def format_exception(e: Exception, limit=20): traceback_str = "".join(traceback.format_tb(e.__traceback__, limit=limit)) return f"{type(e).__name__}: {e}\nTraceback:\n{traceback_str}" class SubmititRunner(submitit.helpers.Checkpointable): """A callable which is passed to submitit to launch the jobs.""" def __init__(self, port, cfg): self.cfg = cfg self.port = port self.has_setup = False def run_trainer(self): job_env = submitit.JobEnvironment() # Need to add this again so the hydra.job.set_env PYTHONPATH # is also set when launching jobs. add_pythonpath_to_sys_path() os.environ["MASTER_ADDR"] = job_env.hostnames[0] os.environ["MASTER_PORT"] = str(self.port) os.environ["RANK"] = str(job_env.global_rank) os.environ["LOCAL_RANK"] = str(job_env.local_rank) os.environ["WORLD_SIZE"] = str(job_env.num_tasks) register_omegaconf_resolvers() cfg_resolved = OmegaConf.to_container(self.cfg, resolve=False) cfg_resolved = OmegaConf.create(cfg_resolved) trainer = instantiate(cfg_resolved.trainer, _recursive_=False) trainer.run() def __call__(self): job_env = submitit.JobEnvironment() self.setup_job_info(job_env.job_id, job_env.global_rank) try: self.run_trainer() except Exception as e: # Log the exception. Then raise it again (as what SubmititRunner currently does). message = format_exception(e) logging.error(message) raise e def setup_job_info(self, job_id, rank): """Set up slurm job info""" self.job_info = { "job_id": job_id, "rank": rank, "cluster": self.cfg.get("cluster", None), "experiment_log_dir": self.cfg.launcher.experiment_log_dir, } self.has_setup = True def add_pythonpath_to_sys_path(): if "PYTHONPATH" not in os.environ or not os.environ["PYTHONPATH"]: return sys.path = os.environ["PYTHONPATH"].split(":") + sys.path def main(args, cfg) -> None: if cfg.launcher.experiment_log_dir is None: cfg.launcher.experiment_log_dir = os.path.join( os.getcwd(), "sam2_logs", args.config ) print("###################### Train App Config ####################") print(OmegaConf.to_yaml(cfg)) print("############################################################") add_pythonpath_to_sys_path() makedir(cfg.launcher.experiment_log_dir) with g_pathmgr.open( os.path.join(cfg.launcher.experiment_log_dir, "config.yaml"), "w" ) as f: f.write(OmegaConf.to_yaml(cfg)) cfg_resolved = OmegaConf.to_container(cfg, resolve=False) cfg_resolved = OmegaConf.create(cfg_resolved) with g_pathmgr.open( os.path.join(cfg.launcher.experiment_log_dir, "config_resolved.yaml"), "w" ) as f: f.write(OmegaConf.to_yaml(cfg_resolved, resolve=True)) submitit_conf = cfg.get("submitit", None) assert submitit_conf is not None, "Missing submitit config" submitit_dir = cfg.launcher.experiment_log_dir submitit_dir = os.path.join(submitit_dir, "submitit_logs") # Priotrize cmd line args cfg.launcher.gpus_per_node = ( args.num_gpus if args.num_gpus is not None else cfg.launcher.gpus_per_node ) cfg.launcher.num_nodes = ( args.num_nodes if args.num_nodes is not None else cfg.launcher.num_nodes ) submitit_conf.use_cluster = ( args.use_cluster if args.use_cluster is not None else submitit_conf.use_cluster ) if submitit_conf.use_cluster: executor = submitit.AutoExecutor(folder=submitit_dir) submitit_conf.partition = ( args.partition if args.partition is not None else submitit_conf.get("partition", None) ) submitit_conf.account = ( args.account if args.account is not None else submitit_conf.get("account", None) ) submitit_conf.qos = ( args.qos if args.qos is not None else submitit_conf.get("qos", None) ) job_kwargs = { "timeout_min": 60 * submitit_conf.timeout_hour, "name": ( submitit_conf.name if hasattr(submitit_conf, "name") else args.config ), "slurm_partition": submitit_conf.partition, "gpus_per_node": cfg.launcher.gpus_per_node, "tasks_per_node": cfg.launcher.gpus_per_node, # one task per GPU "cpus_per_task": submitit_conf.cpus_per_task, "nodes": cfg.launcher.num_nodes, "slurm_additional_parameters": { "exclude": " ".join(submitit_conf.get("exclude_nodes", [])), }, } if "include_nodes" in submitit_conf: assert ( len(submitit_conf["include_nodes"]) >= cfg.launcher.num_nodes ), "Not enough nodes" job_kwargs["slurm_additional_parameters"]["nodelist"] = " ".join( submitit_conf["include_nodes"] ) if submitit_conf.account is not None: job_kwargs["slurm_additional_parameters"]["account"] = submitit_conf.account if submitit_conf.qos is not None: job_kwargs["slurm_additional_parameters"]["qos"] = submitit_conf.qos if submitit_conf.get("mem_gb", None) is not None: job_kwargs["mem_gb"] = submitit_conf.mem_gb elif submitit_conf.get("mem", None) is not None: job_kwargs["slurm_mem"] = submitit_conf.mem if submitit_conf.get("constraints", None) is not None: job_kwargs["slurm_constraint"] = submitit_conf.constraints if submitit_conf.get("comment", None) is not None: job_kwargs["slurm_comment"] = submitit_conf.comment # Supports only cpu-bind option within srun_args. New options can be added here if submitit_conf.get("srun_args", None) is not None: job_kwargs["slurm_srun_args"] = [] if submitit_conf.srun_args.get("cpu_bind", None) is not None: job_kwargs["slurm_srun_args"].extend( ["--cpu-bind", submitit_conf.srun_args.cpu_bind] ) print("###################### SLURM Config ####################") print(job_kwargs) print("##########################################") executor.update_parameters(**job_kwargs) main_port = random.randint( submitit_conf.port_range[0], submitit_conf.port_range[1] ) runner = SubmititRunner(main_port, cfg) job = executor.submit(runner) print(f"Submitit Job ID: {job.job_id}") runner.setup_job_info(job.job_id, rank=0) else: # Handle the master_addr separately master_addr = args.master_addr if args.master_addr else "localhost" main_port = args.main_port if args.main_port else random.randint( submitit_conf.port_range[0], submitit_conf.port_range[1] ) if 'SLURM_PROCID' in os.environ: node_rank = int(os.environ['SLURM_PROCID']) else: node_rank = 0 single_node_runner(cfg, main_port, node_rank=node_rank, master_addr=master_addr) if __name__ == "__main__": initialize_config_module("sam2", version_base="1.2") parser = ArgumentParser() parser.add_argument( "-c", "--config", required=True, type=str, help="path to config file (e.g. configs/sam2.1_training/sam2.1_hiera_b+_MOSE_finetune.yaml)", ) parser.add_argument( "--use-cluster", type=int, default=None, help="whether to launch on a cluster, 0: run locally, 1: run on a cluster", ) parser.add_argument("--partition", type=str, default=None, help="SLURM partition") parser.add_argument("--account", type=str, default=None, help="SLURM account") parser.add_argument("--qos", type=str, default=None, help="SLURM qos") parser.add_argument( "--num-gpus", type=int, default=None, help="number of GPUS per node" ) parser.add_argument("--num-nodes", type=int, default=None, help="Number of nodes") parser.add_argument("--master-addr", type=str, default=None, help="Master node address") parser.add_argument("--main-port", type=int, default=None, help="Main port for communication") parser.add_argument("--dataset-path", type=str, default=None, help="Path to the dataset, overrides cfg.dataset.folder") parser.add_argument("--output-path", type=str, default=None, help="Path to the experiment output, overrides cfg.launcher.experiment_log_dir") args = parser.parse_args() args.use_cluster = bool(args.use_cluster) if args.use_cluster is not None else None register_omegaconf_resolvers() # Override dataset folder and experiment output path if specified cfg = compose(config_name=args.config) if args.dataset_path is not None: cfg.dataset.folder = args.dataset_path if args.output_path is not None: cfg.launcher.experiment_log_dir = args.output_path main(args, cfg)