# 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):

"""Single GPU process"""

os.environ["MASTER_ADDR"] = "localhost"

os.environ["MASTER_PORT"] = str(main_port)

os.environ["RANK"] = str(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):

assert cfg.launcher.num_nodes == 1

num_proc = cfg.launcher.gpus_per_node

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=num_proc)

else:

mp_runner = torch.multiprocessing.start_processes

args = (main_port, cfg, num_proc)

# Note: using "fork" below, "spawn" causes time and error regressions. Using

# spawn changes the default multiprocessing context to spawn, which doesn't

# interact well with the dataloaders (likely due to the use of OpenCV).

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) -> None:

cfg = compose(config_name=args.config)

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:

cfg.launcher.num_nodes = 1

main_port = random.randint(

submitit_conf.port_range[0], submitit_conf.port_range[1]

)

single_node_runner(cfg, main_port)

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")

args = parser.parse_args()

args.use_cluster = bool(args.use_cluster) if args.use_cluster is not None else None

register_omegaconf_resolvers()

main(args)