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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved | |
""" | |
A script to run multinode training with submitit. | |
""" | |
import argparse | |
import os | |
import uuid | |
from pathlib import Path | |
import main as detection | |
import submitit | |
def parse_args(): | |
detection_parser = detection.get_args_parser() | |
parser = argparse.ArgumentParser("Submitit for detection", parents=[detection_parser]) | |
parser.add_argument("--ngpus", default=8, type=int, help="Number of gpus to request on each node") | |
parser.add_argument("--nodes", default=4, type=int, help="Number of nodes to request") | |
parser.add_argument("--timeout", default=60, type=int, help="Duration of the job") | |
parser.add_argument("--job_dir", default="", type=str, help="Job dir. Leave empty for automatic.") | |
return parser.parse_args() | |
def get_shared_folder() -> Path: | |
user = os.getenv("USER") | |
if Path("/checkpoint/").is_dir(): | |
p = Path(f"/checkpoint/{user}/experiments") | |
p.mkdir(exist_ok=True) | |
return p | |
raise RuntimeError("No shared folder available") | |
def get_init_file(): | |
# Init file must not exist, but it's parent dir must exist. | |
os.makedirs(str(get_shared_folder()), exist_ok=True) | |
init_file = get_shared_folder() / f"{uuid.uuid4().hex}_init" | |
if init_file.exists(): | |
os.remove(str(init_file)) | |
return init_file | |
class Trainer(object): | |
def __init__(self, args): | |
self.args = args | |
def __call__(self): | |
import main as detection | |
self._setup_gpu_args() | |
detection.main(self.args) | |
def checkpoint(self): | |
import os | |
import submitit | |
from pathlib import Path | |
self.args.dist_url = get_init_file().as_uri() | |
checkpoint_file = os.path.join(self.args.output_dir, "checkpoint.pth") | |
if os.path.exists(checkpoint_file): | |
self.args.resume = checkpoint_file | |
print("Requeuing ", self.args) | |
empty_trainer = type(self)(self.args) | |
return submitit.helpers.DelayedSubmission(empty_trainer) | |
def _setup_gpu_args(self): | |
import submitit | |
from pathlib import Path | |
job_env = submitit.JobEnvironment() | |
self.args.output_dir = Path(str(self.args.output_dir).replace("%j", str(job_env.job_id))) | |
self.args.gpu = job_env.local_rank | |
self.args.rank = job_env.global_rank | |
self.args.world_size = job_env.num_tasks | |
print(f"Process group: {job_env.num_tasks} tasks, rank: {job_env.global_rank}") | |
def main(): | |
args = parse_args() | |
if args.job_dir == "": | |
args.job_dir = get_shared_folder() / "%j" | |
# Note that the folder will depend on the job_id, to easily track experiments | |
executor = submitit.AutoExecutor(folder=args.job_dir, slurm_max_num_timeout=30) | |
# cluster setup is defined by environment variables | |
num_gpus_per_node = args.ngpus | |
nodes = args.nodes | |
timeout_min = args.timeout | |
executor.update_parameters( | |
mem_gb=40 * num_gpus_per_node, | |
gpus_per_node=num_gpus_per_node, | |
tasks_per_node=num_gpus_per_node, # one task per GPU | |
cpus_per_task=10, | |
nodes=nodes, | |
timeout_min=timeout_min, # max is 60 * 72 | |
) | |
executor.update_parameters(name="detr") | |
args.dist_url = get_init_file().as_uri() | |
args.output_dir = args.job_dir | |
trainer = Trainer(args) | |
job = executor.submit(trainer) | |
print("Submitted job_id:", job.job_id) | |
if __name__ == "__main__": | |
main() | |