# Ultralytics YOLO 🚀, GPL-3.0 license import os import shutil import socket import sys import tempfile from . import USER_CONFIG_DIR def find_free_network_port() -> int: # https://github.com/Lightning-AI/lightning/blob/master/src/lightning_lite/plugins/environments/lightning.py """Finds a free port on localhost. It is useful in single-node training when we don't want to connect to a real main node but have to set the `MASTER_PORT` environment variable. """ s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind(("", 0)) port = s.getsockname()[1] s.close() return port def generate_ddp_file(trainer): import_path = '.'.join(str(trainer.__class__).split(".")[1:-1]) if not trainer.resume: shutil.rmtree(trainer.save_dir) # remove the save_dir content = f'''config = {dict(trainer.args)} \nif __name__ == "__main__": from ultralytics.{import_path} import {trainer.__class__.__name__} trainer = {trainer.__class__.__name__}(config=config) trainer.train()''' (USER_CONFIG_DIR / 'DDP').mkdir(exist_ok=True) with tempfile.NamedTemporaryFile(prefix="_temp_", suffix=f"{id(trainer)}.py", mode="w+", encoding='utf-8', dir=USER_CONFIG_DIR / 'DDP', delete=False) as file: file.write(content) return file.name def generate_ddp_command(world_size, trainer): import __main__ # noqa local import to avoid https://github.com/Lightning-AI/lightning/issues/15218 file_name = os.path.abspath(sys.argv[0]) using_cli = not file_name.endswith(".py") if using_cli: file_name = generate_ddp_file(trainer) return [ sys.executable, "-m", "torch.distributed.run", "--nproc_per_node", f"{world_size}", "--master_port", f"{find_free_network_port()}", file_name] + sys.argv[1:] def ddp_cleanup(command, trainer): # delete temp file if created tempfile_suffix = f"{id(trainer)}.py" if tempfile_suffix in "".join(command): for chunk in command: if tempfile_suffix in chunk: os.remove(chunk) break