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| # Ultralytics YOLO π, AGPL-3.0 license | |
| import os | |
| import shutil | |
| import socket | |
| import sys | |
| import tempfile | |
| from . import USER_CONFIG_DIR | |
| from .torch_utils import TORCH_1_9 | |
| def find_free_network_port() -> int: | |
| """ | |
| 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. | |
| """ | |
| with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: | |
| s.bind(("127.0.0.1", 0)) | |
| return s.getsockname()[1] # port | |
| def generate_ddp_file(trainer): | |
| """Generates a DDP file and returns its file name.""" | |
| module, name = f"{trainer.__class__.__module__}.{trainer.__class__.__name__}".rsplit(".", 1) | |
| content = f""" | |
| # Ultralytics Multi-GPU training temp file (should be automatically deleted after use) | |
| overrides = {vars(trainer.args)} | |
| if __name__ == "__main__": | |
| from {module} import {name} | |
| from ultralytics.utils import DEFAULT_CFG_DICT | |
| cfg = DEFAULT_CFG_DICT.copy() | |
| cfg.update(save_dir='') # handle the extra key 'save_dir' | |
| trainer = {name}(cfg=cfg, overrides=overrides) | |
| trainer.args.model = "{getattr(trainer.hub_session, 'model_url', trainer.args.model)}" | |
| results = 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): | |
| """Generates and returns command for distributed training.""" | |
| import __main__ # noqa local import to avoid https://github.com/Lightning-AI/lightning/issues/15218 | |
| if not trainer.resume: | |
| shutil.rmtree(trainer.save_dir) # remove the save_dir | |
| file = generate_ddp_file(trainer) | |
| dist_cmd = "torch.distributed.run" if TORCH_1_9 else "torch.distributed.launch" | |
| port = find_free_network_port() | |
| cmd = [sys.executable, "-m", dist_cmd, "--nproc_per_node", f"{world_size}", "--master_port", f"{port}", file] | |
| return cmd, file | |
| def ddp_cleanup(trainer, file): | |
| """Delete temp file if created.""" | |
| if f"{id(trainer)}.py" in file: # if temp_file suffix in file | |
| os.remove(file) | |