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