| |
| import importlib.util |
| import json |
| import os |
| import subprocess |
| import sys |
| import yaml |
| from typing import Dict, List, Optional |
|
|
| from swift.utils import get_logger |
|
|
| logger = get_logger() |
|
|
| ROUTE_MAPPING: Dict[str, str] = { |
| 'pt': 'swift.cli.pt', |
| 'sft': 'swift.cli.sft', |
| 'infer': 'swift.cli.infer', |
| 'merge-lora': 'swift.cli.merge_lora', |
| 'web-ui': 'swift.cli.web_ui', |
| 'deploy': 'swift.cli.deploy', |
| 'rollout': 'swift.cli.rollout', |
| 'rlhf': 'swift.cli.rlhf', |
| 'sample': 'swift.cli.sample', |
| 'export': 'swift.cli.export', |
| 'eval': 'swift.cli.eval', |
| 'app': 'swift.cli.app', |
| } |
|
|
|
|
| def use_torchrun() -> bool: |
| nproc_per_node = os.getenv('NPROC_PER_NODE') |
| nnodes = os.getenv('NNODES') |
| if nproc_per_node is None and nnodes is None: |
| return False |
| return True |
|
|
|
|
| def parse_yaml_args(argv): |
| if not argv: |
| return |
| config = None |
| if argv[0].endswith('.json'): |
| with open(argv[0], 'r') as f: |
| config = json.load(f) |
| elif argv[0].endswith('.yaml') or argv[0].endswith('.yml'): |
| with open(argv[0], 'r') as f: |
| config = yaml.safe_load(f) |
| if config is None: |
| return |
| |
| os.environ['SWIFT_CONFIG_FILE'] = argv[0] |
|
|
| env = config.pop('ENV', None) |
| if env: |
| for k, v in env.items(): |
| os.environ[k] = str(v) |
| config_argv = [] |
| for k, v in config.items(): |
| config_argv.append(f'--{k}') |
| if isinstance(v, list): |
| config_argv += v |
| else: |
| if isinstance(v, dict): |
| v = json.dumps(v, ensure_ascii=False) |
| else: |
| v = str(v) |
| config_argv.append(v) |
| argv[0:1] = config_argv |
|
|
|
|
| def get_torchrun_args() -> Optional[List[str]]: |
| if not use_torchrun(): |
| return |
| torchrun_args = [] |
| for env_key in ['NPROC_PER_NODE', 'MASTER_PORT', 'NNODES', 'NODE_RANK', 'MASTER_ADDR']: |
| env_val = os.getenv(env_key) |
| if env_val is None: |
| continue |
| torchrun_args += [f'--{env_key.lower()}', env_val] |
| return torchrun_args |
|
|
|
|
| def cli_main(route_mapping: Optional[Dict[str, str]] = None, is_megatron: bool = False) -> None: |
| route_mapping = route_mapping or ROUTE_MAPPING |
| argv = sys.argv[1:] |
| method_name = argv[0].replace('_', '-') |
| argv = argv[1:] |
| file_path = importlib.util.find_spec(route_mapping[method_name]).origin |
| torchrun_args = get_torchrun_args() |
| parse_yaml_args(argv) |
| python_cmd = sys.executable |
| if torchrun_args is None or (not is_megatron and method_name not in {'pt', 'sft', 'rlhf', 'infer'}): |
| args = [python_cmd, file_path, *argv] |
| else: |
| args = [python_cmd, '-m', 'torch.distributed.run', *torchrun_args, file_path, *argv] |
| print(f"run sh: `{' '.join(args)}`", flush=True) |
| result = subprocess.run(args) |
| if result.returncode != 0: |
| sys.exit(result.returncode) |
|
|
|
|
| if __name__ == '__main__': |
| cli_main() |
|
|
