Files
2025-04-05 17:35:45 -07:00

58 lines
1.7 KiB
Python

# SPDX-License-Identifier: Apache-2.0
import os
import subprocess
import sys
from fastvideo.v1.logger import init_logger
logger = init_logger(__name__)
def launch_distributed(num_gpus=None, args=None, master_port=None):
"""
Launch a distributed job with the given arguments
Args:
num_gpus: Number of GPUs to use
args: Arguments to pass to v1_fastvideo_inference.py (defaults to sys.argv[1:])
master_port: Port for the master process (default: random)
"""
current_env = os.environ.copy()
python_executable = sys.executable
project_root = os.path.abspath(
os.path.join(os.path.dirname(__file__), "../../../.."))
main_script = os.path.join(project_root,
"fastvideo/v1/sample/v1_fastvideo_inference.py")
cmd = [
python_executable, "-m", "torch.distributed.run",
f"--nproc_per_node={num_gpus}"
]
if master_port is not None:
cmd.append(f"--master_port={master_port}")
cmd.append(main_script)
cmd.extend(args)
logger.info("Running inference with %d GPU(s)", num_gpus)
logger.info("Launching command: %s", " ".join(cmd))
current_env["PYTHONIOENCODING"] = "utf-8"
process = subprocess.Popen(cmd,
env=current_env,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
universal_newlines=True,
bufsize=1,
encoding='utf-8',
errors='replace')
if process.stdout:
for line in iter(process.stdout.readline, ''):
print(line.strip())
return process.wait()