希望可以加入任务ID作为TensorBoard日志的前缀，这样可以通过接口获取到任务对应的loss值

我正在基于秋叶训练器开发一款GUI训练管理工具，但发现可用api比较少，很多功能无法实现。例如获取任务的日志或者训练进度等信息，希望可以完善一下api能力。当前有一个硬性问题是无法获取任务对应的TensorBoard日志，保存的日志未和任务产生关联，因此通过查看源码发现在run_train方法中可以传入日志前缀，这样改动后即可在业务侧调用接口获取任务对应的日志数据，由此我获得到了日志的loss和训练step相关数据

```python
def run_train(toml_path: str,
trainer_file: str = "./scripts/train_network.py",
gpu_ids: Optional[list] = None,
cpu_threads: Optional[int] = 2):
log.info(f"Training started with config file / 训练开始，使用配置文件: {toml_path}")

customize_env = os.environ.copy()
customize_env["ACCELERATE_DISABLE_RICH"] = "1"
customize_env["PYTHONUNBUFFERED"] = "1"
customize_env["PYTHONWARNINGS"] = "ignore::FutureWarning,ignore::UserWarning"
# 创建任务ID
if not (task := tm.create_task([], customize_env)):
return APIResponse(status="error", message="Failed to create task / 无法创建训练任务")

args = [
sys.executable, "-m", "accelerate.commands.launch", # use -m to avoid python script executable error
"--num_cpu_threads_per_process", str(cpu_threads), # cpu threads
"--quiet", # silence accelerate error message
trainer_file,
"--config_file", toml_path,
"--log_prefix", f"{task.task_id}_",
]

if gpu_ids:
customize_env["CUDA_VISIBLE_DEVICES"] = ",".join(gpu_ids)
log.info(f"Using GPU(s) / 使用 GPU: {gpu_ids}")

if len(gpu_ids) > 1:
args[3:3] = ["--multi_gpu", "--num_processes", str(len(gpu_ids))]
if sys.platform == "win32":
customize_env["USE_LIBUV"] = "0"

task.command = args

def _run():
try:
task.execute()
result = task.communicate()
if result.returncode != 0:
log.error(f"Training failed / 训练失败")
else:
log.info(f"Training finished / 训练完成")
except Exception as e:
log.error(f"An error occurred when training / 训练出现致命错误: {e}")

coro = asyncio.to_thread(_run)
asyncio.create_task(coro)

return APIResponse(status="success", message=f"Training started / 训练开始 ID: {task.task_id}")
```