What will be the behaviour when ProcessPoolExecutor & Multiple Workers started using Gunicorn (FastAPI) are used together?

Question

I have a sample code of FastAPI that utilizes ProcessPoolExecutor during start up:

@asynccontextmanager
async def lifespan(app: FastAPI):
    applog.info(f"{ENGINE_MODULENAME} app is starting executor...")
    process_pool_size = constant.PROCESS_POOL_SIZE if constant.PROCESS_POOL_SIZE > 0 else None
    app.state.executor = ProcessPoolExecutor(process_pool_size)
    applog.info(f"Executor initiated with {app.state.executor._max_workers} workers.")

    preloaded_models = {}
    app.state.model = preloaded_models
    applog.info("Application loaded with serving models.")

    preloaded_data = {}
    app.state.data = preloaded_data
    applog.info("Application loaded with serving data.")

    yield

    del preloaded_models
    del app.state.model
    applog.info("Application removed serving models.")

    del preloaded_data
    del app.state.data
    applog.info("Application removed serving data.")

    applog.info(f"{ENGINE_MODULENAME} app is shutting down executor...")
    app.state.executor.shutdown()
    applog.info("Executor shut down successfully.")


app = FastAPI(title=__name__, lifespan=lifespan)

I will start the application via gunicorn:

gunicorn --bind :8002 --worker-class uvicorn.workers.UvicornWorker --workers 4 --timeout 300 --preload --chdir interface app.main:app

For each gunicorn worker, the same logs will print that Executor initiated with the max number of workers (in this case, ProcessExecutor workers

Would this behaviour overload my application and cause it to crash since all 4 workers are printing the same logs?

What is the correct way of combining ProcessExecutor code with Gunicorn to reach the optimal load management in an environment with multiple CPU cores?

I have tried running the above code but did not put it through load testing yet as the process is very expensive in the current workflow designed.