class ModelPool:
    def __init__(self, max_models=3):
        self.lock = Lock()
        self.model_queue = queue.Queue()
        self.max_models = max_models

        # Initialize the pool with a set number of models
        for _ in range(max_models):
            self.model_queue.put(self._create_model())

    def _create_model(self):
        """ Load and return a new instance of the model. """
        model_id = "SG161222/Realistic_Vision_V2.0"
        scheduler = DPMSolverMultistepScheduler.from_pretrained(model_id, subfolder="scheduler")
        pipeline = DiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16, cache_dir="model_cache")
        pipeline = pipeline.to("cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu")
        return pipeline

    def get_model(self):
        """ Get a model from the pool. """
        with self.lock:
            return self.model_queue.get()

    def return_model(self, model):
        """ Return a model to the pool. """
        with self.lock:
            self.model_queue.put(model)

model_pool = ModelPool(max_models=10)

class ModelPool:
    def __init__(self, max_models=3):
        self.lock = Lock()
        self.model_queue = queue.Queue()
        self.max_models = max_models

        # Initialize the pool with a set number of models
        for _ in range(max_models):
            self.model_queue.put(self._create_model())

    def _create_model(self):
        """ Load and return a new instance of the model. """
        model_id = "SG161222/Realistic_Vision_V2.0"
        scheduler = DPMSolverMultistepScheduler.from_pretrained(model_id, subfolder="scheduler")
        pipeline = DiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16, cache_dir="model_cache")
        pipeline = pipeline.to("cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu")
        return pipeline

    def get_model(self):
        """ Get a model from the pool. """
        with self.lock:
            return self.model_queue.get()

    def return_model(self, model):
        """ Return a model to the pool. """
        with self.lock:
            self.model_queue.put(model)

model_pool = ModelPool(max_models=10)