import torch class AnyType(str): """A special class that is always equal in not equal comparisons. Credit to pythongosssss""" def __ne__(self, __value: object) -> bool: return False anyType = AnyType("*") class CUDNNToggleAutoPassthrough: @classmethod def INPUT_TYPES(cls): return { "optional": { "model": ("MODEL",), "conditioning": ("CONDITIONING",), "latent": ("LATENT",), "audio": ("AUDIO",), "image": ("IMAGE",), "wan_model": ("WANVIDEOMODEL",), "any_input": (anyType, {}), }, "required": { "enable_cudnn": ("BOOLEAN", {"default": True}), "cudnn_benchmark": ("BOOLEAN", {"default": False}), }, } RETURN_TYPES = ("MODEL", "CONDITIONING", "LATENT", "AUDIO", "IMAGE", "WANVIDEOMODEL", anyType, "BOOLEAN", "BOOLEAN") RETURN_NAMES = ("model", "conditioning", "latent", "audio", "image", "wan_model", "any_output", "prev_cudnn", "prev_benchmark") FUNCTION = "toggle" CATEGORY = "CFZ/utils" def toggle(self, enable_cudnn, cudnn_benchmark, any_input=None, wan_model=None, model=None, conditioning=None, latent=None, audio=None, image=None): prev_cudnn = torch.backends.cudnn.enabled prev_benchmark = torch.backends.cudnn.benchmark torch.backends.cudnn.enabled = enable_cudnn torch.backends.cudnn.benchmark = cudnn_benchmark if enable_cudnn != prev_cudnn: print(f"[CUDNN_TOGGLE] torch.backends.cudnn.enabled set to {enable_cudnn} (was {prev_cudnn})") else: print(f"[CUDNN_TOGGLE] torch.backends.cudnn.enabled still set to {enable_cudnn}") if cudnn_benchmark != prev_benchmark: print(f"[CUDNN_TOGGLE] torch.backends.cudnn.benchmark set to {cudnn_benchmark} (was {prev_benchmark})") else: print(f"[CUDNN_TOGGLE] torch.backends.cudnn.benchmark still set to {cudnn_benchmark}") return_tuple = (model, conditioning, latent, audio, image, wan_model, any_input, prev_cudnn, prev_benchmark) return return_tuple NODE_CLASS_MAPPINGS = { "CUDNNToggleAutoPassthrough": CUDNNToggleAutoPassthrough } NODE_DISPLAY_NAME_MAPPINGS = { "CUDNNToggleAutoPassthrough": "CFZ CUDNN Toggle" }