Spaces:
Sleeping
Sleeping
| import os | |
| import importlib.util | |
| from comfy.cli_args import args | |
| #Can't use pytorch to get the GPU names because the cuda malloc has to be set before the first import. | |
| def get_gpu_names(): | |
| if os.name == 'nt': | |
| import ctypes | |
| # Define necessary C structures and types | |
| class DISPLAY_DEVICEA(ctypes.Structure): | |
| _fields_ = [ | |
| ('cb', ctypes.c_ulong), | |
| ('DeviceName', ctypes.c_char * 32), | |
| ('DeviceString', ctypes.c_char * 128), | |
| ('StateFlags', ctypes.c_ulong), | |
| ('DeviceID', ctypes.c_char * 128), | |
| ('DeviceKey', ctypes.c_char * 128) | |
| ] | |
| # Load user32.dll | |
| user32 = ctypes.windll.user32 | |
| # Call EnumDisplayDevicesA | |
| def enum_display_devices(): | |
| device_info = DISPLAY_DEVICEA() | |
| device_info.cb = ctypes.sizeof(device_info) | |
| device_index = 0 | |
| gpu_names = set() | |
| while user32.EnumDisplayDevicesA(None, device_index, ctypes.byref(device_info), 0): | |
| device_index += 1 | |
| gpu_names.add(device_info.DeviceString.decode('utf-8')) | |
| return gpu_names | |
| return enum_display_devices() | |
| else: | |
| return set() | |
| blacklist = {"GeForce GTX TITAN X", "GeForce GTX 980", "GeForce GTX 970", "GeForce GTX 960", "GeForce GTX 950", "GeForce 945M", | |
| "GeForce 940M", "GeForce 930M", "GeForce 920M", "GeForce 910M", "GeForce GTX 750", "GeForce GTX 745", "Quadro K620", | |
| "Quadro K1200", "Quadro K2200", "Quadro M500", "Quadro M520", "Quadro M600", "Quadro M620", "Quadro M1000", | |
| "Quadro M1200", "Quadro M2000", "Quadro M2200", "Quadro M3000", "Quadro M4000", "Quadro M5000", "Quadro M5500", "Quadro M6000", | |
| "GeForce MX110", "GeForce MX130", "GeForce 830M", "GeForce 840M", "GeForce GTX 850M", "GeForce GTX 860M", | |
| "GeForce GTX 1650", "GeForce GTX 1630" | |
| } | |
| def cuda_malloc_supported(): | |
| try: | |
| names = get_gpu_names() | |
| except: | |
| names = set() | |
| for x in names: | |
| if "NVIDIA" in x: | |
| for b in blacklist: | |
| if b in x: | |
| return False | |
| return True | |
| if not args.cuda_malloc: | |
| try: | |
| version = "" | |
| torch_spec = importlib.util.find_spec("torch") | |
| for folder in torch_spec.submodule_search_locations: | |
| ver_file = os.path.join(folder, "version.py") | |
| if os.path.isfile(ver_file): | |
| spec = importlib.util.spec_from_file_location("torch_version_import", ver_file) | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| version = module.__version__ | |
| if int(version[0]) >= 2: #enable by default for torch version 2.0 and up | |
| args.cuda_malloc = cuda_malloc_supported() | |
| except: | |
| pass | |
| if args.cuda_malloc and not args.disable_cuda_malloc: | |
| env_var = os.environ.get('PYTORCH_CUDA_ALLOC_CONF', None) | |
| if env_var is None: | |
| env_var = "backend:cudaMallocAsync" | |
| else: | |
| env_var += ",backend:cudaMallocAsync" | |
| os.environ['PYTORCH_CUDA_ALLOC_CONF'] = env_var | |