83 lines
3.1 KiB
Python
83 lines
3.1 KiB
Python
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()
|
|
|
|
def cuda_malloc_supported():
|
|
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"}
|
|
|
|
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
|