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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"}

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