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Remove IPEX and clean up checks and add missing synchronize during empty cache. (#13653)

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Simon Lui 2026-05-01 14:16:41 -07:00 committed by GitHub
parent cf758bd256
commit 63103d519e
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GPG Key ID: B5690EEEBB952194
2 changed files with 3 additions and 16 deletions
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1
comfy/cli_args.py
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@ -90,7 +90,6 @@ parser.add_argument("--force-channels-last", action="store_true", help="Force ch
parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE", const=-1, help="Use torch-directml.")
parser.add_argument("--oneapi-device-selector", type=str, default=None, metavar="SELECTOR_STRING", help="Sets the oneAPI device(s) this instance will use.")
parser.add_argument("--disable-ipex-optimize", action="store_true", help="Disables ipex.optimize default when loading models with Intel's Extension for Pytorch.")
parser.add_argument("--supports-fp8-compute", action="store_true", help="ComfyUI will act like if the device supports fp8 compute.")
class LatentPreviewMethod(enum.Enum):

18
comfy/model_management.py
View File

@ -112,10 +112,6 @@ if args.directml is not None:
# torch_directml.disable_tiled_resources(True)
lowvram_available = False #TODO: need to find a way to get free memory in directml before this can be enabled by default.
try:
import intel_extension_for_pytorch as ipex # noqa: F401
except:
pass
try:
_ = torch.xpu.device_count()
@ -583,9 +579,6 @@ class LoadedModel:
real_model = self.model.model
if is_intel_xpu() and not args.disable_ipex_optimize and 'ipex' in globals() and real_model is not None:
with torch.no_grad():
real_model = ipex.optimize(real_model.eval(), inplace=True, graph_mode=True, concat_linear=True)
self.real_model = weakref.ref(real_model)
self.model_finalizer = weakref.finalize(real_model, cleanup_models)
@ -1581,10 +1574,7 @@ def should_use_fp16(device=None, model_params=0, prioritize_performance=True, ma
return False
if is_intel_xpu():
if torch_version_numeric < (2, 3):
return True
else:
return torch.xpu.get_device_properties(device).has_fp16
return torch.xpu.get_device_properties(device).has_fp16
if is_ascend_npu():
return True
@ -1650,10 +1640,7 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
return False
if is_intel_xpu():
if torch_version_numeric < (2, 3):
return True
else:
return torch.xpu.is_bf16_supported()
return torch.xpu.is_bf16_supported()
if is_ascend_npu():
return True
@ -1784,6 +1771,7 @@ def soft_empty_cache(force=False):
if cpu_state == CPUState.MPS:
torch.mps.empty_cache()
elif is_intel_xpu():
torch.xpu.synchronize()
torch.xpu.empty_cache()
elif is_ascend_npu():
torch.npu.empty_cache()