diff --git a/README.md b/README.md index 7c3c49add..f92c753b6 100644 --- a/README.md +++ b/README.md @@ -229,7 +229,7 @@ check [ChangeLog](CHANGELOG.md) for when feature was first introduced as it will ### **Sponsors**
-Allan GrantBrent OzarMatthew RunoHELLO WORLD SASSalad Technologiesa.v.mantzaris +Allan GrantBrent OzarMatthew RunoHELLO WORLD SASSalad Technologiesa.v.mantzarisToby Worth

diff --git a/modules/intel/ipex/hijacks.py b/modules/intel/ipex/hijacks.py index 4573b7f7f..425882e22 100644 --- a/modules/intel/ipex/hijacks.py +++ b/modules/intel/ipex/hijacks.py @@ -155,7 +155,7 @@ def ipex_hijacks(): lambda orig_func, *args, device=None, **kwargs: check_device(device)) CondFunc('torch.load', lambda orig_func, f, map_location=None, pickle_module=None, *, weights_only=False, mmap=None, **kwargs: - orig_func(orig_func, f, map_location=return_xpu(map_location), pickle_module=pickle_module, weights_only=weights_only, mmap=mmap, **kwargs), + orig_func(f, map_location=return_xpu(map_location), pickle_module=pickle_module, weights_only=weights_only, mmap=mmap, **kwargs), lambda orig_func, f, map_location=None, pickle_module=None, *, weights_only=False, mmap=None, **kwargs: check_device(map_location)) if hasattr(torch.xpu, "Generator"): CondFunc('torch.Generator', @@ -221,7 +221,8 @@ def ipex_hijacks(): torch.UntypedStorage.is_cuda = is_cuda torch.nn.functional.interpolate = interpolate - torch.linalg.solve = linalg_solve + if hasattr(torch.xpu, "Generator"): + torch.linalg.solve = linalg_solve torch.bmm = torch_bmm torch.cat = torch_cat diff --git a/modules/sd_models_compile.py b/modules/sd_models_compile.py index 4840e4c49..a909a3763 100644 --- a/modules/sd_models_compile.py +++ b/modules/sd_models_compile.py @@ -156,7 +156,7 @@ def compile_torch(sd_model): def compile_diffusers(sd_model): if shared.opts.ipex_optimize: sd_model = ipex_optimize(sd_model) - if shared.opts.nncf_compress_weights: + if shared.opts.nncf_compress_weights and not (shared.opts.cuda_compile and shared.opts.cuda_compile_backend == "openvino_fx"): sd_model = nncf_compress_weights(sd_model) if not (shared.opts.cuda_compile or shared.opts.cuda_compile_vae or shared.opts.cuda_compile_upscaler): return sd_model