diff --git a/installer.py b/installer.py index 3093ff51e..47a94a63f 100644 --- a/installer.py +++ b/installer.py @@ -337,7 +337,8 @@ def check_torch(): if args.use_ipex and allow_ipex: import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import log.info(f'Torch backend: Intel IPEX {ipex.__version__}') - log.info(f'{os.popen("icpx --version").read().rstrip()}') + if shutil.which('icpx') is not None: + log.info(f'{os.popen("icpx --version").read().rstrip()}') for device in range(torch.xpu.device_count()): log.info(f'Torch detected GPU: {torch.xpu.get_device_name(device)} VRAM {round(torch.xpu.get_device_properties(device).total_memory / 1024 / 1024)} Compute Units {torch.xpu.get_device_properties(device).max_compute_units}') elif torch.cuda.is_available() and (allow_cuda or allow_rocm): diff --git a/modules/sd_models.py b/modules/sd_models.py index 700212a95..ac4fceaa5 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -721,18 +721,21 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No shared.log.info("Model compile enabled: IPEX Optimize Graph Mode") if op == 'refiner': gpu_vram = memory_stats().get('gpu', {}) - if (gpu_vram.get('total', 0) - gpu_vram.get('used', 0)) >= 7 if "StableDiffusionXL" in sd_model.__class__.__name__ else 3.5: + if not shared.opts.diffusers_move_base and (gpu_vram.get('total', 0) - gpu_vram.get('used', 0)) >= 7 if "StableDiffusionXL" in sd_model.__class__.__name__ else 3.5: sd_model.to(devices.device) base_sent_to_cpu=False else: - shared.log.info(f"Not enough VRAM to optimize refiner, using RAM as fallback. Free VRAM: {gpu_vram.get('total', 0) - gpu_vram.get('used', 0)} GB") + if shared.opts.diffusers_move_base: + pass + else: + shared.log.info(f"Not enough VRAM to optimize refiner, using RAM as fallback. Free VRAM: {gpu_vram.get('total', 0) - gpu_vram.get('used', 0)} GB") + shared.opts.diffusers_move_base=True + shared.opts.diffusers_move_refiner=True shared.log.debug('Moving base model to CPU') model_data.sd_model.to("cpu") devices.torch_gc(force=True) sd_model.to(devices.device) base_sent_to_cpu=True - shared.opts.diffusers_move_base=True - shared.opts.diffusers_move_refiner=True else: sd_model.to(devices.device) sd_model.unet = torch.xpu.optimize(sd_model.unet, dtype=devices.dtype, auto_kernel_selection=True, optimize_lstm=True, # pylint: disable=attribute-defined-outside-init