Unload weights if vram usage goes up between runs. (#10690)
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@@ -503,7 +503,11 @@ class LoadedModel:
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use_more_vram = lowvram_model_memory
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if use_more_vram == 0:
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use_more_vram = 1e32
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self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
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if use_more_vram > 0:
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self.model_use_more_vram(use_more_vram, force_patch_weights=force_patch_weights)
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else:
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self.model.partially_unload(self.model.offload_device, -use_more_vram, force_patch_weights=force_patch_weights)
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real_model = self.model.model
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if is_intel_xpu() and not args.disable_ipex_optimize and 'ipex' in globals() and real_model is not None:
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@@ -689,7 +693,10 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
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current_free_mem = get_free_memory(torch_dev) + loaded_memory
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lowvram_model_memory = max(128 * 1024 * 1024, (current_free_mem - minimum_memory_required), min(current_free_mem * MIN_WEIGHT_MEMORY_RATIO, current_free_mem - minimum_inference_memory()))
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lowvram_model_memory = max(0.1, lowvram_model_memory - loaded_memory)
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lowvram_model_memory = lowvram_model_memory - loaded_memory
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if lowvram_model_memory == 0:
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lowvram_model_memory = 0.1
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if vram_set_state == VRAMState.NO_VRAM:
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lowvram_model_memory = 0.1
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