Fix potential issue if exception happens when patching model.
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4
nodes.py
4
nodes.py
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@ -289,6 +289,7 @@ def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, po
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else:
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noise = torch.randn(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, generator=torch.manual_seed(seed), device="cpu")
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real_model = None
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try:
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real_model = model.patch_model()
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real_model.to(device)
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@ -322,7 +323,8 @@ def common_ksampler(device, model, seed, steps, cfg, sampler_name, scheduler, po
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real_model.cpu()
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model.unpatch_model()
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except Exception as e:
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real_model.cpu()
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if real_model is not None:
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real_model.cpu()
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model.unpatch_model()
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raise e
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