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set devices.dtype_unet correctly
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@ -345,6 +345,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
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if shared.cmd_opts.no_half:
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model.float()
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devices.dtype_unet = torch.float32
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timer.record("apply float()")
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else:
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vae = model.first_stage_model
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@ -362,9 +363,9 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
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if depth_model:
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model.depth_model = depth_model
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devices.dtype_unet = torch.float16
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timer.record("apply half()")
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devices.dtype_unet = torch.float16 if model.is_sdxl and not shared.cmd_opts.no_half else model.model.diffusion_model.dtype
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devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16
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model.first_stage_model.to(devices.dtype_vae)
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