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Merge pull request #5589 from MrCheeze/better-special-model-support
Better support for 2.0-inpainting and 2.0-depth special models
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commit
94450b8877
@ -55,18 +55,20 @@ def setup_for_low_vram(sd_model, use_medvram):
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if hasattr(sd_model.cond_stage_model, 'model'):
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sd_model.cond_stage_model.transformer = sd_model.cond_stage_model.model
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# remove three big modules, cond, first_stage, and unet from the model and then
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# remove four big modules, cond, first_stage, depth (if applicable), and unet from the model and then
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# send the model to GPU. Then put modules back. the modules will be in CPU.
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stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model
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sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model = None, None, None
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stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, getattr(sd_model, 'depth_model', None), sd_model.model
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sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = None, None, None, None
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sd_model.to(devices.device)
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sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.model = stored
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sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = stored
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# register hooks for those the first two models
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# register hooks for those the first three models
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sd_model.cond_stage_model.transformer.register_forward_pre_hook(send_me_to_gpu)
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sd_model.first_stage_model.register_forward_pre_hook(send_me_to_gpu)
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sd_model.first_stage_model.encode = first_stage_model_encode_wrap
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sd_model.first_stage_model.decode = first_stage_model_decode_wrap
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if sd_model.depth_model:
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sd_model.depth_model.register_forward_pre_hook(send_me_to_gpu)
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parents[sd_model.cond_stage_model.transformer] = sd_model.cond_stage_model
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if hasattr(sd_model.cond_stage_model, 'model'):
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@ -324,12 +324,11 @@ def should_hijack_inpainting(checkpoint_info):
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def do_inpainting_hijack():
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# most of this stuff seems to no longer be needed because it is already included into SD2.0
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# LatentInpaintDiffusion remains because SD2.0's LatentInpaintDiffusion can't be loaded without specifying a checkpoint
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# p_sample_plms is needed because PLMS can't work with dicts as conditionings
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# this file should be cleaned up later if weverything tuens out to work fine
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# ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning
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ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion
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# ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion
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# ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim
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# ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim
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@ -293,13 +293,16 @@ def load_model(checkpoint_info=None):
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if should_hijack_inpainting(checkpoint_info):
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# Hardcoded config for now...
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sd_config.model.target = "ldm.models.diffusion.ddpm.LatentInpaintDiffusion"
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sd_config.model.params.use_ema = False
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sd_config.model.params.conditioning_key = "hybrid"
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sd_config.model.params.unet_config.params.in_channels = 9
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sd_config.model.params.finetune_keys = None
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# Create a "fake" config with a different name so that we know to unload it when switching models.
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checkpoint_info = checkpoint_info._replace(config=checkpoint_info.config.replace(".yaml", "-inpainting.yaml"))
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if not hasattr(sd_config.model.params, "use_ema"):
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sd_config.model.params.use_ema = False
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do_inpainting_hijack()
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if shared.cmd_opts.no_half:
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