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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2025-08-04 03:10:21 +00:00
SDXL support
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@@ -53,19 +53,46 @@ def setup_for_low_vram(sd_model, use_medvram):
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send_me_to_gpu(first_stage_model, None)
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return first_stage_model_decode(z)
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# for SD1, cond_stage_model is CLIP and its NN is in the tranformer frield, but for SD2, it's open clip, and it's in model field
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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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to_remain_in_cpu = [
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(sd_model, 'first_stage_model'),
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(sd_model, 'depth_model'),
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(sd_model, 'embedder'),
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(sd_model, 'model'),
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(sd_model, 'embedder'),
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]
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# remove several big modules: cond, first_stage, depth/embedder (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, getattr(sd_model, 'depth_model', None), getattr(sd_model, 'embedder', 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.embedder, sd_model.model = None, None, None, None, None
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is_sdxl = hasattr(sd_model, 'conditioner')
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is_sd2 = not is_sdxl and hasattr(sd_model.cond_stage_model, 'model')
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if is_sdxl:
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to_remain_in_cpu.append((sd_model, 'conditioner'))
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elif is_sd2:
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to_remain_in_cpu.append((sd_model.cond_stage_model, 'model'))
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else:
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to_remain_in_cpu.append((sd_model.cond_stage_model, 'transformer'))
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# remove several big modules: cond, first_stage, depth/embedder (if applicable), and unet from the model
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stored = []
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for obj, field in to_remain_in_cpu:
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module = getattr(obj, field, None)
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stored.append(module)
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setattr(obj, field, None)
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# send the model to GPU.
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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.depth_model, sd_model.embedder, sd_model.model = stored
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# put modules back. the modules will be in CPU.
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for (obj, field), module in zip(to_remain_in_cpu, stored):
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setattr(obj, field, module)
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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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if is_sdxl:
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sd_model.conditioner.register_forward_pre_hook(send_me_to_gpu)
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elif is_sd2:
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sd_model.cond_stage_model.model.register_forward_pre_hook(send_me_to_gpu)
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else:
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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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@@ -75,10 +102,6 @@ def setup_for_low_vram(sd_model, use_medvram):
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sd_model.embedder.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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sd_model.cond_stage_model.model = sd_model.cond_stage_model.transformer
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del sd_model.cond_stage_model.transformer
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if use_medvram:
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sd_model.model.register_forward_pre_hook(send_me_to_gpu)
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else:
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