38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
import torch
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import gradio as gr
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import lora
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import extra_networks_lora
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import ui_extra_networks_lora
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from modules import script_callbacks, ui_extra_networks, extra_networks, shared
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def unload():
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torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora
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torch.nn.Conv2d.forward = torch.nn.Conv2d_forward_before_lora
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def before_ui():
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ui_extra_networks.register_page(ui_extra_networks_lora.ExtraNetworksPageLora())
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extra_networks.register_extra_network(extra_networks_lora.ExtraNetworkLora())
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if not hasattr(torch.nn, 'Linear_forward_before_lora'):
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torch.nn.Linear_forward_before_lora = torch.nn.Linear.forward
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if not hasattr(torch.nn, 'Conv2d_forward_before_lora'):
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torch.nn.Conv2d_forward_before_lora = torch.nn.Conv2d.forward
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torch.nn.Linear.forward = lora.lora_Linear_forward
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torch.nn.Conv2d.forward = lora.lora_Conv2d_forward
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script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)
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script_callbacks.on_script_unloaded(unload)
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script_callbacks.on_before_ui(before_ui)
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shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
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"sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
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"lora_apply_to_outputs": shared.OptionInfo(False, "Apply Lora to outputs rather than inputs when possible (experimental)"),
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}))
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