| import html | |
| import os | |
| import re | |
| import gradio as gr | |
| import modules.hypernetworks.hypernetwork | |
| from modules import devices, sd_hijack, shared | |
| not_available = ["hardswish", "multiheadattention"] | |
| keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available) | |
| def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None): | |
| filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure) | |
| return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {filename}", "" | |
| def train_hypernetwork(*args): | |
| shared.loaded_hypernetworks = [] | |
| assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible' | |
| try: | |
| sd_hijack.undo_optimizations() | |
| hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args) | |
| res = f""" | |
| Training {'interrupted' if shared.state.interrupted else 'finished'} at {hypernetwork.step} steps. | |
| Hypernetwork saved to {html.escape(filename)} | |
| """ | |
| return res, "" | |
| except Exception: | |
| raise | |
| finally: | |
| shared.sd_model.cond_stage_model.to(devices.device) | |
| shared.sd_model.first_stage_model.to(devices.device) | |
| sd_hijack.apply_optimizations() | |