stable-diffusion-webui/modules/hypernetworks/ui.py

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import html
import os
import re
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import gradio as gr
import modules.textual_inversion.preprocess
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import modules.textual_inversion.textual_inversion
from modules import devices, sd_hijack, shared
from modules.hypernetworks import hypernetwork
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def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False):
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# Remove illegal characters from name.
name = "".join( x for x in name if (x.isalnum() or x in "._- "))
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fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
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if not overwrite_old:
assert not os.path.exists(fn), f"file {fn} already exists"
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if type(layer_structure) == str:
layer_structure = [float(x.strip()) for x in layer_structure.split(",")]
hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(
name=name,
enable_sizes=[int(x) for x in enable_sizes],
layer_structure=layer_structure,
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activation_func=activation_func,
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add_layer_norm=add_layer_norm,
use_dropout=use_dropout,
)
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hypernet.save(fn)
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shared.reload_hypernetworks()
return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""
def train_hypernetwork(*args):
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initial_hypernetwork = shared.loaded_hypernetwork
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assert not shared.cmd_opts.lowvram, 'Training models with lowvram is not possible'
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try:
sd_hijack.undo_optimizations()
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hypernetwork, filename = modules.hypernetworks.hypernetwork.train_hypernetwork(*args)
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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:
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shared.loaded_hypernetwork = initial_hypernetwork
shared.sd_model.cond_stage_model.to(devices.device)
shared.sd_model.first_stage_model.to(devices.device)
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sd_hijack.apply_optimizations()