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Finally removed model_hijack

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finally
This commit is contained in:
layerdiffusion
2024-08-05 21:05:25 -07:00
parent 252d437f5d
commit ae1d995d0d
8 changed files with 90 additions and 89 deletions
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76
modules/textual_inversion/ui.py
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@@ -1,38 +1,38 @@
import html
import gradio as gr
import modules.textual_inversion.textual_inversion
from modules import sd_hijack, shared
def create_embedding(name, initialization_text, nvpt, overwrite_old):
filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, overwrite_old, init_text=initialization_text)
sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
def train_embedding(*args):
assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
apply_optimizations = shared.opts.training_xattention_optimizations
try:
if not apply_optimizations:
sd_hijack.undo_optimizations()
embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
res = f"""
Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
Embedding saved to {html.escape(filename)}
"""
return res, ""
except Exception:
raise
finally:
if not apply_optimizations:
sd_hijack.apply_optimizations()
# import html
#
# import gradio as gr
#
# import modules.textual_inversion.textual_inversion
# from modules import sd_hijack, shared
#
#
# def create_embedding(name, initialization_text, nvpt, overwrite_old):
# filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, overwrite_old, init_text=initialization_text)
#
# sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
#
# return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
#
#
# def train_embedding(*args):
#
# assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
#
# apply_optimizations = shared.opts.training_xattention_optimizations
# try:
# if not apply_optimizations:
# sd_hijack.undo_optimizations()
#
# embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
#
# res = f"""
# Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
# Embedding saved to {html.escape(filename)}
# """
# return res, ""
# except Exception:
# raise
# finally:
# if not apply_optimizations:
# sd_hijack.apply_optimizations()
#