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add option to show/hide warnings 

removed hiding warnings from LDSR
fixed/reworked few places that produced warnings
This commit is contained in:
AUTOMATIC 2023-01-18 23:04:24 +03:00
parent 889b851a52
commit 924e222004
10 changed files with 71 additions and 32 deletions
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3
extensions-builtin/LDSR/ldsr_model_arch.py
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@ -1,7 +1,6 @@
import os
import gc
import time
import warnings
import numpy as np
import torch
@ -15,8 +14,6 @@ from ldm.models.diffusion.ddim import DDIMSampler
from ldm.util import instantiate_from_config, ismap
from modules import shared, sd_hijack
warnings.filterwarnings("ignore", category=UserWarning)
cached_ldsr_model: torch.nn.Module = None

2
javascript/localization.js
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@ -11,7 +11,7 @@ ignore_ids_for_localization={
train_embedding: 'OPTION',
train_hypernetwork: 'OPTION',
txt2img_styles: 'OPTION',
img2img_styles 'OPTION',
img2img_styles: 'OPTION',
setting_random_artist_categories: 'SPAN',
setting_face_restoration_model: 'SPAN',
setting_realesrgan_enabled_models: 'SPAN',

7
modules/hypernetworks/hypernetwork.py
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@ -12,7 +12,7 @@ import torch
import tqdm
from einops import rearrange, repeat
from ldm.util import default
from modules import devices, processing, sd_models, shared, sd_samplers, hashes
from modules import devices, processing, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint
from modules.textual_inversion import textual_inversion, logging
from modules.textual_inversion.learn_schedule import LearnRateScheduler
from torch import einsum
@ -575,6 +575,8 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
pbar = tqdm.tqdm(total=steps - initial_step)
try:
sd_hijack_checkpoint.add()
for i in range((steps-initial_step) * gradient_step):
if scheduler.finished:
break
@ -724,6 +726,9 @@ Last saved image: {html.escape(last_saved_image)}<br/>
pbar.close()
hypernetwork.eval()
#report_statistics(loss_dict)
sd_hijack_checkpoint.remove()
filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
hypernetwork.optimizer_name = optimizer_name

8
modules/sd_hijack.py
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@ -69,12 +69,6 @@ def undo_optimizations():
ldm.modules.diffusionmodules.model.AttnBlock.forward = diffusionmodules_model_AttnBlock_forward
def fix_checkpoint():
ldm.modules.attention.BasicTransformerBlock.forward = sd_hijack_checkpoint.BasicTransformerBlock_forward
ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = sd_hijack_checkpoint.ResBlock_forward
ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = sd_hijack_checkpoint.AttentionBlock_forward
class StableDiffusionModelHijack:
fixes = None
comments = []
@ -106,8 +100,6 @@ class StableDiffusionModelHijack:
self.optimization_method = apply_optimizations()
self.clip = m.cond_stage_model
fix_checkpoint()
def flatten(el):
flattened = [flatten(children) for children in el.children()]

38
modules/sd_hijack_checkpoint.py
View File

@ -1,10 +1,46 @@
from torch.utils.checkpoint import checkpoint
import ldm.modules.attention
import ldm.modules.diffusionmodules.openaimodel
def BasicTransformerBlock_forward(self, x, context=None):
return checkpoint(self._forward, x, context)
def AttentionBlock_forward(self, x):
return checkpoint(self._forward, x)
def ResBlock_forward(self, x, emb):
return checkpoint(self._forward, x, emb)
return checkpoint(self._forward, x, emb)
stored = []
def add():
if len(stored) != 0:
return
stored.extend([
ldm.modules.attention.BasicTransformerBlock.forward,
ldm.modules.diffusionmodules.openaimodel.ResBlock.forward,
ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward
])
ldm.modules.attention.BasicTransformerBlock.forward = BasicTransformerBlock_forward
ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = ResBlock_forward
ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = AttentionBlock_forward
def remove():
if len(stored) == 0:
return
ldm.modules.attention.BasicTransformerBlock.forward = stored[0]
ldm.modules.diffusionmodules.openaimodel.ResBlock.forward = stored[1]
ldm.modules.diffusionmodules.openaimodel.AttentionBlock.forward = stored[2]
stored.clear()

1
modules/shared.py
View File

@ -369,6 +369,7 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
}))
options_templates.update(options_section(('system', "System"), {
"show_warnings": OptionInfo(False, "Show warnings in console."),
"memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
"samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
"multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),

6
modules/textual_inversion/textual_inversion.py
View File

@ -15,7 +15,7 @@ import numpy as np
from PIL import Image, PngImagePlugin
from torch.utils.tensorboard import SummaryWriter
from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers
from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint
import modules.textual_inversion.dataset
from modules.textual_inversion.learn_schedule import LearnRateScheduler
@ -452,6 +452,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
pbar = tqdm.tqdm(total=steps - initial_step)
try:
sd_hijack_checkpoint.add()
for i in range((steps-initial_step) * gradient_step):
if scheduler.finished:
break
@ -617,9 +619,11 @@ Last saved image: {html.escape(last_saved_image)}<br/>
pbar.close()
shared.sd_model.first_stage_model.to(devices.device)
shared.parallel_processing_allowed = old_parallel_processing_allowed
sd_hijack_checkpoint.remove()
return embedding, filename
def save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True):
old_embedding_name = embedding.name
old_sd_checkpoint = embedding.sd_checkpoint if hasattr(embedding, "sd_checkpoint") else None

31
modules/ui.py
View File

@ -11,6 +11,7 @@ import tempfile
import time
import traceback
from functools import partial, reduce
import warnings
import gradio as gr
import gradio.routes
@ -41,6 +42,8 @@ from modules.textual_inversion import textual_inversion
import modules.hypernetworks.ui
from modules.generation_parameters_copypaste import image_from_url_text
warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
mimetypes.init()
mimetypes.add_type('application/javascript', '.js')
@ -417,17 +420,16 @@ def apply_setting(key, value):
return value
def update_generation_info(args):
generation_info, html_info, img_index = args
def update_generation_info(generation_info, html_info, img_index):
try:
generation_info = json.loads(generation_info)
if img_index < 0 or img_index >= len(generation_info["infotexts"]):
return html_info
return plaintext_to_html(generation_info["infotexts"][img_index])
return html_info, gr.update()
return plaintext_to_html(generation_info["infotexts"][img_index]), gr.update()
except Exception:
pass
# if the json parse or anything else fails, just return the old html_info
return html_info
return html_info, gr.update()
def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
@ -508,10 +510,9 @@ Requested path was: {f}
generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
generation_info_button.click(
fn=update_generation_info,
_js="(x, y) => [x, y, selected_gallery_index()]",
inputs=[generation_info, html_info],
outputs=[html_info],
preprocess=False
_js="function(x, y, z){ console.log(x, y, z); return [x, y, selected_gallery_index()] }",
inputs=[generation_info, html_info, html_info],
outputs=[html_info, html_info],
)
save.click(
@ -526,7 +527,8 @@ Requested path was: {f}
outputs=[
download_files,
html_log,
]
],
show_progress=False,
)
save_zip.click(
@ -588,7 +590,7 @@ def create_ui():
txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
dummy_component = gr.Label(visible=False)
txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)
with gr.Row().style(equal_height=False):
with gr.Column(variant='compact', elem_id="txt2img_settings"):
@ -768,7 +770,7 @@ def create_ui():
with gr.Blocks(analytics_enabled=False) as img2img_interface:
img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
with FormRow().style(equal_height=False):
with gr.Column(variant='compact', elem_id="img2img_settings"):
@ -1768,7 +1770,10 @@ def create_ui():
if saved_value is None:
ui_settings[key] = getattr(obj, field)
elif condition and not condition(saved_value):
print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
pass
# this warning is generally not useful;
# print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
else:
setattr(obj, field, saved_value)
if init_field is not None:

2
scripts/prompts_from_file.py
View File

@ -116,7 +116,7 @@ class Script(scripts.Script):
checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch"))
prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1, elem_id=self.elem_id("prompt_txt"))
file = gr.File(label="Upload prompt inputs", type='bytes', elem_id=self.elem_id("file"))
file = gr.File(label="Upload prompt inputs", type='binary', elem_id=self.elem_id("file"))
file.change(fn=load_prompt_file, inputs=[file], outputs=[file, prompt_txt, prompt_txt])

5
style.css
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@ -299,9 +299,8 @@ input[type="range"]{
}
/* more gradio's garbage cleanup */
.min-h-\[4rem\] {
min-height: unset !important;
}
.min-h-\[4rem\] { min-height: unset !important; }
.min-h-\[6rem\] { min-height: unset !important; }
.progressDiv{
position: absolute;