From 3bd898b6ce94f34bcc7685672f0e4318d2d86b33 Mon Sep 17 00:00:00 2001
From: invincibledude <>
Date: Sat, 21 Jan 2023 23:14:59 +0300
Subject: First test of different sampler for hi-res fix
---
modules/ui.py | 5 +++++
1 file changed, 5 insertions(+)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index b3105901..6bbbc0f6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -672,6 +672,9 @@ def create_ui():
hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
+ with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact"):
+ hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers], value="---", type="index")
+
elif category == "batch":
if not opts.dimensions_and_batch_together:
with FormRow(elem_id="txt2img_column_batch"):
@@ -730,6 +733,7 @@ def create_ui():
hr_second_pass_steps,
hr_resize_x,
hr_resize_y,
+ hr_sampler_index,
] + custom_inputs,
outputs=[
@@ -785,6 +789,7 @@ def create_ui():
(hr_second_pass_steps, "Hires steps"),
(hr_resize_x, "Hires resize-1"),
(hr_resize_y, "Hires resize-2"),
+ (hr_sampler_index, "Hires sampling method"),
*modules.scripts.scripts_txt2img.infotext_fields
]
parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
--
cgit v1.2.3
From 0f6862ef3041f3ee18e8236765b1c1958c84385b Mon Sep 17 00:00:00 2001
From: invincibledude <>
Date: Sun, 22 Jan 2023 00:11:05 +0300
Subject: PLMS edge-case handling fix 5
---
modules/processing.py | 2 --
modules/txt2img.py | 2 +-
modules/ui.py | 2 +-
3 files changed, 2 insertions(+), 4 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/processing.py b/modules/processing.py
index 6f6efe06..a873498b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -866,8 +866,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if self.hr_sampler == '---':
pass
- elif self.hr_sampler == 'PLMS':
- img2img_sampler_name = 'DDIM'
else:
img2img_sampler_name = self.hr_sampler
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 9c8ec621..c6ea11c2 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -38,7 +38,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
hr_second_pass_steps=hr_second_pass_steps,
hr_resize_x=hr_resize_x,
hr_resize_y=hr_resize_y,
- hr_sampler=sd_samplers.samplers[hr_sampler_index - 1].name
+ hr_sampler=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name
if hr_sampler_index != 0 else '---'
)
diff --git a/modules/ui.py b/modules/ui.py
index 6bbbc0f6..b408379f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -673,7 +673,7 @@ def create_ui():
hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact"):
- hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers], value="---", type="index")
+ hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers_for_img2img], value="---", type="index")
elif category == "batch":
if not opts.dimensions_and_batch_together:
--
cgit v1.2.3
From 8114959e7e937361b719cd85bec246ffd258dca6 Mon Sep 17 00:00:00 2001
From: invincibledude <>
Date: Sun, 22 Jan 2023 14:28:53 +0300
Subject: Hr separate prompt test
---
modules/processing.py | 23 ++++++++++++++++++++++-
modules/txt2img.py | 6 ++++--
modules/ui.py | 10 ++++++++++
3 files changed, 36 insertions(+), 3 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/processing.py b/modules/processing.py
index a873498b..f407e175 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -516,6 +516,23 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
else:
p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)]
+ if type(p) == StableDiffusionProcessingTxt2Img:
+ if p.hr_enabled and p.is_hr_pass:
+ if p.hr_prompt:
+ if type(p.prompt) == list:
+ p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt]
+ else:
+ p.all_prompts = p.batch_size * p.n_iter * [
+ shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)]
+
+ if p.hr_negative_prompt:
+ if type(p.negative_prompt) == list:
+ p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in
+ p.hr_negative_prompt]
+ else:
+ p.all_negative_prompts = p.batch_size * p.n_iter * [
+ shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)]
+
if type(seed) == list:
p.all_seeds = seed
else:
@@ -710,7 +727,7 @@ def old_hires_fix_first_pass_dimensions(width, height):
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
sampler = None
- def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler: str = '---', **kwargs):
+ def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler: str = '---', hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
super().__init__(**kwargs)
self.enable_hr = enable_hr
self.denoising_strength = denoising_strength
@@ -722,6 +739,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.hr_upscale_to_x = hr_resize_x
self.hr_upscale_to_y = hr_resize_y
self.hr_sampler = hr_sampler
+ self.hr_prompt = hr_prompt if hr_prompt != '' else self.prompt
+ self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else self.negative_prompt
+ self.is_hr_pass = False
if firstphase_width != 0 or firstphase_height != 0:
self.hr_upscale_to_x = self.width
@@ -808,6 +828,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if not self.enable_hr:
return samples
+ self.is_hr_pass = True
target_width = self.hr_upscale_to_x
target_height = self.hr_upscale_to_y
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 2eb41f3d..c06f9f9d 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -8,7 +8,7 @@ import modules.processing as processing
from modules.ui import plaintext_to_html
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, *args):
p = StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -38,7 +38,9 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
hr_second_pass_steps=hr_second_pass_steps,
hr_resize_x=hr_resize_x,
hr_resize_y=hr_resize_y,
- hr_sampler=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else '---'
+ hr_sampler=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else '---',
+ hr_prompt=hr_prompt,
+ hr_negative_prompt=hr_negative_prompt
)
p.scripts = modules.scripts.scripts_txt2img
diff --git a/modules/ui.py b/modules/ui.py
index b408379f..e0a9e40b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -675,6 +675,14 @@ def create_ui():
with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact"):
hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers_for_img2img], value="---", type="index")
+ with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact"):
+ with gr.Column(scale=80):
+ with gr.Row():
+ hr_prompt = gr.Textbox(label="Prompt", elem_id=f"hires_prompt", show_label=False, lines=3, placeholder="Prompt that will be used for hires fix pass")
+ with gr.Column(scale=80):
+ with gr.Row():
+ hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt that will be used for hires fix pass")
+
elif category == "batch":
if not opts.dimensions_and_batch_together:
with FormRow(elem_id="txt2img_column_batch"):
@@ -734,6 +742,8 @@ def create_ui():
hr_resize_x,
hr_resize_y,
hr_sampler_index,
+ hr_prompt,
+ hr_negative_prompt,
] + custom_inputs,
outputs=[
--
cgit v1.2.3
From b0ae92d605dfb65314b610589f84b643d535261e Mon Sep 17 00:00:00 2001
From: invincibledude <>
Date: Sun, 22 Jan 2023 15:43:12 +0300
Subject: UI improvements
---
modules/ui.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index e0a9e40b..1656e76d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -678,10 +678,10 @@ def create_ui():
with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact"):
with gr.Column(scale=80):
with gr.Row():
- hr_prompt = gr.Textbox(label="Prompt", elem_id=f"hires_prompt", show_label=False, lines=3, placeholder="Prompt that will be used for hires fix pass")
+ hr_prompt = gr.Textbox(label="Prompt", elem_id=f"hires_prompt", show_label=False, lines=3, placeholder="Prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)")
with gr.Column(scale=80):
with gr.Row():
- hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt that will be used for hires fix pass")
+ hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)")
elif category == "batch":
if not opts.dimensions_and_batch_together:
--
cgit v1.2.3
From bbb1e35ea29f8cfc6a6db3b28b10bfbc99033c70 Mon Sep 17 00:00:00 2001
From: invincibledude <>
Date: Sun, 22 Jan 2023 15:44:59 +0300
Subject: UI and PNG info improvements
---
modules/processing.py | 3 +++
modules/ui.py | 2 ++
2 files changed, 5 insertions(+)
(limited to 'modules/ui.py')
diff --git a/modules/processing.py b/modules/processing.py
index b2de8f92..0cf4771e 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -789,6 +789,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if self.hr_resize_x == 0 and self.hr_resize_y == 0:
self.extra_generation_params["Hires upscale"] = self.hr_scale
+ self.extra_generation_params["Hires sampler"] = self.hr_sampler
+ self.extra_generation_params["Hires prompt"] = self.hr_prompt
+ self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt
self.hr_upscale_to_x = int(self.width * self.hr_scale)
self.hr_upscale_to_y = int(self.height * self.hr_scale)
else:
diff --git a/modules/ui.py b/modules/ui.py
index 1656e76d..64180889 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -800,6 +800,8 @@ def create_ui():
(hr_resize_x, "Hires resize-1"),
(hr_resize_y, "Hires resize-2"),
(hr_sampler_index, "Hires sampling method"),
+ (hr_prompt, "Hires prompt"),
+ (hr_negative_prompt, "Hires negative prompt"),
*modules.scripts.scripts_txt2img.infotext_fields
]
parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
--
cgit v1.2.3
From 771ea212de13711b494b082d8e94e79b17ac9d08 Mon Sep 17 00:00:00 2001
From: pieresimakp <69743585+pieresimakp@users.noreply.github.com>
Date: Fri, 24 Mar 2023 12:41:17 +0800
Subject: added button to grab the width and height from the loaded image in
img2img
---
javascript/hints.js | 1 +
modules/ui.py | 7 +++++--
2 files changed, 6 insertions(+), 2 deletions(-)
(limited to 'modules/ui.py')
diff --git a/javascript/hints.js b/javascript/hints.js
index 7f4101b2..5bbc27a5 100644
--- a/javascript/hints.js
+++ b/javascript/hints.js
@@ -9,6 +9,7 @@ titles = {
"UniPC": "Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models",
"DPM adaptive": "Ignores step count - uses a number of steps determined by the CFG and resolution",
+ "\u{1F4D0}": "Auto detect size from img2img",
"Batch count": "How many batches of images to create (has no impact on generation performance or VRAM usage)",
"Batch size": "How many image to create in a single batch (increases generation performance at cost of higher VRAM usage)",
"CFG Scale": "Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results",
diff --git a/modules/ui.py b/modules/ui.py
index 7e603332..6c623002 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -92,7 +92,7 @@ apply_style_symbol = '\U0001f4cb' # 📋
clear_prompt_symbol = '\U0001F5D1' # 🗑️
extra_networks_symbol = '\U0001F3B4' # 🎴
switch_values_symbol = '\U000021C5' # ⇅
-
+detect_image_size_symbol = '\U0001F4D0' # 📐
def plaintext_to_html(text):
return ui_common.plaintext_to_html(text)
@@ -756,8 +756,10 @@ def create_ui():
with gr.Column(elem_id="img2img_column_size", scale=4):
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
+
+ detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
+
if opts.dimensions_and_batch_together:
with gr.Column(elem_id="img2img_column_batch"):
batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
@@ -904,6 +906,7 @@ def create_ui():
img2img_prompt.submit(**img2img_args)
submit.click(**img2img_args)
+ detect_image_size_btn.click(lambda i, w, h : i.size if i is not None else (w, h), inputs=[init_img, width, height], outputs=[width, height])
res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height])
img2img_interrogate.click(
--
cgit v1.2.3
From fb72066ef6a2fed799468517932a76a39789cca6 Mon Sep 17 00:00:00 2001
From: pieresimakp <69743585+pieresimakp@users.noreply.github.com>
Date: Sat, 25 Mar 2023 23:03:22 +0800
Subject: fixed button position
---
modules/ui.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 9b6e3241..464e4d8c 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -758,8 +758,8 @@ def create_ui():
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
- detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
+ detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
if opts.dimensions_and_batch_together:
--
cgit v1.2.3
From 7201d940a4fe664beb9662fadbeade4ee1d788f7 Mon Sep 17 00:00:00 2001
From: space-nuko <24979496+space-nuko@users.noreply.github.com>
Date: Mon, 3 Apr 2023 21:27:48 -0500
Subject: Improve frontend responsiveness for some buttons
---
javascript/ui.js | 48 ++++++++++++++++++++++++++++++++++++++++++++++++
modules/ui.py | 10 ++++++----
2 files changed, 54 insertions(+), 4 deletions(-)
(limited to 'modules/ui.py')
diff --git a/javascript/ui.js b/javascript/ui.js
index 4a440193..5311e7bc 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -361,3 +361,51 @@ function selectCheckpoint(name){
desiredCheckpointName = name;
gradioApp().getElementById('change_checkpoint').click()
}
+
+function setRandomSeed(target_interface) {
+ let seed = gradioApp().querySelector(`#${target_interface}_seed input`);
+ if (!seed) {
+ return [];
+ }
+ seed.value = "-1";
+ seed.dispatchEvent(new Event("input"));
+ return [];
+}
+
+function setRandomSubseed(target_interface) {
+ let subseed = gradioApp().querySelector(`#${target_interface}_subseed input`);
+ if (!subseed) {
+ return [];
+ }
+ subseed.value = "-1";
+ subseed.dispatchEvent(new Event("input"));
+ return [];
+}
+
+function switchWidthHeightTxt2Img() {
+ let width = gradioApp().querySelector("#txt2img_width input[type=number]");
+ let height = gradioApp().querySelector("#txt2img_height input[type=number]");
+ if (!width || !height) {
+ return [];
+ }
+ let tmp = width.value;
+ width.value = height.value;
+ height.value = tmp;
+ width.dispatchEvent(new Event("input"));
+ height.dispatchEvent(new Event("input"));
+ return [];
+}
+
+function switchWidthHeightImg2Img() {
+ let width = gradioApp().querySelector("#img2img_width input[type=number]");
+ let height = gradioApp().querySelector("#img2img_height input[type=number]");
+ if (!width || !height) {
+ return [];
+ }
+ let tmp = width.value;
+ width.value = height.value;
+ height.value = tmp;
+ width.dispatchEvent(new Event("input"));
+ height.dispatchEvent(new Event("input"));
+ return [];
+}
diff --git a/modules/ui.py b/modules/ui.py
index 627fbe0b..5c693b7a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -192,8 +192,9 @@ def create_seed_inputs(target_interface):
seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
- random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
- random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
+ target_interface_state = gr.Textbox(target_interface, visible=False)
+ random_seed.click(fn=None, _js="setRandomSeed", show_progress=False, inputs=[target_interface_state], outputs=[])
+ random_subseed.click(fn=None, _js="setRandomSubseed", show_progress=False, inputs=[target_interface_state], outputs=[])
def change_visibility(show):
return {comp: gr_show(show) for comp in seed_extras}
@@ -576,7 +577,7 @@ def create_ui():
txt2img_prompt.submit(**txt2img_args)
submit.click(**txt2img_args)
- res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height], show_progress=False)
+ res_switch_btn.click(fn=None, _js="switchWidthHeightTxt2Img", inputs=None, outputs=None, show_progress=False)
txt_prompt_img.change(
fn=modules.images.image_data,
@@ -896,7 +897,8 @@ def create_ui():
img2img_prompt.submit(**img2img_args)
submit.click(**img2img_args)
- res_switch_btn.click(lambda w, h: (h, w), inputs=[width, height], outputs=[width, height], show_progress=False)
+
+ res_switch_btn.click(fn=None, _js="switchWidthHeightImg2Img", inputs=None, outputs=None, show_progress=False)
img2img_interrogate.click(
fn=lambda *args: process_interrogate(interrogate, *args),
--
cgit v1.2.3
From 762265eab58cdb8f2d6398769bab43d8b8db0075 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 07:52:45 +0300
Subject: autofixes from ruff
---
extensions-builtin/LDSR/ldsr_model_arch.py | 1 -
extensions-builtin/LDSR/sd_hijack_autoencoder.py | 2 +-
modules/api/api.py | 14 +++++++-------
modules/extras.py | 4 ++--
modules/images.py | 4 ++--
modules/img2img.py | 2 +-
modules/prompt_parser.py | 2 +-
modules/realesrgan_model.py | 2 +-
modules/sd_disable_initialization.py | 2 +-
modules/sd_hijack.py | 4 ++--
modules/sd_hijack_ip2p.py | 2 +-
modules/sd_hijack_optimizations.py | 1 -
modules/sd_models.py | 6 +++---
modules/textual_inversion/textual_inversion.py | 2 +-
modules/ui.py | 13 ++++++-------
modules/ui_extensions.py | 2 +-
modules/ui_extra_networks.py | 2 +-
pyproject.toml | 4 +++-
scripts/outpainting_mk_2.py | 2 +-
scripts/postprocessing_upscale.py | 6 +++---
scripts/xyz_grid.py | 2 +-
webui.py | 2 +-
22 files changed, 40 insertions(+), 41 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index bc11cc6e..2339de7f 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -110,7 +110,6 @@ class LDSR:
diffusion_steps = int(steps)
eta = 1.0
- down_sample_method = 'Lanczos'
gc.collect()
if torch.cuda.is_available:
diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
index 8e03c7f8..db2231dd 100644
--- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py
+++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
@@ -165,7 +165,7 @@ class VQModel(pl.LightningModule):
def validation_step(self, batch, batch_idx):
log_dict = self._validation_step(batch, batch_idx)
with self.ema_scope():
- log_dict_ema = self._validation_step(batch, batch_idx, suffix="_ema")
+ self._validation_step(batch, batch_idx, suffix="_ema")
return log_dict
def _validation_step(self, batch, batch_idx, suffix=""):
diff --git a/modules/api/api.py b/modules/api/api.py
index 9bb95dfd..d47c39fc 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -60,7 +60,7 @@ def decode_base64_to_image(encoding):
try:
image = Image.open(BytesIO(base64.b64decode(encoding)))
return image
- except Exception as err:
+ except Exception:
raise HTTPException(status_code=500, detail="Invalid encoded image")
def encode_pil_to_base64(image):
@@ -264,11 +264,11 @@ class Api:
if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
for alwayson_script_name in request.alwayson_scripts.keys():
alwayson_script = self.get_script(alwayson_script_name, script_runner)
- if alwayson_script == None:
+ if alwayson_script is None:
raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found")
# Selectable script in always on script param check
- if alwayson_script.alwayson == False:
- raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params")
+ if alwayson_script.alwayson is False:
+ raise HTTPException(status_code=422, detail="Cannot have a selectable script in the always on scripts params")
# always on script with no arg should always run so you don't really need to add them to the requests
if "args" in request.alwayson_scripts[alwayson_script_name]:
# min between arg length in scriptrunner and arg length in the request
@@ -310,7 +310,7 @@ class Api:
p.outpath_samples = opts.outdir_txt2img_samples
shared.state.begin()
- if selectable_scripts != None:
+ if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
else:
@@ -367,7 +367,7 @@ class Api:
p.outpath_samples = opts.outdir_img2img_samples
shared.state.begin()
- if selectable_scripts != None:
+ if selectable_scripts is not None:
p.script_args = script_args
processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
else:
@@ -642,7 +642,7 @@ class Api:
sd_hijack.apply_optimizations()
shared.state.end()
return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
- except AssertionError as msg:
+ except AssertionError:
shared.state.end()
return TrainResponse(info=f"train embedding error: {error}")
diff --git a/modules/extras.py b/modules/extras.py
index ff4e9c4e..eb4f0b42 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -136,14 +136,14 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
result_is_instruct_pix2pix_model = False
if theta_func2:
- shared.state.textinfo = f"Loading B"
+ shared.state.textinfo = "Loading B"
print(f"Loading {secondary_model_info.filename}...")
theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
else:
theta_1 = None
if theta_func1:
- shared.state.textinfo = f"Loading C"
+ shared.state.textinfo = "Loading C"
print(f"Loading {tertiary_model_info.filename}...")
theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
diff --git a/modules/images.py b/modules/images.py
index a41965ab..3d5d76cc 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -409,13 +409,13 @@ class FilenameGenerator:
time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format
try:
time_zone = pytz.timezone(args[1]) if len(args) > 1 else None
- except pytz.exceptions.UnknownTimeZoneError as _:
+ except pytz.exceptions.UnknownTimeZoneError:
time_zone = None
time_zone_time = time_datetime.astimezone(time_zone)
try:
formatted_time = time_zone_time.strftime(time_format)
- except (ValueError, TypeError) as _:
+ except (ValueError, TypeError):
formatted_time = time_zone_time.strftime(self.default_time_format)
return sanitize_filename_part(formatted_time, replace_spaces=False)
diff --git a/modules/img2img.py b/modules/img2img.py
index 9fc3a698..cdae301a 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
# try to find corresponding mask for an image using simple filename matching
mask_image_path = os.path.join(inpaint_mask_dir, os.path.basename(image))
# if not found use first one ("same mask for all images" use-case)
- if not mask_image_path in inpaint_masks:
+ if mask_image_path not in inpaint_masks:
mask_image_path = inpaint_masks[0]
mask_image = Image.open(mask_image_path)
p.image_mask = mask_image
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 69665372..e084e948 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -92,7 +92,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
def get_schedule(prompt):
try:
tree = schedule_parser.parse(prompt)
- except lark.exceptions.LarkError as e:
+ except lark.exceptions.LarkError:
if 0:
import traceback
traceback.print_exc()
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index efd7fca5..9ec1adf2 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -134,6 +134,6 @@ def get_realesrgan_models(scaler):
),
]
return models
- except Exception as e:
+ except Exception:
print("Error making Real-ESRGAN models list:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py
index c4a09d15..9fc89dc6 100644
--- a/modules/sd_disable_initialization.py
+++ b/modules/sd_disable_initialization.py
@@ -61,7 +61,7 @@ class DisableInitialization:
if res is None:
res = original(url, *args, local_files_only=False, **kwargs)
return res
- except Exception as e:
+ except Exception:
return original(url, *args, local_files_only=False, **kwargs)
def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs):
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f4bb0266..d8135211 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -118,7 +118,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
try:
#Delete temporary weights if appended
del sd_model._custom_loss_weight
- except AttributeError as e:
+ except AttributeError:
pass
#If we have an old loss function, reset the loss function to the original one
@@ -133,7 +133,7 @@ def apply_weighted_forward(sd_model):
def undo_weighted_forward(sd_model):
try:
del sd_model.weighted_forward
- except AttributeError as e:
+ except AttributeError:
pass
diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py
index 3c727d3b..41ed54a2 100644
--- a/modules/sd_hijack_ip2p.py
+++ b/modules/sd_hijack_ip2p.py
@@ -10,4 +10,4 @@ def should_hijack_ip2p(checkpoint_info):
ckpt_basename = os.path.basename(checkpoint_info.filename).lower()
cfg_basename = os.path.basename(sd_models_config.find_checkpoint_config_near_filename(checkpoint_info)).lower()
- return "pix2pix" in ckpt_basename and not "pix2pix" in cfg_basename
+ return "pix2pix" in ckpt_basename and "pix2pix" not in cfg_basename
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index f10865cd..b623d53d 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -296,7 +296,6 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_
if chunk_threshold_bytes is not None and qk_matmul_size_bytes <= chunk_threshold_bytes:
# the big matmul fits into our memory limit; do everything in 1 chunk,
# i.e. send it down the unchunked fast-path
- query_chunk_size = q_tokens
kv_chunk_size = k_tokens
with devices.without_autocast(disable=q.dtype == v.dtype):
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 36f643e1..11c1a344 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -239,7 +239,7 @@ def read_metadata_from_safetensors(filename):
if isinstance(v, str) and v[0:1] == '{':
try:
res[k] = json.loads(v)
- except Exception as e:
+ except Exception:
pass
return res
@@ -467,7 +467,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
try:
with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd):
sd_model = instantiate_from_config(sd_config.model)
- except Exception as e:
+ except Exception:
pass
if sd_model is None:
@@ -544,7 +544,7 @@ def reload_model_weights(sd_model=None, info=None):
try:
load_model_weights(sd_model, checkpoint_info, state_dict, timer)
- except Exception as e:
+ except Exception:
print("Failed to load checkpoint, restoring previous")
load_model_weights(sd_model, current_checkpoint_info, None, timer)
raise
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 4368eb63..f753b75f 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -603,7 +603,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
try:
vectorSize = list(data['string_to_param'].values())[0].shape[0]
- except Exception as e:
+ except Exception:
vectorSize = '?'
checkpoint = sd_models.select_checkpoint()
diff --git a/modules/ui.py b/modules/ui.py
index d02f6e82..2171f3aa 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -246,7 +246,7 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
all_seeds = gen_info.get('all_seeds', [-1])
res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
- except json.decoder.JSONDecodeError as e:
+ except json.decoder.JSONDecodeError:
if gen_info_string != '':
print("Error parsing JSON generation info:", file=sys.stderr)
print(gen_info_string, file=sys.stderr)
@@ -736,8 +736,8 @@ def create_ui():
with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch:
hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
gr.HTML(
- f"Process images in a directory on the same machine where the server is running." +
- f"
Use an empty output directory to save pictures normally instead of writing to the output directory." +
+ "
Process images in a directory on the same machine where the server is running." +
+ "
Use an empty output directory to save pictures normally instead of writing to the output directory." +
f"
Add inpaint batch mask directory to enable inpaint batch processing."
f"{hidden}
"
)
@@ -746,7 +746,6 @@ def create_ui():
img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir")
img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]
- img2img_image_inputs = [init_img, sketch, init_img_with_mask, inpaint_color_sketch]
for i, tab in enumerate(img2img_tabs):
tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab])
@@ -1290,8 +1289,8 @@ def create_ui():
with gr.Column(elem_id='ti_gallery_container'):
ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
- ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
- ti_progress = gr.HTML(elem_id="ti_progress", value="")
+ gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4)
+ gr.HTML(elem_id="ti_progress", value="")
ti_outcome = gr.HTML(elem_id="ti_error", value="")
create_embedding.click(
@@ -1668,7 +1667,7 @@ def create_ui():
interface.render()
if os.path.exists(os.path.join(script_path, "notification.mp3")):
- audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
+ gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
footer = shared.html("footer.html")
footer = footer.format(versions=versions_html())
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index d9faf85a..ed70abe5 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -490,7 +490,7 @@ def create_ui():
config_states.list_config_states()
with gr.Blocks(analytics_enabled=False) as ui:
- with gr.Tabs(elem_id="tabs_extensions") as tabs:
+ with gr.Tabs(elem_id="tabs_extensions"):
with gr.TabItem("Installed", id="installed"):
with gr.Row(elem_id="extensions_installed_top"):
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 8c3dea56..49e06289 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -263,7 +263,7 @@ def create_ui(container, button, tabname):
ui.stored_extra_pages = pages_in_preferred_order(extra_pages.copy())
ui.tabname = tabname
- with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
+ with gr.Tabs(elem_id=tabname+"_extra_tabs"):
for page in ui.stored_extra_pages:
page_id = page.title.lower().replace(" ", "_")
diff --git a/pyproject.toml b/pyproject.toml
index 9e9662ad..1e164abc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,7 +2,9 @@
ignore = [
"E501",
- "E731"
+ "E731",
+ "E402", # Module level import not at top of file
+ "F401" # Module imported but unused
]
exclude = ["extensions"]
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index 670bb8ac..b10fed6c 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -72,7 +72,7 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0
height = _np_src_image.shape[1]
num_channels = _np_src_image.shape[2]
- np_src_image = _np_src_image[:] * (1. - np_mask_rgb)
+ _np_src_image[:] * (1. - np_mask_rgb)
np_mask_grey = (np.sum(np_mask_rgb, axis=2) / 3.)
img_mask = np_mask_grey > 1e-6
ref_mask = np_mask_grey < 1e-3
diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py
index ef1186ac..edb70ac0 100644
--- a/scripts/postprocessing_upscale.py
+++ b/scripts/postprocessing_upscale.py
@@ -98,13 +98,13 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
assert upscaler2 or (upscaler_2_name is None), f'could not find upscaler named {upscaler_2_name}'
upscaled_image = self.upscale(pp.image, pp.info, upscaler1, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
- pp.info[f"Postprocess upscaler"] = upscaler1.name
+ pp.info["Postprocess upscaler"] = upscaler1.name
if upscaler2 and upscaler_2_visibility > 0:
second_upscale = self.upscale(pp.image, pp.info, upscaler2, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
upscaled_image = Image.blend(upscaled_image, second_upscale, upscaler_2_visibility)
- pp.info[f"Postprocess upscaler 2"] = upscaler2.name
+ pp.info["Postprocess upscaler 2"] = upscaler2.name
pp.image = upscaled_image
@@ -134,4 +134,4 @@ class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale):
assert upscaler1, f'could not find upscaler named {upscaler_name}'
pp.image = self.upscale(pp.image, pp.info, upscaler1, 0, upscale_by, 0, 0, False)
- pp.info[f"Postprocess upscaler"] = upscaler1.name
+ pp.info["Postprocess upscaler"] = upscaler1.name
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index a725d74a..2ff42ef8 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -316,7 +316,7 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
return Processed(p, [])
z_count = len(zs)
- sub_grids = [None] * z_count
+
for i in range(z_count):
start_index = (i * len(xs) * len(ys)) + i
end_index = start_index + len(xs) * len(ys)
diff --git a/webui.py b/webui.py
index 727ebd31..ec3d2aba 100644
--- a/webui.py
+++ b/webui.py
@@ -360,7 +360,7 @@ def webui():
if cmd_opts.subpath:
redirector = FastAPI()
redirector.get("/")
- mounted_app = gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
+ gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
wait_on_server(shared.demo)
print('Restarting UI...')
--
cgit v1.2.3
From 96d6ca4199e7c5eee8d451618de5161cea317c40 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:25:25 +0300
Subject: manual fixes for ruff
---
extensions-builtin/LDSR/ldsr_model_arch.py | 2 +-
extensions-builtin/LDSR/scripts/ldsr_model.py | 3 +-
extensions-builtin/LDSR/sd_hijack_autoencoder.py | 10 +-
extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 26 ++---
extensions-builtin/ScuNET/scunet_model_arch.py | 9 +-
extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +-
modules/api/api.py | 129 +++++++++++-----------
modules/api/models.py | 5 +-
modules/codeformer/codeformer_arch.py | 2 +-
modules/esrgan_model_arch.py | 2 +
modules/extra_networks_hypernet.py | 2 +-
modules/images.py | 4 +-
modules/img2img.py | 1 -
modules/interrogate.py | 1 -
modules/modelloader.py | 6 +-
modules/models/diffusion/ddpm_edit.py | 26 ++---
modules/models/diffusion/uni_pc/sampler.py | 3 +-
modules/processing.py | 2 +-
modules/prompt_parser.py | 11 +-
modules/textual_inversion/autocrop.py | 2 +-
modules/ui.py | 8 +-
modules/upscaler.py | 2 +-
22 files changed, 129 insertions(+), 129 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index 2339de7f..a5fb8907 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -243,7 +243,7 @@ def make_convolutional_sample(batch, model, custom_steps=None, eta=1.0, quantize
x_sample_noquant = model.decode_first_stage(sample, force_not_quantize=True)
log["sample_noquant"] = x_sample_noquant
log["sample_diff"] = torch.abs(x_sample_noquant - x_sample)
- except:
+ except Exception:
pass
log["sample"] = x_sample
diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py
index da19cff1..e8dc083c 100644
--- a/extensions-builtin/LDSR/scripts/ldsr_model.py
+++ b/extensions-builtin/LDSR/scripts/ldsr_model.py
@@ -7,7 +7,8 @@ from basicsr.utils.download_util import load_file_from_url
from modules.upscaler import Upscaler, UpscalerData
from ldsr_model_arch import LDSR
from modules import shared, script_callbacks
-import sd_hijack_autoencoder, sd_hijack_ddpm_v1
+import sd_hijack_autoencoder
+import sd_hijack_ddpm_v1
class UpscalerLDSR(Upscaler):
diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
index db2231dd..6303fed5 100644
--- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py
+++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
@@ -1,16 +1,21 @@
# The content of this file comes from the ldm/models/autoencoder.py file of the compvis/stable-diffusion repo
# The VQModel & VQModelInterface were subsequently removed from ldm/models/autoencoder.py when we moved to the stability-ai/stablediffusion repo
# As the LDSR upscaler relies on VQModel & VQModelInterface, the hijack aims to put them back into the ldm.models.autoencoder
-
+import numpy as np
import torch
import pytorch_lightning as pl
import torch.nn.functional as F
from contextlib import contextmanager
+
+from torch.optim.lr_scheduler import LambdaLR
+
+from ldm.modules.ema import LitEma
from taming.modules.vqvae.quantize import VectorQuantizer2 as VectorQuantizer
from ldm.modules.diffusionmodules.model import Encoder, Decoder
from ldm.util import instantiate_from_config
import ldm.models.autoencoder
+from packaging import version
class VQModel(pl.LightningModule):
def __init__(self,
@@ -249,7 +254,8 @@ class VQModel(pl.LightningModule):
if plot_ema:
with self.ema_scope():
xrec_ema, _ = self(x)
- if x.shape[1] > 3: xrec_ema = self.to_rgb(xrec_ema)
+ if x.shape[1] > 3:
+ xrec_ema = self.to_rgb(xrec_ema)
log["reconstructions_ema"] = xrec_ema
return log
diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
index 5c0488e5..4d3f6c56 100644
--- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
+++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
@@ -450,7 +450,7 @@ class LatentDiffusionV1(DDPMV1):
self.cond_stage_key = cond_stage_key
try:
self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1
- except:
+ except Exception:
self.num_downs = 0
if not scale_by_std:
self.scale_factor = scale_factor
@@ -877,16 +877,6 @@ class LatentDiffusionV1(DDPMV1):
c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float()))
return self.p_losses(x, c, t, *args, **kwargs)
- def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset
- def rescale_bbox(bbox):
- x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2])
- y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3])
- w = min(bbox[2] / crop_coordinates[2], 1 - x0)
- h = min(bbox[3] / crop_coordinates[3], 1 - y0)
- return x0, y0, w, h
-
- return [rescale_bbox(b) for b in bboxes]
-
def apply_model(self, x_noisy, t, cond, return_ids=False):
if isinstance(cond, dict):
@@ -1157,8 +1147,10 @@ class LatentDiffusionV1(DDPMV1):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(x0_partial)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
return img, intermediates
@torch.no_grad()
@@ -1205,8 +1197,10 @@ class LatentDiffusionV1(DDPMV1):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(img)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
if return_intermediates:
return img, intermediates
@@ -1322,7 +1316,7 @@ class LatentDiffusionV1(DDPMV1):
if inpaint:
# make a simple center square
- b, h, w = z.shape[0], z.shape[2], z.shape[3]
+ h, w = z.shape[2], z.shape[3]
mask = torch.ones(N, h, w).to(self.device)
# zeros will be filled in
mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0.
diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py
index 43ca8d36..8028918a 100644
--- a/extensions-builtin/ScuNET/scunet_model_arch.py
+++ b/extensions-builtin/ScuNET/scunet_model_arch.py
@@ -61,7 +61,9 @@ class WMSA(nn.Module):
Returns:
output: tensor shape [b h w c]
"""
- if self.type != 'W': x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2))
+ if self.type != 'W':
+ x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2))
+
x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size)
h_windows = x.size(1)
w_windows = x.size(2)
@@ -85,8 +87,9 @@ class WMSA(nn.Module):
output = self.linear(output)
output = rearrange(output, 'b (w1 w2) (p1 p2) c -> b (w1 p1) (w2 p2) c', w1=h_windows, p1=self.window_size)
- if self.type != 'W': output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2),
- dims=(1, 2))
+ if self.type != 'W':
+ output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), dims=(1, 2))
+
return output
def relative_embedding(self):
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index e8783bca..d77c3a92 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -45,7 +45,7 @@ class UpscalerSwinIR(Upscaler):
img = upscale(img, model)
try:
torch.cuda.empty_cache()
- except:
+ except Exception:
pass
return img
diff --git a/modules/api/api.py b/modules/api/api.py
index d47c39fc..f52d371b 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -15,7 +15,8 @@ from secrets import compare_digest
import modules.shared as shared
from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing
-from modules.api.models import *
+from modules.api import models
+from modules.shared import opts
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
from modules.textual_inversion.textual_inversion import create_embedding, train_embedding
from modules.textual_inversion.preprocess import preprocess
@@ -25,20 +26,21 @@ from modules.sd_models import checkpoints_list, unload_model_weights, reload_mod
from modules.sd_models_config import find_checkpoint_config_near_filename
from modules.realesrgan_model import get_realesrgan_models
from modules import devices
-from typing import List
+from typing import Dict, List, Any
import piexif
import piexif.helper
+
def upscaler_to_index(name: str):
try:
return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
- except:
- raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in sd_upscalers])}")
+ except Exception:
+ raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}")
def script_name_to_index(name, scripts):
try:
return [script.title().lower() for script in scripts].index(name.lower())
- except:
+ except Exception:
raise HTTPException(status_code=422, detail=f"Script '{name}' not found")
def validate_sampler_name(name):
@@ -99,7 +101,7 @@ def api_middleware(app: FastAPI):
import starlette # importing just so it can be placed on silent list
from rich.console import Console
console = Console()
- except:
+ except Exception:
import traceback
rich_available = False
@@ -166,36 +168,36 @@ class Api:
self.app = app
self.queue_lock = queue_lock
api_middleware(self.app)
- self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse)
- self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse)
- self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
- self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
- self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
- self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
+ self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse)
+ self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse)
+ self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse)
+ self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse)
+ self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse)
+ self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse)
self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"])
- self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel)
+ self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)
self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
- self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel)
- self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem])
- self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem])
- self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem])
- self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem])
- self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem])
- self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem])
- self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
- self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse)
+ self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)
+ self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])
+ self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])
+ self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])
+ self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])
+ self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])
+ self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])
+ self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])
+ self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)
self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
- self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse)
- self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=PreprocessResponse)
- self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
- self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
+ self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse)
+ self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse)
+ self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse)
+ self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse)
+ self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse)
+ self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse)
self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
- self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
+ self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
self.default_script_arg_txt2img = []
self.default_script_arg_img2img = []
@@ -224,7 +226,7 @@ class Api:
t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles]
i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles]
- return ScriptsList(txt2img = t2ilist, img2img = i2ilist)
+ return models.ScriptsList(txt2img=t2ilist, img2img=i2ilist)
def get_script(self, script_name, script_runner):
if script_name is None or script_name == "":
@@ -276,7 +278,7 @@ class Api:
script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx]
return script_args
- def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
+ def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
@@ -320,9 +322,9 @@ class Api:
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
- return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
+ return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
- def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI):
+ def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI):
init_images = img2imgreq.init_images
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
@@ -381,9 +383,9 @@ class Api:
img2imgreq.init_images = None
img2imgreq.mask = None
- return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
+ return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
- def extras_single_image_api(self, req: ExtrasSingleImageRequest):
+ def extras_single_image_api(self, req: models.ExtrasSingleImageRequest):
reqDict = setUpscalers(req)
reqDict['image'] = decode_base64_to_image(reqDict['image'])
@@ -391,9 +393,9 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
+ return models.ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1])
- def extras_batch_images_api(self, req: ExtrasBatchImagesRequest):
+ def extras_batch_images_api(self, req: models.ExtrasBatchImagesRequest):
reqDict = setUpscalers(req)
image_list = reqDict.pop('imageList', [])
@@ -402,15 +404,15 @@ class Api:
with self.queue_lock:
result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict)
- return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
+ return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
- def pnginfoapi(self, req: PNGInfoRequest):
+ def pnginfoapi(self, req: models.PNGInfoRequest):
if(not req.image.strip()):
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
image = decode_base64_to_image(req.image.strip())
if image is None:
- return PNGInfoResponse(info="")
+ return models.PNGInfoResponse(info="")
geninfo, items = images.read_info_from_image(image)
if geninfo is None:
@@ -418,13 +420,13 @@ class Api:
items = {**{'parameters': geninfo}, **items}
- return PNGInfoResponse(info=geninfo, items=items)
+ return models.PNGInfoResponse(info=geninfo, items=items)
- def progressapi(self, req: ProgressRequest = Depends()):
+ def progressapi(self, req: models.ProgressRequest = Depends()):
# copy from check_progress_call of ui.py
if shared.state.job_count == 0:
- return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo)
# avoid dividing zero
progress = 0.01
@@ -446,9 +448,9 @@ class Api:
if shared.state.current_image and not req.skip_current_image:
current_image = encode_pil_to_base64(shared.state.current_image)
- return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
+ return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
- def interrogateapi(self, interrogatereq: InterrogateRequest):
+ def interrogateapi(self, interrogatereq: models.InterrogateRequest):
image_b64 = interrogatereq.image
if image_b64 is None:
raise HTTPException(status_code=404, detail="Image not found")
@@ -465,7 +467,7 @@ class Api:
else:
raise HTTPException(status_code=404, detail="Model not found")
- return InterrogateResponse(caption=processed)
+ return models.InterrogateResponse(caption=processed)
def interruptapi(self):
shared.state.interrupt()
@@ -570,36 +572,36 @@ class Api:
filename = create_embedding(**args) # create empty embedding
sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used
shared.state.end()
- return CreateResponse(info=f"create embedding filename: {filename}")
+ return models.CreateResponse(info=f"create embedding filename: {filename}")
except AssertionError as e:
shared.state.end()
- return TrainResponse(info=f"create embedding error: {e}")
+ return models.TrainResponse(info=f"create embedding error: {e}")
def create_hypernetwork(self, args: dict):
try:
shared.state.begin()
filename = create_hypernetwork(**args) # create empty embedding
shared.state.end()
- return CreateResponse(info=f"create hypernetwork filename: {filename}")
+ return models.CreateResponse(info=f"create hypernetwork filename: {filename}")
except AssertionError as e:
shared.state.end()
- return TrainResponse(info=f"create hypernetwork error: {e}")
+ return models.TrainResponse(info=f"create hypernetwork error: {e}")
def preprocess(self, args: dict):
try:
shared.state.begin()
preprocess(**args) # quick operation unless blip/booru interrogation is enabled
shared.state.end()
- return PreprocessResponse(info = 'preprocess complete')
+ return models.PreprocessResponse(info = 'preprocess complete')
except KeyError as e:
shared.state.end()
- return PreprocessResponse(info=f"preprocess error: invalid token: {e}")
+ return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}")
except AssertionError as e:
shared.state.end()
- return PreprocessResponse(info=f"preprocess error: {e}")
+ return models.PreprocessResponse(info=f"preprocess error: {e}")
except FileNotFoundError as e:
shared.state.end()
- return PreprocessResponse(info=f'preprocess error: {e}')
+ return models.PreprocessResponse(info=f'preprocess error: {e}')
def train_embedding(self, args: dict):
try:
@@ -617,10 +619,10 @@ class Api:
if not apply_optimizations:
sd_hijack.apply_optimizations()
shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
except AssertionError as msg:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {msg}")
+ return models.TrainResponse(info=f"train embedding error: {msg}")
def train_hypernetwork(self, args: dict):
try:
@@ -641,14 +643,15 @@ class Api:
if not apply_optimizations:
sd_hijack.apply_optimizations()
shared.state.end()
- return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
+ return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}")
except AssertionError:
shared.state.end()
- return TrainResponse(info=f"train embedding error: {error}")
+ return models.TrainResponse(info=f"train embedding error: {error}")
def get_memory(self):
try:
- import os, psutil
+ import os
+ import psutil
process = psutil.Process(os.getpid())
res = process.memory_info() # only rss is cross-platform guaranteed so we dont rely on other values
ram_total = 100 * res.rss / process.memory_percent() # and total memory is calculated as actual value is not cross-platform safe
@@ -675,10 +678,10 @@ class Api:
'events': warnings,
}
else:
- cuda = { 'error': 'unavailable' }
+ cuda = {'error': 'unavailable'}
except Exception as err:
- cuda = { 'error': f'{err}' }
- return MemoryResponse(ram = ram, cuda = cuda)
+ cuda = {'error': f'{err}'}
+ return models.MemoryResponse(ram=ram, cuda=cuda)
def launch(self, server_name, port):
self.app.include_router(self.router)
diff --git a/modules/api/models.py b/modules/api/models.py
index 4a70f440..4d291076 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -223,8 +223,9 @@ for key in _options:
if(_options[key].dest != 'help'):
flag = _options[key]
_type = str
- if _options[key].default is not None: _type = type(_options[key].default)
- flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))})
+ if _options[key].default is not None:
+ _type = type(_options[key].default)
+ flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))})
FlagsModel = create_model("Flags", **flags)
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index 11dcc3ee..f1a7cf09 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -7,7 +7,7 @@ from torch import nn, Tensor
import torch.nn.functional as F
from typing import Optional, List
-from modules.codeformer.vqgan_arch import *
+from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
index 6071fea7..7f8bc7c0 100644
--- a/modules/esrgan_model_arch.py
+++ b/modules/esrgan_model_arch.py
@@ -438,9 +438,11 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias=
padding = padding if pad_type == 'zero' else 0
if convtype=='PartialConv2D':
+ from torchvision.ops import PartialConv2d # this is definitely not going to work, but PartialConv2d doesn't work anyway and this shuts up static analyzer
c = PartialConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding,
dilation=dilation, bias=bias, groups=groups)
elif convtype=='DeformConv2D':
+ from torchvision.ops import DeformConv2d # not tested
c = DeformConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding,
dilation=dilation, bias=bias, groups=groups)
elif convtype=='Conv3D':
diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py
index 04f27c9f..aa2a14ef 100644
--- a/modules/extra_networks_hypernet.py
+++ b/modules/extra_networks_hypernet.py
@@ -1,4 +1,4 @@
-from modules import extra_networks, shared, extra_networks
+from modules import extra_networks, shared
from modules.hypernetworks import hypernetwork
diff --git a/modules/images.py b/modules/images.py
index 3d5d76cc..5eb6d855 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -472,9 +472,9 @@ def get_next_sequence_number(path, basename):
prefix_length = len(basename)
for p in os.listdir(path):
if p.startswith(basename):
- l = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
+ parts = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element)
try:
- result = max(int(l[0]), result)
+ result = max(int(parts[0]), result)
except ValueError:
pass
diff --git a/modules/img2img.py b/modules/img2img.py
index cdae301a..32b1ecd6 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -13,7 +13,6 @@ from modules.shared import opts, state
import modules.shared as shared
import modules.processing as processing
from modules.ui import plaintext_to_html
-import modules.images as images
import modules.scripts
diff --git a/modules/interrogate.py b/modules/interrogate.py
index 9f7d657f..22df9216 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -11,7 +11,6 @@ import torch.hub
from torchvision import transforms
from torchvision.transforms.functional import InterpolationMode
-import modules.shared as shared
from modules import devices, paths, shared, lowvram, modelloader, errors
blip_image_eval_size = 384
diff --git a/modules/modelloader.py b/modules/modelloader.py
index cb85ac4f..cf685000 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -108,12 +108,12 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
print(f"Moving {file} from {src_path} to {dest_path}.")
try:
shutil.move(fullpath, dest_path)
- except:
+ except Exception:
pass
if len(os.listdir(src_path)) == 0:
print(f"Removing empty folder: {src_path}")
shutil.rmtree(src_path, True)
- except:
+ except Exception:
pass
@@ -141,7 +141,7 @@ def load_upscalers():
full_model = f"modules.{model_name}_model"
try:
importlib.import_module(full_model)
- except:
+ except Exception:
pass
datas = []
diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py
index f880bc3c..611c2b69 100644
--- a/modules/models/diffusion/ddpm_edit.py
+++ b/modules/models/diffusion/ddpm_edit.py
@@ -479,7 +479,7 @@ class LatentDiffusion(DDPM):
self.cond_stage_key = cond_stage_key
try:
self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1
- except:
+ except Exception:
self.num_downs = 0
if not scale_by_std:
self.scale_factor = scale_factor
@@ -891,16 +891,6 @@ class LatentDiffusion(DDPM):
c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float()))
return self.p_losses(x, c, t, *args, **kwargs)
- def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset
- def rescale_bbox(bbox):
- x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2])
- y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3])
- w = min(bbox[2] / crop_coordinates[2], 1 - x0)
- h = min(bbox[3] / crop_coordinates[3], 1 - y0)
- return x0, y0, w, h
-
- return [rescale_bbox(b) for b in bboxes]
-
def apply_model(self, x_noisy, t, cond, return_ids=False):
if isinstance(cond, dict):
@@ -1171,8 +1161,10 @@ class LatentDiffusion(DDPM):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(x0_partial)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
return img, intermediates
@torch.no_grad()
@@ -1219,8 +1211,10 @@ class LatentDiffusion(DDPM):
if i % log_every_t == 0 or i == timesteps - 1:
intermediates.append(img)
- if callback: callback(i)
- if img_callback: img_callback(img, i)
+ if callback:
+ callback(i)
+ if img_callback:
+ img_callback(img, i)
if return_intermediates:
return img, intermediates
@@ -1337,7 +1331,7 @@ class LatentDiffusion(DDPM):
if inpaint:
# make a simple center square
- b, h, w = z.shape[0], z.shape[2], z.shape[3]
+ h, w = z.shape[2], z.shape[3]
mask = torch.ones(N, h, w).to(self.device)
# zeros will be filled in
mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0.
diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py
index a241c8a7..0a9defa1 100644
--- a/modules/models/diffusion/uni_pc/sampler.py
+++ b/modules/models/diffusion/uni_pc/sampler.py
@@ -54,7 +54,8 @@ class UniPCSampler(object):
if conditioning is not None:
if isinstance(conditioning, dict):
ctmp = conditioning[list(conditioning.keys())[0]]
- while isinstance(ctmp, list): ctmp = ctmp[0]
+ while isinstance(ctmp, list):
+ ctmp = ctmp[0]
cbs = ctmp.shape[0]
if cbs != batch_size:
print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
diff --git a/modules/processing.py b/modules/processing.py
index 1a76e552..6f5233c1 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -664,7 +664,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if not shared.opts.dont_fix_second_order_samplers_schedule:
try:
step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1
- except:
+ except Exception:
pass
uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index e084e948..3a720721 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -54,18 +54,21 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
"""
def collect_steps(steps, tree):
- l = [steps]
+ res = [steps]
+
class CollectSteps(lark.Visitor):
def scheduled(self, tree):
tree.children[-1] = float(tree.children[-1])
if tree.children[-1] < 1:
tree.children[-1] *= steps
tree.children[-1] = min(steps, int(tree.children[-1]))
- l.append(tree.children[-1])
+ res.append(tree.children[-1])
+
def alternate(self, tree):
- l.extend(range(1, steps+1))
+ res.extend(range(1, steps+1))
+
CollectSteps().visit(tree)
- return sorted(set(l))
+ return sorted(set(res))
def at_step(step, tree):
class AtStep(lark.Transformer):
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index ba1bdcd4..d7d8d2e3 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -185,7 +185,7 @@ def image_face_points(im, settings):
try:
faces = classifier.detectMultiScale(gray, scaleFactor=1.1,
minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE)
- except:
+ except Exception:
continue
if len(faces) > 0:
diff --git a/modules/ui.py b/modules/ui.py
index 2171f3aa..6beda76f 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1,15 +1,9 @@
-import html
import json
-import math
import mimetypes
import os
-import platform
-import random
import sys
-import tempfile
-import time
import traceback
-from functools import partial, reduce
+from functools import reduce
import warnings
import gradio as gr
diff --git a/modules/upscaler.py b/modules/upscaler.py
index e2eaa730..0ad4fe99 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -45,7 +45,7 @@ class Upscaler:
try:
import cv2
self.can_tile = True
- except:
+ except Exception:
pass
@abstractmethod
--
cgit v1.2.3
From f741a98baccae100fcfb40c017b5c35c5cba1b0c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 08:43:42 +0300
Subject: imports cleanup for ruff
---
extensions-builtin/Lora/lora.py | 1 -
extensions-builtin/ScuNET/scripts/scunet_model.py | 1 -
extensions-builtin/SwinIR/scripts/swinir_model.py | 3 +--
modules/codeformer/codeformer_arch.py | 4 +---
modules/codeformer/vqgan_arch.py | 2 --
modules/codeformer_model.py | 4 +---
modules/config_states.py | 2 +-
modules/esrgan_model.py | 2 +-
modules/esrgan_model_arch.py | 1 -
modules/extensions.py | 1 -
modules/generation_parameters_copypaste.py | 4 ----
modules/hypernetworks/hypernetwork.py | 3 +--
modules/hypernetworks/ui.py | 2 --
modules/images.py | 2 +-
modules/img2img.py | 5 +----
modules/mac_specific.py | 1 -
modules/modelloader.py | 1 -
modules/models/diffusion/uni_pc/uni_pc.py | 1 -
modules/processing.py | 5 ++---
modules/sd_hijack.py | 2 +-
modules/sd_hijack_inpainting.py | 6 ------
modules/sd_hijack_ip2p.py | 5 +----
modules/sd_hijack_xlmr.py | 2 --
modules/sd_models.py | 2 +-
modules/sd_models_config.py | 1 -
modules/sd_samplers_kdiffusion.py | 1 -
modules/sd_vae.py | 3 ---
modules/shared.py | 3 ---
modules/styles.py | 9 ---------
modules/textual_inversion/autocrop.py | 4 +---
modules/textual_inversion/image_embedding.py | 2 +-
modules/textual_inversion/preprocess.py | 4 ----
modules/textual_inversion/textual_inversion.py | 1 -
modules/txt2img.py | 9 +++------
modules/ui.py | 5 ++---
modules/ui_extra_networks.py | 1 -
modules/ui_postprocessing.py | 2 +-
modules/upscaler.py | 2 --
modules/xlmr.py | 2 +-
pyproject.toml | 11 +++++++----
scripts/custom_code.py | 2 +-
scripts/outpainting_mk_2.py | 4 ++--
scripts/poor_mans_outpainting.py | 4 ++--
scripts/prompt_matrix.py | 7 ++-----
scripts/prompts_from_file.py | 5 +----
scripts/sd_upscale.py | 4 ++--
scripts/xyz_grid.py | 6 ++----
webui.py | 2 +-
48 files changed, 42 insertions(+), 114 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
index ba1293df..0ab43229 100644
--- a/extensions-builtin/Lora/lora.py
+++ b/extensions-builtin/Lora/lora.py
@@ -1,4 +1,3 @@
-import glob
import os
import re
import torch
diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py
index c7fd5739..aa2fdb3a 100644
--- a/extensions-builtin/ScuNET/scripts/scunet_model.py
+++ b/extensions-builtin/ScuNET/scripts/scunet_model.py
@@ -13,7 +13,6 @@ import modules.upscaler
from modules import devices, modelloader
from scunet_model_arch import SCUNet as net
from modules.shared import opts
-from modules import images
class UpscalerScuNET(modules.upscaler.Upscaler):
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index d77c3a92..55dd94ab 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -1,4 +1,3 @@
-import contextlib
import os
import numpy as np
@@ -8,7 +7,7 @@ from basicsr.utils.download_util import load_file_from_url
from tqdm import tqdm
from modules import modelloader, devices, script_callbacks, shared
-from modules.shared import cmd_opts, opts, state
+from modules.shared import opts, state
from swinir_model_arch import SwinIR as net
from swinir_model_arch_v2 import Swin2SR as net2
from modules.upscaler import Upscaler, UpscalerData
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index f1a7cf09..00c407de 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -1,14 +1,12 @@
# this file is copied from CodeFormer repository. Please see comment in modules/codeformer_model.py
import math
-import numpy as np
import torch
from torch import nn, Tensor
import torch.nn.functional as F
-from typing import Optional, List
+from typing import Optional
from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
-from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
def calc_mean_std(feat, eps=1e-5):
diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py
index e7293683..820e6b12 100644
--- a/modules/codeformer/vqgan_arch.py
+++ b/modules/codeformer/vqgan_arch.py
@@ -5,11 +5,9 @@ VQGAN code, adapted from the original created by the Unleashing Transformers aut
https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py
'''
-import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
-import copy
from basicsr.utils import get_root_logger
from basicsr.utils.registry import ARCH_REGISTRY
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index 8d84bbc9..8e56cb89 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -33,11 +33,9 @@ def setup_model(dirname):
try:
from torchvision.transforms.functional import normalize
from modules.codeformer.codeformer_arch import CodeFormer
- from basicsr.utils.download_util import load_file_from_url
- from basicsr.utils import imwrite, img2tensor, tensor2img
+ from basicsr.utils import img2tensor, tensor2img
from facelib.utils.face_restoration_helper import FaceRestoreHelper
from facelib.detection.retinaface import retinaface
- from modules.shared import cmd_opts
net_class = CodeFormer
diff --git a/modules/config_states.py b/modules/config_states.py
index 2ea00929..8f1ff428 100644
--- a/modules/config_states.py
+++ b/modules/config_states.py
@@ -14,7 +14,7 @@ from collections import OrderedDict
import git
from modules import shared, extensions
-from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path, config_states_dir
+from modules.paths_internal import script_path, config_states_dir
all_config_states = OrderedDict()
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index f4369257..85aa6934 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -6,7 +6,7 @@ from PIL import Image
from basicsr.utils.download_util import load_file_from_url
import modules.esrgan_model_arch as arch
-from modules import shared, modelloader, images, devices
+from modules import modelloader, images, devices
from modules.upscaler import Upscaler, UpscalerData
from modules.shared import opts
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
index 7f8bc7c0..4de9dd8d 100644
--- a/modules/esrgan_model_arch.py
+++ b/modules/esrgan_model_arch.py
@@ -2,7 +2,6 @@
from collections import OrderedDict
import math
-import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
diff --git a/modules/extensions.py b/modules/extensions.py
index 34d9d654..829f8cd9 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -3,7 +3,6 @@ import sys
import traceback
import time
-from datetime import datetime
import git
from modules import shared
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index fe8b18b2..f1c59c46 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -1,15 +1,11 @@
import base64
-import html
import io
-import math
import os
import re
-from pathlib import Path
import gradio as gr
from modules.paths import data_path
from modules import shared, ui_tempdir, script_callbacks
-import tempfile
from PIL import Image
re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)'
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 1fc49537..9fe749b7 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -1,4 +1,3 @@
-import csv
import datetime
import glob
import html
@@ -18,7 +17,7 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler
from torch import einsum
from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_
-from collections import defaultdict, deque
+from collections import deque
from statistics import stdev, mean
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index 76599f5a..be168736 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -1,6 +1,4 @@
import html
-import os
-import re
import gradio as gr
import modules.hypernetworks.hypernetwork
diff --git a/modules/images.py b/modules/images.py
index 5eb6d855..7392cb8b 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -19,7 +19,7 @@ import json
import hashlib
from modules import sd_samplers, shared, script_callbacks, errors
-from modules.shared import opts, cmd_opts
+from modules.shared import opts
LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
diff --git a/modules/img2img.py b/modules/img2img.py
index 32b1ecd6..d704bf90 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -1,12 +1,9 @@
-import math
import os
-import sys
-import traceback
import numpy as np
from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
-from modules import devices, sd_samplers
+from modules import sd_samplers
from modules.generation_parameters_copypaste import create_override_settings_dict
from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
from modules.shared import opts, state
diff --git a/modules/mac_specific.py b/modules/mac_specific.py
index 40ce2101..5c2f92a1 100644
--- a/modules/mac_specific.py
+++ b/modules/mac_specific.py
@@ -1,6 +1,5 @@
import torch
import platform
-from modules import paths
from modules.sd_hijack_utils import CondFunc
from packaging import version
diff --git a/modules/modelloader.py b/modules/modelloader.py
index cf685000..92ada694 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -1,4 +1,3 @@
-import glob
import os
import shutil
import importlib
diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py
index 11b330bc..a4c4ef4e 100644
--- a/modules/models/diffusion/uni_pc/uni_pc.py
+++ b/modules/models/diffusion/uni_pc/uni_pc.py
@@ -1,5 +1,4 @@
import torch
-import torch.nn.functional as F
import math
from tqdm.auto import trange
diff --git a/modules/processing.py b/modules/processing.py
index 6f5233c1..c3932d6b 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -2,7 +2,6 @@ import json
import math
import os
import sys
-import warnings
import hashlib
import torch
@@ -11,10 +10,10 @@ from PIL import Image, ImageFilter, ImageOps
import random
import cv2
from skimage import exposure
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
from modules.sd_hijack import model_hijack
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index d8135211..81573b78 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -3,7 +3,7 @@ from torch.nn.functional import silu
from types import MethodType
import modules.textual_inversion.textual_inversion
-from modules import devices, sd_hijack_optimizations, shared, sd_hijack_checkpoint
+from modules import devices, sd_hijack_optimizations, shared
from modules.hypernetworks import hypernetwork
from modules.shared import cmd_opts
from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr
diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py
index 55a2ce4d..344d75c8 100644
--- a/modules/sd_hijack_inpainting.py
+++ b/modules/sd_hijack_inpainting.py
@@ -1,15 +1,9 @@
-import os
import torch
-from einops import repeat
-from omegaconf import ListConfig
-
import ldm.models.diffusion.ddpm
import ldm.models.diffusion.ddim
import ldm.models.diffusion.plms
-from ldm.models.diffusion.ddpm import LatentDiffusion
-from ldm.models.diffusion.plms import PLMSSampler
from ldm.models.diffusion.ddim import DDIMSampler, noise_like
from ldm.models.diffusion.sampling_util import norm_thresholding
diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py
index 41ed54a2..6fe6b6ff 100644
--- a/modules/sd_hijack_ip2p.py
+++ b/modules/sd_hijack_ip2p.py
@@ -1,8 +1,5 @@
-import collections
import os.path
-import sys
-import gc
-import time
+
def should_hijack_ip2p(checkpoint_info):
from modules import sd_models_config
diff --git a/modules/sd_hijack_xlmr.py b/modules/sd_hijack_xlmr.py
index 4ac51c38..28528329 100644
--- a/modules/sd_hijack_xlmr.py
+++ b/modules/sd_hijack_xlmr.py
@@ -1,8 +1,6 @@
-import open_clip.tokenizer
import torch
from modules import sd_hijack_clip, devices
-from modules.shared import opts
class FrozenXLMREmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords):
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 11c1a344..1c09c709 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -565,7 +565,7 @@ def reload_model_weights(sd_model=None, info=None):
def unload_model_weights(sd_model=None, info=None):
- from modules import lowvram, devices, sd_hijack
+ from modules import devices, sd_hijack
timer = Timer()
if model_data.sd_model:
diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py
index 7a79925a..9bfe1237 100644
--- a/modules/sd_models_config.py
+++ b/modules/sd_models_config.py
@@ -1,4 +1,3 @@
-import re
import os
import torch
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 0fc9f456..3b8e9622 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -1,7 +1,6 @@
from collections import deque
import torch
import inspect
-import einops
import k_diffusion.sampling
from modules import prompt_parser, devices, sd_samplers_common
diff --git a/modules/sd_vae.py b/modules/sd_vae.py
index 521e485a..b7176125 100644
--- a/modules/sd_vae.py
+++ b/modules/sd_vae.py
@@ -1,8 +1,5 @@
-import torch
-import safetensors.torch
import os
import collections
-from collections import namedtuple
from modules import paths, shared, devices, script_callbacks, sd_models
import glob
from copy import deepcopy
diff --git a/modules/shared.py b/modules/shared.py
index 4631965b..44cd2c0c 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -1,12 +1,9 @@
-import argparse
import datetime
import json
import os
import sys
import time
-import requests
-from PIL import Image
import gradio as gr
import tqdm
diff --git a/modules/styles.py b/modules/styles.py
index 11642075..c22769cf 100644
--- a/modules/styles.py
+++ b/modules/styles.py
@@ -1,18 +1,9 @@
-# We need this so Python doesn't complain about the unknown StableDiffusionProcessing-typehint at runtime
-from __future__ import annotations
-
import csv
import os
import os.path
import typing
-import collections.abc as abc
-import tempfile
import shutil
-if typing.TYPE_CHECKING:
- # Only import this when code is being type-checked, it doesn't have any effect at runtime
- from .processing import StableDiffusionProcessing
-
class PromptStyle(typing.NamedTuple):
name: str
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py
index d7d8d2e3..7770d22f 100644
--- a/modules/textual_inversion/autocrop.py
+++ b/modules/textual_inversion/autocrop.py
@@ -1,10 +1,8 @@
import cv2
import requests
import os
-from collections import defaultdict
-from math import log, sqrt
import numpy as np
-from PIL import Image, ImageDraw
+from PIL import ImageDraw
GREEN = "#0F0"
BLUE = "#00F"
diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py
index 5593f88c..ee0e850a 100644
--- a/modules/textual_inversion/image_embedding.py
+++ b/modules/textual_inversion/image_embedding.py
@@ -2,7 +2,7 @@ import base64
import json
import numpy as np
import zlib
-from PIL import Image, PngImagePlugin, ImageDraw, ImageFont
+from PIL import Image, ImageDraw, ImageFont
from fonts.ttf import Roboto
import torch
from modules.shared import opts
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index da0bcb26..d0cad09e 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -1,13 +1,9 @@
import os
from PIL import Image, ImageOps
import math
-import platform
-import sys
import tqdm
-import time
from modules import paths, shared, images, deepbooru
-from modules.shared import opts, cmd_opts
from modules.textual_inversion import autocrop
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index f753b75f..9ed9ba45 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -1,7 +1,6 @@
import os
import sys
import traceback
-import inspect
from collections import namedtuple
import torch
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 16841d0f..f022381c 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -1,18 +1,15 @@
import modules.scripts
-from modules import sd_samplers
+from modules import sd_samplers, processing
from modules.generation_parameters_copypaste import create_override_settings_dict
-from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \
- StableDiffusionProcessingImg2Img, process_images
from modules.shared import opts, cmd_opts
import modules.shared as shared
-import modules.processing as processing
from modules.ui import plaintext_to_html
def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args):
override_settings = create_override_settings_dict(override_settings_texts)
- p = StableDiffusionProcessingTxt2Img(
+ p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
@@ -53,7 +50,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
processed = modules.scripts.scripts_txt2img.run(p, *args)
if processed is None:
- processed = process_images(p)
+ processed = processing.process_images(p)
p.close()
diff --git a/modules/ui.py b/modules/ui.py
index 6beda76f..f7e57593 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -14,10 +14,10 @@ from PIL import Image, PngImagePlugin
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress
-from modules.ui_components import FormRow, FormColumn, FormGroup, ToolButton, FormHTML
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path, data_path
-from modules.shared import opts, cmd_opts, restricted_opts
+from modules.shared import opts, cmd_opts
import modules.codeformer_model
import modules.generation_parameters_copypaste as parameters_copypaste
@@ -28,7 +28,6 @@ import modules.shared as shared
import modules.styles
import modules.textual_inversion.ui
from modules import prompt_parser
-from modules.images import save_image
from modules.sd_hijack import model_hijack
from modules.sd_samplers import samplers, samplers_for_img2img
from modules.textual_inversion import textual_inversion
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 49e06289..800e467a 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -1,4 +1,3 @@
-import glob
import os.path
import urllib.parse
from pathlib import Path
diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py
index f25639e5..c7dc1154 100644
--- a/modules/ui_postprocessing.py
+++ b/modules/ui_postprocessing.py
@@ -1,5 +1,5 @@
import gradio as gr
-from modules import scripts_postprocessing, scripts, shared, gfpgan_model, codeformer_model, ui_common, postprocessing, call_queue
+from modules import scripts, shared, ui_common, postprocessing, call_queue
import modules.generation_parameters_copypaste as parameters_copypaste
diff --git a/modules/upscaler.py b/modules/upscaler.py
index 0ad4fe99..777593b0 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -2,8 +2,6 @@ import os
from abc import abstractmethod
import PIL
-import numpy as np
-import torch
from PIL import Image
import modules.shared
diff --git a/modules/xlmr.py b/modules/xlmr.py
index beab3fdf..e056c3f6 100644
--- a/modules/xlmr.py
+++ b/modules/xlmr.py
@@ -1,4 +1,4 @@
-from transformers import BertPreTrainedModel,BertModel,BertConfig
+from transformers import BertPreTrainedModel, BertConfig
import torch.nn as nn
import torch
from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig
diff --git a/pyproject.toml b/pyproject.toml
index 1e164abc..9caa9ba2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,10 +1,13 @@
[tool.ruff]
+exclude = ["extensions"]
+
ignore = [
"E501",
- "E731",
- "E402", # Module level import not at top of file
- "F401" # Module imported but unused
+
+ "F401", # Module imported but unused
]
-exclude = ["extensions"]
+
+[tool.ruff.per-file-ignores]
+"webui.py" = ["E402"] # Module level import not at top of file
\ No newline at end of file
diff --git a/scripts/custom_code.py b/scripts/custom_code.py
index f36a3675..cc6f0d49 100644
--- a/scripts/custom_code.py
+++ b/scripts/custom_code.py
@@ -4,7 +4,7 @@ import ast
import copy
from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import cmd_opts
def convertExpr2Expression(expr):
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index b10fed6c..665dbe89 100644
--- a/scripts/outpainting_mk_2.py
+++ b/scripts/outpainting_mk_2.py
@@ -7,9 +7,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image, ImageDraw
-from modules import images, processing, devices
+from modules import images
from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
# this function is taken from https://github.com/parlance-zz/g-diffuser-bot
diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py
index ddcbd2d3..c0bbecc1 100644
--- a/scripts/poor_mans_outpainting.py
+++ b/scripts/poor_mans_outpainting.py
@@ -4,9 +4,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image, ImageDraw
-from modules import images, processing, devices
+from modules import images, devices
from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
class Script(scripts.Script):
diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py
index e9b11517..fb06beab 100644
--- a/scripts/prompt_matrix.py
+++ b/scripts/prompt_matrix.py
@@ -1,14 +1,11 @@
import math
-from collections import namedtuple
-from copy import copy
-import random
import modules.scripts as scripts
import gradio as gr
from modules import images
-from modules.processing import process_images, Processed
-from modules.shared import opts, cmd_opts, state
+from modules.processing import process_images
+from modules.shared import opts, state
import modules.sd_samplers
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 76dc5778..149bc85f 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -1,6 +1,4 @@
import copy
-import math
-import os
import random
import sys
import traceback
@@ -11,8 +9,7 @@ import gradio as gr
from modules import sd_samplers
from modules.processing import Processed, process_images
-from PIL import Image
-from modules.shared import opts, cmd_opts, state
+from modules.shared import state
def process_string_tag(tag):
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index 332d76d9..d873a09c 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -4,9 +4,9 @@ import modules.scripts as scripts
import gradio as gr
from PIL import Image
-from modules import processing, shared, sd_samplers, images, devices
+from modules import processing, shared, images, devices
from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
class Script(scripts.Script):
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 2ff42ef8..332e0ecd 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -10,15 +10,13 @@ import numpy as np
import modules.scripts as scripts
import gradio as gr
-from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
+from modules import images, sd_samplers, processing, sd_models, sd_vae
from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
import modules.shared as shared
import modules.sd_samplers
import modules.sd_models
import modules.sd_vae
-import glob
-import os
import re
from modules.ui_components import ToolButton
diff --git a/webui.py b/webui.py
index ec3d2aba..48277075 100644
--- a/webui.py
+++ b/webui.py
@@ -43,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
torch.__long_version__ = torch.__version__
torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
-from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
+from modules import shared, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
import modules.codeformer_model as codeformer
import modules.face_restoration
import modules.gfpgan_model as gfpgan
--
cgit v1.2.3
From 4b854806d98cf5ccd48e5cd99c172613da7937f0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 09:02:23 +0300
Subject: F401 fixes for ruff
---
extensions-builtin/LDSR/scripts/ldsr_model.py | 4 ++--
modules/cmd_args.py | 2 +-
modules/deepbooru.py | 1 -
modules/extensions.py | 2 +-
modules/gfpgan_model.py | 2 +-
modules/models/diffusion/uni_pc/__init__.py | 2 +-
modules/paths.py | 4 ++--
modules/realesrgan_model.py | 6 +++---
modules/script_loading.py | 1 -
modules/sd_hijack_inpainting.py | 2 +-
modules/sd_models.py | 4 +---
modules/sd_samplers.py | 2 +-
modules/shared.py | 2 +-
modules/ui.py | 4 ++--
modules/upscaler.py | 2 +-
pyproject.toml | 9 +++++----
webui.py | 8 ++++----
17 files changed, 27 insertions(+), 30 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py
index e8dc083c..fbbe9005 100644
--- a/extensions-builtin/LDSR/scripts/ldsr_model.py
+++ b/extensions-builtin/LDSR/scripts/ldsr_model.py
@@ -7,8 +7,8 @@ from basicsr.utils.download_util import load_file_from_url
from modules.upscaler import Upscaler, UpscalerData
from ldsr_model_arch import LDSR
from modules import shared, script_callbacks
-import sd_hijack_autoencoder
-import sd_hijack_ddpm_v1
+import sd_hijack_autoencoder # noqa: F401
+import sd_hijack_ddpm_v1 # noqa: F401
class UpscalerLDSR(Upscaler):
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index d906a571..e01ca655 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -1,6 +1,6 @@
import argparse
import os
-from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file
+from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file # noqa: F401
parser = argparse.ArgumentParser()
diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 122fce7f..1c4554a2 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -2,7 +2,6 @@ import os
import re
import torch
-from PIL import Image
import numpy as np
from modules import modelloader, paths, deepbooru_model, devices, images, shared
diff --git a/modules/extensions.py b/modules/extensions.py
index 829f8cd9..bc2c0450 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -6,7 +6,7 @@ import time
import git
from modules import shared
-from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path
+from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401
extensions = []
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py
index fbe6215a..0131dea4 100644
--- a/modules/gfpgan_model.py
+++ b/modules/gfpgan_model.py
@@ -78,7 +78,7 @@ def setup_model(dirname):
try:
from gfpgan import GFPGANer
- from facexlib import detection, parsing
+ from facexlib import detection, parsing # noqa: F401
global user_path
global have_gfpgan
global gfpgan_constructor
diff --git a/modules/models/diffusion/uni_pc/__init__.py b/modules/models/diffusion/uni_pc/__init__.py
index e1265e3f..dbb35964 100644
--- a/modules/models/diffusion/uni_pc/__init__.py
+++ b/modules/models/diffusion/uni_pc/__init__.py
@@ -1 +1 @@
-from .sampler import UniPCSampler
+from .sampler import UniPCSampler # noqa: F401
diff --git a/modules/paths.py b/modules/paths.py
index acf1894b..5f6474c0 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -1,8 +1,8 @@
import os
import sys
-from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir
+from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir # noqa: F401
-import modules.safe
+import modules.safe # noqa: F401
# data_path = cmd_opts_pre.data
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py
index 9ec1adf2..c24d8dbb 100644
--- a/modules/realesrgan_model.py
+++ b/modules/realesrgan_model.py
@@ -17,9 +17,9 @@ class UpscalerRealESRGAN(Upscaler):
self.user_path = path
super().__init__()
try:
- from basicsr.archs.rrdbnet_arch import RRDBNet
- from realesrgan import RealESRGANer
- from realesrgan.archs.srvgg_arch import SRVGGNetCompact
+ from basicsr.archs.rrdbnet_arch import RRDBNet # noqa: F401
+ from realesrgan import RealESRGANer # noqa: F401
+ from realesrgan.archs.srvgg_arch import SRVGGNetCompact # noqa: F401
self.enable = True
self.scalers = []
scalers = self.load_models(path)
diff --git a/modules/script_loading.py b/modules/script_loading.py
index a7d2203f..57b15862 100644
--- a/modules/script_loading.py
+++ b/modules/script_loading.py
@@ -2,7 +2,6 @@ import os
import sys
import traceback
import importlib.util
-from types import ModuleType
def load_module(path):
diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py
index 344d75c8..058575b7 100644
--- a/modules/sd_hijack_inpainting.py
+++ b/modules/sd_hijack_inpainting.py
@@ -4,7 +4,7 @@ import ldm.models.diffusion.ddpm
import ldm.models.diffusion.ddim
import ldm.models.diffusion.plms
-from ldm.models.diffusion.ddim import DDIMSampler, noise_like
+from ldm.models.diffusion.ddim import noise_like
from ldm.models.diffusion.sampling_util import norm_thresholding
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 1c09c709..d1e946a5 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -15,7 +15,6 @@ import ldm.modules.midas as midas
from ldm.util import instantiate_from_config
from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config
-from modules.paths import models_path
from modules.sd_hijack_inpainting import do_inpainting_hijack
from modules.timer import Timer
@@ -87,8 +86,7 @@ class CheckpointInfo:
try:
# this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
-
- from transformers import logging, CLIPModel
+ from transformers import logging, CLIPModel # noqa: F401
logging.set_verbosity_error()
except Exception:
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index ff361f22..4f1bf21d 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -1,7 +1,7 @@
from modules import sd_samplers_compvis, sd_samplers_kdiffusion, shared
# imports for functions that previously were here and are used by other modules
-from modules.sd_samplers_common import samples_to_image_grid, sample_to_image
+from modules.sd_samplers_common import samples_to_image_grid, sample_to_image # noqa: F401
all_samplers = [
*sd_samplers_kdiffusion.samplers_data_k_diffusion,
diff --git a/modules/shared.py b/modules/shared.py
index 44cd2c0c..7d70f041 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -12,7 +12,7 @@ import modules.memmon
import modules.styles
import modules.devices as devices
from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args
-from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir
+from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401
from ldm.models.diffusion.ddpm import LatentDiffusion
demo = None
diff --git a/modules/ui.py b/modules/ui.py
index f7e57593..782b569d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -10,10 +10,10 @@ import gradio as gr
import gradio.routes
import gradio.utils
import numpy as np
-from PIL import Image, PngImagePlugin
+from PIL import Image, PngImagePlugin # noqa: F401
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path, data_path
diff --git a/modules/upscaler.py b/modules/upscaler.py
index 777593b0..e145be30 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -41,7 +41,7 @@ class Upscaler:
os.makedirs(self.model_path, exist_ok=True)
try:
- import cv2
+ import cv2 # noqa: F401
self.can_tile = True
except Exception:
pass
diff --git a/pyproject.toml b/pyproject.toml
index 9caa9ba2..0883c127 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,13 +1,14 @@
[tool.ruff]
+target-version = "py310"
+
exclude = ["extensions"]
ignore = [
- "E501",
-
- "F401", # Module imported but unused
+ "E501", # Line too long
+ "E731", # Do not assign a `lambda` expression, use a `def`
]
[tool.ruff.per-file-ignores]
-"webui.py" = ["E402"] # Module level import not at top of file
\ No newline at end of file
+"webui.py" = ["E402"] # Module level import not at top of file
diff --git a/webui.py b/webui.py
index 48277075..5d5e80b5 100644
--- a/webui.py
+++ b/webui.py
@@ -16,12 +16,12 @@ from packaging import version
import logging
logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
-from modules import paths, timer, import_hook, errors
+from modules import paths, timer, import_hook, errors # noqa: F401
startup_timer = timer.Timer()
import torch
-import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
+import pytorch_lightning # noqa: F401 # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
@@ -31,12 +31,12 @@ startup_timer.record("import torch")
import gradio
startup_timer.record("import gradio")
-import ldm.modules.encoders.modules
+import ldm.modules.encoders.modules # noqa: F401
startup_timer.record("import ldm")
from modules import extra_networks, ui_extra_networks_checkpoints
from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
-from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call
+from modules.call_queue import wrap_queued_call, queue_lock
# Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors
if ".dev" in torch.__version__ or "+git" in torch.__version__:
--
cgit v1.2.3
From 028d3f6425d85f122027c127fba8bcbf4f66ee75 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 11:05:02 +0300
Subject: ruff auto fixes
---
extensions-builtin/LDSR/sd_hijack_autoencoder.py | 4 ++--
extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 12 ++++++------
extensions-builtin/Lora/lora.py | 12 ++++++------
extensions-builtin/Lora/scripts/lora_script.py | 2 +-
modules/config_states.py | 2 +-
modules/deepbooru.py | 2 +-
modules/devices.py | 2 +-
modules/hypernetworks/hypernetwork.py | 2 +-
modules/hypernetworks/ui.py | 4 ++--
modules/interrogate.py | 2 +-
modules/modelloader.py | 2 +-
modules/models/diffusion/ddpm_edit.py | 4 ++--
modules/scripts_auto_postprocessing.py | 2 +-
modules/sd_hijack.py | 2 +-
modules/sd_hijack_optimizations.py | 14 +++++++-------
modules/sd_samplers_compvis.py | 2 +-
modules/sd_samplers_kdiffusion.py | 2 +-
modules/shared.py | 6 +++---
modules/textual_inversion/textual_inversion.py | 2 +-
modules/ui.py | 8 ++++----
modules/ui_extra_networks.py | 4 ++--
modules/ui_tempdir.py | 2 +-
22 files changed, 47 insertions(+), 47 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
index 6303fed5..f457ca93 100644
--- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py
+++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py
@@ -288,5 +288,5 @@ class VQModelInterface(VQModel):
dec = self.decoder(quant)
return dec
-setattr(ldm.models.autoencoder, "VQModel", VQModel)
-setattr(ldm.models.autoencoder, "VQModelInterface", VQModelInterface)
+ldm.models.autoencoder.VQModel = VQModel
+ldm.models.autoencoder.VQModelInterface = VQModelInterface
diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
index 4d3f6c56..d8fc30e3 100644
--- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
+++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
@@ -1116,7 +1116,7 @@ class LatentDiffusionV1(DDPMV1):
if cond is not None:
if isinstance(cond, dict):
cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
- list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
+ [x[:batch_size] for x in cond[key]] for key in cond}
else:
cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
@@ -1215,7 +1215,7 @@ class LatentDiffusionV1(DDPMV1):
if cond is not None:
if isinstance(cond, dict):
cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
- list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
+ [x[:batch_size] for x in cond[key]] for key in cond}
else:
cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
return self.p_sample_loop(cond,
@@ -1437,7 +1437,7 @@ class Layout2ImgDiffusionV1(LatentDiffusionV1):
logs['bbox_image'] = cond_img
return logs
-setattr(ldm.models.diffusion.ddpm, "DDPMV1", DDPMV1)
-setattr(ldm.models.diffusion.ddpm, "LatentDiffusionV1", LatentDiffusionV1)
-setattr(ldm.models.diffusion.ddpm, "DiffusionWrapperV1", DiffusionWrapperV1)
-setattr(ldm.models.diffusion.ddpm, "Layout2ImgDiffusionV1", Layout2ImgDiffusionV1)
+ldm.models.diffusion.ddpm.DDPMV1 = DDPMV1
+ldm.models.diffusion.ddpm.LatentDiffusionV1 = LatentDiffusionV1
+ldm.models.diffusion.ddpm.DiffusionWrapperV1 = DiffusionWrapperV1
+ldm.models.diffusion.ddpm.Layout2ImgDiffusionV1 = Layout2ImgDiffusionV1
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
index 0ab43229..9795540f 100644
--- a/extensions-builtin/Lora/lora.py
+++ b/extensions-builtin/Lora/lora.py
@@ -172,7 +172,7 @@ def load_lora(name, filename):
else:
print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}')
continue
- assert False, f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}'
+ raise AssertionError(f"Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}")
with torch.no_grad():
module.weight.copy_(weight)
@@ -184,7 +184,7 @@ def load_lora(name, filename):
elif lora_key == "lora_down.weight":
lora_module.down = module
else:
- assert False, f'Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha'
+ raise AssertionError(f"Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha")
if len(keys_failed_to_match) > 0:
print(f"Failed to match keys when loading Lora {filename}: {keys_failed_to_match}")
@@ -202,7 +202,7 @@ def load_loras(names, multipliers=None):
loaded_loras.clear()
loras_on_disk = [available_lora_aliases.get(name, None) for name in names]
- if any([x is None for x in loras_on_disk]):
+ if any(x is None for x in loras_on_disk):
list_available_loras()
loras_on_disk = [available_lora_aliases.get(name, None) for name in names]
@@ -309,7 +309,7 @@ def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.Mu
print(f'failed to calculate lora weights for layer {lora_layer_name}')
- setattr(self, "lora_current_names", wanted_names)
+ self.lora_current_names = wanted_names
def lora_forward(module, input, original_forward):
@@ -343,8 +343,8 @@ def lora_forward(module, input, original_forward):
def lora_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]):
- setattr(self, "lora_current_names", ())
- setattr(self, "lora_weights_backup", None)
+ self.lora_current_names = ()
+ self.lora_weights_backup = None
def lora_Linear_forward(self, input):
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index 7db971fd..b70e2de7 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -53,7 +53,7 @@ script_callbacks.on_infotext_pasted(lora.infotext_pasted)
shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
- "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
+ "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(lora.available_loras)}, refresh=lora.list_available_loras),
}))
diff --git a/modules/config_states.py b/modules/config_states.py
index 8f1ff428..75da862a 100644
--- a/modules/config_states.py
+++ b/modules/config_states.py
@@ -35,7 +35,7 @@ def list_config_states():
j["filepath"] = path
config_states.append(j)
- config_states = list(sorted(config_states, key=lambda cs: cs["created_at"], reverse=True))
+ config_states = sorted(config_states, key=lambda cs: cs["created_at"], reverse=True)
for cs in config_states:
timestamp = time.asctime(time.gmtime(cs["created_at"]))
diff --git a/modules/deepbooru.py b/modules/deepbooru.py
index 1c4554a2..547e1b4c 100644
--- a/modules/deepbooru.py
+++ b/modules/deepbooru.py
@@ -78,7 +78,7 @@ class DeepDanbooru:
res = []
- filtertags = set([x.strip().replace(' ', '_') for x in shared.opts.deepbooru_filter_tags.split(",")])
+ filtertags = {x.strip().replace(' ', '_') for x in shared.opts.deepbooru_filter_tags.split(",")}
for tag in [x for x in tags if x not in filtertags]:
probability = probability_dict[tag]
diff --git a/modules/devices.py b/modules/devices.py
index c705a3cb..d8a34a0f 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -65,7 +65,7 @@ def enable_tf32():
# enabling benchmark option seems to enable a range of cards to do fp16 when they otherwise can't
# see https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/4407
- if any([torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())]):
+ if any(torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())):
torch.backends.cudnn.benchmark = True
torch.backends.cuda.matmul.allow_tf32 = True
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 9fe749b7..6ef0bfdf 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -403,7 +403,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
k = self.to_k(context_k)
v = self.to_v(context_v)
- q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+ q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v))
sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index be168736..e3f9eb13 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -5,13 +5,13 @@ 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)
+keys = [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}", ""
+ return gr.Dropdown.update(choices=sorted(shared.hypernetworks.keys())), f"Created: {filename}", ""
def train_hypernetwork(*args):
diff --git a/modules/interrogate.py b/modules/interrogate.py
index 22df9216..a1c8e537 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -159,7 +159,7 @@ class InterrogateModels:
text_array = text_array[0:int(shared.opts.interrogate_clip_dict_limit)]
top_count = min(top_count, len(text_array))
- text_tokens = clip.tokenize([text for text in text_array], truncate=True).to(devices.device_interrogate)
+ text_tokens = clip.tokenize(list(text_array), truncate=True).to(devices.device_interrogate)
text_features = self.clip_model.encode_text(text_tokens).type(self.dtype)
text_features /= text_features.norm(dim=-1, keepdim=True)
diff --git a/modules/modelloader.py b/modules/modelloader.py
index 92ada694..25612bf8 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -39,7 +39,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
if os.path.islink(full_path) and not os.path.exists(full_path):
print(f"Skipping broken symlink: {full_path}")
continue
- if ext_blacklist is not None and any([full_path.endswith(x) for x in ext_blacklist]):
+ if ext_blacklist is not None and any(full_path.endswith(x) for x in ext_blacklist):
continue
if full_path not in output:
output.append(full_path)
diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py
index 611c2b69..09432117 100644
--- a/modules/models/diffusion/ddpm_edit.py
+++ b/modules/models/diffusion/ddpm_edit.py
@@ -1130,7 +1130,7 @@ class LatentDiffusion(DDPM):
if cond is not None:
if isinstance(cond, dict):
cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
- list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
+ [x[:batch_size] for x in cond[key]] for key in cond}
else:
cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
@@ -1229,7 +1229,7 @@ class LatentDiffusion(DDPM):
if cond is not None:
if isinstance(cond, dict):
cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
- list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
+ [x[:batch_size] for x in cond[key]] for key in cond}
else:
cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
return self.p_sample_loop(cond,
diff --git a/modules/scripts_auto_postprocessing.py b/modules/scripts_auto_postprocessing.py
index 30d6d658..d63078de 100644
--- a/modules/scripts_auto_postprocessing.py
+++ b/modules/scripts_auto_postprocessing.py
@@ -17,7 +17,7 @@ class ScriptPostprocessingForMainUI(scripts.Script):
return self.postprocessing_controls.values()
def postprocess_image(self, p, script_pp, *args):
- args_dict = {k: v for k, v in zip(self.postprocessing_controls, args)}
+ args_dict = dict(zip(self.postprocessing_controls, args))
pp = scripts_postprocessing.PostprocessedImage(script_pp.image)
pp.info = {}
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 81573b78..e374aeb8 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -37,7 +37,7 @@ def apply_optimizations():
optimization_method = None
- can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(getattr(torch.nn.functional, "scaled_dot_product_attention")) # not everyone has torch 2.x to use sdp
+ can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp
if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0)):
print("Applying xformers cross attention optimization.")
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index b623d53d..a174bbe1 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -49,7 +49,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
v_in = self.to_v(context_v)
del context, context_k, context_v, x
- q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+ q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in))
del q_in, k_in, v_in
dtype = q.dtype
@@ -98,7 +98,7 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
del context, x
- q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
+ q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in))
del q_in, k_in, v_in
r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
@@ -229,7 +229,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
with devices.without_autocast(disable=not shared.opts.upcast_attn):
k = k * self.scale
- q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
+ q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v))
r = einsum_op(q, k, v)
r = r.to(dtype)
return self.to_out(rearrange(r, '(b h) n d -> b n (h d)', h=h))
@@ -334,7 +334,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
k_in = self.to_k(context_k)
v_in = self.to_v(context_v)
- q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b n h d', h=h), (q_in, k_in, v_in))
+ q, k, v = (rearrange(t, 'b n (h d) -> b n h d', h=h) for t in (q_in, k_in, v_in))
del q_in, k_in, v_in
dtype = q.dtype
@@ -460,7 +460,7 @@ def xformers_attnblock_forward(self, x):
k = self.k(h_)
v = self.v(h_)
b, c, h, w = q.shape
- q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v))
+ q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v))
dtype = q.dtype
if shared.opts.upcast_attn:
q, k = q.float(), k.float()
@@ -482,7 +482,7 @@ def sdp_attnblock_forward(self, x):
k = self.k(h_)
v = self.v(h_)
b, c, h, w = q.shape
- q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v))
+ q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v))
dtype = q.dtype
if shared.opts.upcast_attn:
q, k = q.float(), k.float()
@@ -506,7 +506,7 @@ def sub_quad_attnblock_forward(self, x):
k = self.k(h_)
v = self.v(h_)
b, c, h, w = q.shape
- q, k, v = map(lambda t: rearrange(t, 'b c h w -> b (h w) c'), (q, k, v))
+ q, k, v = (rearrange(t, 'b c h w -> b (h w) c') for t in (q, k, v))
q = q.contiguous()
k = k.contiguous()
v = v.contiguous()
diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py
index bfcc5574..7427648f 100644
--- a/modules/sd_samplers_compvis.py
+++ b/modules/sd_samplers_compvis.py
@@ -83,7 +83,7 @@ class VanillaStableDiffusionSampler:
conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step)
unconditional_conditioning = prompt_parser.reconstruct_cond_batch(unconditional_conditioning, self.step)
- assert all([len(conds) == 1 for conds in conds_list]), 'composition via AND is not supported for DDIM/PLMS samplers'
+ assert all(len(conds) == 1 for conds in conds_list), 'composition via AND is not supported for DDIM/PLMS samplers'
cond = tensor
# for DDIM, shapes must match, we can't just process cond and uncond independently;
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 3b8e9622..2f733cf5 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -86,7 +86,7 @@ class CFGDenoiser(torch.nn.Module):
conds_list, tensor = prompt_parser.reconstruct_multicond_batch(cond, self.step)
uncond = prompt_parser.reconstruct_cond_batch(uncond, self.step)
- assert not is_edit_model or all([len(conds) == 1 for conds in conds_list]), "AND is not supported for InstructPix2Pix checkpoint (unless using Image CFG scale = 1.0)"
+ assert not is_edit_model or all(len(conds) == 1 for conds in conds_list), "AND is not supported for InstructPix2Pix checkpoint (unless using Image CFG scale = 1.0)"
batch_size = len(conds_list)
repeats = [len(conds_list[i]) for i in range(batch_size)]
diff --git a/modules/shared.py b/modules/shared.py
index 7d70f041..e2691585 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
"extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
"extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
"extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
- "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+ "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(hypernetworks.keys())}, refresh=reload_hypernetworks),
}))
options_templates.update(options_section(('ui', "User interface"), {
@@ -403,7 +403,7 @@ options_templates.update(options_section(('ui', "User interface"), {
"keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
"keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
"quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}),
- "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}),
+ "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}),
"ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
"ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"),
"localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)),
@@ -583,7 +583,7 @@ class Options:
if item.section not in section_ids:
section_ids[item.section] = len(section_ids)
- self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])}
+ self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section]))
def cast_value(self, key, value):
"""casts an arbitrary to the same type as this setting's value with key
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 9ed9ba45..c37bb2ad 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -167,7 +167,7 @@ class EmbeddingDatabase:
if 'string_to_param' in data:
param_dict = data['string_to_param']
if hasattr(param_dict, '_parameters'):
- param_dict = getattr(param_dict, '_parameters') # fix for torch 1.12.1 loading saved file from torch 1.11
+ param_dict = param_dict._parameters # fix for torch 1.12.1 loading saved file from torch 1.11
assert len(param_dict) == 1, 'embedding file has multiple terms in it'
emb = next(iter(param_dict.items()))[1]
# diffuser concepts
diff --git a/modules/ui.py b/modules/ui.py
index 782b569d..84d661b2 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1222,7 +1222,7 @@ def create_ui():
)
def get_textual_inversion_template_names():
- return sorted([x for x in textual_inversion.textual_inversion_templates])
+ return sorted(textual_inversion.textual_inversion_templates)
with gr.Tab(label="Train", id="train"):
gr.HTML(value="Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images [wiki]
")
@@ -1230,8 +1230,8 @@ def create_ui():
train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
- train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
- create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
+ train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=list(shared.hypernetworks.keys()))
+ create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks.keys())}, "refresh_train_hypernetwork_name")
with FormRow():
embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
@@ -1808,7 +1808,7 @@ def create_ui():
if type(x) == gr.Dropdown:
def check_dropdown(val):
if getattr(x, 'multiselect', False):
- return all([value in x.choices for value in val])
+ return all(value in x.choices for value in val)
else:
return val in x.choices
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 800e467a..ab585917 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -26,7 +26,7 @@ def register_page(page):
def fetch_file(filename: str = ""):
from starlette.responses import FileResponse
- if not any([Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs]):
+ if not any(Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs):
raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.")
ext = os.path.splitext(filename)[1].lower()
@@ -326,7 +326,7 @@ def setup_ui(ui, gallery):
is_allowed = False
for extra_page in ui.stored_extra_pages:
- if any([path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()]):
+ if any(path_is_parent(x, filename) for x in extra_page.allowed_directories_for_previews()):
is_allowed = True
break
diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py
index 46fa9cb0..cac73c51 100644
--- a/modules/ui_tempdir.py
+++ b/modules/ui_tempdir.py
@@ -23,7 +23,7 @@ def register_tmp_file(gradio, filename):
def check_tmp_file(gradio, filename):
if hasattr(gradio, 'temp_file_sets'):
- return any([filename in fileset for fileset in gradio.temp_file_sets])
+ return any(filename in fileset for fileset in gradio.temp_file_sets)
if hasattr(gradio, 'temp_dirs'):
return any(Path(temp_dir).resolve() in Path(filename).resolve().parents for temp_dir in gradio.temp_dirs)
--
cgit v1.2.3
From a5121e7a0623db328a9462d340d389ed6737374a Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 11:37:18 +0300
Subject: fixes for B007
---
extensions-builtin/LDSR/ldsr_model_arch.py | 2 +-
extensions-builtin/Lora/lora.py | 2 +-
extensions-builtin/ScuNET/scripts/scunet_model.py | 2 +-
extensions-builtin/SwinIR/swinir_model_arch.py | 2 +-
extensions-builtin/SwinIR/swinir_model_arch_v2.py | 2 +-
modules/codeformer_model.py | 2 +-
modules/esrgan_model.py | 8 ++------
modules/extra_networks.py | 2 +-
modules/generation_parameters_copypaste.py | 2 +-
modules/hypernetworks/hypernetwork.py | 12 ++++++------
modules/images.py | 2 +-
modules/interrogate.py | 4 ++--
modules/prompt_parser.py | 14 +++++++-------
modules/safe.py | 4 ++--
modules/scripts.py | 10 +++++-----
modules/scripts_postprocessing.py | 8 ++++----
modules/sd_hijack_clip.py | 2 +-
modules/shared.py | 6 +++---
modules/textual_inversion/learn_schedule.py | 2 +-
modules/textual_inversion/textual_inversion.py | 10 +++++-----
modules/ui.py | 6 +++---
modules/ui_extra_networks.py | 2 +-
modules/ui_tempdir.py | 2 +-
modules/upscaler.py | 2 +-
pyproject.toml | 1 -
scripts/prompts_from_file.py | 2 +-
scripts/sd_upscale.py | 4 ++--
scripts/xyz_grid.py | 2 +-
28 files changed, 57 insertions(+), 62 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index a5fb8907..27e38549 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -88,7 +88,7 @@ class LDSR:
x_t = None
logs = None
- for n in range(n_runs):
+ for _ in range(n_runs):
if custom_shape is not None:
x_t = torch.randn(1, custom_shape[1], custom_shape[2], custom_shape[3]).to(model.device)
x_t = repeat(x_t, '1 c h w -> b c h w', b=custom_shape[0])
diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py
index 9795540f..7b56136f 100644
--- a/extensions-builtin/Lora/lora.py
+++ b/extensions-builtin/Lora/lora.py
@@ -418,7 +418,7 @@ def infotext_pasted(infotext, params):
added = []
- for k, v in params.items():
+ for k in params:
if not k.startswith("AddNet Model "):
continue
diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py
index aa2fdb3a..1f5ea0d3 100644
--- a/extensions-builtin/ScuNET/scripts/scunet_model.py
+++ b/extensions-builtin/ScuNET/scripts/scunet_model.py
@@ -132,7 +132,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler):
model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64)
model.load_state_dict(torch.load(filename), strict=True)
model.eval()
- for k, v in model.named_parameters():
+ for _, v in model.named_parameters():
v.requires_grad = False
model = model.to(device)
diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py
index 75f7bedc..de195d9b 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch.py
@@ -848,7 +848,7 @@ class SwinIR(nn.Module):
H, W = self.patches_resolution
flops += H * W * 3 * self.embed_dim * 9
flops += self.patch_embed.flops()
- for i, layer in enumerate(self.layers):
+ for layer in self.layers:
flops += layer.flops()
flops += H * W * 3 * self.embed_dim * self.embed_dim
flops += self.upsample.flops()
diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
index d4c0b0da..15777af9 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
@@ -1001,7 +1001,7 @@ class Swin2SR(nn.Module):
H, W = self.patches_resolution
flops += H * W * 3 * self.embed_dim * 9
flops += self.patch_embed.flops()
- for i, layer in enumerate(self.layers):
+ for layer in self.layers:
flops += layer.flops()
flops += H * W * 3 * self.embed_dim * self.embed_dim
flops += self.upsample.flops()
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
index 8e56cb89..ececdbae 100644
--- a/modules/codeformer_model.py
+++ b/modules/codeformer_model.py
@@ -94,7 +94,7 @@ def setup_model(dirname):
self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5)
self.face_helper.align_warp_face()
- for idx, cropped_face in enumerate(self.face_helper.cropped_faces):
+ for cropped_face in self.face_helper.cropped_faces:
cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
cropped_face_t = cropped_face_t.unsqueeze(0).to(devices.device_codeformer)
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py
index 85aa6934..a009eb42 100644
--- a/modules/esrgan_model.py
+++ b/modules/esrgan_model.py
@@ -16,9 +16,7 @@ def mod2normal(state_dict):
# this code is copied from https://github.com/victorca25/iNNfer
if 'conv_first.weight' in state_dict:
crt_net = {}
- items = []
- for k, v in state_dict.items():
- items.append(k)
+ items = list(state_dict)
crt_net['model.0.weight'] = state_dict['conv_first.weight']
crt_net['model.0.bias'] = state_dict['conv_first.bias']
@@ -52,9 +50,7 @@ def resrgan2normal(state_dict, nb=23):
if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict:
re8x = 0
crt_net = {}
- items = []
- for k, v in state_dict.items():
- items.append(k)
+ items = list(state_dict)
crt_net['model.0.weight'] = state_dict['conv_first.weight']
crt_net['model.0.bias'] = state_dict['conv_first.bias']
diff --git a/modules/extra_networks.py b/modules/extra_networks.py
index 1978673d..f9db41bc 100644
--- a/modules/extra_networks.py
+++ b/modules/extra_networks.py
@@ -91,7 +91,7 @@ def deactivate(p, extra_network_data):
"""call deactivate for extra networks in extra_network_data in specified order, then call
deactivate for all remaining registered networks"""
- for extra_network_name, extra_network_args in extra_network_data.items():
+ for extra_network_name in extra_network_data:
extra_network = extra_network_registry.get(extra_network_name, None)
if extra_network is None:
continue
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 7fbbe707..b0e945a1 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -247,7 +247,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
lines.append(lastline)
lastline = ''
- for i, line in enumerate(lines):
+ for line in lines:
line = line.strip()
if line.startswith("Negative prompt:"):
done_with_prompt = True
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 6ef0bfdf..38ef074f 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -177,34 +177,34 @@ class Hypernetwork:
def weights(self):
res = []
- for k, layers in self.layers.items():
+ for layers in self.layers.values():
for layer in layers:
res += layer.parameters()
return res
def train(self, mode=True):
- for k, layers in self.layers.items():
+ for layers in self.layers.values():
for layer in layers:
layer.train(mode=mode)
for param in layer.parameters():
param.requires_grad = mode
def to(self, device):
- for k, layers in self.layers.items():
+ for layers in self.layers.values():
for layer in layers:
layer.to(device)
return self
def set_multiplier(self, multiplier):
- for k, layers in self.layers.items():
+ for layers in self.layers.values():
for layer in layers:
layer.multiplier = multiplier
return self
def eval(self):
- for k, layers in self.layers.items():
+ for layers in self.layers.values():
for layer in layers:
layer.eval()
for param in layer.parameters():
@@ -619,7 +619,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
try:
sd_hijack_checkpoint.add()
- for i in range((steps-initial_step) * gradient_step):
+ for _ in range((steps-initial_step) * gradient_step):
if scheduler.finished:
break
if shared.state.interrupted:
diff --git a/modules/images.py b/modules/images.py
index 7392cb8b..c4e98c75 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -149,7 +149,7 @@ def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0):
return ImageFont.truetype(Roboto, fontsize)
def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize):
- for i, line in enumerate(lines):
+ for line in lines:
fnt = initial_fnt
fontsize = initial_fontsize
while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0:
diff --git a/modules/interrogate.py b/modules/interrogate.py
index a1c8e537..111b1322 100644
--- a/modules/interrogate.py
+++ b/modules/interrogate.py
@@ -207,8 +207,8 @@ class InterrogateModels:
image_features /= image_features.norm(dim=-1, keepdim=True)
- for name, topn, items in self.categories():
- matches = self.rank(image_features, items, top_count=topn)
+ for cat in self.categories():
+ matches = self.rank(image_features, cat.items, top_count=cat.topn)
for match, score in matches:
if shared.opts.interrogate_return_ranks:
res += f", ({match}:{score/100:.3f})"
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 3a720721..b4aff704 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -143,7 +143,7 @@ def get_learned_conditioning(model, prompts, steps):
conds = model.get_learned_conditioning(texts)
cond_schedule = []
- for i, (end_at_step, text) in enumerate(prompt_schedule):
+ for i, (end_at_step, _) in enumerate(prompt_schedule):
cond_schedule.append(ScheduledPromptConditioning(end_at_step, conds[i]))
cache[prompt] = cond_schedule
@@ -219,8 +219,8 @@ def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_s
res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype)
for i, cond_schedule in enumerate(c):
target_index = 0
- for current, (end_at, cond) in enumerate(cond_schedule):
- if current_step <= end_at:
+ for current, entry in enumerate(cond_schedule):
+ if current_step <= entry.end_at_step:
target_index = current
break
res[i] = cond_schedule[target_index].cond
@@ -234,13 +234,13 @@ def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step):
tensors = []
conds_list = []
- for batch_no, composable_prompts in enumerate(c.batch):
+ for composable_prompts in c.batch:
conds_for_batch = []
- for cond_index, composable_prompt in enumerate(composable_prompts):
+ for composable_prompt in composable_prompts:
target_index = 0
- for current, (end_at, cond) in enumerate(composable_prompt.schedules):
- if current_step <= end_at:
+ for current, entry in enumerate(composable_prompt.schedules):
+ if current_step <= entry.end_at_step:
target_index = current
break
diff --git a/modules/safe.py b/modules/safe.py
index 2d5b972f..1e791c5b 100644
--- a/modules/safe.py
+++ b/modules/safe.py
@@ -95,11 +95,11 @@ def check_pt(filename, extra_handler):
except zipfile.BadZipfile:
- # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle
+ # if it's not a zip file, it's an old pytorch format, with five objects written to pickle
with open(filename, "rb") as file:
unpickler = RestrictedUnpickler(file)
unpickler.extra_handler = extra_handler
- for i in range(5):
+ for _ in range(5):
unpickler.load()
diff --git a/modules/scripts.py b/modules/scripts.py
index d945b89f..0c12ebd5 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -231,7 +231,7 @@ def load_scripts():
syspath = sys.path
def register_scripts_from_module(module):
- for key, script_class in module.__dict__.items():
+ for script_class in module.__dict__.values():
if type(script_class) != type:
continue
@@ -295,9 +295,9 @@ class ScriptRunner:
auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data()
- for script_class, path, basedir, script_module in auto_processing_scripts + scripts_data:
- script = script_class()
- script.filename = path
+ for script_data in auto_processing_scripts + scripts_data:
+ script = script_data.script_class()
+ script.filename = script_data.path
script.is_txt2img = not is_img2img
script.is_img2img = is_img2img
@@ -492,7 +492,7 @@ class ScriptRunner:
module = script_loading.load_module(script.filename)
cache[filename] = module
- for key, script_class in module.__dict__.items():
+ for script_class in module.__dict__.values():
if type(script_class) == type and issubclass(script_class, Script):
self.scripts[si] = script_class()
self.scripts[si].filename = filename
diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py
index b11568c0..6751406c 100644
--- a/modules/scripts_postprocessing.py
+++ b/modules/scripts_postprocessing.py
@@ -66,9 +66,9 @@ class ScriptPostprocessingRunner:
def initialize_scripts(self, scripts_data):
self.scripts = []
- for script_class, path, basedir, script_module in scripts_data:
- script: ScriptPostprocessing = script_class()
- script.filename = path
+ for script_data in scripts_data:
+ script: ScriptPostprocessing = script_data.script_class()
+ script.filename = script_data.path
if script.name == "Simple Upscale":
continue
@@ -124,7 +124,7 @@ class ScriptPostprocessingRunner:
script_args = args[script.args_from:script.args_to]
process_args = {}
- for (name, component), value in zip(script.controls.items(), script_args):
+ for (name, component), value in zip(script.controls.items(), script_args): # noqa B007
process_args[name] = value
script.process(pp, **process_args)
diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index 9fa5c5c5..c0c350f6 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
self.hijack.fixes = [x.fixes for x in batch_chunk]
for fixes in self.hijack.fixes:
- for position, embedding in fixes:
+ for position, embedding in fixes: # noqa: B007
used_embeddings[embedding.name] = embedding
z = self.process_tokens(tokens, multipliers)
diff --git a/modules/shared.py b/modules/shared.py
index e2691585..913c9e63 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -211,7 +211,7 @@ class OptionInfo:
def options_section(section_identifier, options_dict):
- for k, v in options_dict.items():
+ for v in options_dict.values():
v.section = section_identifier
return options_dict
@@ -579,7 +579,7 @@ class Options:
section_ids = {}
settings_items = self.data_labels.items()
- for k, item in settings_items:
+ for _, item in settings_items:
if item.section not in section_ids:
section_ids[item.section] = len(section_ids)
@@ -740,7 +740,7 @@ def walk_files(path, allowed_extensions=None):
if allowed_extensions is not None:
allowed_extensions = set(allowed_extensions)
- for root, dirs, files in os.walk(path):
+ for root, _, files in os.walk(path):
for filename in files:
if allowed_extensions is not None:
_, ext = os.path.splitext(filename)
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py
index fda58898..c56bea45 100644
--- a/modules/textual_inversion/learn_schedule.py
+++ b/modules/textual_inversion/learn_schedule.py
@@ -12,7 +12,7 @@ class LearnScheduleIterator:
self.it = 0
self.maxit = 0
try:
- for i, pair in enumerate(pairs):
+ for pair in pairs:
if not pair.strip():
continue
tmp = pair.split(':')
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index c37bb2ad..47035332 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -29,7 +29,7 @@ textual_inversion_templates = {}
def list_textual_inversion_templates():
textual_inversion_templates.clear()
- for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):
+ for root, _, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir):
for fn in fns:
path = os.path.join(root, fn)
@@ -198,7 +198,7 @@ class EmbeddingDatabase:
if not os.path.isdir(embdir.path):
return
- for root, dirs, fns in os.walk(embdir.path, followlinks=True):
+ for root, _, fns in os.walk(embdir.path, followlinks=True):
for fn in fns:
try:
fullfn = os.path.join(root, fn)
@@ -215,7 +215,7 @@ class EmbeddingDatabase:
def load_textual_inversion_embeddings(self, force_reload=False):
if not force_reload:
need_reload = False
- for path, embdir in self.embedding_dirs.items():
+ for embdir in self.embedding_dirs.values():
if embdir.has_changed():
need_reload = True
break
@@ -228,7 +228,7 @@ class EmbeddingDatabase:
self.skipped_embeddings.clear()
self.expected_shape = self.get_expected_shape()
- for path, embdir in self.embedding_dirs.items():
+ for embdir in self.embedding_dirs.values():
self.load_from_dir(embdir)
embdir.update()
@@ -469,7 +469,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
try:
sd_hijack_checkpoint.add()
- for i in range((steps-initial_step) * gradient_step):
+ for _ in range((steps-initial_step) * gradient_step):
if scheduler.finished:
break
if shared.state.interrupted:
diff --git a/modules/ui.py b/modules/ui.py
index 84d661b2..83bfb7d8 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -416,7 +416,7 @@ def create_sampler_and_steps_selection(choices, tabname):
def ordered_ui_categories():
user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))}
- for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):
+ for _, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):
yield category
@@ -1646,7 +1646,7 @@ def create_ui():
with gr.Blocks(theme=shared.gradio_theme, analytics_enabled=False, title="Stable Diffusion") as demo:
with gr.Row(elem_id="quicksettings", variant="compact"):
- for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
+ for _i, k, _item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
component = create_setting_component(k, is_quicksettings=True)
component_dict[k] = component
@@ -1673,7 +1673,7 @@ def create_ui():
outputs=[text_settings, result],
)
- for i, k, item in quicksettings_list:
+ for _i, k, _item in quicksettings_list:
component = component_dict[k]
info = opts.data_labels[k]
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index ab585917..2fd82e8e 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -90,7 +90,7 @@ class ExtraNetworksPage:
subdirs = {}
for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]:
- for root, dirs, files in os.walk(parentdir):
+ for root, dirs, _ in os.walk(parentdir):
for dirname in dirs:
x = os.path.join(root, dirname)
diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py
index cac73c51..f05049e1 100644
--- a/modules/ui_tempdir.py
+++ b/modules/ui_tempdir.py
@@ -72,7 +72,7 @@ def cleanup_tmpdr():
if temp_dir == "" or not os.path.isdir(temp_dir):
return
- for root, dirs, files in os.walk(temp_dir, topdown=False):
+ for root, _, files in os.walk(temp_dir, topdown=False):
for name in files:
_, extension = os.path.splitext(name)
if extension != ".png":
diff --git a/modules/upscaler.py b/modules/upscaler.py
index e145be30..8acb6e96 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -55,7 +55,7 @@ class Upscaler:
dest_w = int(img.width * scale)
dest_h = int(img.height * scale)
- for i in range(3):
+ for _ in range(3):
shape = (img.width, img.height)
img = self.do_upscale(img, selected_model)
diff --git a/pyproject.toml b/pyproject.toml
index 346a0cde..c88907be 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,7 +20,6 @@ ignore = [
"I001", # Import block is un-sorted or un-formatted
"C901", # Function is too complex
"C408", # Rewrite as a literal
- "B007", # Loop control variable not used within loop body
]
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 149bc85f..27af5ff6 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -156,7 +156,7 @@ class Script(scripts.Script):
images = []
all_prompts = []
infotexts = []
- for n, args in enumerate(jobs):
+ for args in jobs:
state.job = f"{state.job_no + 1} out of {state.job_count}"
copy_p = copy.copy(p)
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index d873a09c..0b1d3096 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -56,7 +56,7 @@ class Script(scripts.Script):
work = []
- for y, h, row in grid.tiles:
+ for _y, _h, row in grid.tiles:
for tiledata in row:
work.append(tiledata[2])
@@ -85,7 +85,7 @@ class Script(scripts.Script):
work_results += processed.images
image_index = 0
- for y, h, row in grid.tiles:
+ for _y, _h, row in grid.tiles:
for tiledata in row:
tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height))
image_index += 1
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 332e0ecd..38a20381 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -704,7 +704,7 @@ class Script(scripts.Script):
if not include_sub_grids:
# Done with sub-grids, drop all related information:
- for sg in range(z_count):
+ for _ in range(z_count):
del processed.images[1]
del processed.all_prompts[1]
del processed.all_seeds[1]
--
cgit v1.2.3
From 3ec7b705c78b7aca9569c92a419837352c7a4ec6 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 21:21:32 +0300
Subject: suggestions and fixes from the PR
---
extensions-builtin/Lora/scripts/lora_script.py | 2 +-
extensions-builtin/SwinIR/swinir_model_arch.py | 6 +-----
extensions-builtin/SwinIR/swinir_model_arch_v2.py | 11 ++---------
modules/codeformer/codeformer_arch.py | 7 ++-----
modules/hypernetworks/ui.py | 4 ++--
modules/models/diffusion/uni_pc/uni_pc.py | 4 ++--
modules/scripts_postprocessing.py | 2 +-
modules/sd_hijack_clip.py | 2 +-
modules/shared.py | 2 +-
modules/textual_inversion/textual_inversion.py | 3 +--
modules/ui.py | 4 ++--
11 files changed, 16 insertions(+), 31 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index b70e2de7..13d297d7 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -53,7 +53,7 @@ script_callbacks.on_infotext_pasted(lora.infotext_pasted)
shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
- "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(lora.available_loras)}, refresh=lora.list_available_loras),
+ "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None", *lora.available_loras]}, refresh=lora.list_available_loras),
}))
diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py
index de195d9b..73e37cfa 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch.py
@@ -644,17 +644,13 @@ class SwinIR(nn.Module):
"""
def __init__(self, img_size=64, patch_size=1, in_chans=3,
- embed_dim=96, depths=None, num_heads=None,
+ embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6),
window_size=7, mlp_ratio=4., qkv_bias=True, qk_scale=None,
drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,
norm_layer=nn.LayerNorm, ape=False, patch_norm=True,
use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',
**kwargs):
super(SwinIR, self).__init__()
-
- depths = depths or [6, 6, 6, 6]
- num_heads = num_heads or [6, 6, 6, 6]
-
num_in_ch = in_chans
num_out_ch = in_chans
num_feat = 64
diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
index 15777af9..3ca9be78 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
@@ -74,12 +74,9 @@ class WindowAttention(nn.Module):
"""
def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_drop=0., proj_drop=0.,
- pretrained_window_size=None):
+ pretrained_window_size=(0, 0)):
super().__init__()
-
- pretrained_window_size = pretrained_window_size or [0, 0]
-
self.dim = dim
self.window_size = window_size # Wh, Ww
self.pretrained_window_size = pretrained_window_size
@@ -701,17 +698,13 @@ class Swin2SR(nn.Module):
"""
def __init__(self, img_size=64, patch_size=1, in_chans=3,
- embed_dim=96, depths=None, num_heads=None,
+ embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6),
window_size=7, mlp_ratio=4., qkv_bias=True,
drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,
norm_layer=nn.LayerNorm, ape=False, patch_norm=True,
use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',
**kwargs):
super(Swin2SR, self).__init__()
-
- depths = depths or [6, 6, 6, 6]
- num_heads = num_heads or [6, 6, 6, 6]
-
num_in_ch = in_chans
num_out_ch = in_chans
num_feat = 64
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index ff1c0b4b..45c70f84 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -161,13 +161,10 @@ class Fuse_sft_block(nn.Module):
class CodeFormer(VQAutoEncoder):
def __init__(self, dim_embd=512, n_head=8, n_layers=9,
codebook_size=1024, latent_size=256,
- connect_list=None,
- fix_modules=None):
+ connect_list=('32', '64', '128', '256'),
+ fix_modules=('quantize', 'generator')):
super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size)
- connect_list = connect_list or ['32', '64', '128', '256']
- fix_modules = fix_modules or ['quantize', 'generator']
-
if fix_modules is not None:
for module in fix_modules:
for param in getattr(self, module).parameters():
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index e3f9eb13..8b6255e2 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -5,13 +5,13 @@ import modules.hypernetworks.hypernetwork
from modules import devices, sd_hijack, shared
not_available = ["hardswish", "multiheadattention"]
-keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available]
+keys = [x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict 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(shared.hypernetworks.keys())), f"Created: {filename}", ""
+ return gr.Dropdown.update(choices=sorted(shared.hypernetworks)), f"Created: {filename}", ""
def train_hypernetwork(*args):
diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py
index f6c49f87..a227b947 100644
--- a/modules/models/diffusion/uni_pc/uni_pc.py
+++ b/modules/models/diffusion/uni_pc/uni_pc.py
@@ -275,8 +275,8 @@ def model_wrapper(
A noise prediction model that accepts the noised data and the continuous time as the inputs.
"""
- model_kwargs = model_kwargs or []
- classifier_kwargs = classifier_kwargs or []
+ model_kwargs = model_kwargs or {}
+ classifier_kwargs = classifier_kwargs or {}
def get_model_input_time(t_continuous):
"""
diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py
index 6751406c..bac1335d 100644
--- a/modules/scripts_postprocessing.py
+++ b/modules/scripts_postprocessing.py
@@ -124,7 +124,7 @@ class ScriptPostprocessingRunner:
script_args = args[script.args_from:script.args_to]
process_args = {}
- for (name, component), value in zip(script.controls.items(), script_args): # noqa B007
+ for (name, _component), value in zip(script.controls.items(), script_args):
process_args[name] = value
script.process(pp, **process_args)
diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index c0c350f6..cc6e8c21 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
self.hijack.fixes = [x.fixes for x in batch_chunk]
for fixes in self.hijack.fixes:
- for position, embedding in fixes: # noqa: B007
+ for _position, embedding in fixes:
used_embeddings[embedding.name] = embedding
z = self.process_tokens(tokens, multipliers)
diff --git a/modules/shared.py b/modules/shared.py
index 913c9e63..ac67adc0 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -381,7 +381,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
"extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
"extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
"extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
- "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + list(hypernetworks.keys())}, refresh=reload_hypernetworks),
+ "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", hypernetworks]}, refresh=reload_hypernetworks),
}))
options_templates.update(options_section(('ui', "User interface"), {
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 47035332..9e1b2b9a 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -166,8 +166,7 @@ class EmbeddingDatabase:
# textual inversion embeddings
if 'string_to_param' in data:
param_dict = data['string_to_param']
- if hasattr(param_dict, '_parameters'):
- param_dict = param_dict._parameters # fix for torch 1.12.1 loading saved file from torch 1.11
+ param_dict = getattr(param_dict, '_parameters', param_dict) # fix for torch 1.12.1 loading saved file from torch 1.11
assert len(param_dict) == 1, 'embedding file has multiple terms in it'
emb = next(iter(param_dict.items()))[1]
# diffuser concepts
diff --git a/modules/ui.py b/modules/ui.py
index 83bfb7d8..7ee99473 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1230,8 +1230,8 @@ def create_ui():
train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
- train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=list(shared.hypernetworks.keys()))
- create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks.keys())}, "refresh_train_hypernetwork_name")
+ train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=sorted(shared.hypernetworks))
+ create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted(shared.hypernetworks)}, "refresh_train_hypernetwork_name")
with FormRow():
embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
--
cgit v1.2.3
From 8aa87c564a79965013715d56a5f90d2a34d5d6ee Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 10 May 2023 23:41:08 +0300
Subject: add UI to edit defaults allow setting defaults for elements in
extensions' tabs fix a problem with ESRGAN upscalers disappearing after UI
reload implicit change: HTML element id for train tab from tab_ti to
tab_train (will this break things?)
---
modules/modelloader.py | 27 +++----
modules/ui.py | 122 +++++------------------------
modules/ui_loadsave.py | 208 +++++++++++++++++++++++++++++++++++++++++++++++++
style.css | 4 +
webui.py | 6 +-
5 files changed, 242 insertions(+), 125 deletions(-)
create mode 100644 modules/ui_loadsave.py
(limited to 'modules/ui.py')
diff --git a/modules/modelloader.py b/modules/modelloader.py
index 25612bf8..2a479bcb 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -116,20 +116,6 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
pass
-builtin_upscaler_classes = []
-forbidden_upscaler_classes = set()
-
-
-def list_builtin_upscalers():
- builtin_upscaler_classes.clear()
- builtin_upscaler_classes.extend(Upscaler.__subclasses__())
-
-def forbid_loaded_nonbuiltin_upscalers():
- for cls in Upscaler.__subclasses__():
- if cls not in builtin_upscaler_classes:
- forbidden_upscaler_classes.add(cls)
-
-
def load_upscalers():
# We can only do this 'magic' method to dynamically load upscalers if they are referenced,
# so we'll try to import any _model.py files before looking in __subclasses__
@@ -145,10 +131,17 @@ def load_upscalers():
datas = []
commandline_options = vars(shared.cmd_opts)
- for cls in Upscaler.__subclasses__():
- if cls in forbidden_upscaler_classes:
- continue
+ # some of upscaler classes will not go away after reloading their modules, and we'll end
+ # up with two copies of those classes. The newest copy will always be the last in the list,
+ # so we go from end to beginning and ignore duplicates
+ used_classes = {}
+ for cls in reversed(Upscaler.__subclasses__()):
+ classname = str(cls)
+ if classname not in used_classes:
+ used_classes[classname] = cls
+
+ for cls in reversed(used_classes.values()):
name = cls.__name__
cmd_name = f"{name.lower().replace('upscaler', '')}_models_path"
scaler = cls(commandline_options.get(cmd_name, None))
diff --git a/modules/ui.py b/modules/ui.py
index 7ee99473..1efb656a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -13,7 +13,7 @@ import numpy as np
from PIL import Image, PngImagePlugin # noqa: F401
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress
+from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave
from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
from modules.paths import script_path, data_path
@@ -86,16 +86,6 @@ def send_gradio_gallery_to_image(x):
return None
return image_from_url_text(x[0])
-def visit(x, func, path=""):
- if hasattr(x, 'children'):
- if isinstance(x, gr.Tabs) and x.elem_id is not None:
- # Tabs element can't have a label, have to use elem_id instead
- func(f"{path}/Tabs@{x.elem_id}", x)
- for c in x.children:
- visit(c, func, path)
- elif x.label is not None:
- func(f"{path}/{x.label}", x)
-
def add_style(name: str, prompt: str, negative_prompt: str):
if name is None:
@@ -1471,6 +1461,8 @@ def create_ui():
return res
+ loadsave = ui_loadsave.UiLoadsave(cmd_opts.ui_config_file)
+
components = []
component_dict = {}
shared.settings_components = component_dict
@@ -1558,6 +1550,9 @@ def create_ui():
current_row.__exit__()
current_tab.__exit__()
+ with gr.TabItem("Defaults", id="defaults", elem_id="settings_tab_defaults"):
+ loadsave.create_ui()
+
with gr.TabItem("Actions", id="actions", elem_id="settings_tab_actions"):
request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
@@ -1631,7 +1626,7 @@ def create_ui():
(extras_interface, "Extras", "extras"),
(pnginfo_interface, "PNG Info", "pnginfo"),
(modelmerger_interface, "Checkpoint Merger", "modelmerger"),
- (train_interface, "Train", "ti"),
+ (train_interface, "Train", "train"),
]
interfaces += script_callbacks.ui_tabs_callback()
@@ -1659,6 +1654,16 @@ def create_ui():
with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"):
interface.render()
+ for interface, _label, ifid in interfaces:
+ if ifid in ["extensions", "settings"]:
+ continue
+
+ loadsave.add_block(interface, ifid)
+
+ loadsave.add_component(f"webui/Tabs@{tabs.elem_id}", tabs)
+
+ loadsave.setup_ui()
+
if os.path.exists(os.path.join(script_path, "notification.mp3")):
gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
@@ -1747,97 +1752,8 @@ def create_ui():
]
)
- ui_config_file = cmd_opts.ui_config_file
- ui_settings = {}
- settings_count = len(ui_settings)
- error_loading = False
-
- try:
- if os.path.exists(ui_config_file):
- with open(ui_config_file, "r", encoding="utf8") as file:
- ui_settings = json.load(file)
- except Exception:
- error_loading = True
- print("Error loading settings:", file=sys.stderr)
- print(traceback.format_exc(), file=sys.stderr)
-
- def loadsave(path, x):
- def apply_field(obj, field, condition=None, init_field=None):
- key = f"{path}/{field}"
-
- if getattr(obj, 'custom_script_source', None) is not None:
- key = f"customscript/{obj.custom_script_source}/{key}"
-
- if getattr(obj, 'do_not_save_to_config', False):
- return
-
- saved_value = ui_settings.get(key, None)
- if saved_value is None:
- ui_settings[key] = getattr(obj, field)
- elif condition and not condition(saved_value):
- 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:
- init_field(saved_value)
-
- if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton] and x.visible:
- apply_field(x, 'visible')
-
- if type(x) == gr.Slider:
- apply_field(x, 'value')
- apply_field(x, 'minimum')
- apply_field(x, 'maximum')
- apply_field(x, 'step')
-
- if type(x) == gr.Radio:
- apply_field(x, 'value', lambda val: val in x.choices)
-
- if type(x) == gr.Checkbox:
- apply_field(x, 'value')
-
- if type(x) == gr.Textbox:
- apply_field(x, 'value')
-
- if type(x) == gr.Number:
- apply_field(x, 'value')
-
- if type(x) == gr.Dropdown:
- def check_dropdown(val):
- if getattr(x, 'multiselect', False):
- return all(value in x.choices for value in val)
- else:
- return val in x.choices
-
- apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
-
- def check_tab_id(tab_id):
- tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children))
- if type(tab_id) == str:
- tab_ids = [t.id for t in tab_items]
- return tab_id in tab_ids
- elif type(tab_id) == int:
- return tab_id >= 0 and tab_id < len(tab_items)
- else:
- return False
-
- if type(x) == gr.Tabs:
- apply_field(x, 'selected', check_tab_id)
-
- visit(txt2img_interface, loadsave, "txt2img")
- visit(img2img_interface, loadsave, "img2img")
- visit(extras_interface, loadsave, "extras")
- visit(modelmerger_interface, loadsave, "modelmerger")
- visit(train_interface, loadsave, "train")
-
- loadsave(f"webui/Tabs@{tabs.elem_id}", tabs)
-
- if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
- with open(ui_config_file, "w", encoding="utf8") as file:
- json.dump(ui_settings, file, indent=4)
+ loadsave.dump_defaults()
+ demo.ui_loadsave = loadsave
# Required as a workaround for change() event not triggering when loading values from ui-config.json
interp_description.value = update_interp_description(interp_method.value)
diff --git a/modules/ui_loadsave.py b/modules/ui_loadsave.py
new file mode 100644
index 00000000..728fec9e
--- /dev/null
+++ b/modules/ui_loadsave.py
@@ -0,0 +1,208 @@
+import json
+import os
+
+import gradio as gr
+
+from modules import errors
+from modules.ui_components import ToolButton
+
+
+class UiLoadsave:
+ """allows saving and restorig default values for gradio components"""
+
+ def __init__(self, filename):
+ self.filename = filename
+ self.ui_settings = {}
+ self.component_mapping = {}
+ self.error_loading = False
+ self.finalized_ui = False
+
+ self.ui_defaults_view = None
+ self.ui_defaults_apply = None
+ self.ui_defaults_review = None
+
+ try:
+ if os.path.exists(self.filename):
+ self.ui_settings = self.read_from_file()
+ except Exception as e:
+ self.error_loading = True
+ errors.display(e, "loading settings")
+
+ def add_component(self, path, x):
+ """adds component to the registry of tracked components"""
+
+ assert not self.finalized_ui
+
+ def apply_field(obj, field, condition=None, init_field=None):
+ key = f"{path}/{field}"
+
+ if getattr(obj, 'custom_script_source', None) is not None:
+ key = f"customscript/{obj.custom_script_source}/{key}"
+
+ if getattr(obj, 'do_not_save_to_config', False):
+ return
+
+ saved_value = self.ui_settings.get(key, None)
+ if saved_value is None:
+ self.ui_settings[key] = getattr(obj, field)
+ elif condition and not condition(saved_value):
+ pass
+ else:
+ setattr(obj, field, saved_value)
+ if init_field is not None:
+ init_field(saved_value)
+
+ if field == 'value' and key not in self.component_mapping:
+ self.component_mapping[key] = x
+
+ if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton] and x.visible:
+ apply_field(x, 'visible')
+
+ if type(x) == gr.Slider:
+ apply_field(x, 'value')
+ apply_field(x, 'minimum')
+ apply_field(x, 'maximum')
+ apply_field(x, 'step')
+
+ if type(x) == gr.Radio:
+ apply_field(x, 'value', lambda val: val in x.choices)
+
+ if type(x) == gr.Checkbox:
+ apply_field(x, 'value')
+
+ if type(x) == gr.Textbox:
+ apply_field(x, 'value')
+
+ if type(x) == gr.Number:
+ apply_field(x, 'value')
+
+ if type(x) == gr.Dropdown:
+ def check_dropdown(val):
+ if getattr(x, 'multiselect', False):
+ return all(value in x.choices for value in val)
+ else:
+ return val in x.choices
+
+ apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
+
+ def check_tab_id(tab_id):
+ tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children))
+ if type(tab_id) == str:
+ tab_ids = [t.id for t in tab_items]
+ return tab_id in tab_ids
+ elif type(tab_id) == int:
+ return 0 <= tab_id < len(tab_items)
+ else:
+ return False
+
+ if type(x) == gr.Tabs:
+ apply_field(x, 'selected', check_tab_id)
+
+ def add_block(self, x, path=""):
+ """adds all components inside a gradio block x to the registry of tracked components"""
+
+ if hasattr(x, 'children'):
+ if isinstance(x, gr.Tabs) and x.elem_id is not None:
+ # Tabs element can't have a label, have to use elem_id instead
+ self.add_component(f"{path}/Tabs@{x.elem_id}", x)
+ for c in x.children:
+ self.add_block(c, path)
+ elif x.label is not None:
+ self.add_component(f"{path}/{x.label}", x)
+
+ def read_from_file(self):
+ with open(self.filename, "r", encoding="utf8") as file:
+ return json.load(file)
+
+ def write_to_file(self, current_ui_settings):
+ with open(self.filename, "w", encoding="utf8") as file:
+ json.dump(current_ui_settings, file, indent=4)
+
+ def dump_defaults(self):
+ """saves default values to a file unless tjhe file is present and there was an error loading default values at start"""
+
+ if self.error_loading and os.path.exists(self.filename):
+ return
+
+ self.write_to_file(self.ui_settings)
+
+ def iter_changes(self, current_ui_settings, values):
+ """
+ given a dictionary with defaults from a file and current values from gradio elements, returns
+ an iterator over tuples of values that are not the same between the file and the current;
+ tuple contents are: path, old value, new value
+ """
+
+ for (path, component), new_value in zip(self.component_mapping.items(), values):
+ old_value = current_ui_settings.get(path)
+
+ choices = getattr(component, 'choices', None)
+ if isinstance(new_value, int) and choices:
+ if new_value >= len(choices):
+ continue
+
+ new_value = choices[new_value]
+
+ if new_value == old_value:
+ continue
+
+ if old_value is None and new_value == '' or new_value == []:
+ continue
+
+ yield path, old_value, new_value
+
+ def ui_view(self, *values):
+ text = ["| Path | Old value | New value |
|---|
"]
+
+ for path, old_value, new_value in self.iter_changes(self.read_from_file(), values):
+ if old_value is None:
+ old_value = "None"
+
+ text.append(f"| {path} | {old_value} | {new_value} |
")
+
+ if len(text) == 1:
+ text.append("| No changes |
")
+
+ text.append("")
+ return "".join(text)
+
+ def ui_apply(self, *values):
+ num_changed = 0
+
+ current_ui_settings = self.read_from_file()
+
+ for path, _, new_value in self.iter_changes(current_ui_settings.copy(), values):
+ num_changed += 1
+ current_ui_settings[path] = new_value
+
+ if num_changed == 0:
+ return "No changes."
+
+ self.write_to_file(current_ui_settings)
+
+ return f"Wrote {num_changed} changes."
+
+ def create_ui(self):
+ """creates ui elements for editing defaults UI, without adding any logic to them"""
+
+ gr.HTML(
+ f"This page allows you to change default values in UI elements on other tabs.
"
+ f"Make your changes, press 'View changes' to review the changed default values,
"
+ f"then press 'Apply' to write them to {self.filename}.
"
+ f"New defaults will apply after you restart the UI.
"
+ )
+
+ with gr.Row():
+ self.ui_defaults_view = gr.Button(value='View changes', elem_id="ui_defaults_view", variant="secondary")
+ self.ui_defaults_apply = gr.Button(value='Apply', elem_id="ui_defaults_apply", variant="primary")
+
+ self.ui_defaults_review = gr.HTML("")
+
+ def setup_ui(self):
+ """adds logic to elements created with create_ui; all add_block class must be made before this"""
+
+ assert not self.finalized_ui
+ self.finalized_ui = True
+
+ self.ui_defaults_view.click(fn=self.ui_view, inputs=list(self.component_mapping.values()), outputs=[self.ui_defaults_review])
+ self.ui_defaults_apply.click(fn=self.ui_apply, inputs=list(self.component_mapping.values()), outputs=[self.ui_defaults_review])
diff --git a/style.css b/style.css
index b823c7dd..4ac919b5 100644
--- a/style.css
+++ b/style.css
@@ -414,6 +414,10 @@ table.settings-value-table td{
max-width: 36em;
}
+.ui-defaults-none{
+ color: #aaa !important;
+}
+
/* live preview */
.progressDiv{
position: relative;
diff --git a/webui.py b/webui.py
index 5d5e80b5..2eecfaa0 100644
--- a/webui.py
+++ b/webui.py
@@ -181,14 +181,11 @@ def initialize():
gfpgan.setup_model(cmd_opts.gfpgan_models_path)
startup_timer.record("setup gfpgan")
- modelloader.list_builtin_upscalers()
- startup_timer.record("list builtin upscalers")
-
modules.scripts.load_scripts()
startup_timer.record("load scripts")
modelloader.load_upscalers()
- #startup_timer.record("load upscalers") #Is this necessary? I don't know.
+ startup_timer.record("load upscalers")
modules.sd_vae.refresh_vae_list()
startup_timer.record("refresh VAE")
@@ -388,7 +385,6 @@ def webui():
localization.list_localizations(cmd_opts.localizations_dir)
- modelloader.forbid_loaded_nonbuiltin_upscalers()
modules.scripts.reload_scripts()
startup_timer.record("load scripts")
--
cgit v1.2.3
From 49a55b410b66b7dd9be9335d8a2e3a71e4f8b15c Mon Sep 17 00:00:00 2001
From: Aarni Koskela
Date: Thu, 11 May 2023 18:28:15 +0300
Subject: Autofix Ruff W (not W605) (mostly whitespace)
---
extensions-builtin/LDSR/ldsr_model_arch.py | 4 +-
extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 6 +--
extensions-builtin/ScuNET/scunet_model_arch.py | 2 +-
extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +-
extensions-builtin/SwinIR/swinir_model_arch.py | 2 +-
extensions-builtin/SwinIR/swinir_model_arch_v2.py | 52 +++++++++++------------
launch.py | 2 +-
modules/api/api.py | 4 +-
modules/api/models.py | 2 +-
modules/cmd_args.py | 2 +-
modules/codeformer/codeformer_arch.py | 14 +++---
modules/codeformer/vqgan_arch.py | 38 ++++++++---------
modules/esrgan_model_arch.py | 4 +-
modules/extras.py | 2 +-
modules/hypernetworks/hypernetwork.py | 12 +++---
modules/images.py | 2 +-
modules/mac_specific.py | 4 +-
modules/masking.py | 2 +-
modules/ngrok.py | 4 +-
modules/processing.py | 2 +-
modules/script_callbacks.py | 14 +++---
modules/sd_hijack.py | 12 +++---
modules/sd_hijack_optimizations.py | 32 +++++++-------
modules/sd_models.py | 4 +-
modules/sd_samplers_kdiffusion.py | 18 ++++----
modules/sub_quadratic_attention.py | 2 +-
modules/textual_inversion/dataset.py | 4 +-
modules/textual_inversion/preprocess.py | 2 +-
modules/textual_inversion/textual_inversion.py | 16 +++----
modules/ui.py | 18 ++++----
modules/ui_extensions.py | 6 +--
modules/xlmr.py | 6 +--
pyproject.toml | 5 ++-
scripts/img2imgalt.py | 14 +++---
scripts/loopback.py | 8 ++--
scripts/poor_mans_outpainting.py | 2 +-
scripts/prompt_matrix.py | 2 +-
scripts/prompts_from_file.py | 4 +-
scripts/sd_upscale.py | 2 +-
39 files changed, 167 insertions(+), 166 deletions(-)
(limited to 'modules/ui.py')
diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py
index 2173de79..7f450086 100644
--- a/extensions-builtin/LDSR/ldsr_model_arch.py
+++ b/extensions-builtin/LDSR/ldsr_model_arch.py
@@ -130,11 +130,11 @@ class LDSR:
im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS)
else:
print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)")
-
+
# pad width and height to multiples of 64, pads with the edge values of image to avoid artifacts
pad_w, pad_h = np.max(((2, 2), np.ceil(np.array(im_og.size) / 64).astype(int)), axis=0) * 64 - im_og.size
im_padded = Image.fromarray(np.pad(np.array(im_og), ((0, pad_h), (0, pad_w), (0, 0)), mode='edge'))
-
+
logs = self.run(model["model"], im_padded, diffusion_steps, eta)
sample = logs["sample"]
diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
index 57c02d12..631a08ef 100644
--- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
+++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py
@@ -460,7 +460,7 @@ class LatentDiffusionV1(DDPMV1):
self.instantiate_cond_stage(cond_stage_config)
self.cond_stage_forward = cond_stage_forward
self.clip_denoised = False
- self.bbox_tokenizer = None
+ self.bbox_tokenizer = None
self.restarted_from_ckpt = False
if ckpt_path is not None:
@@ -792,7 +792,7 @@ class LatentDiffusionV1(DDPMV1):
z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1])) # (bn, nc, ks[0], ks[1], L )
# 2. apply model loop over last dim
- if isinstance(self.first_stage_model, VQModelInterface):
+ if isinstance(self.first_stage_model, VQModelInterface):
output_list = [self.first_stage_model.decode(z[:, :, :, :, i],
force_not_quantize=predict_cids or force_not_quantize)
for i in range(z.shape[-1])]
@@ -890,7 +890,7 @@ class LatentDiffusionV1(DDPMV1):
if hasattr(self, "split_input_params"):
assert len(cond) == 1 # todo can only deal with one conditioning atm
- assert not return_ids
+ assert not return_ids
ks = self.split_input_params["ks"] # eg. (128, 128)
stride = self.split_input_params["stride"] # eg. (64, 64)
diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py
index 8028918a..b51a8806 100644
--- a/extensions-builtin/ScuNET/scunet_model_arch.py
+++ b/extensions-builtin/ScuNET/scunet_model_arch.py
@@ -265,4 +265,4 @@ class SCUNet(nn.Module):
nn.init.constant_(m.bias, 0)
elif isinstance(m, nn.LayerNorm):
nn.init.constant_(m.bias, 0)
- nn.init.constant_(m.weight, 1.0)
\ No newline at end of file
+ nn.init.constant_(m.weight, 1.0)
diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py
index 55dd94ab..0ba50487 100644
--- a/extensions-builtin/SwinIR/scripts/swinir_model.py
+++ b/extensions-builtin/SwinIR/scripts/swinir_model.py
@@ -150,7 +150,7 @@ def inference(img, model, tile, tile_overlap, window_size, scale):
for w_idx in w_idx_list:
if state.interrupted or state.skipped:
break
-
+
in_patch = img[..., h_idx: h_idx + tile, w_idx: w_idx + tile]
out_patch = model(in_patch)
out_patch_mask = torch.ones_like(out_patch)
diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py
index 73e37cfa..93b93274 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch.py
@@ -805,7 +805,7 @@ class SwinIR(nn.Module):
def forward(self, x):
H, W = x.shape[2:]
x = self.check_image_size(x)
-
+
self.mean = self.mean.type_as(x)
x = (x - self.mean) * self.img_range
diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
index 3ca9be78..dad22cca 100644
--- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py
+++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py
@@ -241,7 +241,7 @@ class SwinTransformerBlock(nn.Module):
attn_mask = None
self.register_buffer("attn_mask", attn_mask)
-
+
def calculate_mask(self, x_size):
# calculate attention mask for SW-MSA
H, W = x_size
@@ -263,7 +263,7 @@ class SwinTransformerBlock(nn.Module):
attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2)
attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(attn_mask == 0, float(0.0))
- return attn_mask
+ return attn_mask
def forward(self, x, x_size):
H, W = x_size
@@ -288,7 +288,7 @@ class SwinTransformerBlock(nn.Module):
attn_windows = self.attn(x_windows, mask=self.attn_mask) # nW*B, window_size*window_size, C
else:
attn_windows = self.attn(x_windows, mask=self.calculate_mask(x_size).to(x.device))
-
+
# merge windows
attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C)
shifted_x = window_reverse(attn_windows, self.window_size, H, W) # B H' W' C
@@ -369,7 +369,7 @@ class PatchMerging(nn.Module):
H, W = self.input_resolution
flops = (H // 2) * (W // 2) * 4 * self.dim * 2 * self.dim
flops += H * W * self.dim // 2
- return flops
+ return flops
class BasicLayer(nn.Module):
""" A basic Swin Transformer layer for one stage.
@@ -447,7 +447,7 @@ class BasicLayer(nn.Module):
nn.init.constant_(blk.norm1.weight, 0)
nn.init.constant_(blk.norm2.bias, 0)
nn.init.constant_(blk.norm2.weight, 0)
-
+
class PatchEmbed(nn.Module):
r""" Image to Patch Embedding
Args:
@@ -492,7 +492,7 @@ class PatchEmbed(nn.Module):
flops = Ho * Wo * self.embed_dim * self.in_chans * (self.patch_size[0] * self.patch_size[1])
if self.norm is not None:
flops += Ho * Wo * self.embed_dim
- return flops
+ return flops
class RSTB(nn.Module):
"""Residual Swin Transformer Block (RSTB).
@@ -531,7 +531,7 @@ class RSTB(nn.Module):
num_heads=num_heads,
window_size=window_size,
mlp_ratio=mlp_ratio,
- qkv_bias=qkv_bias,
+ qkv_bias=qkv_bias,
drop=drop, attn_drop=attn_drop,
drop_path=drop_path,
norm_layer=norm_layer,
@@ -622,7 +622,7 @@ class Upsample(nn.Sequential):
else:
raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.')
super(Upsample, self).__init__(*m)
-
+
class Upsample_hf(nn.Sequential):
"""Upsample module.
@@ -642,7 +642,7 @@ class Upsample_hf(nn.Sequential):
m.append(nn.PixelShuffle(3))
else:
raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.')
- super(Upsample_hf, self).__init__(*m)
+ super(Upsample_hf, self).__init__(*m)
class UpsampleOneStep(nn.Sequential):
@@ -667,8 +667,8 @@ class UpsampleOneStep(nn.Sequential):
H, W = self.input_resolution
flops = H * W * self.num_feat * 3 * 9
return flops
-
-
+
+
class Swin2SR(nn.Module):
r""" Swin2SR
@@ -699,7 +699,7 @@ class Swin2SR(nn.Module):
def __init__(self, img_size=64, patch_size=1, in_chans=3,
embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6),
- window_size=7, mlp_ratio=4., qkv_bias=True,
+ window_size=7, mlp_ratio=4., qkv_bias=True,
drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1,
norm_layer=nn.LayerNorm, ape=False, patch_norm=True,
use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv',
@@ -764,7 +764,7 @@ class Swin2SR(nn.Module):
num_heads=num_heads[i_layer],
window_size=window_size,
mlp_ratio=self.mlp_ratio,
- qkv_bias=qkv_bias,
+ qkv_bias=qkv_bias,
drop=drop_rate, attn_drop=attn_drop_rate,
drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])], # no impact on SR results
norm_layer=norm_layer,
@@ -776,7 +776,7 @@ class Swin2SR(nn.Module):
)
self.layers.append(layer)
-
+
if self.upsampler == 'pixelshuffle_hf':
self.layers_hf = nn.ModuleList()
for i_layer in range(self.num_layers):
@@ -787,7 +787,7 @@ class Swin2SR(nn.Module):
num_heads=num_heads[i_layer],
window_size=window_size,
mlp_ratio=self.mlp_ratio,
- qkv_bias=qkv_bias,
+ qkv_bias=qkv_bias,
drop=drop_rate, attn_drop=attn_drop_rate,
drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])], # no impact on SR results
norm_layer=norm_layer,
@@ -799,7 +799,7 @@ class Swin2SR(nn.Module):
)
self.layers_hf.append(layer)
-
+
self.norm = norm_layer(self.num_features)
# build the last conv layer in deep feature extraction
@@ -829,10 +829,10 @@ class Swin2SR(nn.Module):
self.conv_aux = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
self.conv_after_aux = nn.Sequential(
nn.Conv2d(3, num_feat, 3, 1, 1),
- nn.LeakyReLU(inplace=True))
+ nn.LeakyReLU(inplace=True))
self.upsample = Upsample(upscale, num_feat)
self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
-
+
elif self.upsampler == 'pixelshuffle_hf':
self.conv_before_upsample = nn.Sequential(nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
nn.LeakyReLU(inplace=True))
@@ -846,7 +846,7 @@ class Swin2SR(nn.Module):
nn.Conv2d(embed_dim, num_feat, 3, 1, 1),
nn.LeakyReLU(inplace=True))
self.conv_last_hf = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1)
-
+
elif self.upsampler == 'pixelshuffledirect':
# for lightweight SR (to save parameters)
self.upsample = UpsampleOneStep(upscale, embed_dim, num_out_ch,
@@ -905,7 +905,7 @@ class Swin2SR(nn.Module):
x = self.patch_unembed(x, x_size)
return x
-
+
def forward_features_hf(self, x):
x_size = (x.shape[2], x.shape[3])
x = self.patch_embed(x)
@@ -919,7 +919,7 @@ class Swin2SR(nn.Module):
x = self.norm(x) # B L C
x = self.patch_unembed(x, x_size)
- return x
+ return x
def forward(self, x):
H, W = x.shape[2:]
@@ -951,7 +951,7 @@ class Swin2SR(nn.Module):
x = self.conv_after_body(self.forward_features(x)) + x
x_before = self.conv_before_upsample(x)
x_out = self.conv_last(self.upsample(x_before))
-
+
x_hf = self.conv_first_hf(x_before)
x_hf = self.conv_after_body_hf(self.forward_features_hf(x_hf)) + x_hf
x_hf = self.conv_before_upsample_hf(x_hf)
@@ -977,15 +977,15 @@ class Swin2SR(nn.Module):
x_first = self.conv_first(x)
res = self.conv_after_body(self.forward_features(x_first)) + x_first
x = x + self.conv_last(res)
-
+
x = x / self.img_range + self.mean
if self.upsampler == "pixelshuffle_aux":
return x[:, :, :H*self.upscale, :W*self.upscale], aux
-
+
elif self.upsampler == "pixelshuffle_hf":
x_out = x_out / self.img_range + self.mean
return x_out[:, :, :H*self.upscale, :W*self.upscale], x[:, :, :H*self.upscale, :W*self.upscale], x_hf[:, :, :H*self.upscale, :W*self.upscale]
-
+
else:
return x[:, :, :H*self.upscale, :W*self.upscale]
@@ -1014,4 +1014,4 @@ if __name__ == '__main__':
x = torch.randn((1, 3, height, width))
x = model(x)
- print(x.shape)
\ No newline at end of file
+ print(x.shape)
diff --git a/launch.py b/launch.py
index 670af87c..62b33f14 100644
--- a/launch.py
+++ b/launch.py
@@ -327,7 +327,7 @@ def prepare_environment():
if args.update_all_extensions:
git_pull_recursive(extensions_dir)
-
+
if "--exit" in sys.argv:
print("Exiting because of --exit argument")
exit(0)
diff --git a/modules/api/api.py b/modules/api/api.py
index 594fa655..165985c3 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -227,7 +227,7 @@ class Api:
script_idx = script_name_to_index(script_name, script_runner.selectable_scripts)
script = script_runner.selectable_scripts[script_idx]
return script, script_idx
-
+
def get_scripts_list(self):
t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles]
i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles]
@@ -237,7 +237,7 @@ class Api:
def get_script(self, script_name, script_runner):
if script_name is None or script_name == "":
return None, None
-
+
script_idx = script_name_to_index(script_name, script_runner.scripts)
return script_runner.scripts[script_idx]
diff --git a/modules/api/models.py b/modules/api/models.py
index 4d291076..006ccdb7 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -289,4 +289,4 @@ class MemoryResponse(BaseModel):
class ScriptsList(BaseModel):
txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)")
- img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)")
\ No newline at end of file
+ img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)")
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index e01ca655..f4a4ab36 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -102,4 +102,4 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra
parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers")
parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
-parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
\ No newline at end of file
+parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py
index 45c70f84..12db6814 100644
--- a/modules/codeformer/codeformer_arch.py
+++ b/modules/codeformer/codeformer_arch.py
@@ -119,7 +119,7 @@ class TransformerSALayer(nn.Module):
tgt_mask: Optional[Tensor] = None,
tgt_key_padding_mask: Optional[Tensor] = None,
query_pos: Optional[Tensor] = None):
-
+
# self attention
tgt2 = self.norm1(tgt)
q = k = self.with_pos_embed(tgt2, query_pos)
@@ -159,7 +159,7 @@ class Fuse_sft_block(nn.Module):
@ARCH_REGISTRY.register()
class CodeFormer(VQAutoEncoder):
- def __init__(self, dim_embd=512, n_head=8, n_layers=9,
+ def __init__(self, dim_embd=512, n_head=8, n_layers=9,
codebook_size=1024, latent_size=256,
connect_list=('32', '64', '128', '256'),
fix_modules=('quantize', 'generator')):
@@ -179,14 +179,14 @@ class CodeFormer(VQAutoEncoder):
self.feat_emb = nn.Linear(256, self.dim_embd)
# transformer
- self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0)
+ self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0)
for _ in range(self.n_layers)])
# logits_predict head
self.idx_pred_layer = nn.Sequential(
nn.LayerNorm(dim_embd),
nn.Linear(dim_embd, codebook_size, bias=False))
-
+
self.channels = {
'16': 512,
'32': 256,
@@ -221,7 +221,7 @@ class CodeFormer(VQAutoEncoder):
enc_feat_dict = {}
out_list = [self.fuse_encoder_block[f_size] for f_size in self.connect_list]
for i, block in enumerate(self.encoder.blocks):
- x = block(x)
+ x = block(x)
if i in out_list:
enc_feat_dict[str(x.shape[-1])] = x.clone()
@@ -266,11 +266,11 @@ class CodeFormer(VQAutoEncoder):
fuse_list = [self.fuse_generator_block[f_size] for f_size in self.connect_list]
for i, block in enumerate(self.generator.blocks):
- x = block(x)
+ x = block(x)
if i in fuse_list: # fuse after i-th block
f_size = str(x.shape[-1])
if w>0:
x = self.fuse_convs_dict[f_size](enc_feat_dict[f_size].detach(), x, w)
out = x
# logits doesn't need softmax before cross_entropy loss
- return out, logits, lq_feat
\ No newline at end of file
+ return out, logits, lq_feat
diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py
index b24a0394..09ee6660 100644
--- a/modules/codeformer/vqgan_arch.py
+++ b/modules/codeformer/vqgan_arch.py
@@ -13,7 +13,7 @@ from basicsr.utils.registry import ARCH_REGISTRY
def normalize(in_channels):
return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)
-
+
@torch.jit.script
def swish(x):
@@ -210,15 +210,15 @@ class AttnBlock(nn.Module):
# compute attention
b, c, h, w = q.shape
q = q.reshape(b, c, h*w)
- q = q.permute(0, 2, 1)
+ q = q.permute(0, 2, 1)
k = k.reshape(b, c, h*w)
- w_ = torch.bmm(q, k)
+ w_ = torch.bmm(q, k)
w_ = w_ * (int(c)**(-0.5))
w_ = F.softmax(w_, dim=2)
# attend to values
v = v.reshape(b, c, h*w)
- w_ = w_.permute(0, 2, 1)
+ w_ = w_.permute(0, 2, 1)
h_ = torch.bmm(v, w_)
h_ = h_.reshape(b, c, h, w)
@@ -270,18 +270,18 @@ class Encoder(nn.Module):
def forward(self, x):
for block in self.blocks:
x = block(x)
-
+
return x
class Generator(nn.Module):
def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions):
super().__init__()
- self.nf = nf
- self.ch_mult = ch_mult
+ self.nf = nf
+ self.ch_mult = ch_mult
self.num_resolutions = len(self.ch_mult)
self.num_res_blocks = res_blocks
- self.resolution = img_size
+ self.resolution = img_size
self.attn_resolutions = attn_resolutions
self.in_channels = emb_dim
self.out_channels = 3
@@ -315,24 +315,24 @@ class Generator(nn.Module):
blocks.append(nn.Conv2d(block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1))
self.blocks = nn.ModuleList(blocks)
-
+
def forward(self, x):
for block in self.blocks:
x = block(x)
-
+
return x
-
+
@ARCH_REGISTRY.register()
class VQAutoEncoder(nn.Module):
def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=None, codebook_size=1024, emb_dim=256,
beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None):
super().__init__()
logger = get_root_logger()
- self.in_channels = 3
- self.nf = nf
- self.n_blocks = res_blocks
+ self.in_channels = 3
+ self.nf = nf
+ self.n_blocks = res_blocks
self.codebook_size = codebook_size
self.embed_dim = emb_dim
self.ch_mult = ch_mult
@@ -363,11 +363,11 @@ class VQAutoEncoder(nn.Module):
self.kl_weight
)
self.generator = Generator(
- self.nf,
+ self.nf,
self.embed_dim,
- self.ch_mult,
- self.n_blocks,
- self.resolution,
+ self.ch_mult,
+ self.n_blocks,
+ self.resolution,
self.attn_resolutions
)
@@ -432,4 +432,4 @@ class VQGANDiscriminator(nn.Module):
raise ValueError('Wrong params!')
def forward(self, x):
- return self.main(x)
\ No newline at end of file
+ return self.main(x)
diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py
index 4de9dd8d..2b9888ba 100644
--- a/modules/esrgan_model_arch.py
+++ b/modules/esrgan_model_arch.py
@@ -105,7 +105,7 @@ class ResidualDenseBlock_5C(nn.Module):
Modified options that can be used:
- "Partial Convolution based Padding" arXiv:1811.11718
- "Spectral normalization" arXiv:1802.05957
- - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C.
+ - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C.
{Rakotonirina} and A. {Rasoanaivo}
"""
@@ -170,7 +170,7 @@ class GaussianNoise(nn.Module):
scale = self.sigma * x.detach() if self.is_relative_detach else self.sigma * x
sampled_noise = self.noise.repeat(*x.size()).normal_() * scale
x = x + sampled_noise
- return x
+ return x
def conv1x1(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False)
diff --git a/modules/extras.py b/modules/extras.py
index eb4f0b42..bdf9b3b7 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -199,7 +199,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
result_is_inpainting_model = True
else:
theta_0[key] = theta_func2(a, b, multiplier)
-
+
theta_0[key] = to_half(theta_0[key], save_as_half)
shared.state.sampling_step += 1
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 38ef074f..570b5603 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -540,7 +540,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
return hypernetwork, filename
scheduler = LearnRateScheduler(learn_rate, steps, initial_step)
-
+
clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else None
if clip_grad:
clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, initial_step, verbose=False)
@@ -593,7 +593,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
print(e)
scaler = torch.cuda.amp.GradScaler()
-
+
batch_size = ds.batch_size
gradient_step = ds.gradient_step
# n steps = batch_size * gradient_step * n image processed
@@ -636,7 +636,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
if clip_grad:
clip_grad_sched.step(hypernetwork.step)
-
+
with devices.autocast():
x = batch.latent_sample.to(devices.device, non_blocking=pin_memory)
if use_weight:
@@ -657,14 +657,14 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
_loss_step += loss.item()
scaler.scale(loss).backward()
-
+
# go back until we reach gradient accumulation steps
if (j + 1) % gradient_step != 0:
continue
loss_logging.append(_loss_step)
if clip_grad:
clip_grad(weights, clip_grad_sched.learn_rate)
-
+
scaler.step(optimizer)
scaler.update()
hypernetwork.step += 1
@@ -674,7 +674,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
_loss_step = 0
steps_done = hypernetwork.step + 1
-
+
epoch_num = hypernetwork.step // steps_per_epoch
epoch_step = hypernetwork.step % steps_per_epoch
diff --git a/modules/images.py b/modules/images.py
index 3b8b62d9..b2de3662 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -367,7 +367,7 @@ class FilenameGenerator:
self.seed = seed
self.prompt = prompt
self.image = image
-
+
def hasprompt(self, *args):
lower = self.prompt.lower()
if self.p is None or self.prompt is None:
diff --git a/modules/mac_specific.py b/modules/mac_specific.py
index 5c2f92a1..d74c6b95 100644
--- a/modules/mac_specific.py
+++ b/modules/mac_specific.py
@@ -42,7 +42,7 @@ if has_mps:
# MPS workaround for https://github.com/pytorch/pytorch/issues/79383
CondFunc('torch.Tensor.to', lambda orig_func, self, *args, **kwargs: orig_func(self.contiguous(), *args, **kwargs),
lambda _, self, *args, **kwargs: self.device.type != 'mps' and (args and isinstance(args[0], torch.device) and args[0].type == 'mps' or isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps'))
- # MPS workaround for https://github.com/pytorch/pytorch/issues/80800
+ # MPS workaround for https://github.com/pytorch/pytorch/issues/80800
CondFunc('torch.nn.functional.layer_norm', lambda orig_func, *args, **kwargs: orig_func(*([args[0].contiguous()] + list(args[1:])), **kwargs),
lambda _, *args, **kwargs: args and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps')
# MPS workaround for https://github.com/pytorch/pytorch/issues/90532
@@ -60,4 +60,4 @@ if has_mps:
# MPS workaround for https://github.com/pytorch/pytorch/issues/92311
if platform.processor() == 'i386':
for funcName in ['torch.argmax', 'torch.Tensor.argmax']:
- CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps')
\ No newline at end of file
+ CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps')
diff --git a/modules/masking.py b/modules/masking.py
index a5c4d2da..be9f84c7 100644
--- a/modules/masking.py
+++ b/modules/masking.py
@@ -4,7 +4,7 @@ from PIL import Image, ImageFilter, ImageOps
def get_crop_region(mask, pad=0):
"""finds a rectangular region that contains all masked ares in an image. Returns (x1, y1, x2, y2) coordinates of the rectangle.
For example, if a user has painted the top-right part of a 512x512 image", the result may be (256, 0, 512, 256)"""
-
+
h, w = mask.shape
crop_left = 0
diff --git a/modules/ngrok.py b/modules/ngrok.py
index 7a7b4b26..67a74e85 100644
--- a/modules/ngrok.py
+++ b/modules/ngrok.py
@@ -13,7 +13,7 @@ def connect(token, port, region):
config = conf.PyngrokConfig(
auth_token=token, region=region
)
-
+
# Guard for existing tunnels
existing = ngrok.get_tunnels(pyngrok_config=config)
if existing:
@@ -24,7 +24,7 @@ def connect(token, port, region):
print(f'ngrok has already been connected to localhost:{port}! URL: {public_url}\n'
'You can use this link after the launch is complete.')
return
-
+
try:
if account is None:
public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url
diff --git a/modules/processing.py b/modules/processing.py
index c3932d6b..f902b9df 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -164,7 +164,7 @@ class StableDiffusionProcessing:
self.all_subseeds = None
self.iteration = 0
self.is_hr_pass = False
-
+
@property
def sd_model(self):
diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index 17109732..7d9dd736 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -32,22 +32,22 @@ class CFGDenoiserParams:
def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond):
self.x = x
"""Latent image representation in the process of being denoised"""
-
+
self.image_cond = image_cond
"""Conditioning image"""
-
+
self.sigma = sigma
"""Current sigma noise step value"""
-
+
self.sampling_step = sampling_step
"""Current Sampling step number"""
-
+
self.total_sampling_steps = total_sampling_steps
"""Total number of sampling steps planned"""
-
+
self.text_cond = text_cond
""" Encoder hidden states of text conditioning from prompt"""
-
+
self.text_uncond = text_uncond
""" Encoder hidden states of text conditioning from negative prompt"""
@@ -240,7 +240,7 @@ def add_callback(callbacks, fun):
callbacks.append(ScriptCallback(filename, fun))
-
+
def remove_current_script_callbacks():
stack = [x for x in inspect.stack() if x.filename != __file__]
filename = stack[0].filename if len(stack) > 0 else 'unknown file'
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index e374aeb8..7e50f1ab 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -34,7 +34,7 @@ def apply_optimizations():
ldm.modules.diffusionmodules.model.nonlinearity = silu
ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th
-
+
optimization_method = None
can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp
@@ -92,12 +92,12 @@ def fix_checkpoint():
def weighted_loss(sd_model, pred, target, mean=True):
#Calculate the weight normally, but ignore the mean
loss = sd_model._old_get_loss(pred, target, mean=False)
-
+
#Check if we have weights available
weight = getattr(sd_model, '_custom_loss_weight', None)
if weight is not None:
loss *= weight
-
+
#Return the loss, as mean if specified
return loss.mean() if mean else loss
@@ -105,7 +105,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
try:
#Temporarily append weights to a place accessible during loss calc
sd_model._custom_loss_weight = w
-
+
#Replace 'get_loss' with a weight-aware one. Otherwise we need to reimplement 'forward' completely
#Keep 'get_loss', but don't overwrite the previous old_get_loss if it's already set
if not hasattr(sd_model, '_old_get_loss'):
@@ -120,7 +120,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs):
del sd_model._custom_loss_weight
except AttributeError:
pass
-
+
#If we have an old loss function, reset the loss function to the original one
if hasattr(sd_model, '_old_get_loss'):
sd_model.get_loss = sd_model._old_get_loss
@@ -184,7 +184,7 @@ class StableDiffusionModelHijack:
def undo_hijack(self, m):
if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
- m.cond_stage_model = m.cond_stage_model.wrapped
+ m.cond_stage_model = m.cond_stage_model.wrapped
elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords:
m.cond_stage_model = m.cond_stage_model.wrapped
diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index a174bbe1..f00fe55c 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -62,10 +62,10 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
end = i + 2
s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end])
s1 *= self.scale
-
+
s2 = s1.softmax(dim=-1)
del s1
-
+
r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end])
del s2
del q, k, v
@@ -95,43 +95,43 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
with devices.without_autocast(disable=not shared.opts.upcast_attn):
k_in = k_in * self.scale
-
+
del context, x
-
+
q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in))
del q_in, k_in, v_in
-
+
r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
-
+
mem_free_total = get_available_vram()
-
+
gb = 1024 ** 3
tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size()
modifier = 3 if q.element_size() == 2 else 2.5
mem_required = tensor_size * modifier
steps = 1
-
+
if mem_required > mem_free_total:
steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2)))
# print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB "
# f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}")
-
+
if steps > 64:
max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64
raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). '
f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free')
-
+
slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1]
for i in range(0, q.shape[1], slice_size):
end = i + slice_size
s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k)
-
+
s2 = s1.softmax(dim=-1, dtype=q.dtype)
del s1
-
+
r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v)
del s2
-
+
del q, k, v
r1 = r1.to(dtype)
@@ -228,7 +228,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None):
with devices.without_autocast(disable=not shared.opts.upcast_attn):
k = k * self.scale
-
+
q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v))
r = einsum_op(q, k, v)
r = r.to(dtype)
@@ -369,7 +369,7 @@ def scaled_dot_product_attention_forward(self, x, context=None, mask=None):
q = q_in.view(batch_size, -1, h, head_dim).transpose(1, 2)
k = k_in.view(batch_size, -1, h, head_dim).transpose(1, 2)
v = v_in.view(batch_size, -1, h, head_dim).transpose(1, 2)
-
+
del q_in, k_in, v_in
dtype = q.dtype
@@ -451,7 +451,7 @@ def cross_attention_attnblock_forward(self, x):
h3 += x
return h3
-
+
def xformers_attnblock_forward(self, x):
try:
h_ = x
diff --git a/modules/sd_models.py b/modules/sd_models.py
index d1e946a5..3316d021 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -165,7 +165,7 @@ def model_hash(filename):
def select_checkpoint():
model_checkpoint = shared.opts.sd_model_checkpoint
-
+
checkpoint_info = checkpoint_alisases.get(model_checkpoint, None)
if checkpoint_info is not None:
return checkpoint_info
@@ -372,7 +372,7 @@ def enable_midas_autodownload():
if not os.path.exists(path):
if not os.path.exists(midas_path):
mkdir(midas_path)
-
+
print(f"Downloading midas model weights for {model_type} to {path}")
request.urlretrieve(midas_urls[model_type], path)
print(f"{model_type} downloaded")
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 2f733cf5..e9e41818 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -93,10 +93,10 @@ class CFGDenoiser(torch.nn.Module):
if shared.sd_model.model.conditioning_key == "crossattn-adm":
image_uncond = torch.zeros_like(image_cond)
- make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm}
+ make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm}
else:
image_uncond = image_cond
- make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]}
+ make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]}
if not is_edit_model:
x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x])
@@ -316,7 +316,7 @@ class KDiffusionSampler:
sigma_sched = sigmas[steps - t_enc - 1:]
xi = x + noise * sigma_sched[0]
-
+
extra_params_kwargs = self.initialize(p)
parameters = inspect.signature(self.func).parameters
@@ -339,9 +339,9 @@ class KDiffusionSampler:
self.model_wrap_cfg.init_latent = x
self.last_latent = x
extra_args={
- 'cond': conditioning,
- 'image_cond': image_conditioning,
- 'uncond': unconditional_conditioning,
+ 'cond': conditioning,
+ 'image_cond': image_conditioning,
+ 'uncond': unconditional_conditioning,
'cond_scale': p.cfg_scale,
's_min_uncond': self.s_min_uncond
}
@@ -374,9 +374,9 @@ class KDiffusionSampler:
self.last_latent = x
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
- 'cond': conditioning,
- 'image_cond': image_conditioning,
- 'uncond': unconditional_conditioning,
+ 'cond': conditioning,
+ 'image_cond': image_conditioning,
+ 'uncond': unconditional_conditioning,
'cond_scale': p.cfg_scale,
's_min_uncond': self.s_min_uncond
}, disable=False, callback=self.callback_state, **extra_params_kwargs))
diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py
index cc38debd..497568eb 100644
--- a/modules/sub_quadratic_attention.py
+++ b/modules/sub_quadratic_attention.py
@@ -179,7 +179,7 @@ def efficient_dot_product_attention(
chunk_idx,
min(query_chunk_size, q_tokens)
)
-
+
summarize_chunk: SummarizeChunk = partial(_summarize_chunk, scale=scale)
summarize_chunk: SummarizeChunk = partial(checkpoint, summarize_chunk) if use_checkpoint else summarize_chunk
compute_query_chunk_attn: ComputeQueryChunkAttn = partial(
diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py
index 41610e03..b9621fc9 100644
--- a/modules/textual_inversion/dataset.py
+++ b/modules/textual_inversion/dataset.py
@@ -118,7 +118,7 @@ class PersonalizedBase(Dataset):
weight = torch.ones(latent_sample.shape)
else:
weight = None
-
+
if latent_sampling_method == "random":
entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist, weight=weight)
else:
@@ -243,4 +243,4 @@ class BatchLoaderRandom(BatchLoader):
return self
def collate_wrapper_random(batch):
- return BatchLoaderRandom(batch)
\ No newline at end of file
+ return BatchLoaderRandom(batch)
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py
index d0cad09e..a009d8e8 100644
--- a/modules/textual_inversion/preprocess.py
+++ b/modules/textual_inversion/preprocess.py
@@ -125,7 +125,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr
default=None
)
return wh and center_crop(image, *wh)
-
+
def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None):
width = process_width
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 9e1b2b9a..d489ed1e 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -323,16 +323,16 @@ def tensorboard_add(tensorboard_writer, loss, global_step, step, learn_rate, epo
tensorboard_add_scaler(tensorboard_writer, f"Learn rate/train/epoch-{epoch_num}", learn_rate, step)
def tensorboard_add_scaler(tensorboard_writer, tag, value, step):
- tensorboard_writer.add_scalar(tag=tag,
+ tensorboard_writer.add_scalar(tag=tag,
scalar_value=value, global_step=step)
def tensorboard_add_image(tensorboard_writer, tag, pil_image, step):
# Convert a pil image to a torch tensor
img_tensor = torch.as_tensor(np.array(pil_image, copy=True))
- img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0],
+ img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0],
len(pil_image.getbands()))
img_tensor = img_tensor.permute((2, 0, 1))
-
+
tensorboard_writer.add_image(tag, img_tensor, global_step=step)
def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_model_every, create_image_every, log_directory, name="embedding"):
@@ -402,7 +402,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
if initial_step >= steps:
shared.state.textinfo = "Model has already been trained beyond specified max steps"
return embedding, filename
-
+
scheduler = LearnRateScheduler(learn_rate, steps, initial_step)
clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else \
torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else \
@@ -412,7 +412,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
# dataset loading may take a while, so input validations and early returns should be done before this
shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
old_parallel_processing_allowed = shared.parallel_processing_allowed
-
+
if shared.opts.training_enable_tensorboard:
tensorboard_writer = tensorboard_setup(log_directory)
@@ -439,7 +439,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
optimizer_saved_dict = torch.load(f"{filename}.optim", map_location='cpu')
if embedding.checksum() == optimizer_saved_dict.get('hash', None):
optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None)
-
+
if optimizer_state_dict is not None:
optimizer.load_state_dict(optimizer_state_dict)
print("Loaded existing optimizer from checkpoint")
@@ -485,7 +485,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
if clip_grad:
clip_grad_sched.step(embedding.step)
-
+
with devices.autocast():
x = batch.latent_sample.to(devices.device, non_blocking=pin_memory)
if use_weight:
@@ -513,7 +513,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
# go back until we reach gradient accumulation steps
if (j + 1) % gradient_step != 0:
continue
-
+
if clip_grad:
clip_grad(embedding.vec, clip_grad_sched.learn_rate)
diff --git a/modules/ui.py b/modules/ui.py
index 1efb656a..ff82fff6 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1171,7 +1171,7 @@ def create_ui():
process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
+
with gr.Column(visible=False) as process_multicrop_col:
gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
with gr.Row():
@@ -1183,7 +1183,7 @@ def create_ui():
with gr.Row():
process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective")
process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold")
-
+
with gr.Row():
with gr.Column(scale=3):
gr.HTML(value="")
@@ -1226,7 +1226,7 @@ def create_ui():
with FormRow():
embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
-
+
with FormRow():
clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
@@ -1565,7 +1565,7 @@ def create_ui():
gr.HTML(shared.html("licenses.html"), elem_id="licenses")
gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-
+
def unload_sd_weights():
modules.sd_models.unload_model_weights()
@@ -1841,15 +1841,15 @@ def versions_html():
return f"""
version: {tag}
- •
+ •
python: {python_version}
- •
+ •
torch: {getattr(torch, '__long_version__',torch.__version__)}
- •
+ •
xformers: {xformers_version}
- •
+ •
gradio: {gr.__version__}
- •
+ •
checkpoint: N/A
"""
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index ed70abe5..af497733 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -467,7 +467,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text="
{html.escape(description)} Added: {html.escape(added)} |
{install_code} |
-
+
"""
for tag in [x for x in extension_tags if x not in tags]:
@@ -535,9 +535,9 @@ def create_ui():
hide_tags = gr.CheckboxGroup(value=["ads", "localization", "installed"], label="Hide extensions with tags", choices=["script", "ads", "localization", "installed"])
sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order", ], type="index")
- with gr.Row():
+ with gr.Row():
search_extensions_text = gr.Text(label="Search").style(container=False)
-
+
install_result = gr.HTML()
available_extensions_table = gr.HTML()
diff --git a/modules/xlmr.py b/modules/xlmr.py
index e056c3f6..a407a3ca 100644
--- a/modules/xlmr.py
+++ b/modules/xlmr.py
@@ -28,7 +28,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel):
config_class = BertSeriesConfig
def __init__(self, config=None, **kargs):
- # modify initialization for autoloading
+ # modify initialization for autoloading
if config is None:
config = XLMRobertaConfig()
config.attention_probs_dropout_prob= 0.1
@@ -74,7 +74,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel):
text["attention_mask"] = torch.tensor(
text['attention_mask']).to(device)
features = self(**text)
- return features['projection_state']
+ return features['projection_state']
def forward(
self,
@@ -134,4 +134,4 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel):
class RobertaSeriesModelWithTransformation(BertSeriesModelWithTransformation):
base_model_prefix = 'roberta'
- config_class= RobertaSeriesConfig
\ No newline at end of file
+ config_class= RobertaSeriesConfig
diff --git a/pyproject.toml b/pyproject.toml
index c88907be..d4a1bbf4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,6 +6,7 @@ extend-select = [
"B",
"C",
"I",
+ "W",
]
exclude = [
@@ -20,7 +21,7 @@ ignore = [
"I001", # Import block is un-sorted or un-formatted
"C901", # Function is too complex
"C408", # Rewrite as a literal
-
+ "W605", # invalid escape sequence, messes with some docstrings
]
[tool.ruff.per-file-ignores]
@@ -28,4 +29,4 @@ ignore = [
[tool.ruff.flake8-bugbear]
# Allow default arguments like, e.g., `data: List[str] = fastapi.Query(None)`.
-extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"]
\ No newline at end of file
+extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"]
diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py
index bb00fb3f..1e833fa8 100644
--- a/scripts/img2imgalt.py
+++ b/scripts/img2imgalt.py
@@ -149,9 +149,9 @@ class Script(scripts.Script):
sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False, elem_id=self.elem_id("sigma_adjustment"))
return [
- info,
+ info,
override_sampler,
- override_prompt, original_prompt, original_negative_prompt,
+ override_prompt, original_prompt, original_negative_prompt,
override_steps, st,
override_strength,
cfg, randomness, sigma_adjustment,
@@ -191,17 +191,17 @@ class Script(scripts.Script):
self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt, sigma_adjustment)
rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w, p=p)
-
+
combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5)
-
+
sampler = sd_samplers.create_sampler(p.sampler_name, p.sd_model)
sigmas = sampler.model_wrap.get_sigmas(p.steps)
-
+
noise_dt = combined_noise - (p.init_latent / sigmas[0])
-
+
p.seed = p.seed + 1
-
+
return sampler.sample_img2img(p, p.init_latent, noise_dt, conditioning, unconditional_conditioning, image_conditioning=p.image_conditioning)
p.sample = sample_extra
diff --git a/scripts/loopback.py b/scripts/loopback.py
index ad6609be..2d5feaf9 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -14,7 +14,7 @@ class Script(scripts.Script):
def show(self, is_img2img):
return is_img2img
- def ui(self, is_img2img):
+ def ui(self, is_img2img):
loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=self.elem_id("loops"))
final_denoising_strength = gr.Slider(minimum=0, maximum=1, step=0.01, label='Final denoising strength', value=0.5, elem_id=self.elem_id("final_denoising_strength"))
denoising_curve = gr.Dropdown(label="Denoising strength curve", choices=["Aggressive", "Linear", "Lazy"], value="Linear")
@@ -104,7 +104,7 @@ class Script(scripts.Script):
p.seed = processed.seed + 1
p.denoising_strength = calculate_denoising_strength(i + 1)
-
+
if state.skipped:
break
@@ -121,7 +121,7 @@ class Script(scripts.Script):
all_images.append(last_image)
p.inpainting_fill = original_inpainting_fill
-
+
if state.interrupted:
break
@@ -132,7 +132,7 @@ class Script(scripts.Script):
if opts.return_grid:
grids.append(grid)
-
+
all_images = grids + all_images
processed = Processed(p, all_images, initial_seed, initial_info)
diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py
index c0bbecc1..ea0632b6 100644
--- a/scripts/poor_mans_outpainting.py
+++ b/scripts/poor_mans_outpainting.py
@@ -19,7 +19,7 @@ class Script(scripts.Script):
def ui(self, is_img2img):
if not is_img2img:
return None
-
+
pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=self.elem_id("pixels"))
mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id=self.elem_id("mask_blur"))
inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", elem_id=self.elem_id("inpainting_fill"))
diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py
index fb06beab..88324fe6 100644
--- a/scripts/prompt_matrix.py
+++ b/scripts/prompt_matrix.py
@@ -96,7 +96,7 @@ class Script(scripts.Script):
p.prompt_for_display = positive_prompt
processed = process_images(p)
- grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2))
+ grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2))
grid = images.draw_prompt_matrix(grid, processed.images[0].width, processed.images[0].height, prompt_matrix_parts, margin_size)
processed.images.insert(0, grid)
processed.index_of_first_image = 1
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 9607077a..2378816f 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -109,7 +109,7 @@ class Script(scripts.Script):
def title(self):
return "Prompts from file or textbox"
- def ui(self, is_img2img):
+ def ui(self, is_img2img):
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False, elem_id=self.elem_id("checkbox_iterate"))
checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch"))
@@ -166,7 +166,7 @@ class Script(scripts.Script):
proc = process_images(copy_p)
images += proc.images
-
+
if checkbox_iterate:
p.seed = p.seed + (p.batch_size * p.n_iter)
all_prompts += proc.all_prompts
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index 0b1d3096..e614c23b 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -16,7 +16,7 @@ class Script(scripts.Script):
def show(self, is_img2img):
return is_img2img
- def ui(self, is_img2img):
+ def ui(self, is_img2img):
info = gr.HTML("Will upscale the image by the selected scale factor; use width and height sliders to set tile size
")
overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, elem_id=self.elem_id("overlap"))
scale_factor = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label='Scale Factor', value=2.0, elem_id=self.elem_id("scale_factor"))
--
cgit v1.2.3
From 1f57b948b78df872c5a8a1c6e6c7e3c35e06f969 Mon Sep 17 00:00:00 2001
From: Aarni Koskela
Date: Sat, 13 May 2023 19:14:10 +0300
Subject: Move localization to its own script block and load it first
---
modules/localization.py | 4 ++--
modules/ui.py | 12 ++++++------
2 files changed, 8 insertions(+), 8 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/localization.py b/modules/localization.py
index f6a6f2fb..ee9c65e7 100644
--- a/modules/localization.py
+++ b/modules/localization.py
@@ -23,7 +23,7 @@ def list_localizations(dirname):
localizations[fn] = file.path
-def localization_js(current_localization_name):
+def localization_js(current_localization_name: str) -> str:
fn = localizations.get(current_localization_name, None)
data = {}
if fn is not None:
@@ -34,4 +34,4 @@ def localization_js(current_localization_name):
print(f"Error loading localization from {fn}:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
- return f"var localization = {json.dumps(data)}\n"
+ return f"window.localization = {json.dumps(data)}"
diff --git a/modules/ui.py b/modules/ui.py
index ff82fff6..ff25c4ce 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1771,12 +1771,11 @@ def webpath(fn):
def javascript_html():
- script_js = os.path.join(script_path, "script.js")
- head = f'\n'
+ # Ensure localization is in `window` before scripts
+ head = f'\n'
- inline = f"{localization.localization_js(shared.opts.localization)};"
- if cmd_opts.theme is not None:
- inline += f"set_theme('{cmd_opts.theme}');"
+ script_js = os.path.join(script_path, "script.js")
+ head += f'\n'
for script in modules.scripts.list_scripts("javascript", ".js"):
head += f'\n'
@@ -1784,7 +1783,8 @@ def javascript_html():
for script in modules.scripts.list_scripts("javascript", ".mjs"):
head += f'\n'
- head += f'\n'
+ if cmd_opts.theme:
+ head += f'\n'
return head
--
cgit v1.2.3
From 6302978ff8e51ad0917c62806ca127b514088a70 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Tue, 16 May 2023 15:14:44 +0300
Subject: restore nqsp in footer that was lost during linting
---
modules/ui.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index ff25c4ce..8e51e782 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1841,15 +1841,15 @@ def versions_html():
return f"""
version: {tag}
- •
+ •
python: {python_version}
- •
+ •
torch: {getattr(torch, '__long_version__',torch.__version__)}
- •
+ •
xformers: {xformers_version}
- •
+ •
gradio: {gr.__version__}
- •
+ •
checkpoint: N/A
"""
--
cgit v1.2.3
From 0d31f20cbd556ea4ba3d8ad9254bcce71c32088c Mon Sep 17 00:00:00 2001
From: bobzilladev
Date: Tue, 16 May 2023 13:15:30 -0400
Subject: Use ngrok-py library
---
launch.py | 4 ++--
modules/cmd_args.py | 3 ++-
modules/ngrok.py | 37 ++++++++++++++-----------------------
modules/ui.py | 2 +-
4 files changed, 19 insertions(+), 27 deletions(-)
(limited to 'modules/ui.py')
diff --git a/launch.py b/launch.py
index cfc0cffa..871d3ea8 100644
--- a/launch.py
+++ b/launch.py
@@ -294,8 +294,8 @@ def prepare_environment():
elif platform.system() == "Linux":
run_pip(f"install {xformers_package}", "xformers")
- if not is_installed("pyngrok") and args.ngrok:
- run_pip("install pyngrok", "ngrok")
+ if not is_installed("ngrok") and args.ngrok:
+ run_pip("install ngrok", "ngrok")
os.makedirs(os.path.join(script_path, dir_repos), exist_ok=True)
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index d906a571..bf18b7b7 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -1,4 +1,5 @@
import argparse
+import json
import os
from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file
@@ -39,7 +40,7 @@ parser.add_argument("--precision", type=str, help="evaluate at this precision",
parser.add_argument("--upcast-sampling", action='store_true', help="upcast sampling. No effect with --no-half. Usually produces similar results to --no-half with better performance while using less memory.")
parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site")
parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
-parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us")
+parser.add_argument("--ngrok-options", type=json.loads, help='The options to pass to ngrok in JSON format, e.g.: \'{"authtoken_from_env":true, "basic_auth":"user:password", "oauth_provider":"google", "oauth_allow_emails":"user@asdf.com"}\'', default=dict())
parser.add_argument("--enable-insecure-extension-access", action='store_true', help="enable extensions tab regardless of other options")
parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
diff --git a/modules/ngrok.py b/modules/ngrok.py
index 7a7b4b26..caa352d1 100644
--- a/modules/ngrok.py
+++ b/modules/ngrok.py
@@ -1,6 +1,7 @@
-from pyngrok import ngrok, conf, exception
+import ngrok
-def connect(token, port, region):
+# Connect to ngrok for ingress
+def connect(token, port, options):
account = None
if token is None:
token = 'None'
@@ -10,28 +11,18 @@ def connect(token, port, region):
token, username, password = token.split(':', 2)
account = f"{username}:{password}"
- config = conf.PyngrokConfig(
- auth_token=token, region=region
- )
-
- # Guard for existing tunnels
- existing = ngrok.get_tunnels(pyngrok_config=config)
- if existing:
- for established in existing:
- # Extra configuration in the case that the user is also using ngrok for other tunnels
- if established.config['addr'][-4:] == str(port):
- public_url = existing[0].public_url
- print(f'ngrok has already been connected to localhost:{port}! URL: {public_url}\n'
- 'You can use this link after the launch is complete.')
- return
-
+ # For all options see: https://github.com/ngrok/ngrok-py/blob/main/examples/ngrok-connect-full.py
+ if not options.get('authtoken_from_env'):
+ options['authtoken'] = token
+ if account:
+ options['basic_auth'] = account
+ if not options.get('session_metadata'):
+ options['session_metadata'] = 'stable-diffusion-webui'
+
try:
- if account is None:
- public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url
- else:
- public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True, auth=account).public_url
- except exception.PyngrokNgrokError:
- print(f'Invalid ngrok authtoken, ngrok connection aborted.\n'
+ public_url = ngrok.connect(f"127.0.0.1:{port}", **options).url()
+ except Exception as e:
+ print(f'Invalid ngrok authtoken? ngrok connection aborted due to: {e}\n'
f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
else:
print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
diff --git a/modules/ui.py b/modules/ui.py
index f07bcc41..5f5405f0 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -59,7 +59,7 @@ if cmd_opts.ngrok is not None:
ngrok.connect(
cmd_opts.ngrok,
cmd_opts.port if cmd_opts.port is not None else 7860,
- cmd_opts.ngrok_region
+ cmd_opts.ngrok_options
)
--
cgit v1.2.3
From 85b4f89926f7c3aaa7846dcbb47df3fd3b483b6b Mon Sep 17 00:00:00 2001
From: Aarni Koskela
Date: Thu, 11 May 2023 23:46:45 +0300
Subject: Replace state.need_restart with state.server_command + replace poll
loop with signal
---
modules/shared.py | 42 +++++++++++++++++++++++++++++++++++++++++-
modules/ui.py | 6 +-----
modules/ui_extensions.py | 7 ++-----
webui.py | 39 ++++++++++++++++++++++++---------------
4 files changed, 68 insertions(+), 26 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/shared.py b/modules/shared.py
index 3abf71c0..648a2a19 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -2,6 +2,7 @@ import datetime
import json
import os
import sys
+import threading
import time
import gradio as gr
@@ -110,8 +111,47 @@ class State:
id_live_preview = 0
textinfo = None
time_start = None
- need_restart = False
server_start = None
+ _server_command_signal = threading.Event()
+ _server_command: str | None = None
+
+ @property
+ def need_restart(self) -> bool:
+ # Compatibility getter for need_restart.
+ return self.server_command == "restart"
+
+ @need_restart.setter
+ def need_restart(self, value: bool) -> None:
+ # Compatibility setter for need_restart.
+ if value:
+ self.server_command = "restart"
+
+ @property
+ def server_command(self):
+ return self._server_command
+
+ @server_command.setter
+ def server_command(self, value: str | None) -> None:
+ """
+ Set the server command to `value` and signal that it's been set.
+ """
+ self._server_command = value
+ self._server_command_signal.set()
+
+ def wait_for_server_command(self, timeout: float | None = None) -> str | None:
+ """
+ Wait for server command to get set; return and clear the value and signal.
+ """
+ if self._server_command_signal.wait(timeout):
+ self._server_command_signal.clear()
+ req = self._server_command
+ self._server_command = None
+ return req
+ return None
+
+ def request_restart(self) -> None:
+ self.interrupt()
+ self.server_command = True
def skip(self):
self.skipped = True
diff --git a/modules/ui.py b/modules/ui.py
index 8e51e782..bed8464e 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1609,12 +1609,8 @@ def create_ui():
outputs=[]
)
- def request_restart():
- shared.state.interrupt()
- shared.state.need_restart = True
-
restart_gradio.click(
- fn=request_restart,
+ fn=shared.state.request_restart,
_js='restart_reload',
inputs=[],
outputs=[],
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index d7a0f685..4ba3bdd7 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -52,9 +52,7 @@ def apply_and_restart(disable_list, update_list, disable_all):
shared.opts.disabled_extensions = disabled
shared.opts.disable_all_extensions = disable_all
shared.opts.save(shared.config_filename)
-
- shared.state.interrupt()
- shared.state.need_restart = True
+ shared.state.request_restart()
def save_config_state(name):
@@ -92,8 +90,7 @@ def restore_config_state(confirmed, config_state_name, restore_type):
if restore_type == "webui" or restore_type == "both":
config_states.restore_webui_config(config_state)
- shared.state.interrupt()
- shared.state.need_restart = True
+ shared.state.request_restart()
return ""
diff --git a/webui.py b/webui.py
index 293a16cc..39dec3ca 100644
--- a/webui.py
+++ b/webui.py
@@ -234,7 +234,10 @@ def initialize():
print(f'Interrupted with signal {sig} in {frame}')
os._exit(0)
- signal.signal(signal.SIGINT, sigint_handler)
+ if not os.environ.get("COVERAGE_RUN"):
+ # Don't install the immediate-quit handler when running under coverage,
+ # as then the coverage report won't be generated.
+ signal.signal(signal.SIGINT, sigint_handler)
def setup_middleware(app):
@@ -255,19 +258,6 @@ def create_api(app):
return api
-def wait_on_server(demo=None):
- while 1:
- time.sleep(0.5)
- if shared.state.need_restart:
- shared.state.need_restart = False
- time.sleep(0.5)
- demo.close()
- time.sleep(0.5)
-
- modules.script_callbacks.app_reload_callback()
- break
-
-
def api_only():
initialize()
@@ -328,6 +318,7 @@ def webui():
inbrowser=cmd_opts.autolaunch,
prevent_thread_lock=True
)
+
# after initial launch, disable --autolaunch for subsequent restarts
cmd_opts.autolaunch = False
@@ -359,8 +350,26 @@ def webui():
redirector.get("/")
gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}")
- wait_on_server(shared.demo)
+ try:
+ while True:
+ server_command = shared.state.wait_for_server_command(timeout=5)
+ if server_command:
+ if server_command in ("stop", "restart"):
+ break
+ else:
+ print(f"Unknown server command: {server_command}")
+ except KeyboardInterrupt:
+ server_command = "stop"
+
+ if server_command == "stop":
+ # If we catch a keyboard interrupt, we want to stop the server and exit.
+ print('Caught KeyboardInterrupt, stopping...')
+ shared.demo.close()
+ break
print('Restarting UI...')
+ shared.demo.close()
+ time.sleep(0.5)
+ modules.script_callbacks.app_reload_callback()
startup_timer.reset()
--
cgit v1.2.3
From b397f63e00bbfbe9087d80abb457aa9a593b181b Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 17 May 2023 23:11:33 +0300
Subject: add option to reorder tabs fix Reload UI not working
---
modules/shared.py | 3 ++-
modules/ui.py | 5 ++++-
2 files changed, 6 insertions(+), 2 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/shared.py b/modules/shared.py
index 23563582..332cf1cf 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -151,7 +151,7 @@ class State:
def request_restart(self) -> None:
self.interrupt()
- self.server_command = True
+ self.server_command = "restart"
def skip(self):
self.skipped = True
@@ -478,6 +478,7 @@ options_templates.update(options_section(('ui', "User interface"), {
"keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
"keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),
"quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_restart(),
+ "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(),
"hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(),
"ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
"ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(),
diff --git a/modules/ui.py b/modules/ui.py
index bed8464e..a47af214 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1644,7 +1644,10 @@ def create_ui():
parameters_copypaste.connect_paste_params_buttons()
with gr.Tabs(elem_id="tabs") as tabs:
- for interface, label, ifid in interfaces:
+ tab_order = {k: i for i, k in enumerate(opts.ui_tab_order)}
+ sorted_interfaces = sorted(interfaces, key=lambda x: tab_order.get(x[1], 9999))
+
+ for interface, label, ifid in sorted_interfaces:
if label in shared.opts.hidden_tabs:
continue
with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"):
--
cgit v1.2.3
From e5dd4b4ebf817d35285095baa2246dfc5647186e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 17 May 2023 23:27:06 +0300
Subject: remove some code duplication from #9348
---
javascript/ui.js | 54 +++++++++++++++---------------------------------------
modules/ui.py | 9 ++++-----
2 files changed, 19 insertions(+), 44 deletions(-)
(limited to 'modules/ui.py')
diff --git a/javascript/ui.js b/javascript/ui.js
index 56ee05aa..6d4119d7 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -441,51 +441,27 @@ function updateImg2imgResizeToTextAfterChangingImage(){
}
-function setRandomSeed(target_interface) {
- let seed = gradioApp().querySelector(`#${target_interface}_seed input`);
- if (!seed) {
- return [];
- }
- seed.value = "-1";
- seed.dispatchEvent(new Event("input"));
- return [];
-}
-function setRandomSubseed(target_interface) {
- let subseed = gradioApp().querySelector(`#${target_interface}_subseed input`);
- if (!subseed) {
- return [];
- }
- subseed.value = "-1";
- subseed.dispatchEvent(new Event("input"));
- return [];
-}
-function switchWidthHeightTxt2Img() {
- let width = gradioApp().querySelector("#txt2img_width input[type=number]");
- let height = gradioApp().querySelector("#txt2img_height input[type=number]");
- if (!width || !height) {
- return [];
- }
- let tmp = width.value;
- width.value = height.value;
- height.value = tmp;
- width.dispatchEvent(new Event("input"));
- height.dispatchEvent(new Event("input"));
+function setRandomSeed(elem_id) {
+ var input = gradioApp().querySelector("#" + elem_id + " input");
+ if (!input) return [];
+
+ input.value = "-1";
+ updateInput(input);
return [];
}
-function switchWidthHeightImg2Img() {
- let width = gradioApp().querySelector("#img2img_width input[type=number]");
- let height = gradioApp().querySelector("#img2img_height input[type=number]");
- if (!width || !height) {
- return [];
- }
- let tmp = width.value;
+function switchWidthHeight(tabname) {
+ var width = gradioApp().querySelector("#" + tabname + "_width input[type=number]");
+ var height = gradioApp().querySelector("#" + tabname + "_height input[type=number]");
+ if (!width || !height) return [];
+
+ var tmp = width.value;
width.value = height.value;
height.value = tmp;
- width.dispatchEvent(new Event("input"));
- height.dispatchEvent(new Event("input"));
+
+ updateInput(width);
+ updateInput(height);
return [];
}
-
diff --git a/modules/ui.py b/modules/ui.py
index 552a8af2..e9438df3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -189,9 +189,8 @@ def create_seed_inputs(target_interface):
seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=f"{target_interface}_seed_resize_from_w")
seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=f"{target_interface}_seed_resize_from_h")
- target_interface_state = gr.Textbox(target_interface, visible=False)
- random_seed.click(fn=None, _js="setRandomSeed", show_progress=False, inputs=[target_interface_state], outputs=[])
- random_subseed.click(fn=None, _js="setRandomSubseed", show_progress=False, inputs=[target_interface_state], outputs=[])
+ random_seed.click(fn=None, _js="function(){setRandomSeed('" + target_interface + "_seed')}", show_progress=False, inputs=[], outputs=[])
+ random_subseed.click(fn=None, _js="function(){setRandomSeed('" + target_interface + "_subseed')}", show_progress=False, inputs=[], outputs=[])
def change_visibility(show):
return {comp: gr_show(show) for comp in seed_extras}
@@ -575,7 +574,7 @@ def create_ui():
txt2img_prompt.submit(**txt2img_args)
submit.click(**txt2img_args)
- res_switch_btn.click(fn=None, _js="switchWidthHeightTxt2Img", inputs=None, outputs=None, show_progress=False)
+ res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('txt2img')}", inputs=None, outputs=None, show_progress=False)
restore_progress_button.click(
fn=progress.restore_progress,
@@ -951,7 +950,7 @@ def create_ui():
img2img_prompt.submit(**img2img_args)
submit.click(**img2img_args)
- res_switch_btn.click(fn=None, _js="switchWidthHeightImg2Img", inputs=None, outputs=None, show_progress=False)
+ res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('img2img')}", inputs=None, outputs=None, show_progress=False)
restore_progress_button.click(
fn=progress.restore_progress,
--
cgit v1.2.3
From 61ee563df9112ae04e547622b4c5e9fd4bc9d978 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Wed, 17 May 2023 23:42:01 +0300
Subject: option to specify editor height for img2img
---
modules/shared.py | 1 +
modules/ui.py | 8 ++++----
style.css | 6 ------
3 files changed, 5 insertions(+), 10 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/shared.py b/modules/shared.py
index 332cf1cf..9e9e8cd4 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -460,6 +460,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
options_templates.update(options_section(('ui', "User interface"), {
"localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(),
"gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(),
+ "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(),
"return_grid": OptionInfo(True, "Show grid in results for web"),
"return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"),
"return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"),
diff --git a/modules/ui.py b/modules/ui.py
index e9438df3..eda55f40 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -687,19 +687,19 @@ def create_ui():
img2img_selected_tab = gr.State(0)
with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
- init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=480)
+ init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=opts.img2img_editor_height)
add_copy_image_controls('img2img', init_img)
with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch:
- sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
+ sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height)
add_copy_image_controls('sketch', sketch)
with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint:
- init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=480)
+ init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=opts.img2img_editor_height)
add_copy_image_controls('inpaint', init_img_with_mask)
with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color:
- inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=480)
+ inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height)
inpaint_color_sketch_orig = gr.State(None)
add_copy_image_controls('inpaint_sketch', inpaint_color_sketch)
diff --git a/style.css b/style.css
index f8ffbd8d..f977fe62 100644
--- a/style.css
+++ b/style.css
@@ -328,12 +328,6 @@ div#extras_scale_to_tab div.form{
flex-direction: row;
}
-#mode_img2img .gradio-image > div.fixed-height, #mode_img2img .gradio-image > div.fixed-height img{
- height: 480px !important;
- max-height: 480px !important;
- min-height: 480px !important;
-}
-
#img2img_sketch, #img2maskimg, #inpaint_sketch {
overflow: overlay !important;
resize: auto;
--
cgit v1.2.3
From 3694379f26500f54a7c6ece3d171ffd6635e7a93 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 18 May 2023 00:03:16 +0300
Subject: rework #8863 to work with all img2img tabs
---
modules/ui.py | 10 ++++++++--
style.css | 4 ++--
2 files changed, 10 insertions(+), 4 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index b915482f..9ae0e2a5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -954,6 +954,14 @@ def create_ui():
res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('img2img')}", inputs=None, outputs=None, show_progress=False)
+ detect_image_size_btn.click(
+ fn=lambda w, h, _: (w or gr.update(), h or gr.update()),
+ _js="currentImg2imgSourceResolution",
+ inputs=[dummy_component, dummy_component, dummy_component],
+ outputs=[width, height],
+ show_progress=False,
+ )
+
restore_progress_button.click(
fn=progress.restore_progress,
_js="restoreProgressImg2img",
@@ -967,8 +975,6 @@ def create_ui():
show_progress=False,
)
- detect_image_size_btn.click(lambda i, w, h : i.size if i is not None else (w, h), inputs=[init_img, width, height], outputs=[width, height])
-
img2img_interrogate.click(
fn=lambda *args: process_interrogate(interrogate, *args),
**interrogate_args,
diff --git a/style.css b/style.css
index f977fe62..b300dfa1 100644
--- a/style.css
+++ b/style.css
@@ -320,8 +320,8 @@ button.custom-button{
div.dimensions-tools{
min-width: 0 !important;
max-width: fit-content;
- flex-direction: row;
- align-content: center;
+ flex-direction: column;
+ place-content: center;
}
div#extras_scale_to_tab div.form{
--
cgit v1.2.3
From bb431df52bf3dc5e233e42907f2d8f56e4fb6c0c Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 18 May 2023 10:16:33 +0300
Subject: python linter fixes
---
modules/ui.py | 2 +-
modules/ui_extra_networks.py | 1 -
2 files changed, 1 insertion(+), 2 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 386f493b..3be5257a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -974,7 +974,7 @@ def create_ui():
],
show_progress=False,
)
-
+
img2img_interrogate.click(
fn=lambda *args: process_interrogate(interrogate, *args),
**interrogate_args,
diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 8669cc1a..8bd0722e 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -1,7 +1,6 @@
import os.path
import urllib.parse
from pathlib import Path
-from PIL import PngImagePlugin
from modules import shared
from modules.images import read_info_from_image, save_image_with_geninfo
--
cgit v1.2.3
From 63c02314ccad8aaed853cf5b17e79c4a32d14657 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Thu, 18 May 2023 13:06:13 -0400
Subject: .change -> .release for hires input
Improves overall UI responsiveness.
---
modules/ui.py | 12 ++++++++----
1 file changed, 8 insertions(+), 4 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 3be5257a..02596757 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -513,15 +513,14 @@ def create_ui():
with FormGroup(elem_id="txt2img_script_container"):
custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
- hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
- for input in hr_resolution_preview_inputs:
- input.change(
+ def update_resolution_hires_input(inp, evt):
+ getattr(inp, evt)(
fn=calc_resolution_hires,
inputs=hr_resolution_preview_inputs,
outputs=[hr_final_resolution],
show_progress=False,
)
- input.change(
+ getattr(inp, evt)(
None,
_js="onCalcResolutionHires",
inputs=hr_resolution_preview_inputs,
@@ -529,6 +528,11 @@ def create_ui():
show_progress=False,
)
+ hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
+ update_resolution_hires_input(enable_hr, 'change')
+ for input in hr_resolution_preview_inputs[1:]:
+ update_resolution_hires_input(input, 'release')
+
txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
--
cgit v1.2.3
From ff0e17174f8d93a71fdd5a4a80a4629bbf97f822 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 18 May 2023 20:16:09 +0300
Subject: rework hires prompts/sampler code to among other things support
different extra networks in first/second pass rework quoting for infotext
items that have commas in them to use json (should be backwards compatible
except for cases where it didn't work previously) add some locals from
processing function into the Processing class as fields
---
modules/generation_parameters_copypaste.py | 36 ++--
modules/processing.py | 261 ++++++++++++++++-------------
modules/shared.py | 6 +-
modules/txt2img.py | 4 +-
modules/ui.py | 14 +-
5 files changed, 188 insertions(+), 133 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index b34046a0..d5f0a49b 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -1,5 +1,6 @@
import base64
import io
+import json
import os
import re
@@ -34,13 +35,20 @@ def reset():
def quote(text):
- if ',' not in str(text):
+ if ',' not in str(text) and '\n' not in str(text):
return text
- text = str(text)
- text = text.replace('\\', '\\\\')
- text = text.replace('"', '\\"')
- return f'"{text}"'
+ return json.dumps(text, ensure_ascii=False)
+
+
+def unquote(text):
+ if len(text) == 0 or text[0] != '"' or text[-1] != '"':
+ return text
+
+ try:
+ return json.loads(text)
+ except Exception:
+ return text
def image_from_url_text(filedata):
@@ -261,7 +269,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
res["Negative prompt"] = negative_prompt
for k, v in re_param.findall(lastline):
- v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v
+ if v[0] == '"' and v[-1] == '"':
+ v = unquote(v)
+
m = re_imagesize.match(v)
if m is not None:
res[f"{k}-1"] = m.group(1)
@@ -269,11 +279,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
else:
res[k] = v
- if k.startswith("Hires prompt"):
- res["Hires prompt"] = v[1:][:-1].replace(';', ',')
- elif k.startswith("Hires negative prompt"):
- res["Hires negative prompt"] = v[1:][:-1].replace(';', ',')
-
# Missing CLIP skip means it was set to 1 (the default)
if "Clip skip" not in res:
res["Clip skip"] = "1"
@@ -286,6 +291,15 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
res["Hires resize-1"] = 0
res["Hires resize-2"] = 0
+ if "Hires sampler" not in res:
+ res["Hires sampler"] = "Use same sampler"
+
+ if "Hires prompt" not in res:
+ res["Hires prompt"] = ""
+
+ if "Hires negative prompt" not in res:
+ res["Hires negative prompt"] = ""
+
restore_old_hires_fix_params(res)
# Missing RNG means the default was set, which is GPU RNG
diff --git a/modules/processing.py b/modules/processing.py
index dd14c486..29a3743f 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -169,6 +169,16 @@ class StableDiffusionProcessing:
self.is_hr_pass = False
self.sampler = None
+ self.prompts = None
+ self.negative_prompts = None
+ self.seeds = None
+ self.subseeds = None
+
+ self.step_multiplier = 1
+ self.cached_uc = [None, None]
+ self.cached_c = [None, None]
+ self.uc = None
+ self.c = None
@property
def sd_model(self):
@@ -271,11 +281,15 @@ class StableDiffusionProcessing:
def init(self, all_prompts, all_seeds, all_subseeds):
pass
- def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts, hr_conditioning=None, hr_unconditional_conditioning=None):
+ def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
raise NotImplementedError()
def close(self):
self.sampler = None
+ self.c = None
+ self.uc = None
+ self.cached_c = [None, None]
+ self.cached_uc = [None, None]
def get_token_merging_ratio(self, for_hr=False):
if for_hr:
@@ -283,6 +297,52 @@ class StableDiffusionProcessing:
return self.token_merging_ratio or opts.token_merging_ratio
+ def setup_prompts(self):
+ if type(self.prompt) == list:
+ self.all_prompts = self.prompt
+ else:
+ self.all_prompts = self.batch_size * self.n_iter * [self.prompt]
+
+ if type(self.negative_prompt) == list:
+ self.all_negative_prompts = self.negative_prompt
+ else:
+ self.all_negative_prompts = self.batch_size * self.n_iter * [self.negative_prompt]
+
+ self.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_prompts]
+ self.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_negative_prompts]
+
+ def get_conds_with_caching(self, function, required_prompts, steps, cache):
+ """
+ Returns the result of calling function(shared.sd_model, required_prompts, steps)
+ using a cache to store the result if the same arguments have been used before.
+
+ cache is an array containing two elements. The first element is a tuple
+ representing the previously used arguments, or None if no arguments
+ have been used before. The second element is where the previously
+ computed result is stored.
+ """
+
+ if cache[0] is not None and (required_prompts, steps) == cache[0]:
+ return cache[1]
+
+ with devices.autocast():
+ cache[1] = function(shared.sd_model, required_prompts, steps)
+
+ cache[0] = (required_prompts, steps)
+ return cache[1]
+
+ def setup_conds(self):
+ sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
+ self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
+
+ self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.negative_prompts, self.steps * self.step_multiplier, self.cached_uc)
+ self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.prompts, self.steps * self.step_multiplier, self.cached_c)
+
+ def parse_extra_network_prompts(self):
+ self.prompts, extra_network_data = extra_networks.parse_prompts(self.prompts)
+
+ return extra_network_data
+
class Processed:
def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None, comments=""):
@@ -582,29 +642,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
comments = {}
- if type(p.prompt) == list:
- p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.prompt]
- else:
- p.all_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)]
-
- if type(p.negative_prompt) == list:
- p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.negative_prompt]
- else:
- p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)]
-
- if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr and p.hr_prompt == '':
- p.all_hr_prompts, p.all_hr_negative_prompts = p.all_prompts, p.all_negative_prompts
- elif p.enable_hr and p.hr_prompt != '':
- if type(p.prompt) == list:
- p.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt]
- else:
- p.all_hr_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)]
-
- if type(p.negative_prompt) == list:
- p.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.hr_negative_prompt]
- else:
- p.all_hr_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)]
+ p.setup_prompts()
if type(seed) == list:
p.all_seeds = seed
@@ -628,29 +666,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
infotexts = []
output_images = []
- cached_uc = [None, None]
- cached_c = [None, None]
-
- def get_conds_with_caching(function, required_prompts, steps, cache):
- """
- Returns the result of calling function(shared.sd_model, required_prompts, steps)
- using a cache to store the result if the same arguments have been used before.
-
- cache is an array containing two elements. The first element is a tuple
- representing the previously used arguments, or None if no arguments
- have been used before. The second element is where the previously
- computed result is stored.
- """
-
- if cache[0] is not None and (required_prompts, steps) == cache[0]:
- return cache[1]
-
- with devices.autocast():
- cache[1] = function(shared.sd_model, required_prompts, steps)
-
- cache[0] = (required_prompts, steps)
- return cache[1]
-
with torch.no_grad(), p.sd_model.ema_scope():
with devices.autocast():
p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
@@ -672,40 +687,25 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if state.interrupted:
break
- prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
- negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
-
- if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr:
- if p.hr_prompt == '':
- hr_prompts, hr_negative_prompts = prompts, negative_prompts
- else:
- hr_prompts = p.all_hr_prompts[n * p.batch_size:(n + 1) * p.batch_size]
- hr_negative_prompts = p.all_hr_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
-
- seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
- subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
+ p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
+ p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
+ p.seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
+ p.subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
if p.scripts is not None:
- p.scripts.before_process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds)
+ p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
- if len(prompts) == 0:
+ if len(p.prompts) == 0:
break
- prompts, extra_network_data = extra_networks.parse_prompts(prompts)
-
- if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr and hr_prompts != prompts:
- _, hr_extra_network_data = extra_networks.parse_prompts(hr_prompts)
- extra_network_data.update(hr_extra_network_data)
-
+ extra_network_data = p.parse_extra_network_prompts()
if not p.disable_extra_networks:
with devices.autocast():
extra_networks.activate(p, extra_network_data)
if p.scripts is not None:
- p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds)
+ p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
# params.txt should be saved after scripts.process_batch, since the
# infotext could be modified by that callback
@@ -716,18 +716,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
processed = Processed(p, [], p.seed, "")
file.write(processed.infotext(p, 0))
- sampler_config = sd_samplers.find_sampler_config(p.sampler_name)
- step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
- uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc)
- c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c)
-
- if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr:
- if prompts != hr_prompts:
- hr_uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, p.steps, cached_uc)
- hr_c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, p.steps, cached_c)
- else:
- hr_uc, hr_c = uc, c
+ p.setup_conds()
if len(model_hijack.comments) > 0:
for comment in model_hijack.comments:
@@ -736,15 +725,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.n_iter > 1:
shared.state.job = f"Batch {n+1} out of {p.n_iter}"
-
with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast():
- if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr:
- samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, hr_conditioning=hr_c, hr_unconditional_conditioning=hr_uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
- else:
- samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
- else:
- samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
+ samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
x_samples_ddim = [decode_first_stage(p.sd_model, samples_ddim[i:i+1].to(dtype=devices.dtype_vae))[0].cpu() for i in range(samples_ddim.size(0))]
for x in x_samples_ddim:
@@ -771,7 +753,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.restore_faces:
if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
- images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
+ images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
devices.torch_gc()
@@ -788,13 +770,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.color_corrections is not None and i < len(p.color_corrections):
if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
- images.save_image(image_without_cc, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
+ images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
image = apply_color_correction(p.color_corrections[i], image)
image = apply_overlay(image, p.paste_to, i, p.overlay_images)
if opts.samples_save and not p.do_not_save_samples:
- images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
+ images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p)
text = infotext(n, i)
infotexts.append(text)
@@ -807,10 +789,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
if opts.save_mask:
- images.save_image(image_mask, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
+ images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
if opts.save_mask_composite:
- images.save_image(image_mask_composite, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
+ images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
if opts.return_mask:
output_images.append(image_mask)
@@ -879,7 +861,7 @@ def old_hires_fix_first_pass_dimensions(width, height):
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
sampler = None
- def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler: str = '---', hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
+ def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
super().__init__(**kwargs)
self.enable_hr = enable_hr
self.denoising_strength = denoising_strength
@@ -890,9 +872,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.hr_resize_y = hr_resize_y
self.hr_upscale_to_x = hr_resize_x
self.hr_upscale_to_y = hr_resize_y
- self.hr_sampler = hr_sampler
- self.hr_prompt = hr_prompt if hr_prompt != '' else ''
- self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else ''
+ self.hr_sampler_name = hr_sampler_name
+ self.hr_prompt = hr_prompt
+ self.hr_negative_prompt = hr_negative_prompt
self.all_hr_prompts = None
self.all_hr_negative_prompts = None
@@ -906,14 +888,23 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.truncate_y = 0
self.applied_old_hires_behavior_to = None
+ self.hr_prompts = None
+ self.hr_negative_prompts = None
+ self.hr_extra_network_data = None
+
+ self.hr_c = None
+ self.hr_uc = None
+
def init(self, all_prompts, all_seeds, all_subseeds):
if self.enable_hr:
- if self.hr_sampler != '---':
- self.extra_generation_params["Hires sampler"] = self.hr_sampler
+ if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name:
+ self.extra_generation_params["Hires sampler"] = self.hr_sampler_name
+
+ if tuple(self.hr_prompt) != tuple(self.prompt):
+ self.extra_generation_params["Hires prompt"] = self.hr_prompt
- if self.hr_prompt != '':
- self.extra_generation_params["Hires prompt"] = f'({self.hr_prompt.replace(",", ";")})'
- self.extra_generation_params["Hires negative prompt"] = f'({self.hr_negative_prompt.replace(",", ";")})'
+ if tuple(self.hr_negative_prompt) != tuple(self.negative_prompt):
+ self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt
if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height):
self.hr_resize_x = self.width
@@ -975,7 +966,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if self.hr_upscaler is not None:
self.extra_generation_params["Hires upscaler"] = self.hr_upscaler
- def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts, hr_conditioning=None, hr_unconditional_conditioning=None):
+ def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest")
@@ -1044,16 +1035,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
shared.state.nextjob()
- img2img_sampler_name = self.sampler_name
+ img2img_sampler_name = self.hr_sampler_name or self.sampler_name
if self.sampler_name in ['PLMS', 'UniPC']: # PLMS/UniPC do not support img2img so we just silently switch to DDIM
img2img_sampler_name = 'DDIM'
- if self.hr_sampler == '---':
- pass
- else:
- img2img_sampler_name = self.hr_sampler
-
self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model)
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
@@ -1064,9 +1050,13 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
x = None
devices.torch_gc()
+ if not self.disable_extra_networks:
+ with devices.autocast():
+ extra_networks.activate(self, self.hr_extra_network_data)
+
sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio(for_hr=True))
- samples = self.sampler.sample_img2img(self, samples, noise, hr_conditioning, hr_unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
+ samples = self.sampler.sample_img2img(self, samples, noise, self.hr_c, self.hr_uc, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio())
@@ -1074,6 +1064,53 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return samples
+ def close(self):
+ self.hr_c = None
+ self.hr_uc = None
+
+ def setup_prompts(self):
+ super().setup_prompts()
+
+ if not self.enable_hr:
+ return
+
+ if self.hr_prompt == '':
+ self.hr_prompt = self.prompt
+
+ if self.hr_negative_prompt == '':
+ self.hr_negative_prompt = self.negative_prompt
+
+ if type(self.hr_prompt) == list:
+ self.all_hr_prompts = self.hr_prompt
+ else:
+ self.all_hr_prompts = self.batch_size * self.n_iter * [self.hr_prompt]
+
+ if type(self.hr_negative_prompt) == list:
+ self.all_hr_negative_prompts = self.hr_negative_prompt
+ else:
+ self.all_hr_negative_prompts = self.batch_size * self.n_iter * [self.hr_negative_prompt]
+
+ self.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_hr_prompts]
+ self.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_hr_negative_prompts]
+
+ def setup_conds(self):
+ super().setup_conds()
+
+ if self.enable_hr:
+ self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.hr_negative_prompts, self.steps * self.step_multiplier, self.cached_uc)
+ self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.hr_prompts, self.steps * self.step_multiplier, self.cached_c)
+
+ def parse_extra_network_prompts(self):
+ res = super().parse_extra_network_prompts()
+
+ if self.enable_hr:
+ self.hr_prompts = self.all_hr_prompts[self.iteration * self.batch_size:(self.iteration + 1) * self.batch_size]
+ self.hr_negative_prompts = self.all_hr_negative_prompts[self.iteration * self.batch_size:(self.iteration + 1) * self.batch_size]
+
+ self.hr_prompts, self.hr_extra_network_data = extra_networks.parse_prompts(self.hr_prompts)
+
+ return res
+
class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
sampler = None
diff --git a/modules/shared.py b/modules/shared.py
index 9e9e8cd4..fdbab5c4 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -454,6 +454,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
"extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks").info("in pixels"),
"extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"),
"extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"),
+ "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(),
"sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks),
}))
@@ -481,8 +482,9 @@ options_templates.update(options_section(('ui', "User interface"), {
"quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_restart(),
"ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(),
"hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(),
- "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
- "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(),
+ "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order").needs_restart(),
+ "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires sampler selection").needs_restart(),
+ "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(),
}))
options_templates.update(options_section(('infotext', "Infotext"), {
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 3b4c985e..2e7d202d 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html
def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, *args):
override_settings = create_override_settings_dict(override_settings_texts)
-
+
p = processing.StableDiffusionProcessingTxt2Img(
sd_model=shared.sd_model,
outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
@@ -39,7 +39,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
hr_second_pass_steps=hr_second_pass_steps,
hr_resize_x=hr_resize_x,
hr_resize_y=hr_resize_y,
- hr_sampler=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else '---',
+ hr_sampler_name=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else None,
hr_prompt=hr_prompt,
hr_negative_prompt=hr_negative_prompt,
override_settings=override_settings,
diff --git a/modules/ui.py b/modules/ui.py
index c3ff48b4..2016ed74 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -499,16 +499,16 @@ def create_ui():
hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
- with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact"):
- hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers_for_img2img], value="---", type="index")
+ with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container:
+ hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index")
- with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact"):
+ with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
with gr.Column(scale=80):
with gr.Row():
- hr_prompt = gr.Textbox(label="Prompt", elem_id=f"hires_prompt", show_label=False, lines=3, placeholder="Prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)")
+ hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.")
with gr.Column(scale=80):
with gr.Row():
- hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)")
+ hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.")
elif category == "batch":
if not opts.dimensions_and_batch_together:
@@ -646,9 +646,11 @@ def create_ui():
(hr_second_pass_steps, "Hires steps"),
(hr_resize_x, "Hires resize-1"),
(hr_resize_y, "Hires resize-2"),
- (hr_sampler_index, "Hires sampling method"),
+ (hr_sampler_index, "Hires sampler"),
+ (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" else gr.update()),
(hr_prompt, "Hires prompt"),
(hr_negative_prompt, "Hires negative prompt"),
+ (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()),
*modules.scripts.scripts_txt2img.infotext_fields
]
parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings)
--
cgit v1.2.3
From 57275da90379ae78232944e7cf181a55ed7c1b57 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Thu, 18 May 2023 13:25:32 -0400
Subject: Reorder variable assignment
---
modules/ui.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 02596757..4d1b9078 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -513,6 +513,8 @@ def create_ui():
with FormGroup(elem_id="txt2img_script_container"):
custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
+ hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
+
def update_resolution_hires_input(inp, evt):
getattr(inp, evt)(
fn=calc_resolution_hires,
@@ -528,7 +530,6 @@ def create_ui():
show_progress=False,
)
- hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
update_resolution_hires_input(enable_hr, 'change')
for input in hr_resolution_preview_inputs[1:]:
update_resolution_hires_input(input, 'release')
--
cgit v1.2.3
From bd877d7b5adb53c4fb3b68361695b0d88aeeb589 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 18 May 2023 22:49:00 +0300
Subject: rework #10519
---
modules/ui.py | 12 +++++-------
1 file changed, 5 insertions(+), 7 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 70a597d7..beccf78b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -526,14 +526,16 @@ def create_ui():
hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
- def update_resolution_hires_input(inp, evt):
- getattr(inp, evt)(
+ for component in hr_resolution_preview_inputs:
+ event = component.release if isinstance(component, gr.Slider) else component.change
+
+ event(
fn=calc_resolution_hires,
inputs=hr_resolution_preview_inputs,
outputs=[hr_final_resolution],
show_progress=False,
)
- getattr(inp, evt)(
+ event(
None,
_js="onCalcResolutionHires",
inputs=hr_resolution_preview_inputs,
@@ -541,10 +543,6 @@ def create_ui():
show_progress=False,
)
- update_resolution_hires_input(enable_hr, 'change')
- for input in hr_resolution_preview_inputs[1:]:
- update_resolution_hires_input(input, 'release')
-
txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
--
cgit v1.2.3
From 9a86932c8bbac06afc70ea190399e767763d877e Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 19 May 2023 18:49:39 +0300
Subject: change width/heights slider steps to 64 from 8
---
modules/ui.py | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index beccf78b..82820ab5 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -463,8 +463,8 @@ def create_ui():
elif category == "dimensions":
with FormRow():
with gr.Column(elem_id="txt2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+ width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="txt2img_width")
+ height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="txt2img_height")
with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", label="Switch dims")
@@ -792,8 +792,8 @@ def create_ui():
with gr.Tab(label="Resize to") as tab_scale_to:
with FormRow():
with gr.Column(elem_id="img2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+ width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="img2img_width")
+ height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="img2img_height")
with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
@@ -1183,8 +1183,8 @@ def create_ui():
with gr.Tab(label="Preprocess images", id="preprocess_images"):
process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
- process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
- process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
+ process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="train_process_width")
+ process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="train_process_height")
preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
with gr.Row():
@@ -1276,8 +1276,8 @@ def create_ui():
template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
- training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
- training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
+ training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="train_training_width")
+ training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="train_training_height")
varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
--
cgit v1.2.3
From b2b06eee02a6f3d0d6f00558a53a17413a6396ca Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sat, 20 May 2023 13:31:18 -0400
Subject: Support edit attn shortcut in hires fix prompts
---
modules/ui.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index 82820ab5..c1f7a6a3 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -502,7 +502,7 @@ def create_ui():
with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container:
hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index")
- with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
+ with FormRow(elem_id="txt2img_hires_fix_row4_toprow", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
with gr.Column(scale=80):
with gr.Row():
hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.")
--
cgit v1.2.3
From 373903d8518c8e0309fabd8e9d08ad61022b8447 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sat, 20 May 2023 19:34:50 +0000
Subject: hiresfix prompt: add classes, update css sel
---
javascript/edit-attention.js | 2 +-
modules/ui.py | 10 +++++-----
2 files changed, 6 insertions(+), 6 deletions(-)
(limited to 'modules/ui.py')
diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index fdf00b4d..ffa73147 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -1,6 +1,6 @@
function keyupEditAttention(event) {
let target = event.originalTarget || event.composedPath()[0];
- if (!target.matches("[id*='_toprow'] [id*='_prompt'] textarea")) return;
+ if (!target.matches("*:is([id*='_toprow'] [id*='_prompt'], .prompt) textarea")) return;
if (!(event.metaKey || event.ctrlKey)) return;
let isPlus = event.key == "ArrowUp";
diff --git a/modules/ui.py b/modules/ui.py
index c1f7a6a3..c0626587 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -272,12 +272,12 @@ def create_toprow(is_img2img):
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
- prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")
+ prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"])
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
- negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
+ negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"])
button_interrogate = None
button_deepbooru = None
@@ -502,13 +502,13 @@ def create_ui():
with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container:
hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index")
- with FormRow(elem_id="txt2img_hires_fix_row4_toprow", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
+ with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
with gr.Column(scale=80):
with gr.Row():
- hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.")
+ hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"])
with gr.Column(scale=80):
with gr.Row():
- hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.")
+ hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"])
elif category == "batch":
if not opts.dimensions_and_batch_together:
--
cgit v1.2.3
From fe73d6439ab80589700ca9de4c8df478cc3cde48 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sun, 21 May 2023 17:35:19 +0300
Subject: Revert "change width/heights slider steps to 64 from 8"
This reverts commit 9a86932c8bbac06afc70ea190399e767763d877e.
---
modules/ui.py | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
(limited to 'modules/ui.py')
diff --git a/modules/ui.py b/modules/ui.py
index c0626587..e62182da 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -463,8 +463,8 @@ def create_ui():
elif category == "dimensions":
with FormRow():
with gr.Column(elem_id="txt2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="txt2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="txt2img_height")
+ width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+ height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", label="Switch dims")
@@ -792,8 +792,8 @@ def create_ui():
with gr.Tab(label="Resize to") as tab_scale_to:
with FormRow():
with gr.Column(elem_id="img2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="img2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="img2img_height")
+ width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+ height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
@@ -1183,8 +1183,8 @@ def create_ui():
with gr.Tab(label="Preprocess images", id="preprocess_images"):
process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
- process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="train_process_width")
- process_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="train_process_height")
+ process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
+ process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
with gr.Row():
@@ -1276,8 +1276,8 @@ def create_ui():
template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
- training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512, elem_id="train_training_width")
- training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512, elem_id="train_training_height")
+ training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
+ training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
--
cgit v1.2.3