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-rw-r--r--javascript/ui.js21
-rw-r--r--modules/errors.py2
-rw-r--r--modules/launch_utils.py2
-rwxr-xr-xmodules/processing.py27
-rw-r--r--modules/prompt_parser.py2
-rw-r--r--modules/scripts.py4
-rw-r--r--modules/sd_samplers_common.py2
-rw-r--r--modules/shared_options.py1
-rwxr-xr-xwebui.sh2
9 files changed, 25 insertions, 38 deletions
diff --git a/javascript/ui.js b/javascript/ui.js
index bade3089..bedcbf3e 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -19,28 +19,11 @@ function all_gallery_buttons() {
}
function selected_gallery_button() {
- var allCurrentButtons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery].gradio-gallery .thumbnail-item.thumbnail-small.selected');
- var visibleCurrentButton = null;
- allCurrentButtons.forEach(function(elem) {
- if (elem.parentElement.offsetParent) {
- visibleCurrentButton = elem;
- }
- });
- return visibleCurrentButton;
+ return all_gallery_buttons().find(elem => elem.classList.contains('selected')) ?? null;
}
function selected_gallery_index() {
- var buttons = all_gallery_buttons();
- var button = selected_gallery_button();
-
- var result = -1;
- buttons.forEach(function(v, i) {
- if (v == button) {
- result = i;
- }
- });
-
- return result;
+ return all_gallery_buttons().findIndex(elem => elem.classList.contains('selected'));
}
function extract_image_from_gallery(gallery) {
diff --git a/modules/errors.py b/modules/errors.py
index 192cd8ff..d4238e63 100644
--- a/modules/errors.py
+++ b/modules/errors.py
@@ -94,7 +94,7 @@ def check_versions():
import gradio
expected_torch_version = "2.0.0"
- expected_xformers_version = "0.0.20"
+ expected_xformers_version = "0.0.21"
expected_gradio_version = "3.39.0"
if version.parse(torch.__version__) < version.parse(expected_torch_version):
diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 7e4d5a61..c54e199f 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -310,7 +310,7 @@ def prepare_environment():
torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.0.1 torchvision==0.15.2 --extra-index-url {torch_index_url}")
requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
- xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.20')
+ xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.21')
clip_package = os.environ.get('CLIP_PACKAGE', "https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip")
openclip_package = os.environ.get('OPENCLIP_PACKAGE', "https://github.com/mlfoundations/open_clip/archive/bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b.zip")
diff --git a/modules/processing.py b/modules/processing.py
index e62db62f..ea481fab 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -386,14 +386,14 @@ class StableDiffusionProcessing:
return self.token_merging_ratio or opts.token_merging_ratio
def setup_prompts(self):
- if type(self.prompt) == list:
+ if isinstance(self.prompt,list):
self.all_prompts = self.prompt
- elif type(self.negative_prompt) == list:
+ elif isinstance(self.negative_prompt, list):
self.all_prompts = [self.prompt] * len(self.negative_prompt)
else:
self.all_prompts = self.batch_size * self.n_iter * [self.prompt]
- if type(self.negative_prompt) == list:
+ if isinstance(self.negative_prompt, list):
self.all_negative_prompts = self.negative_prompt
else:
self.all_negative_prompts = [self.negative_prompt] * len(self.all_prompts)
@@ -512,10 +512,10 @@ class Processed:
self.s_noise = p.s_noise
self.s_min_uncond = p.s_min_uncond
self.sampler_noise_scheduler_override = p.sampler_noise_scheduler_override
- self.prompt = self.prompt if type(self.prompt) != list else self.prompt[0]
- self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]
- self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1
- self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1
+ self.prompt = self.prompt if not isinstance(self.prompt, list) else self.prompt[0]
+ self.negative_prompt = self.negative_prompt if not isinstance(self.negative_prompt, list) else self.negative_prompt[0]
+ self.seed = int(self.seed if not isinstance(self.seed, list) else self.seed[0]) if self.seed is not None else -1
+ self.subseed = int(self.subseed if not isinstance(self.subseed, list) else self.subseed[0]) if self.subseed is not None else -1
self.is_using_inpainting_conditioning = p.is_using_inpainting_conditioning
self.all_prompts = all_prompts or p.all_prompts or [self.prompt]
@@ -741,7 +741,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
def process_images_inner(p: StableDiffusionProcessing) -> Processed:
"""this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
- if type(p.prompt) == list:
+ if isinstance(p.prompt, list):
assert(len(p.prompt) > 0)
else:
assert p.prompt is not None
@@ -772,12 +772,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
p.setup_prompts()
- if type(seed) == list:
+ if isinstance(seed, list):
p.all_seeds = seed
else:
p.all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(p.all_prompts))]
- if type(subseed) == list:
+ if isinstance(subseed, list):
p.all_subseeds = subseed
else:
p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
@@ -1155,6 +1155,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
devices.torch_gc()
def sample_hr_pass(self, samples, decoded_samples, seeds, subseeds, subseed_strength, prompts):
+ if shared.state.interrupted:
+ return samples
+
self.is_hr_pass = True
target_width = self.hr_upscale_to_x
@@ -1268,12 +1271,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if self.hr_negative_prompt == '':
self.hr_negative_prompt = self.negative_prompt
- if type(self.hr_prompt) == list:
+ if isinstance(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:
+ if isinstance(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]
diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 32d214e3..e811ae99 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -86,7 +86,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
yield args[(step - 1) % len(args)]
def start(self, args):
def flatten(x):
- if type(x) == str:
+ if isinstance(x, str):
yield x
else:
for gen in x:
diff --git a/modules/scripts.py b/modules/scripts.py
index fcab5d3a..e8518ad0 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -269,7 +269,7 @@ class Script:
"""helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id"""
need_tabname = self.show(True) == self.show(False)
- tabkind = 'img2img' if self.is_img2img else 'txt2txt'
+ tabkind = 'img2img' if self.is_img2img else 'txt2img'
tabname = f"{tabkind}_" if need_tabname else ""
title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower()))
@@ -289,7 +289,7 @@ class ScriptBuiltinUI(Script):
"""helper function to generate id for a HTML element, constructs final id out of tab and user-supplied item_id"""
need_tabname = self.show(True) == self.show(False)
- tabname = ('img2img' if self.is_img2img else 'txt2txt') + "_" if need_tabname else ""
+ tabname = ('img2img' if self.is_img2img else 'txt2img') + "_" if need_tabname else ""
return f'{tabname}{item_id}'
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 7dc79ea8..f0bc8e6a 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -36,7 +36,7 @@ approximation_indexes = {"Full": 0, "Approx NN": 1, "Approx cheap": 2, "TAESD":
def samples_to_images_tensor(sample, approximation=None, model=None):
'''latents -> images [-1, 1]'''
- if approximation is None:
+ if approximation is None or (shared.state.interrupted and opts.live_preview_fast_interrupt):
approximation = approximation_indexes.get(opts.show_progress_type, 0)
if approximation == 2:
diff --git a/modules/shared_options.py b/modules/shared_options.py
index cdc42b3d..8630d474 100644
--- a/modules/shared_options.py
+++ b/modules/shared_options.py
@@ -282,6 +282,7 @@ options_templates.update(options_section(('ui', "Live previews"), {
"show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap", "TAESD"]}).info("Full = slow but pretty; Approx NN and TAESD = fast but low quality; Approx cheap = super fast but terrible otherwise"),
"live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
"live_preview_refresh_period": OptionInfo(1000, "Progressbar and preview update period").info("in milliseconds"),
+ "live_preview_fast_interrupt": OptionInfo(False, "Return image with chosen live preview method on interrupt").info("makes interrupts faster"),
}))
options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
diff --git a/webui.sh b/webui.sh
index cb8b9d14..781aa734 100755
--- a/webui.sh
+++ b/webui.sh
@@ -245,7 +245,7 @@ while [[ "$KEEP_GOING" -eq "1" ]]; do
printf "Launching launch.py..."
printf "\n%s\n" "${delimiter}"
prepare_tcmalloc
- "${python_cmd}" "${LAUNCH_SCRIPT}" "$@"
+ "${python_cmd}" -u "${LAUNCH_SCRIPT}" "$@"
fi
if [[ ! -f tmp/restart ]]; then
generated by cgit v1.2.3 (git 2.25.1) at 2025-04-29 02:24:11 +0000