mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-12-28 10:25:05 +08:00
Merge branch 'dev' into extra-networks-buttons
This commit is contained in:
commit
6e420c7be2
@ -78,6 +78,8 @@ module.exports = {
|
||||
//extraNetworks.js
|
||||
requestGet: "readonly",
|
||||
popup: "readonly",
|
||||
// profilerVisualization.js
|
||||
createVisualizationTable: "readonly",
|
||||
// from python
|
||||
localization: "readonly",
|
||||
// progrssbar.js
|
||||
|
10
.github/workflows/on_pull_request.yaml
vendored
10
.github/workflows/on_pull_request.yaml
vendored
@ -11,8 +11,8 @@ jobs:
|
||||
if: github.event_name != 'pull_request' || github.event.pull_request.head.repo.full_name != github.event.pull_request.base.repo.full_name
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v3
|
||||
- uses: actions/setup-python@v4
|
||||
uses: actions/checkout@v4
|
||||
- uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: 3.11
|
||||
# NB: there's no cache: pip here since we're not installing anything
|
||||
@ -20,7 +20,7 @@ jobs:
|
||||
# not to have GHA download an (at the time of writing) 4 GB cache
|
||||
# of PyTorch and other dependencies.
|
||||
- name: Install Ruff
|
||||
run: pip install ruff==0.1.6
|
||||
run: pip install ruff==0.3.3
|
||||
- name: Run Ruff
|
||||
run: ruff .
|
||||
lint-js:
|
||||
@ -29,9 +29,9 @@ jobs:
|
||||
if: github.event_name != 'pull_request' || github.event.pull_request.head.repo.full_name != github.event.pull_request.base.repo.full_name
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
- name: Install Node.js
|
||||
uses: actions/setup-node@v3
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 18
|
||||
- run: npm i --ci
|
||||
|
10
.github/workflows/run_tests.yaml
vendored
10
.github/workflows/run_tests.yaml
vendored
@ -11,9 +11,9 @@ jobs:
|
||||
if: github.event_name != 'pull_request' || github.event.pull_request.head.repo.full_name != github.event.pull_request.base.repo.full_name
|
||||
steps:
|
||||
- name: Checkout Code
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: 3.10.6
|
||||
cache: pip
|
||||
@ -22,7 +22,7 @@ jobs:
|
||||
launch.py
|
||||
- name: Cache models
|
||||
id: cache-models
|
||||
uses: actions/cache@v3
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: models
|
||||
key: "2023-12-30"
|
||||
@ -68,13 +68,13 @@ jobs:
|
||||
python -m coverage report -i
|
||||
python -m coverage html -i
|
||||
- name: Upload main app output
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
if: always()
|
||||
with:
|
||||
name: output
|
||||
path: output.txt
|
||||
- name: Upload coverage HTML
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
if: always()
|
||||
with:
|
||||
name: htmlcov
|
||||
|
1
.gitignore
vendored
1
.gitignore
vendored
@ -38,3 +38,4 @@ notification.mp3
|
||||
/package-lock.json
|
||||
/.coverage*
|
||||
/test/test_outputs
|
||||
/cache
|
||||
|
18
CHANGELOG.md
18
CHANGELOG.md
@ -14,7 +14,7 @@
|
||||
* Add support for DAT upscaler models ([#14690](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14690), [#15039](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15039))
|
||||
* Extra Networks Tree View ([#14588](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14588), [#14900](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14900))
|
||||
* NPU Support ([#14801](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14801))
|
||||
* Propmpt comments support
|
||||
* Prompt comments support
|
||||
|
||||
### Minor:
|
||||
* Allow pasting in WIDTHxHEIGHT strings into the width/height fields ([#14296](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14296))
|
||||
@ -59,7 +59,7 @@
|
||||
* modules/api/api.py: add api endpoint to refresh embeddings list ([#14715](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14715))
|
||||
* set_named_arg ([#14773](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14773))
|
||||
* add before_token_counter callback and use it for prompt comments
|
||||
* ResizeHandleRow - allow overriden column scale parameter ([#15004](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15004))
|
||||
* ResizeHandleRow - allow overridden column scale parameter ([#15004](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15004))
|
||||
|
||||
### Performance
|
||||
* Massive performance improvement for extra networks directories with a huge number of files in them in an attempt to tackle #14507 ([#14528](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14528))
|
||||
@ -101,7 +101,7 @@
|
||||
* Gracefully handle mtime read exception from cache ([#14933](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14933))
|
||||
* Only trigger interrupt on `Esc` when interrupt button visible ([#14932](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14932))
|
||||
* Disable prompt token counters option actually disables token counting rather than just hiding results.
|
||||
* avoid doble upscaling in inpaint ([#14966](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14966))
|
||||
* avoid double upscaling in inpaint ([#14966](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14966))
|
||||
* Fix #14591 using translated content to do categories mapping ([#14995](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14995))
|
||||
* fix: the `split_threshold` parameter does not work when running Split oversized images ([#15006](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15006))
|
||||
* Fix resize-handle for mobile ([#15010](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15010), [#15065](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15065))
|
||||
@ -171,7 +171,7 @@
|
||||
* infotext updates: add option to disregard certain infotext fields, add option to not include VAE in infotext, add explanation to infotext settings page, move some options to infotext settings page
|
||||
* add FP32 fallback support on sd_vae_approx ([#14046](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14046))
|
||||
* support XYZ scripts / split hires path from unet ([#14126](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14126))
|
||||
* allow use of mutiple styles csv files ([#14125](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14125))
|
||||
* allow use of multiple styles csv files ([#14125](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14125))
|
||||
* make extra network card description plaintext by default, with an option (Treat card description as HTML) to re-enable HTML as it was (originally by [#13241](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/13241))
|
||||
|
||||
### Extensions and API:
|
||||
@ -308,7 +308,7 @@
|
||||
* new samplers: Restart, DPM++ 2M SDE Exponential, DPM++ 2M SDE Heun, DPM++ 2M SDE Heun Karras, DPM++ 2M SDE Heun Exponential, DPM++ 3M SDE, DPM++ 3M SDE Karras, DPM++ 3M SDE Exponential ([#12300](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12300), [#12519](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12519), [#12542](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12542))
|
||||
* rework DDIM, PLMS, UniPC to use CFG denoiser same as in k-diffusion samplers:
|
||||
* makes all of them work with img2img
|
||||
* makes prompt composition posssible (AND)
|
||||
* makes prompt composition possible (AND)
|
||||
* makes them available for SDXL
|
||||
* always show extra networks tabs in the UI ([#11808](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/11808))
|
||||
* use less RAM when creating models ([#11958](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/11958), [#12599](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12599))
|
||||
@ -484,7 +484,7 @@
|
||||
* user metadata system for custom networks
|
||||
* extended Lora metadata editor: set activation text, default weight, view tags, training info
|
||||
* Lora extension rework to include other types of networks (all that were previously handled by LyCORIS extension)
|
||||
* show github stars for extenstions
|
||||
* show github stars for extensions
|
||||
* img2img batch mode can read extra stuff from png info
|
||||
* img2img batch works with subdirectories
|
||||
* hotkeys to move prompt elements: alt+left/right
|
||||
@ -703,7 +703,7 @@
|
||||
* do not wait for Stable Diffusion model to load at startup
|
||||
* add filename patterns: `[denoising]`
|
||||
* directory hiding for extra networks: dirs starting with `.` will hide their cards on extra network tabs unless specifically searched for
|
||||
* LoRA: for the `<...>` text in prompt, use name of LoRA that is in the metdata of the file, if present, instead of filename (both can be used to activate LoRA)
|
||||
* LoRA: for the `<...>` text in prompt, use name of LoRA that is in the metadata of the file, if present, instead of filename (both can be used to activate LoRA)
|
||||
* LoRA: read infotext params from kohya-ss's extension parameters if they are present and if his extension is not active
|
||||
* LoRA: fix some LoRAs not working (ones that have 3x3 convolution layer)
|
||||
* LoRA: add an option to use old method of applying LoRAs (producing same results as with kohya-ss)
|
||||
@ -733,7 +733,7 @@
|
||||
* fix gamepad navigation
|
||||
* make the lightbox fullscreen image function properly
|
||||
* fix squished thumbnails in extras tab
|
||||
* keep "search" filter for extra networks when user refreshes the tab (previously it showed everthing after you refreshed)
|
||||
* keep "search" filter for extra networks when user refreshes the tab (previously it showed everything after you refreshed)
|
||||
* fix webui showing the same image if you configure the generation to always save results into same file
|
||||
* fix bug with upscalers not working properly
|
||||
* fix MPS on PyTorch 2.0.1, Intel Macs
|
||||
@ -751,7 +751,7 @@
|
||||
* switch to PyTorch 2.0.0 (except for AMD GPUs)
|
||||
* visual improvements to custom code scripts
|
||||
* add filename patterns: `[clip_skip]`, `[hasprompt<>]`, `[batch_number]`, `[generation_number]`
|
||||
* add support for saving init images in img2img, and record their hashes in infotext for reproducability
|
||||
* add support for saving init images in img2img, and record their hashes in infotext for reproducibility
|
||||
* automatically select current word when adjusting weight with ctrl+up/down
|
||||
* add dropdowns for X/Y/Z plot
|
||||
* add setting: Stable Diffusion/Random number generator source: makes it possible to make images generated from a given manual seed consistent across different GPUs
|
||||
|
@ -98,6 +98,7 @@ Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-di
|
||||
- [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended)
|
||||
- [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
|
||||
- [Intel CPUs, Intel GPUs (both integrated and discrete)](https://github.com/openvinotoolkit/stable-diffusion-webui/wiki/Installation-on-Intel-Silicon) (external wiki page)
|
||||
- [Ascend NPUs](https://github.com/wangshuai09/stable-diffusion-webui/wiki/Install-and-run-on-Ascend-NPUs) (external wiki page)
|
||||
|
||||
Alternatively, use online services (like Google Colab):
|
||||
|
||||
|
5
_typos.toml
Normal file
5
_typos.toml
Normal file
@ -0,0 +1,5 @@
|
||||
[default.extend-words]
|
||||
# Part of "RGBa" (Pillow's pre-multiplied alpha RGB mode)
|
||||
Ba = "Ba"
|
||||
# HSA is something AMD uses for their GPUs
|
||||
HSA = "HSA"
|
@ -301,7 +301,7 @@ class DDPMV1(pl.LightningModule):
|
||||
elif self.parameterization == "x0":
|
||||
target = x_start
|
||||
else:
|
||||
raise NotImplementedError(f"Paramterization {self.parameterization} not yet supported")
|
||||
raise NotImplementedError(f"Parameterization {self.parameterization} not yet supported")
|
||||
|
||||
loss = self.get_loss(model_out, target, mean=False).mean(dim=[1, 2, 3])
|
||||
|
||||
@ -880,7 +880,7 @@ class LatentDiffusionV1(DDPMV1):
|
||||
def apply_model(self, x_noisy, t, cond, return_ids=False):
|
||||
|
||||
if isinstance(cond, dict):
|
||||
# hybrid case, cond is exptected to be a dict
|
||||
# hybrid case, cond is expected to be a dict
|
||||
pass
|
||||
else:
|
||||
if not isinstance(cond, list):
|
||||
@ -916,7 +916,7 @@ class LatentDiffusionV1(DDPMV1):
|
||||
cond_list = [{c_key: [c[:, :, :, :, i]]} for i in range(c.shape[-1])]
|
||||
|
||||
elif self.cond_stage_key == 'coordinates_bbox':
|
||||
assert 'original_image_size' in self.split_input_params, 'BoudingBoxRescaling is missing original_image_size'
|
||||
assert 'original_image_size' in self.split_input_params, 'BoundingBoxRescaling is missing original_image_size'
|
||||
|
||||
# assuming padding of unfold is always 0 and its dilation is always 1
|
||||
n_patches_per_row = int((w - ks[0]) / stride[0] + 1)
|
||||
@ -926,7 +926,7 @@ class LatentDiffusionV1(DDPMV1):
|
||||
num_downs = self.first_stage_model.encoder.num_resolutions - 1
|
||||
rescale_latent = 2 ** (num_downs)
|
||||
|
||||
# get top left postions of patches as conforming for the bbbox tokenizer, therefore we
|
||||
# get top left positions of patches as conforming for the bbbox tokenizer, therefore we
|
||||
# need to rescale the tl patch coordinates to be in between (0,1)
|
||||
tl_patch_coordinates = [(rescale_latent * stride[0] * (patch_nr % n_patches_per_row) / full_img_w,
|
||||
rescale_latent * stride[1] * (patch_nr // n_patches_per_row) / full_img_h)
|
||||
|
@ -30,7 +30,7 @@ def factorization(dimension: int, factor:int=-1) -> tuple[int, int]:
|
||||
In LoRA with Kroneckor Product, first value is a value for weight scale.
|
||||
secon value is a value for weight.
|
||||
|
||||
Becuase of non-commutative property, A⊗B ≠ B⊗A. Meaning of two matrices is slightly different.
|
||||
Because of non-commutative property, A⊗B ≠ B⊗A. Meaning of two matrices is slightly different.
|
||||
|
||||
examples)
|
||||
factor
|
||||
|
@ -117,6 +117,12 @@ class NetworkModule:
|
||||
|
||||
if hasattr(self.sd_module, 'weight'):
|
||||
self.shape = self.sd_module.weight.shape
|
||||
elif isinstance(self.sd_module, nn.MultiheadAttention):
|
||||
# For now, only self-attn use Pytorch's MHA
|
||||
# So assume all qkvo proj have same shape
|
||||
self.shape = self.sd_module.out_proj.weight.shape
|
||||
else:
|
||||
self.shape = None
|
||||
|
||||
self.ops = None
|
||||
self.extra_kwargs = {}
|
||||
@ -146,6 +152,9 @@ class NetworkModule:
|
||||
self.alpha = weights.w["alpha"].item() if "alpha" in weights.w else None
|
||||
self.scale = weights.w["scale"].item() if "scale" in weights.w else None
|
||||
|
||||
self.dora_scale = weights.w.get("dora_scale", None)
|
||||
self.dora_norm_dims = len(self.shape) - 1
|
||||
|
||||
def multiplier(self):
|
||||
if 'transformer' in self.sd_key[:20]:
|
||||
return self.network.te_multiplier
|
||||
@ -160,6 +169,27 @@ class NetworkModule:
|
||||
|
||||
return 1.0
|
||||
|
||||
def apply_weight_decompose(self, updown, orig_weight):
|
||||
# Match the device/dtype
|
||||
orig_weight = orig_weight.to(updown.dtype)
|
||||
dora_scale = self.dora_scale.to(device=orig_weight.device, dtype=updown.dtype)
|
||||
updown = updown.to(orig_weight.device)
|
||||
|
||||
merged_scale1 = updown + orig_weight
|
||||
merged_scale1_norm = (
|
||||
merged_scale1.transpose(0, 1)
|
||||
.reshape(merged_scale1.shape[1], -1)
|
||||
.norm(dim=1, keepdim=True)
|
||||
.reshape(merged_scale1.shape[1], *[1] * self.dora_norm_dims)
|
||||
.transpose(0, 1)
|
||||
)
|
||||
|
||||
dora_merged = (
|
||||
merged_scale1 * (dora_scale / merged_scale1_norm)
|
||||
)
|
||||
final_updown = dora_merged - orig_weight
|
||||
return final_updown
|
||||
|
||||
def finalize_updown(self, updown, orig_weight, output_shape, ex_bias=None):
|
||||
if self.bias is not None:
|
||||
updown = updown.reshape(self.bias.shape)
|
||||
@ -175,6 +205,9 @@ class NetworkModule:
|
||||
if ex_bias is not None:
|
||||
ex_bias = ex_bias * self.multiplier()
|
||||
|
||||
if self.dora_scale is not None:
|
||||
updown = self.apply_weight_decompose(updown, orig_weight)
|
||||
|
||||
return updown * self.calc_scale() * self.multiplier(), ex_bias
|
||||
|
||||
def calc_updown(self, target):
|
||||
|
@ -36,13 +36,6 @@ class NetworkModuleOFT(network.NetworkModule):
|
||||
# self.alpha is unused
|
||||
self.dim = self.oft_blocks.shape[1] # (num_blocks, block_size, block_size)
|
||||
|
||||
# LyCORIS BOFT
|
||||
if self.oft_blocks.dim() == 4:
|
||||
self.is_boft = True
|
||||
self.rescale = weights.w.get('rescale', None)
|
||||
if self.rescale is not None:
|
||||
self.rescale = self.rescale.reshape(-1, *[1]*(self.org_module[0].weight.dim() - 1))
|
||||
|
||||
is_linear = type(self.sd_module) in [torch.nn.Linear, torch.nn.modules.linear.NonDynamicallyQuantizableLinear]
|
||||
is_conv = type(self.sd_module) in [torch.nn.Conv2d]
|
||||
is_other_linear = type(self.sd_module) in [torch.nn.MultiheadAttention] # unsupported
|
||||
@ -54,6 +47,13 @@ class NetworkModuleOFT(network.NetworkModule):
|
||||
elif is_other_linear:
|
||||
self.out_dim = self.sd_module.embed_dim
|
||||
|
||||
# LyCORIS BOFT
|
||||
if self.oft_blocks.dim() == 4:
|
||||
self.is_boft = True
|
||||
self.rescale = weights.w.get('rescale', None)
|
||||
if self.rescale is not None and not is_other_linear:
|
||||
self.rescale = self.rescale.reshape(-1, *[1]*(self.org_module[0].weight.dim() - 1))
|
||||
|
||||
self.num_blocks = self.dim
|
||||
self.block_size = self.out_dim // self.dim
|
||||
self.constraint = (0 if self.alpha is None else self.alpha) * self.out_dim
|
||||
|
@ -355,7 +355,7 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
|
||||
"""
|
||||
Applies the currently selected set of networks to the weights of torch layer self.
|
||||
If weights already have this particular set of networks applied, does nothing.
|
||||
If not, restores orginal weights from backup and alters weights according to networks.
|
||||
If not, restores original weights from backup and alters weights according to networks.
|
||||
"""
|
||||
|
||||
network_layer_name = getattr(self, 'network_layer_name', None)
|
||||
@ -429,9 +429,12 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
|
||||
if isinstance(self, torch.nn.MultiheadAttention) and module_q and module_k and module_v and module_out:
|
||||
try:
|
||||
with torch.no_grad():
|
||||
updown_q, _ = module_q.calc_updown(self.in_proj_weight)
|
||||
updown_k, _ = module_k.calc_updown(self.in_proj_weight)
|
||||
updown_v, _ = module_v.calc_updown(self.in_proj_weight)
|
||||
# Send "real" orig_weight into MHA's lora module
|
||||
qw, kw, vw = self.in_proj_weight.chunk(3, 0)
|
||||
updown_q, _ = module_q.calc_updown(qw)
|
||||
updown_k, _ = module_k.calc_updown(kw)
|
||||
updown_v, _ = module_v.calc_updown(vw)
|
||||
del qw, kw, vw
|
||||
updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
|
||||
updown_out, ex_bias = module_out.calc_updown(self.out_proj.weight)
|
||||
|
||||
|
@ -29,6 +29,7 @@ onUiLoaded(async() => {
|
||||
});
|
||||
|
||||
function getActiveTab(elements, all = false) {
|
||||
if (!elements.img2imgTabs) return null;
|
||||
const tabs = elements.img2imgTabs.querySelectorAll("button");
|
||||
|
||||
if (all) return tabs;
|
||||
@ -43,6 +44,7 @@ onUiLoaded(async() => {
|
||||
// Get tab ID
|
||||
function getTabId(elements) {
|
||||
const activeTab = getActiveTab(elements);
|
||||
if (!activeTab) return null;
|
||||
return tabNameToElementId[activeTab.innerText];
|
||||
}
|
||||
|
||||
@ -252,6 +254,7 @@ onUiLoaded(async() => {
|
||||
let isMoving = false;
|
||||
let mouseX, mouseY;
|
||||
let activeElement;
|
||||
let interactedWithAltKey = false;
|
||||
|
||||
const elements = Object.fromEntries(
|
||||
Object.keys(elementIDs).map(id => [
|
||||
@ -277,7 +280,7 @@ onUiLoaded(async() => {
|
||||
const targetElement = gradioApp().querySelector(elemId);
|
||||
|
||||
if (!targetElement) {
|
||||
console.log("Element not found");
|
||||
console.log("Element not found", elemId);
|
||||
return;
|
||||
}
|
||||
|
||||
@ -292,7 +295,7 @@ onUiLoaded(async() => {
|
||||
|
||||
// Create tooltip
|
||||
function createTooltip() {
|
||||
const toolTipElemnt =
|
||||
const toolTipElement =
|
||||
targetElement.querySelector(".image-container");
|
||||
const tooltip = document.createElement("div");
|
||||
tooltip.className = "canvas-tooltip";
|
||||
@ -355,7 +358,7 @@ onUiLoaded(async() => {
|
||||
tooltip.appendChild(tooltipContent);
|
||||
|
||||
// Add a hint element to the target element
|
||||
toolTipElemnt.appendChild(tooltip);
|
||||
toolTipElement.appendChild(tooltip);
|
||||
}
|
||||
|
||||
//Show tool tip if setting enable
|
||||
@ -365,9 +368,9 @@ onUiLoaded(async() => {
|
||||
|
||||
// In the course of research, it was found that the tag img is very harmful when zooming and creates white canvases. This hack allows you to almost never think about this problem, it has no effect on webui.
|
||||
function fixCanvas() {
|
||||
const activeTab = getActiveTab(elements).textContent.trim();
|
||||
const activeTab = getActiveTab(elements)?.textContent.trim();
|
||||
|
||||
if (activeTab !== "img2img") {
|
||||
if (activeTab && activeTab !== "img2img") {
|
||||
const img = targetElement.querySelector(`${elemId} img`);
|
||||
|
||||
if (img && img.style.display !== "none") {
|
||||
@ -508,6 +511,10 @@ onUiLoaded(async() => {
|
||||
if (isModifierKey(e, hotkeysConfig.canvas_hotkey_zoom)) {
|
||||
e.preventDefault();
|
||||
|
||||
if (hotkeysConfig.canvas_hotkey_zoom === "Alt") {
|
||||
interactedWithAltKey = true;
|
||||
}
|
||||
|
||||
let zoomPosX, zoomPosY;
|
||||
let delta = 0.2;
|
||||
if (elemData[elemId].zoomLevel > 7) {
|
||||
@ -783,6 +790,7 @@ onUiLoaded(async() => {
|
||||
targetElement.addEventListener("mouseleave", handleMouseLeave);
|
||||
|
||||
// Reset zoom when click on another tab
|
||||
if (elements.img2imgTabs) {
|
||||
elements.img2imgTabs.addEventListener("click", resetZoom);
|
||||
elements.img2imgTabs.addEventListener("click", () => {
|
||||
// targetElement.style.width = "";
|
||||
@ -790,16 +798,21 @@ onUiLoaded(async() => {
|
||||
setTimeout(fitToElement, 0);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
targetElement.addEventListener("wheel", e => {
|
||||
// change zoom level
|
||||
const operation = e.deltaY > 0 ? "-" : "+";
|
||||
const operation = (e.deltaY || -e.wheelDelta) > 0 ? "-" : "+";
|
||||
changeZoomLevel(operation, e);
|
||||
|
||||
// Handle brush size adjustment with ctrl key pressed
|
||||
if (isModifierKey(e, hotkeysConfig.canvas_hotkey_adjust)) {
|
||||
e.preventDefault();
|
||||
|
||||
if (hotkeysConfig.canvas_hotkey_adjust === "Alt") {
|
||||
interactedWithAltKey = true;
|
||||
}
|
||||
|
||||
// Increase or decrease brush size based on scroll direction
|
||||
adjustBrushSize(elemId, e.deltaY);
|
||||
}
|
||||
@ -839,6 +852,20 @@ onUiLoaded(async() => {
|
||||
document.addEventListener("keydown", handleMoveKeyDown);
|
||||
document.addEventListener("keyup", handleMoveKeyUp);
|
||||
|
||||
|
||||
// Prevent firefox from opening main menu when alt is used as a hotkey for zoom or brush size
|
||||
function handleAltKeyUp(e) {
|
||||
if (e.key !== "Alt" || !interactedWithAltKey) {
|
||||
return;
|
||||
}
|
||||
|
||||
e.preventDefault();
|
||||
interactedWithAltKey = false;
|
||||
}
|
||||
|
||||
document.addEventListener("keyup", handleAltKeyUp);
|
||||
|
||||
|
||||
// Detect zoom level and update the pan speed.
|
||||
function updatePanPosition(movementX, movementY) {
|
||||
let panSpeed = 2;
|
||||
|
@ -8,8 +8,8 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas
|
||||
"canvas_hotkey_grow_brush": shared.OptionInfo("W", "Enlarge the brush size"),
|
||||
"canvas_hotkey_move": shared.OptionInfo("F", "Moving the canvas").info("To work correctly in firefox, turn off 'Automatically search the page text when typing' in the browser settings"),
|
||||
"canvas_hotkey_fullscreen": shared.OptionInfo("S", "Fullscreen Mode, maximizes the picture so that it fits into the screen and stretches it to its full width "),
|
||||
"canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"),
|
||||
"canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, neededs for testing"),
|
||||
"canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas position"),
|
||||
"canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, needed for testing"),
|
||||
"canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"),
|
||||
"canvas_auto_expand": shared.OptionInfo(True, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"),
|
||||
"canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"),
|
||||
|
@ -1,7 +1,7 @@
|
||||
import math
|
||||
|
||||
import gradio as gr
|
||||
from modules import scripts, shared, ui_components, ui_settings, infotext_utils
|
||||
from modules import scripts, shared, ui_components, ui_settings, infotext_utils, errors
|
||||
from modules.ui_components import FormColumn
|
||||
|
||||
|
||||
@ -42,7 +42,11 @@ class ExtraOptionsSection(scripts.Script):
|
||||
setting_name = extra_options[index]
|
||||
|
||||
with FormColumn():
|
||||
try:
|
||||
comp = ui_settings.create_setting_component(setting_name)
|
||||
except KeyError:
|
||||
errors.report(f"Can't add extra options for {setting_name} in ui")
|
||||
continue
|
||||
|
||||
self.comps.append(comp)
|
||||
self.setting_names.append(setting_name)
|
||||
|
@ -57,10 +57,14 @@ def latent_blend(settings, a, b, t):
|
||||
|
||||
# NOTE: We use inplace operations wherever possible.
|
||||
|
||||
if len(t.shape) == 3:
|
||||
# [4][w][h] to [1][4][w][h]
|
||||
t2 = t.unsqueeze(0)
|
||||
# [4][w][h] to [1][1][w][h] - the [4] seem redundant.
|
||||
t3 = t[0].unsqueeze(0).unsqueeze(0)
|
||||
else:
|
||||
t2 = t
|
||||
t3 = t[:, 0][:, None]
|
||||
|
||||
one_minus_t2 = 1 - t2
|
||||
one_minus_t3 = 1 - t3
|
||||
@ -104,7 +108,7 @@ def latent_blend(settings, a, b, t):
|
||||
|
||||
def get_modified_nmask(settings, nmask, sigma):
|
||||
"""
|
||||
Converts a negative mask representing the transparency of the original latent vectors being overlayed
|
||||
Converts a negative mask representing the transparency of the original latent vectors being overlaid
|
||||
to a mask that is scaled according to the denoising strength for this step.
|
||||
|
||||
Where:
|
||||
@ -135,7 +139,10 @@ def apply_adaptive_masks(
|
||||
from PIL import Image, ImageOps, ImageFilter
|
||||
|
||||
# TODO: Bias the blending according to the latent mask, add adjustable parameter for bias control.
|
||||
if len(nmask.shape) == 3:
|
||||
latent_mask = nmask[0].float()
|
||||
else:
|
||||
latent_mask = nmask[:, 0].float()
|
||||
# convert the original mask into a form we use to scale distances for thresholding
|
||||
mask_scalar = 1 - (torch.clamp(latent_mask, min=0, max=1) ** (settings.mask_blend_scale / 2))
|
||||
mask_scalar = (0.5 * (1 - settings.composite_mask_influence)
|
||||
@ -157,7 +164,14 @@ def apply_adaptive_masks(
|
||||
percentile_min=0.25, percentile_max=0.75, min_width=1)
|
||||
|
||||
# The distance at which opacity of original decreases to 50%
|
||||
if len(mask_scalar.shape) == 3:
|
||||
if mask_scalar.shape[0] > i:
|
||||
half_weighted_distance = settings.composite_difference_threshold * mask_scalar[i]
|
||||
else:
|
||||
half_weighted_distance = settings.composite_difference_threshold * mask_scalar[0]
|
||||
else:
|
||||
half_weighted_distance = settings.composite_difference_threshold * mask_scalar
|
||||
|
||||
converted_mask = converted_mask / half_weighted_distance
|
||||
|
||||
converted_mask = 1 / (1 + converted_mask ** settings.composite_difference_contrast)
|
||||
|
8
html/extra-networks-pane-dirs.html
Normal file
8
html/extra-networks-pane-dirs.html
Normal file
@ -0,0 +1,8 @@
|
||||
<div class="extra-network-pane-content-dirs">
|
||||
<div id='{tabname}_{extra_networks_tabname}_dirs' class='extra-network-dirs'>
|
||||
{dirs_html}
|
||||
</div>
|
||||
<div id='{tabname}_{extra_networks_tabname}_cards' class='extra-network-cards'>
|
||||
{items_html}
|
||||
</div>
|
||||
</div>
|
8
html/extra-networks-pane-tree.html
Normal file
8
html/extra-networks-pane-tree.html
Normal file
@ -0,0 +1,8 @@
|
||||
<div class="extra-network-pane-content-tree resize-handle-row">
|
||||
<div id='{tabname}_{extra_networks_tabname}_tree' class='extra-network-tree' style='flex-basis: {extra_networks_tree_view_default_width}px'>
|
||||
{tree_html}
|
||||
</div>
|
||||
<div id='{tabname}_{extra_networks_tabname}_cards' class='extra-network-cards' style='flex-grow: 1;'>
|
||||
{items_html}
|
||||
</div>
|
||||
</div>
|
@ -1,23 +1,53 @@
|
||||
<div id='{tabname}_{extra_networks_tabname}_pane' class='extra-network-pane'>
|
||||
<div id='{tabname}_{extra_networks_tabname}_pane' class='extra-network-pane {tree_view_div_default_display_class}'>
|
||||
<div class="extra-network-control" id="{tabname}_{extra_networks_tabname}_controls" style="display:none" >
|
||||
<div class="extra-network-control--search">
|
||||
<input
|
||||
id="{tabname}_{extra_networks_tabname}_extra_search"
|
||||
class="extra-network-control--search-text"
|
||||
type="search"
|
||||
placeholder="Filter files"
|
||||
placeholder="Search"
|
||||
>
|
||||
</div>
|
||||
|
||||
<small>Sort: </small>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort"
|
||||
class="extra-network-control--sort"
|
||||
data-sortmode="{data_sortmode}"
|
||||
data-sortkey="{data_sortkey}"
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort_path"
|
||||
class="extra-network-control--sort{sort_path_active}"
|
||||
data-sortkey="default"
|
||||
title="Sort by path"
|
||||
onclick="extraNetworksControlSortOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--sort-icon"></i>
|
||||
<i class="extra-network-control--icon extra-network-control--sort-icon"></i>
|
||||
</div>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort_name"
|
||||
class="extra-network-control--sort{sort_name_active}"
|
||||
data-sortkey="name"
|
||||
title="Sort by name"
|
||||
onclick="extraNetworksControlSortOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--icon extra-network-control--sort-icon"></i>
|
||||
</div>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort_date_created"
|
||||
class="extra-network-control--sort{sort_date_created_active}"
|
||||
data-sortkey="date_created"
|
||||
title="Sort by date created"
|
||||
onclick="extraNetworksControlSortOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--icon extra-network-control--sort-icon"></i>
|
||||
</div>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort_date_modified"
|
||||
class="extra-network-control--sort{sort_date_modified_active}"
|
||||
data-sortkey="date_modified"
|
||||
title="Sort by date modified"
|
||||
onclick="extraNetworksControlSortOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--icon extra-network-control--sort-icon"></i>
|
||||
</div>
|
||||
|
||||
<small> </small>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_sort_dir"
|
||||
class="extra-network-control--sort-dir"
|
||||
@ -25,15 +55,18 @@
|
||||
title="Sort ascending"
|
||||
onclick="extraNetworksControlSortDirOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--sort-dir-icon"></i>
|
||||
<i class="extra-network-control--icon extra-network-control--sort-dir-icon"></i>
|
||||
</div>
|
||||
|
||||
|
||||
<small> </small>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_tree_view"
|
||||
class="extra-network-control--tree-view {tree_view_btn_extra_class}"
|
||||
title="Enable Tree View"
|
||||
onclick="extraNetworksControlTreeViewOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--tree-view-icon"></i>
|
||||
<i class="extra-network-control--icon extra-network-control--tree-view-icon"></i>
|
||||
</div>
|
||||
<div
|
||||
id="{tabname}_{extra_networks_tabname}_extra_refresh"
|
||||
@ -41,15 +74,8 @@
|
||||
title="Refresh page"
|
||||
onclick="extraNetworksControlRefreshOnClick(event, '{tabname}', '{extra_networks_tabname}');"
|
||||
>
|
||||
<i class="extra-network-control--refresh-icon"></i>
|
||||
</div>
|
||||
</div>
|
||||
<div class="extra-network-pane-content">
|
||||
<div id='{tabname}_{extra_networks_tabname}_tree' class='extra-network-tree {tree_view_div_extra_class}'>
|
||||
{tree_html}
|
||||
</div>
|
||||
<div id='{tabname}_{extra_networks_tabname}_cards' class='extra-network-cards'>
|
||||
{items_html}
|
||||
<i class="extra-network-control--icon extra-network-control--refresh-icon"></i>
|
||||
</div>
|
||||
</div>
|
||||
{pane_content}
|
||||
</div>
|
@ -50,17 +50,17 @@ function dimensionChange(e, is_width, is_height) {
|
||||
var scaledx = targetElement.naturalWidth * viewportscale;
|
||||
var scaledy = targetElement.naturalHeight * viewportscale;
|
||||
|
||||
var cleintRectTop = (viewportOffset.top + window.scrollY);
|
||||
var cleintRectLeft = (viewportOffset.left + window.scrollX);
|
||||
var cleintRectCentreY = cleintRectTop + (targetElement.clientHeight / 2);
|
||||
var cleintRectCentreX = cleintRectLeft + (targetElement.clientWidth / 2);
|
||||
var clientRectTop = (viewportOffset.top + window.scrollY);
|
||||
var clientRectLeft = (viewportOffset.left + window.scrollX);
|
||||
var clientRectCentreY = clientRectTop + (targetElement.clientHeight / 2);
|
||||
var clientRectCentreX = clientRectLeft + (targetElement.clientWidth / 2);
|
||||
|
||||
var arscale = Math.min(scaledx / currentWidth, scaledy / currentHeight);
|
||||
var arscaledx = currentWidth * arscale;
|
||||
var arscaledy = currentHeight * arscale;
|
||||
|
||||
var arRectTop = cleintRectCentreY - (arscaledy / 2);
|
||||
var arRectLeft = cleintRectCentreX - (arscaledx / 2);
|
||||
var arRectTop = clientRectCentreY - (arscaledy / 2);
|
||||
var arRectLeft = clientRectCentreX - (arscaledx / 2);
|
||||
var arRectWidth = arscaledx;
|
||||
var arRectHeight = arscaledy;
|
||||
|
||||
|
27
javascript/dragdrop.js
vendored
27
javascript/dragdrop.js
vendored
@ -74,22 +74,39 @@ window.document.addEventListener('dragover', e => {
|
||||
e.dataTransfer.dropEffect = 'copy';
|
||||
});
|
||||
|
||||
window.document.addEventListener('drop', e => {
|
||||
window.document.addEventListener('drop', async e => {
|
||||
const target = e.composedPath()[0];
|
||||
if (!eventHasFiles(e)) return;
|
||||
const url = e.dataTransfer.getData('text/uri-list') || e.dataTransfer.getData('text/plain');
|
||||
if (!eventHasFiles(e) && !url) return;
|
||||
|
||||
if (dragDropTargetIsPrompt(target)) {
|
||||
e.stopPropagation();
|
||||
e.preventDefault();
|
||||
|
||||
let prompt_target = get_tab_index('tabs') == 1 ? "img2img_prompt_image" : "txt2img_prompt_image";
|
||||
const isImg2img = get_tab_index('tabs') == 1;
|
||||
let prompt_image_target = isImg2img ? "img2img_prompt_image" : "txt2img_prompt_image";
|
||||
|
||||
const imgParent = gradioApp().getElementById(prompt_target);
|
||||
const imgParent = gradioApp().getElementById(prompt_image_target);
|
||||
const files = e.dataTransfer.files;
|
||||
const fileInput = imgParent.querySelector('input[type="file"]');
|
||||
if (fileInput) {
|
||||
if (eventHasFiles(e) && fileInput) {
|
||||
fileInput.files = files;
|
||||
fileInput.dispatchEvent(new Event('change'));
|
||||
} else if (url) {
|
||||
try {
|
||||
const request = await fetch(url);
|
||||
if (!request.ok) {
|
||||
console.error('Error fetching URL:', url, request.status);
|
||||
return;
|
||||
}
|
||||
const data = new DataTransfer();
|
||||
data.items.add(new File([await request.blob()], 'image.png'));
|
||||
fileInput.files = data.files;
|
||||
fileInput.dispatchEvent(new Event('change'));
|
||||
} catch (error) {
|
||||
console.error('Error fetching URL:', url, error);
|
||||
return;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -64,6 +64,14 @@ function keyupEditAttention(event) {
|
||||
selectionEnd++;
|
||||
}
|
||||
|
||||
// deselect surrounding whitespace
|
||||
while (text[selectionStart] == " " && selectionStart < selectionEnd) {
|
||||
selectionStart++;
|
||||
}
|
||||
while (text[selectionEnd - 1] == " " && selectionEnd > selectionStart) {
|
||||
selectionEnd--;
|
||||
}
|
||||
|
||||
target.setSelectionRange(selectionStart, selectionEnd);
|
||||
return true;
|
||||
}
|
||||
|
@ -39,12 +39,12 @@ function setupExtraNetworksForTab(tabname) {
|
||||
// tabname_full = {tabname}_{extra_networks_tabname}
|
||||
var tabname_full = elem.id;
|
||||
var search = gradioApp().querySelector("#" + tabname_full + "_extra_search");
|
||||
var sort_mode = gradioApp().querySelector("#" + tabname_full + "_extra_sort");
|
||||
var sort_dir = gradioApp().querySelector("#" + tabname_full + "_extra_sort_dir");
|
||||
var refresh = gradioApp().querySelector("#" + tabname_full + "_extra_refresh");
|
||||
var currentSort = '';
|
||||
|
||||
// If any of the buttons above don't exist, we want to skip this iteration of the loop.
|
||||
if (!search || !sort_mode || !sort_dir || !refresh) {
|
||||
if (!search || !sort_dir || !refresh) {
|
||||
return; // `return` is equivalent of `continue` but for forEach loops.
|
||||
}
|
||||
|
||||
@ -52,7 +52,7 @@ function setupExtraNetworksForTab(tabname) {
|
||||
var searchTerm = search.value.toLowerCase();
|
||||
gradioApp().querySelectorAll('#' + tabname + '_extra_tabs div.card').forEach(function(elem) {
|
||||
var searchOnly = elem.querySelector('.search_only');
|
||||
var text = Array.prototype.map.call(elem.querySelectorAll('.search_terms'), function(t) {
|
||||
var text = Array.prototype.map.call(elem.querySelectorAll('.search_terms, .description'), function(t) {
|
||||
return t.textContent.toLowerCase();
|
||||
}).join(" ");
|
||||
|
||||
@ -71,42 +71,46 @@ function setupExtraNetworksForTab(tabname) {
|
||||
};
|
||||
|
||||
var applySort = function(force) {
|
||||
var cards = gradioApp().querySelectorAll('#' + tabname + '_extra_tabs div.card');
|
||||
var cards = gradioApp().querySelectorAll('#' + tabname_full + ' div.card');
|
||||
var parent = gradioApp().querySelector('#' + tabname_full + "_cards");
|
||||
var reverse = sort_dir.dataset.sortdir == "Descending";
|
||||
var sortKey = sort_mode.dataset.sortmode.toLowerCase().replace("sort", "").replaceAll(" ", "_").replace(/_+$/, "").trim() || "name";
|
||||
sortKey = "sort" + sortKey.charAt(0).toUpperCase() + sortKey.slice(1);
|
||||
var sortKeyStore = sortKey + "-" + (reverse ? "Descending" : "Ascending") + "-" + cards.length;
|
||||
var activeSearchElem = gradioApp().querySelector('#' + tabname_full + "_controls .extra-network-control--sort.extra-network-control--enabled");
|
||||
var sortKey = activeSearchElem ? activeSearchElem.dataset.sortkey : "default";
|
||||
var sortKeyDataField = "sort" + sortKey.charAt(0).toUpperCase() + sortKey.slice(1);
|
||||
var sortKeyStore = sortKey + "-" + sort_dir.dataset.sortdir + "-" + cards.length;
|
||||
|
||||
if (sortKeyStore == sort_mode.dataset.sortkey && !force) {
|
||||
if (sortKeyStore == currentSort && !force) {
|
||||
return;
|
||||
}
|
||||
sort_mode.dataset.sortkey = sortKeyStore;
|
||||
currentSort = sortKeyStore;
|
||||
|
||||
cards.forEach(function(card) {
|
||||
card.originalParentElement = card.parentElement;
|
||||
});
|
||||
var sortedCards = Array.from(cards);
|
||||
sortedCards.sort(function(cardA, cardB) {
|
||||
var a = cardA.dataset[sortKey];
|
||||
var b = cardB.dataset[sortKey];
|
||||
var a = cardA.dataset[sortKeyDataField];
|
||||
var b = cardB.dataset[sortKeyDataField];
|
||||
if (!isNaN(a) && !isNaN(b)) {
|
||||
return parseInt(a) - parseInt(b);
|
||||
}
|
||||
|
||||
return (a < b ? -1 : (a > b ? 1 : 0));
|
||||
});
|
||||
|
||||
if (reverse) {
|
||||
sortedCards.reverse();
|
||||
}
|
||||
cards.forEach(function(card) {
|
||||
card.remove();
|
||||
});
|
||||
|
||||
parent.innerHTML = '';
|
||||
|
||||
var frag = document.createDocumentFragment();
|
||||
sortedCards.forEach(function(card) {
|
||||
card.originalParentElement.appendChild(card);
|
||||
frag.appendChild(card);
|
||||
});
|
||||
parent.appendChild(frag);
|
||||
};
|
||||
|
||||
search.addEventListener("input", applyFilter);
|
||||
search.addEventListener("input", function() {
|
||||
applyFilter();
|
||||
});
|
||||
applySort();
|
||||
applyFilter();
|
||||
extraNetworksApplySort[tabname_full] = applySort;
|
||||
@ -272,6 +276,15 @@ function saveCardPreview(event, tabname, filename) {
|
||||
event.preventDefault();
|
||||
}
|
||||
|
||||
function extraNetworksSearchButton(tabname, extra_networks_tabname, event) {
|
||||
var searchTextarea = gradioApp().querySelector("#" + tabname + "_" + extra_networks_tabname + "_extra_search");
|
||||
var button = event.target;
|
||||
var text = button.classList.contains("search-all") ? "" : button.textContent.trim();
|
||||
|
||||
searchTextarea.value = text;
|
||||
updateInput(searchTextarea);
|
||||
}
|
||||
|
||||
function extraNetworksTreeProcessFileClick(event, btn, tabname, extra_networks_tabname) {
|
||||
/**
|
||||
* Processes `onclick` events when user clicks on files in tree.
|
||||
@ -290,7 +303,7 @@ function extraNetworksTreeProcessDirectoryClick(event, btn, tabname, extra_netwo
|
||||
* Processes `onclick` events when user clicks on directories in tree.
|
||||
*
|
||||
* Here is how the tree reacts to clicks for various states:
|
||||
* unselected unopened directory: Diretory is selected and expanded.
|
||||
* unselected unopened directory: Directory is selected and expanded.
|
||||
* unselected opened directory: Directory is selected.
|
||||
* selected opened directory: Directory is collapsed and deselected.
|
||||
* chevron is clicked: Directory is expanded or collapsed. Selected state unchanged.
|
||||
@ -383,36 +396,17 @@ function extraNetworksTreeOnClick(event, tabname, extra_networks_tabname) {
|
||||
}
|
||||
|
||||
function extraNetworksControlSortOnClick(event, tabname, extra_networks_tabname) {
|
||||
/**
|
||||
* Handles `onclick` events for the Sort Mode button.
|
||||
*
|
||||
* Modifies the data attributes of the Sort Mode button to cycle between
|
||||
* various sorting modes.
|
||||
*
|
||||
* @param event The generated event.
|
||||
* @param tabname The name of the active tab in the sd webui. Ex: txt2img, img2img, etc.
|
||||
* @param extra_networks_tabname The id of the active extraNetworks tab. Ex: lora, checkpoints, etc.
|
||||
*/
|
||||
var curr_mode = event.currentTarget.dataset.sortmode;
|
||||
var el_sort_dir = gradioApp().querySelector("#" + tabname + "_" + extra_networks_tabname + "_extra_sort_dir");
|
||||
var sort_dir = el_sort_dir.dataset.sortdir;
|
||||
if (curr_mode == "path") {
|
||||
event.currentTarget.dataset.sortmode = "name";
|
||||
event.currentTarget.dataset.sortkey = "sortName-" + sort_dir + "-640";
|
||||
event.currentTarget.setAttribute("title", "Sort by filename");
|
||||
} else if (curr_mode == "name") {
|
||||
event.currentTarget.dataset.sortmode = "date_created";
|
||||
event.currentTarget.dataset.sortkey = "sortDate_created-" + sort_dir + "-640";
|
||||
event.currentTarget.setAttribute("title", "Sort by date created");
|
||||
} else if (curr_mode == "date_created") {
|
||||
event.currentTarget.dataset.sortmode = "date_modified";
|
||||
event.currentTarget.dataset.sortkey = "sortDate_modified-" + sort_dir + "-640";
|
||||
event.currentTarget.setAttribute("title", "Sort by date modified");
|
||||
} else {
|
||||
event.currentTarget.dataset.sortmode = "path";
|
||||
event.currentTarget.dataset.sortkey = "sortPath-" + sort_dir + "-640";
|
||||
event.currentTarget.setAttribute("title", "Sort by path");
|
||||
}
|
||||
/** Handles `onclick` events for Sort Mode buttons. */
|
||||
|
||||
var self = event.currentTarget;
|
||||
var parent = event.currentTarget.parentElement;
|
||||
|
||||
parent.querySelectorAll('.extra-network-control--sort').forEach(function(x) {
|
||||
x.classList.remove('extra-network-control--enabled');
|
||||
});
|
||||
|
||||
self.classList.add('extra-network-control--enabled');
|
||||
|
||||
applyExtraNetworkSort(tabname + "_" + extra_networks_tabname);
|
||||
}
|
||||
|
||||
@ -447,8 +441,12 @@ function extraNetworksControlTreeViewOnClick(event, tabname, extra_networks_tabn
|
||||
* @param tabname The name of the active tab in the sd webui. Ex: txt2img, img2img, etc.
|
||||
* @param extra_networks_tabname The id of the active extraNetworks tab. Ex: lora, checkpoints, etc.
|
||||
*/
|
||||
gradioApp().getElementById(tabname + "_" + extra_networks_tabname + "_tree").classList.toggle("hidden");
|
||||
event.currentTarget.classList.toggle("extra-network-control--enabled");
|
||||
var button = event.currentTarget;
|
||||
button.classList.toggle("extra-network-control--enabled");
|
||||
var show = !button.classList.contains("extra-network-control--enabled");
|
||||
|
||||
var pane = gradioApp().getElementById(tabname + "_" + extra_networks_tabname + "_pane");
|
||||
pane.classList.toggle("extra-network-dirs-hidden", show);
|
||||
}
|
||||
|
||||
function extraNetworksControlRefreshOnClick(event, tabname, extra_networks_tabname) {
|
||||
@ -509,12 +507,76 @@ function popupId(id) {
|
||||
popup(storedPopupIds[id]);
|
||||
}
|
||||
|
||||
function extraNetworksFlattenMetadata(obj) {
|
||||
const result = {};
|
||||
|
||||
// Convert any stringified JSON objects to actual objects
|
||||
for (const key of Object.keys(obj)) {
|
||||
if (typeof obj[key] === 'string') {
|
||||
try {
|
||||
const parsed = JSON.parse(obj[key]);
|
||||
if (parsed && typeof parsed === 'object') {
|
||||
obj[key] = parsed;
|
||||
}
|
||||
} catch (error) {
|
||||
continue;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Flatten the object
|
||||
for (const key of Object.keys(obj)) {
|
||||
if (typeof obj[key] === 'object' && obj[key] !== null) {
|
||||
const nested = extraNetworksFlattenMetadata(obj[key]);
|
||||
for (const nestedKey of Object.keys(nested)) {
|
||||
result[`${key}/${nestedKey}`] = nested[nestedKey];
|
||||
}
|
||||
} else {
|
||||
result[key] = obj[key];
|
||||
}
|
||||
}
|
||||
|
||||
// Special case for handling modelspec keys
|
||||
for (const key of Object.keys(result)) {
|
||||
if (key.startsWith("modelspec.")) {
|
||||
result[key.replaceAll(".", "/")] = result[key];
|
||||
delete result[key];
|
||||
}
|
||||
}
|
||||
|
||||
// Add empty keys to designate hierarchy
|
||||
for (const key of Object.keys(result)) {
|
||||
const parts = key.split("/");
|
||||
for (let i = 1; i < parts.length; i++) {
|
||||
const parent = parts.slice(0, i).join("/");
|
||||
if (!result[parent]) {
|
||||
result[parent] = "";
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
function extraNetworksShowMetadata(text) {
|
||||
try {
|
||||
let parsed = JSON.parse(text);
|
||||
if (parsed && typeof parsed === 'object') {
|
||||
parsed = extraNetworksFlattenMetadata(parsed);
|
||||
const table = createVisualizationTable(parsed, 0);
|
||||
popup(table);
|
||||
return;
|
||||
}
|
||||
} catch (error) {
|
||||
console.eror(error);
|
||||
}
|
||||
|
||||
var elem = document.createElement('pre');
|
||||
elem.classList.add('popup-metadata');
|
||||
elem.textContent = text;
|
||||
|
||||
popup(elem);
|
||||
return;
|
||||
}
|
||||
|
||||
function requestGet(url, data, handler, errorHandler) {
|
||||
|
@ -131,19 +131,15 @@ function setupImageForLightbox(e) {
|
||||
e.style.cursor = 'pointer';
|
||||
e.style.userSelect = 'none';
|
||||
|
||||
var isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1;
|
||||
|
||||
// For Firefox, listening on click first switched to next image then shows the lightbox.
|
||||
// If you know how to fix this without switching to mousedown event, please.
|
||||
// For other browsers the event is click to make it possiblr to drag picture.
|
||||
var event = isFirefox ? 'mousedown' : 'click';
|
||||
|
||||
e.addEventListener(event, function(evt) {
|
||||
e.addEventListener('mousedown', function(evt) {
|
||||
if (evt.button == 1) {
|
||||
open(evt.target.src);
|
||||
evt.preventDefault();
|
||||
return;
|
||||
}
|
||||
}, true);
|
||||
|
||||
e.addEventListener('click', function(evt) {
|
||||
if (!opts.js_modal_lightbox || evt.button != 0) return;
|
||||
|
||||
modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed);
|
||||
|
@ -33,23 +33,33 @@ function createRow(table, cellName, items) {
|
||||
return res;
|
||||
}
|
||||
|
||||
function showProfile(path, cutoff = 0.05) {
|
||||
requestGet(path, {}, function(data) {
|
||||
function createVisualizationTable(data, cutoff = 0, sort = "") {
|
||||
var table = document.createElement('table');
|
||||
table.className = 'popup-table';
|
||||
|
||||
data.records['total'] = data.total;
|
||||
var keys = Object.keys(data.records).sort(function(a, b) {
|
||||
return data.records[b] - data.records[a];
|
||||
var keys = Object.keys(data);
|
||||
if (sort === "number") {
|
||||
keys = keys.sort(function(a, b) {
|
||||
return data[b] - data[a];
|
||||
});
|
||||
} else {
|
||||
keys = keys.sort();
|
||||
}
|
||||
var items = keys.map(function(x) {
|
||||
return {key: x, parts: x.split('/'), time: data.records[x]};
|
||||
return {key: x, parts: x.split('/'), value: data[x]};
|
||||
});
|
||||
var maxLength = items.reduce(function(a, b) {
|
||||
return Math.max(a, b.parts.length);
|
||||
}, 0);
|
||||
|
||||
var cols = createRow(table, 'th', ['record', 'seconds']);
|
||||
var cols = createRow(
|
||||
table,
|
||||
'th',
|
||||
[
|
||||
cutoff === 0 ? 'key' : 'record',
|
||||
cutoff === 0 ? 'value' : 'seconds'
|
||||
]
|
||||
);
|
||||
cols[0].colSpan = maxLength;
|
||||
|
||||
function arraysEqual(a, b) {
|
||||
@ -60,21 +70,25 @@ function showProfile(path, cutoff = 0.05) {
|
||||
var matching = items.filter(function(x) {
|
||||
return x.parts[level] && !x.parts[level + 1] && arraysEqual(x.parts.slice(0, level), parent);
|
||||
});
|
||||
var sorted = matching.sort(function(a, b) {
|
||||
return b.time - a.time;
|
||||
if (sort === "number") {
|
||||
matching = matching.sort(function(a, b) {
|
||||
return b.value - a.value;
|
||||
});
|
||||
} else {
|
||||
matching = matching.sort();
|
||||
}
|
||||
var othersTime = 0;
|
||||
var othersList = [];
|
||||
var othersRows = [];
|
||||
var childrenRows = [];
|
||||
sorted.forEach(function(x) {
|
||||
var visible = x.time >= cutoff && !hide;
|
||||
matching.forEach(function(x) {
|
||||
var visible = (cutoff === 0 && !hide) || (x.value >= cutoff && !hide);
|
||||
|
||||
var cells = [];
|
||||
for (var i = 0; i < maxLength; i++) {
|
||||
cells.push(x.parts[i]);
|
||||
}
|
||||
cells.push(x.time.toFixed(3));
|
||||
cells.push(cutoff === 0 ? x.value : x.value.toFixed(3));
|
||||
var cols = createRow(table, 'td', cells);
|
||||
for (i = 0; i < level; i++) {
|
||||
cols[i].className = 'muted';
|
||||
@ -85,10 +99,10 @@ function showProfile(path, cutoff = 0.05) {
|
||||
tr.classList.add("hidden");
|
||||
}
|
||||
|
||||
if (x.time >= cutoff) {
|
||||
if (cutoff === 0 || x.value >= cutoff) {
|
||||
childrenRows.push(tr);
|
||||
} else {
|
||||
othersTime += x.time;
|
||||
othersTime += x.value;
|
||||
othersList.push(x.parts[level]);
|
||||
othersRows.push(tr);
|
||||
}
|
||||
@ -147,6 +161,13 @@ function showProfile(path, cutoff = 0.05) {
|
||||
|
||||
addLevel(0, []);
|
||||
|
||||
return table;
|
||||
}
|
||||
|
||||
function showProfile(path, cutoff = 0.05) {
|
||||
requestGet(path, {}, function(data) {
|
||||
data.records['total'] = data.total;
|
||||
const table = createVisualizationTable(data.records, cutoff, "number");
|
||||
popup(table);
|
||||
});
|
||||
}
|
||||
|
@ -22,6 +22,9 @@
|
||||
}
|
||||
|
||||
function displayResizeHandle(parent) {
|
||||
if (!parent.needHideOnMoblie) {
|
||||
return true;
|
||||
}
|
||||
if (window.innerWidth < GRADIO_MIN_WIDTH * 2 + PAD * 4) {
|
||||
parent.style.display = 'flex';
|
||||
parent.resizeHandle.style.display = "none";
|
||||
@ -41,7 +44,7 @@
|
||||
|
||||
const ratio = newParentWidth / oldParentWidth;
|
||||
|
||||
const newWidthL = Math.max(Math.floor(ratio * widthL), GRADIO_MIN_WIDTH);
|
||||
const newWidthL = Math.max(Math.floor(ratio * widthL), parent.minLeftColWidth);
|
||||
setLeftColGridTemplate(parent, newWidthL);
|
||||
|
||||
R.parentWidth = newParentWidth;
|
||||
@ -64,7 +67,24 @@
|
||||
|
||||
parent.style.display = 'grid';
|
||||
parent.style.gap = '0';
|
||||
const gridTemplateColumns = `${parent.children[0].style.flexGrow}fr ${PAD}px ${parent.children[1].style.flexGrow}fr`;
|
||||
let leftColTemplate = "";
|
||||
if (parent.children[0].style.flexGrow) {
|
||||
leftColTemplate = `${parent.children[0].style.flexGrow}fr`;
|
||||
parent.minLeftColWidth = GRADIO_MIN_WIDTH;
|
||||
parent.minRightColWidth = GRADIO_MIN_WIDTH;
|
||||
parent.needHideOnMoblie = true;
|
||||
} else {
|
||||
leftColTemplate = parent.children[0].style.flexBasis;
|
||||
parent.minLeftColWidth = parent.children[0].style.flexBasis.slice(0, -2) / 2;
|
||||
parent.minRightColWidth = 0;
|
||||
parent.needHideOnMoblie = false;
|
||||
}
|
||||
|
||||
if (!leftColTemplate) {
|
||||
leftColTemplate = '1fr';
|
||||
}
|
||||
|
||||
const gridTemplateColumns = `${leftColTemplate} ${PAD}px ${parent.children[1].style.flexGrow}fr`;
|
||||
parent.style.gridTemplateColumns = gridTemplateColumns;
|
||||
parent.style.originalGridTemplateColumns = gridTemplateColumns;
|
||||
|
||||
@ -132,7 +152,7 @@
|
||||
} else {
|
||||
delta = R.screenX - evt.changedTouches[0].screenX;
|
||||
}
|
||||
const leftColWidth = Math.max(Math.min(R.leftColStartWidth - delta, R.parent.offsetWidth - GRADIO_MIN_WIDTH - PAD), GRADIO_MIN_WIDTH);
|
||||
const leftColWidth = Math.max(Math.min(R.leftColStartWidth - delta, R.parent.offsetWidth - R.parent.minRightColWidth - PAD), R.parent.minLeftColWidth);
|
||||
setLeftColGridTemplate(R.parent, leftColWidth);
|
||||
}
|
||||
});
|
||||
@ -171,10 +191,15 @@
|
||||
setupResizeHandle = setup;
|
||||
})();
|
||||
|
||||
onUiLoaded(function() {
|
||||
|
||||
function setupAllResizeHandles() {
|
||||
for (var elem of gradioApp().querySelectorAll('.resize-handle-row')) {
|
||||
if (!elem.querySelector('.resize-handle')) {
|
||||
if (!elem.querySelector('.resize-handle') && !elem.children[0].classList.contains("hidden")) {
|
||||
setupResizeHandle(elem);
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
onUiLoaded(setupAllResizeHandles);
|
||||
|
||||
|
@ -136,8 +136,7 @@ function showSubmitInterruptingPlaceholder(tabname) {
|
||||
function showRestoreProgressButton(tabname, show) {
|
||||
var button = gradioApp().getElementById(tabname + "_restore_progress");
|
||||
if (!button) return;
|
||||
|
||||
button.style.display = show ? "flex" : "none";
|
||||
button.style.setProperty('display', show ? 'flex' : 'none', 'important');
|
||||
}
|
||||
|
||||
function submit() {
|
||||
@ -209,6 +208,7 @@ function restoreProgressTxt2img() {
|
||||
var id = localGet("txt2img_task_id");
|
||||
|
||||
if (id) {
|
||||
showSubmitInterruptingPlaceholder('txt2img');
|
||||
requestProgress(id, gradioApp().getElementById('txt2img_gallery_container'), gradioApp().getElementById('txt2img_gallery'), function() {
|
||||
showSubmitButtons('txt2img', true);
|
||||
}, null, 0);
|
||||
@ -223,6 +223,7 @@ function restoreProgressImg2img() {
|
||||
var id = localGet("img2img_task_id");
|
||||
|
||||
if (id) {
|
||||
showSubmitInterruptingPlaceholder('img2img');
|
||||
requestProgress(id, gradioApp().getElementById('img2img_gallery_container'), gradioApp().getElementById('img2img_gallery'), function() {
|
||||
showSubmitButtons('img2img', true);
|
||||
}, null, 0);
|
||||
@ -411,7 +412,7 @@ function switchWidthHeight(tabname) {
|
||||
|
||||
var onEditTimers = {};
|
||||
|
||||
// calls func after afterMs milliseconds has passed since the input elem has beed enited by user
|
||||
// calls func after afterMs milliseconds has passed since the input elem has been edited by user
|
||||
function onEdit(editId, elem, afterMs, func) {
|
||||
var edited = function() {
|
||||
var existingTimer = onEditTimers[editId];
|
||||
|
@ -23,7 +23,7 @@ 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.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
|
||||
from PIL import PngImagePlugin, Image
|
||||
from PIL import PngImagePlugin
|
||||
from modules.sd_models_config import find_checkpoint_config_near_filename
|
||||
from modules.realesrgan_model import get_realesrgan_models
|
||||
from modules import devices
|
||||
@ -85,7 +85,7 @@ def decode_base64_to_image(encoding):
|
||||
headers = {'user-agent': opts.api_useragent} if opts.api_useragent else {}
|
||||
response = requests.get(encoding, timeout=30, headers=headers)
|
||||
try:
|
||||
image = Image.open(BytesIO(response.content))
|
||||
image = images.read(BytesIO(response.content))
|
||||
return image
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail="Invalid image url") from e
|
||||
@ -93,7 +93,7 @@ def decode_base64_to_image(encoding):
|
||||
if encoding.startswith("data:image/"):
|
||||
encoding = encoding.split(";")[1].split(",")[1]
|
||||
try:
|
||||
image = Image.open(BytesIO(base64.b64decode(encoding)))
|
||||
image = images.read(BytesIO(base64.b64decode(encoding)))
|
||||
return image
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail="Invalid encoded image") from e
|
||||
@ -360,7 +360,7 @@ class Api:
|
||||
return script_args
|
||||
|
||||
def apply_infotext(self, request, tabname, *, script_runner=None, mentioned_script_args=None):
|
||||
"""Processes `infotext` field from the `request`, and sets other fields of the `request` accoring to what's in infotext.
|
||||
"""Processes `infotext` field from the `request`, and sets other fields of the `request` according to what's in infotext.
|
||||
|
||||
If request already has a field set, and that field is encountered in infotext too, the value from infotext is ignored.
|
||||
|
||||
@ -409,8 +409,8 @@ class Api:
|
||||
if request.override_settings is None:
|
||||
request.override_settings = {}
|
||||
|
||||
overriden_settings = infotext_utils.get_override_settings(params)
|
||||
for _, setting_name, value in overriden_settings:
|
||||
overridden_settings = infotext_utils.get_override_settings(params)
|
||||
for _, setting_name, value in overridden_settings:
|
||||
if setting_name not in request.override_settings:
|
||||
request.override_settings[setting_name] = value
|
||||
|
||||
|
@ -2,48 +2,55 @@ import json
|
||||
import os
|
||||
import os.path
|
||||
import threading
|
||||
import time
|
||||
|
||||
import diskcache
|
||||
import tqdm
|
||||
|
||||
from modules.paths import data_path, script_path
|
||||
|
||||
cache_filename = os.environ.get('SD_WEBUI_CACHE_FILE', os.path.join(data_path, "cache.json"))
|
||||
cache_data = None
|
||||
cache_dir = os.environ.get('SD_WEBUI_CACHE_DIR', os.path.join(data_path, "cache"))
|
||||
caches = {}
|
||||
cache_lock = threading.Lock()
|
||||
|
||||
dump_cache_after = None
|
||||
dump_cache_thread = None
|
||||
|
||||
|
||||
def dump_cache():
|
||||
"""
|
||||
Marks cache for writing to disk. 5 seconds after no one else flags the cache for writing, it is written.
|
||||
"""
|
||||
"""old function for dumping cache to disk; does nothing since diskcache."""
|
||||
|
||||
global dump_cache_after
|
||||
global dump_cache_thread
|
||||
pass
|
||||
|
||||
def thread_func():
|
||||
global dump_cache_after
|
||||
global dump_cache_thread
|
||||
|
||||
while dump_cache_after is not None and time.time() < dump_cache_after:
|
||||
time.sleep(1)
|
||||
def make_cache(subsection: str) -> diskcache.Cache:
|
||||
return diskcache.Cache(
|
||||
os.path.join(cache_dir, subsection),
|
||||
size_limit=2**32, # 4 GB, culling oldest first
|
||||
disk_min_file_size=2**18, # keep up to 256KB in Sqlite
|
||||
)
|
||||
|
||||
with cache_lock:
|
||||
cache_filename_tmp = cache_filename + "-"
|
||||
with open(cache_filename_tmp, "w", encoding="utf8") as file:
|
||||
json.dump(cache_data, file, indent=4, ensure_ascii=False)
|
||||
|
||||
os.replace(cache_filename_tmp, cache_filename)
|
||||
def convert_old_cached_data():
|
||||
try:
|
||||
with open(cache_filename, "r", encoding="utf8") as file:
|
||||
data = json.load(file)
|
||||
except FileNotFoundError:
|
||||
return
|
||||
except Exception:
|
||||
os.replace(cache_filename, os.path.join(script_path, "tmp", "cache.json"))
|
||||
print('[ERROR] issue occurred while trying to read cache.json; old cache has been moved to tmp/cache.json')
|
||||
return
|
||||
|
||||
dump_cache_after = None
|
||||
dump_cache_thread = None
|
||||
total_count = sum(len(keyvalues) for keyvalues in data.values())
|
||||
|
||||
with cache_lock:
|
||||
dump_cache_after = time.time() + 5
|
||||
if dump_cache_thread is None:
|
||||
dump_cache_thread = threading.Thread(name='cache-writer', target=thread_func)
|
||||
dump_cache_thread.start()
|
||||
with tqdm.tqdm(total=total_count, desc="converting cache") as progress:
|
||||
for subsection, keyvalues in data.items():
|
||||
cache_obj = caches.get(subsection)
|
||||
if cache_obj is None:
|
||||
cache_obj = make_cache(subsection)
|
||||
caches[subsection] = cache_obj
|
||||
|
||||
for key, value in keyvalues.items():
|
||||
cache_obj[key] = value
|
||||
progress.update(1)
|
||||
|
||||
|
||||
def cache(subsection):
|
||||
@ -54,28 +61,21 @@ def cache(subsection):
|
||||
subsection (str): The subsection identifier for the cache.
|
||||
|
||||
Returns:
|
||||
dict: The cache data for the specified subsection.
|
||||
diskcache.Cache: The cache data for the specified subsection.
|
||||
"""
|
||||
|
||||
global cache_data
|
||||
|
||||
if cache_data is None:
|
||||
cache_obj = caches.get(subsection)
|
||||
if not cache_obj:
|
||||
with cache_lock:
|
||||
if cache_data is None:
|
||||
try:
|
||||
with open(cache_filename, "r", encoding="utf8") as file:
|
||||
cache_data = json.load(file)
|
||||
except FileNotFoundError:
|
||||
cache_data = {}
|
||||
except Exception:
|
||||
os.replace(cache_filename, os.path.join(script_path, "tmp", "cache.json"))
|
||||
print('[ERROR] issue occurred while trying to read cache.json, move current cache to tmp/cache.json and create new cache')
|
||||
cache_data = {}
|
||||
if not os.path.exists(cache_dir) and os.path.isfile(cache_filename):
|
||||
convert_old_cached_data()
|
||||
|
||||
s = cache_data.get(subsection, {})
|
||||
cache_data[subsection] = s
|
||||
cache_obj = caches.get(subsection)
|
||||
if not cache_obj:
|
||||
cache_obj = make_cache(subsection)
|
||||
caches[subsection] = cache_obj
|
||||
|
||||
return s
|
||||
return cache_obj
|
||||
|
||||
|
||||
def cached_data_for_file(subsection, title, filename, func):
|
||||
|
@ -100,8 +100,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
|
||||
sys_pct = sys_peak/max(sys_total, 1) * 100
|
||||
|
||||
toltip_a = "Active: peak amount of video memory used during generation (excluding cached data)"
|
||||
toltip_r = "Reserved: total amout of video memory allocated by the Torch library "
|
||||
toltip_sys = "System: peak amout of video memory allocated by all running programs, out of total capacity"
|
||||
toltip_r = "Reserved: total amount of video memory allocated by the Torch library "
|
||||
toltip_sys = "System: peak amount of video memory allocated by all running programs, out of total capacity"
|
||||
|
||||
text_a = f"<abbr title='{toltip_a}'>A</abbr>: <span class='measurement'>{active_peak/1024:.2f} GB</span>"
|
||||
text_r = f"<abbr title='{toltip_r}'>R</abbr>: <span class='measurement'>{reserved_peak/1024:.2f} GB</span>"
|
||||
|
@ -121,4 +121,7 @@ parser.add_argument('--api-server-stop', action='store_true', help='enable serve
|
||||
parser.add_argument('--timeout-keep-alive', type=int, default=30, help='set timeout_keep_alive for uvicorn')
|
||||
parser.add_argument("--disable-all-extensions", action='store_true', help="prevent all extensions from running regardless of any other settings", default=False)
|
||||
parser.add_argument("--disable-extra-extensions", action='store_true', help="prevent all extensions except built-in from running regardless of any other settings", default=False)
|
||||
parser.add_argument("--skip-load-model-at-start", action='store_true', help="if load a model at web start, only take effect when --nowebui", )
|
||||
parser.add_argument("--skip-load-model-at-start", action='store_true', help="if load a model at web start, only take effect when --nowebui")
|
||||
parser.add_argument("--unix-filenames-sanitization", action='store_true', help="allow any symbols except '/' in filenames. May conflict with your browser and file system")
|
||||
parser.add_argument("--filenames-max-length", type=int, default=128, help='maximal length of filenames of saved images. If you override it, it can conflict with your file system')
|
||||
parser.add_argument("--no-prompt-history", action='store_true', help="disable read prompt from last generation feature; settings this argument will not create '--data_path/params.txt' file")
|
||||
|
@ -259,7 +259,7 @@ def test_for_nans(x, where):
|
||||
def first_time_calculation():
|
||||
"""
|
||||
just do any calculation with pytorch layers - the first time this is done it allocaltes about 700MB of memory and
|
||||
spends about 2.7 seconds doing that, at least wih NVidia.
|
||||
spends about 2.7 seconds doing that, at least with NVidia.
|
||||
"""
|
||||
|
||||
x = torch.zeros((1, 1)).to(device, dtype)
|
||||
|
@ -1,6 +1,7 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import configparser
|
||||
import dataclasses
|
||||
import os
|
||||
import threading
|
||||
import re
|
||||
@ -9,6 +10,10 @@ from modules import shared, errors, cache, scripts
|
||||
from modules.gitpython_hack import Repo
|
||||
from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401
|
||||
|
||||
extensions: list[Extension] = []
|
||||
extension_paths: dict[str, Extension] = {}
|
||||
loaded_extensions: dict[str, Exception] = {}
|
||||
|
||||
|
||||
os.makedirs(extensions_dir, exist_ok=True)
|
||||
|
||||
@ -22,6 +27,13 @@ def active():
|
||||
return [x for x in extensions if x.enabled]
|
||||
|
||||
|
||||
@dataclasses.dataclass
|
||||
class CallbackOrderInfo:
|
||||
name: str
|
||||
before: list
|
||||
after: list
|
||||
|
||||
|
||||
class ExtensionMetadata:
|
||||
filename = "metadata.ini"
|
||||
config: configparser.ConfigParser
|
||||
@ -42,7 +54,7 @@ class ExtensionMetadata:
|
||||
self.canonical_name = self.config.get("Extension", "Name", fallback=canonical_name)
|
||||
self.canonical_name = canonical_name.lower().strip()
|
||||
|
||||
self.requires = self.get_script_requirements("Requires", "Extension")
|
||||
self.requires = None
|
||||
|
||||
def get_script_requirements(self, field, section, extra_section=None):
|
||||
"""reads a list of requirements from the config; field is the name of the field in the ini file,
|
||||
@ -54,7 +66,15 @@ class ExtensionMetadata:
|
||||
if extra_section:
|
||||
x = x + ', ' + self.config.get(extra_section, field, fallback='')
|
||||
|
||||
return self.parse_list(x.lower())
|
||||
listed_requirements = self.parse_list(x.lower())
|
||||
res = []
|
||||
|
||||
for requirement in listed_requirements:
|
||||
loaded_requirements = (x for x in requirement.split("|") if x in loaded_extensions)
|
||||
relevant_requirement = next(loaded_requirements, requirement)
|
||||
res.append(relevant_requirement)
|
||||
|
||||
return res
|
||||
|
||||
def parse_list(self, text):
|
||||
"""converts a line from config ("ext1 ext2, ext3 ") into a python list (["ext1", "ext2", "ext3"])"""
|
||||
@ -65,6 +85,22 @@ class ExtensionMetadata:
|
||||
# both "," and " " are accepted as separator
|
||||
return [x for x in re.split(r"[,\s]+", text.strip()) if x]
|
||||
|
||||
def list_callback_order_instructions(self):
|
||||
for section in self.config.sections():
|
||||
if not section.startswith("callbacks/"):
|
||||
continue
|
||||
|
||||
callback_name = section[10:]
|
||||
|
||||
if not callback_name.startswith(self.canonical_name):
|
||||
errors.report(f"Callback order section for extension {self.canonical_name} is referencing the wrong extension: {section}")
|
||||
continue
|
||||
|
||||
before = self.parse_list(self.config.get(section, 'Before', fallback=''))
|
||||
after = self.parse_list(self.config.get(section, 'After', fallback=''))
|
||||
|
||||
yield CallbackOrderInfo(callback_name, before, after)
|
||||
|
||||
|
||||
class Extension:
|
||||
lock = threading.Lock()
|
||||
@ -156,6 +192,8 @@ class Extension:
|
||||
def check_updates(self):
|
||||
repo = Repo(self.path)
|
||||
for fetch in repo.remote().fetch(dry_run=True):
|
||||
if self.branch and fetch.name != f'{repo.remote().name}/{self.branch}':
|
||||
continue
|
||||
if fetch.flags != fetch.HEAD_UPTODATE:
|
||||
self.can_update = True
|
||||
self.status = "new commits"
|
||||
@ -186,6 +224,8 @@ class Extension:
|
||||
|
||||
def list_extensions():
|
||||
extensions.clear()
|
||||
extension_paths.clear()
|
||||
loaded_extensions.clear()
|
||||
|
||||
if shared.cmd_opts.disable_all_extensions:
|
||||
print("*** \"--disable-all-extensions\" arg was used, will not load any extensions ***")
|
||||
@ -196,7 +236,6 @@ def list_extensions():
|
||||
elif shared.opts.disable_all_extensions == "extra":
|
||||
print("*** \"Disable all extensions\" option was set, will only load built-in extensions ***")
|
||||
|
||||
loaded_extensions = {}
|
||||
|
||||
# scan through extensions directory and load metadata
|
||||
for dirname in [extensions_builtin_dir, extensions_dir]:
|
||||
@ -220,8 +259,12 @@ def list_extensions():
|
||||
is_builtin = dirname == extensions_builtin_dir
|
||||
extension = Extension(name=extension_dirname, path=path, enabled=extension_dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin, metadata=metadata)
|
||||
extensions.append(extension)
|
||||
extension_paths[extension.path] = extension
|
||||
loaded_extensions[canonical_name] = extension
|
||||
|
||||
for extension in extensions:
|
||||
extension.metadata.requires = extension.metadata.get_script_requirements("Requires", "Extension")
|
||||
|
||||
# check for requirements
|
||||
for extension in extensions:
|
||||
if not extension.enabled:
|
||||
@ -238,4 +281,16 @@ def list_extensions():
|
||||
continue
|
||||
|
||||
|
||||
extensions: list[Extension] = []
|
||||
def find_extension(filename):
|
||||
parentdir = os.path.dirname(os.path.realpath(filename))
|
||||
|
||||
while parentdir != filename:
|
||||
extension = extension_paths.get(parentdir)
|
||||
if extension is not None:
|
||||
return extension
|
||||
|
||||
filename = parentdir
|
||||
parentdir = os.path.dirname(filename)
|
||||
|
||||
return None
|
||||
|
||||
|
@ -60,7 +60,7 @@ class ExtraNetwork:
|
||||
Where name matches the name of this ExtraNetwork object, and arg1:arg2:arg3 are any natural number of text arguments
|
||||
separated by colon.
|
||||
|
||||
Even if the user does not mention this ExtraNetwork in his prompt, the call will stil be made, with empty params_list -
|
||||
Even if the user does not mention this ExtraNetwork in his prompt, the call will still be made, with empty params_list -
|
||||
in this case, all effects of this extra networks should be disabled.
|
||||
|
||||
Can be called multiple times before deactivate() - each new call should override the previous call completely.
|
||||
|
@ -95,6 +95,7 @@ class HypernetworkModule(torch.nn.Module):
|
||||
zeros_(b)
|
||||
else:
|
||||
raise KeyError(f"Key {weight_init} is not defined as initialization!")
|
||||
devices.torch_npu_set_device()
|
||||
self.to(devices.device)
|
||||
|
||||
def fix_old_state_dict(self, state_dict):
|
||||
|
@ -12,7 +12,7 @@ import re
|
||||
import numpy as np
|
||||
import piexif
|
||||
import piexif.helper
|
||||
from PIL import Image, ImageFont, ImageDraw, ImageColor, PngImagePlugin
|
||||
from PIL import Image, ImageFont, ImageDraw, ImageColor, PngImagePlugin, ImageOps
|
||||
import string
|
||||
import json
|
||||
import hashlib
|
||||
@ -321,13 +321,16 @@ def resize_image(resize_mode, im, width, height, upscaler_name=None):
|
||||
return res
|
||||
|
||||
|
||||
if not shared.cmd_opts.unix_filenames_sanitization:
|
||||
invalid_filename_chars = '#<>:"/\\|?*\n\r\t'
|
||||
else:
|
||||
invalid_filename_chars = '/'
|
||||
invalid_filename_prefix = ' '
|
||||
invalid_filename_postfix = ' .'
|
||||
re_nonletters = re.compile(r'[\s' + string.punctuation + ']+')
|
||||
re_pattern = re.compile(r"(.*?)(?:\[([^\[\]]+)\]|$)")
|
||||
re_pattern_arg = re.compile(r"(.*)<([^>]*)>$")
|
||||
max_filename_part_length = 128
|
||||
max_filename_part_length = shared.cmd_opts.filenames_max_length
|
||||
NOTHING_AND_SKIP_PREVIOUS_TEXT = object()
|
||||
|
||||
|
||||
@ -770,7 +773,7 @@ def image_data(data):
|
||||
import gradio as gr
|
||||
|
||||
try:
|
||||
image = Image.open(io.BytesIO(data))
|
||||
image = read(io.BytesIO(data))
|
||||
textinfo, _ = read_info_from_image(image)
|
||||
return textinfo, None
|
||||
except Exception:
|
||||
@ -797,3 +800,30 @@ def flatten(img, bgcolor):
|
||||
|
||||
return img.convert('RGB')
|
||||
|
||||
|
||||
def read(fp, **kwargs):
|
||||
image = Image.open(fp, **kwargs)
|
||||
image = fix_image(image)
|
||||
|
||||
return image
|
||||
|
||||
|
||||
def fix_image(image: Image.Image):
|
||||
if image is None:
|
||||
return None
|
||||
|
||||
try:
|
||||
image = ImageOps.exif_transpose(image)
|
||||
image = fix_png_transparency(image)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return image
|
||||
|
||||
|
||||
def fix_png_transparency(image: Image.Image):
|
||||
if image.mode not in ("RGB", "P") or not isinstance(image.info.get("transparency"), bytes):
|
||||
return image
|
||||
|
||||
image = image.convert("RGBA")
|
||||
return image
|
||||
|
@ -6,7 +6,7 @@ import numpy as np
|
||||
from PIL import Image, ImageOps, ImageFilter, ImageEnhance, UnidentifiedImageError
|
||||
import gradio as gr
|
||||
|
||||
from modules import images as imgutil
|
||||
from modules import images
|
||||
from modules.infotext_utils import create_override_settings_dict, parse_generation_parameters
|
||||
from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
|
||||
from modules.shared import opts, state
|
||||
@ -21,7 +21,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
output_dir = output_dir.strip()
|
||||
processing.fix_seed(p)
|
||||
|
||||
images = list(shared.walk_files(input_dir, allowed_extensions=(".png", ".jpg", ".jpeg", ".webp", ".tif", ".tiff")))
|
||||
batch_images = list(shared.walk_files(input_dir, allowed_extensions=(".png", ".jpg", ".jpeg", ".webp", ".tif", ".tiff")))
|
||||
|
||||
is_inpaint_batch = False
|
||||
if inpaint_mask_dir:
|
||||
@ -31,9 +31,9 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
if is_inpaint_batch:
|
||||
print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.")
|
||||
|
||||
print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
|
||||
print(f"Will process {len(batch_images)} images, creating {p.n_iter * p.batch_size} new images for each.")
|
||||
|
||||
state.job_count = len(images) * p.n_iter
|
||||
state.job_count = len(batch_images) * p.n_iter
|
||||
|
||||
# extract "default" params to use in case getting png info fails
|
||||
prompt = p.prompt
|
||||
@ -46,8 +46,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
sd_model_checkpoint_override = get_closet_checkpoint_match(override_settings.get("sd_model_checkpoint", None))
|
||||
batch_results = None
|
||||
discard_further_results = False
|
||||
for i, image in enumerate(images):
|
||||
state.job = f"{i+1} out of {len(images)}"
|
||||
for i, image in enumerate(batch_images):
|
||||
state.job = f"{i+1} out of {len(batch_images)}"
|
||||
if state.skipped:
|
||||
state.skipped = False
|
||||
|
||||
@ -55,7 +55,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
break
|
||||
|
||||
try:
|
||||
img = Image.open(image)
|
||||
img = images.read(image)
|
||||
except UnidentifiedImageError as e:
|
||||
print(e)
|
||||
continue
|
||||
@ -86,7 +86,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
# otherwise user has many masks with the same name but different extensions
|
||||
mask_image_path = masks_found[0]
|
||||
|
||||
mask_image = Image.open(mask_image_path)
|
||||
mask_image = images.read(mask_image_path)
|
||||
p.image_mask = mask_image
|
||||
|
||||
if use_png_info:
|
||||
@ -94,8 +94,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
|
||||
info_img = img
|
||||
if png_info_dir:
|
||||
info_img_path = os.path.join(png_info_dir, os.path.basename(image))
|
||||
info_img = Image.open(info_img_path)
|
||||
geninfo, _ = imgutil.read_info_from_image(info_img)
|
||||
info_img = images.read(info_img_path)
|
||||
geninfo, _ = images.read_info_from_image(info_img)
|
||||
parsed_parameters = parse_generation_parameters(geninfo)
|
||||
parsed_parameters = {k: v for k, v in parsed_parameters.items() if k in (png_info_props or {})}
|
||||
except Exception:
|
||||
@ -175,9 +175,8 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
|
||||
image = None
|
||||
mask = None
|
||||
|
||||
# Use the EXIF orientation of photos taken by smartphones.
|
||||
if image is not None:
|
||||
image = ImageOps.exif_transpose(image)
|
||||
image = images.fix_image(image)
|
||||
mask = images.fix_image(mask)
|
||||
|
||||
if selected_scale_tab == 1 and not is_batch:
|
||||
assert image, "Can't scale by because no image is selected"
|
||||
|
@ -8,7 +8,7 @@ import sys
|
||||
|
||||
import gradio as gr
|
||||
from modules.paths import data_path
|
||||
from modules import shared, ui_tempdir, script_callbacks, processing, infotext_versions
|
||||
from modules import shared, ui_tempdir, script_callbacks, processing, infotext_versions, images, prompt_parser
|
||||
from PIL import Image
|
||||
|
||||
sys.modules['modules.generation_parameters_copypaste'] = sys.modules[__name__] # alias for old name
|
||||
@ -83,7 +83,7 @@ def image_from_url_text(filedata):
|
||||
assert is_in_right_dir, 'trying to open image file outside of allowed directories'
|
||||
|
||||
filename = filename.rsplit('?', 1)[0]
|
||||
return Image.open(filename)
|
||||
return images.read(filename)
|
||||
|
||||
if type(filedata) == list:
|
||||
if len(filedata) == 0:
|
||||
@ -95,7 +95,7 @@ def image_from_url_text(filedata):
|
||||
filedata = filedata[len("data:image/png;base64,"):]
|
||||
|
||||
filedata = base64.decodebytes(filedata.encode('utf-8'))
|
||||
image = Image.open(io.BytesIO(filedata))
|
||||
image = images.read(io.BytesIO(filedata))
|
||||
return image
|
||||
|
||||
|
||||
@ -265,17 +265,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
|
||||
else:
|
||||
prompt += ("" if prompt == "" else "\n") + line
|
||||
|
||||
if shared.opts.infotext_styles != "Ignore":
|
||||
found_styles, prompt, negative_prompt = shared.prompt_styles.extract_styles_from_prompt(prompt, negative_prompt)
|
||||
|
||||
if shared.opts.infotext_styles == "Apply":
|
||||
res["Styles array"] = found_styles
|
||||
elif shared.opts.infotext_styles == "Apply if any" and found_styles:
|
||||
res["Styles array"] = found_styles
|
||||
|
||||
res["Prompt"] = prompt
|
||||
res["Negative prompt"] = negative_prompt
|
||||
|
||||
for k, v in re_param.findall(lastline):
|
||||
try:
|
||||
if v[0] == '"' and v[-1] == '"':
|
||||
@ -290,6 +279,26 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
|
||||
except Exception:
|
||||
print(f"Error parsing \"{k}: {v}\"")
|
||||
|
||||
# Extract styles from prompt
|
||||
if shared.opts.infotext_styles != "Ignore":
|
||||
found_styles, prompt_no_styles, negative_prompt_no_styles = shared.prompt_styles.extract_styles_from_prompt(prompt, negative_prompt)
|
||||
|
||||
same_hr_styles = True
|
||||
if ("Hires prompt" in res or "Hires negative prompt" in res) and (infotext_ver > infotext_versions.v180_hr_styles if (infotext_ver := infotext_versions.parse_version(res.get("Version"))) else True):
|
||||
hr_prompt, hr_negative_prompt = res.get("Hires prompt", prompt), res.get("Hires negative prompt", negative_prompt)
|
||||
hr_found_styles, hr_prompt_no_styles, hr_negative_prompt_no_styles = shared.prompt_styles.extract_styles_from_prompt(hr_prompt, hr_negative_prompt)
|
||||
if same_hr_styles := found_styles == hr_found_styles:
|
||||
res["Hires prompt"] = '' if hr_prompt_no_styles == prompt_no_styles else hr_prompt_no_styles
|
||||
res['Hires negative prompt'] = '' if hr_negative_prompt_no_styles == negative_prompt_no_styles else hr_negative_prompt_no_styles
|
||||
|
||||
if same_hr_styles:
|
||||
prompt, negative_prompt = prompt_no_styles, negative_prompt_no_styles
|
||||
if (shared.opts.infotext_styles == "Apply if any" and found_styles) or shared.opts.infotext_styles == "Apply":
|
||||
res['Styles array'] = found_styles
|
||||
|
||||
res["Prompt"] = prompt
|
||||
res["Negative prompt"] = negative_prompt
|
||||
|
||||
# Missing CLIP skip means it was set to 1 (the default)
|
||||
if "Clip skip" not in res:
|
||||
res["Clip skip"] = "1"
|
||||
@ -356,9 +365,15 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
|
||||
if "Cache FP16 weight for LoRA" not in res and res["FP8 weight"] != "Disable":
|
||||
res["Cache FP16 weight for LoRA"] = False
|
||||
|
||||
if "Emphasis" not in res:
|
||||
prompt_attention = prompt_parser.parse_prompt_attention(prompt)
|
||||
prompt_attention += prompt_parser.parse_prompt_attention(negative_prompt)
|
||||
prompt_uses_emphasis = len(prompt_attention) != len([p for p in prompt_attention if p[1] == 1.0 or p[0] == 'BREAK'])
|
||||
if "Emphasis" not in res and prompt_uses_emphasis:
|
||||
res["Emphasis"] = "Original"
|
||||
|
||||
if "Refiner switch by sampling steps" not in res:
|
||||
res["Refiner switch by sampling steps"] = False
|
||||
|
||||
infotext_versions.backcompat(res)
|
||||
|
||||
for key in skip_fields:
|
||||
@ -456,7 +471,7 @@ def get_override_settings(params, *, skip_fields=None):
|
||||
|
||||
def connect_paste(button, paste_fields, input_comp, override_settings_component, tabname):
|
||||
def paste_func(prompt):
|
||||
if not prompt and not shared.cmd_opts.hide_ui_dir_config:
|
||||
if not prompt and not shared.cmd_opts.hide_ui_dir_config and not shared.cmd_opts.no_prompt_history:
|
||||
filename = os.path.join(data_path, "params.txt")
|
||||
try:
|
||||
with open(filename, "r", encoding="utf8") as file:
|
||||
|
@ -5,6 +5,8 @@ import re
|
||||
|
||||
v160 = version.parse("1.6.0")
|
||||
v170_tsnr = version.parse("v1.7.0-225")
|
||||
v180 = version.parse("1.8.0")
|
||||
v180_hr_styles = version.parse("1.8.0-139")
|
||||
|
||||
|
||||
def parse_version(text):
|
||||
@ -40,3 +42,5 @@ def backcompat(d):
|
||||
if ver < v170_tsnr:
|
||||
d["Downcast alphas_cumprod"] = True
|
||||
|
||||
if ver < v180 and d.get('Refiner'):
|
||||
d["Refiner switch by sampling steps"] = True
|
||||
|
@ -109,7 +109,7 @@ def initialize_rest(*, reload_script_modules=False):
|
||||
with startup_timer.subcategory("load scripts"):
|
||||
scripts.load_scripts()
|
||||
|
||||
if reload_script_modules:
|
||||
if reload_script_modules and shared.opts.enable_reloading_ui_scripts:
|
||||
for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
|
||||
importlib.reload(module)
|
||||
startup_timer.record("reload script modules")
|
||||
@ -139,7 +139,7 @@ def initialize_rest(*, reload_script_modules=False):
|
||||
"""
|
||||
Accesses shared.sd_model property to load model.
|
||||
After it's available, if it has been loaded before this access by some extension,
|
||||
its optimization may be None because the list of optimizaers has neet been filled
|
||||
its optimization may be None because the list of optimizers has not been filled
|
||||
by that time, so we apply optimization again.
|
||||
"""
|
||||
from modules import devices
|
||||
|
@ -55,7 +55,7 @@ and delete current Python and "venv" folder in WebUI's directory.
|
||||
|
||||
You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3106/
|
||||
|
||||
{"Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases" if is_windows else ""}
|
||||
{"Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre" if is_windows else ""}
|
||||
|
||||
Use --skip-python-version-check to suppress this warning.
|
||||
""")
|
||||
|
@ -12,7 +12,7 @@ log = logging.getLogger(__name__)
|
||||
|
||||
# before torch version 1.13, has_mps is only available in nightly pytorch and macOS 12.3+,
|
||||
# use check `getattr` and try it for compatibility.
|
||||
# in torch version 1.13, backends.mps.is_available() and backends.mps.is_built() are introduced in to check mps availabilty,
|
||||
# in torch version 1.13, backends.mps.is_available() and backends.mps.is_built() are introduced in to check mps availability,
|
||||
# since torch 2.0.1+ nightly build, getattr(torch, 'has_mps', False) was deprecated, see https://github.com/pytorch/pytorch/pull/103279
|
||||
def check_for_mps() -> bool:
|
||||
if version.parse(torch.__version__) <= version.parse("2.0.1"):
|
||||
|
@ -110,7 +110,7 @@ def load_upscalers():
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
datas = []
|
||||
data = []
|
||||
commandline_options = vars(shared.cmd_opts)
|
||||
|
||||
# some of upscaler classes will not go away after reloading their modules, and we'll end
|
||||
@ -129,10 +129,10 @@ def load_upscalers():
|
||||
scaler = cls(commandline_model_path)
|
||||
scaler.user_path = commandline_model_path
|
||||
scaler.model_download_path = commandline_model_path or scaler.model_path
|
||||
datas += scaler.scalers
|
||||
data += scaler.scalers
|
||||
|
||||
shared.sd_upscalers = sorted(
|
||||
datas,
|
||||
data,
|
||||
# Special case for UpscalerNone keeps it at the beginning of the list.
|
||||
key=lambda x: x.name.lower() if not isinstance(x.scaler, (UpscalerNone, UpscalerLanczos, UpscalerNearest)) else ""
|
||||
)
|
||||
|
@ -341,7 +341,7 @@ class DDPM(pl.LightningModule):
|
||||
elif self.parameterization == "x0":
|
||||
target = x_start
|
||||
else:
|
||||
raise NotImplementedError(f"Paramterization {self.parameterization} not yet supported")
|
||||
raise NotImplementedError(f"Parameterization {self.parameterization} not yet supported")
|
||||
|
||||
loss = self.get_loss(model_out, target, mean=False).mean(dim=[1, 2, 3])
|
||||
|
||||
@ -901,7 +901,7 @@ class LatentDiffusion(DDPM):
|
||||
def apply_model(self, x_noisy, t, cond, return_ids=False):
|
||||
|
||||
if isinstance(cond, dict):
|
||||
# hybrid case, cond is exptected to be a dict
|
||||
# hybrid case, cond is expected to be a dict
|
||||
pass
|
||||
else:
|
||||
if not isinstance(cond, list):
|
||||
@ -937,7 +937,7 @@ class LatentDiffusion(DDPM):
|
||||
cond_list = [{c_key: [c[:, :, :, :, i]]} for i in range(c.shape[-1])]
|
||||
|
||||
elif self.cond_stage_key == 'coordinates_bbox':
|
||||
assert 'original_image_size' in self.split_input_params, 'BoudingBoxRescaling is missing original_image_size'
|
||||
assert 'original_image_size' in self.split_input_params, 'BoundingBoxRescaling is missing original_image_size'
|
||||
|
||||
# assuming padding of unfold is always 0 and its dilation is always 1
|
||||
n_patches_per_row = int((w - ks[0]) / stride[0] + 1)
|
||||
@ -947,7 +947,7 @@ class LatentDiffusion(DDPM):
|
||||
num_downs = self.first_stage_model.encoder.num_resolutions - 1
|
||||
rescale_latent = 2 ** (num_downs)
|
||||
|
||||
# get top left postions of patches as conforming for the bbbox tokenizer, therefore we
|
||||
# get top left positions of patches as conforming for the bbbox tokenizer, therefore we
|
||||
# need to rescale the tl patch coordinates to be in between (0,1)
|
||||
tl_patch_coordinates = [(rescale_latent * stride[0] * (patch_nr % n_patches_per_row) / full_img_w,
|
||||
rescale_latent * stride[1] * (patch_nr // n_patches_per_row) / full_img_h)
|
||||
|
@ -240,6 +240,9 @@ class Options:
|
||||
|
||||
item_categories = {}
|
||||
for item in self.data_labels.values():
|
||||
if item.section[0] is None:
|
||||
continue
|
||||
|
||||
category = categories.mapping.get(item.category_id)
|
||||
category = "Uncategorized" if category is None else category.label
|
||||
if category not in item_categories:
|
||||
|
@ -32,6 +32,6 @@ models_path = os.path.join(data_path, "models")
|
||||
extensions_dir = os.path.join(data_path, "extensions")
|
||||
extensions_builtin_dir = os.path.join(script_path, "extensions-builtin")
|
||||
config_states_dir = os.path.join(script_path, "config_states")
|
||||
default_output_dir = os.path.join(data_path, "output")
|
||||
default_output_dir = os.path.join(data_path, "outputs")
|
||||
|
||||
roboto_ttf_file = os.path.join(modules_path, 'Roboto-Regular.ttf')
|
||||
|
@ -17,10 +17,10 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
|
||||
if extras_mode == 1:
|
||||
for img in image_folder:
|
||||
if isinstance(img, Image.Image):
|
||||
image = img
|
||||
image = images.fix_image(img)
|
||||
fn = ''
|
||||
else:
|
||||
image = Image.open(os.path.abspath(img.name))
|
||||
image = images.read(os.path.abspath(img.name))
|
||||
fn = os.path.splitext(img.orig_name)[0]
|
||||
yield image, fn
|
||||
elif extras_mode == 2:
|
||||
@ -56,7 +56,7 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
|
||||
|
||||
if isinstance(image_placeholder, str):
|
||||
try:
|
||||
image_data = Image.open(image_placeholder)
|
||||
image_data = images.read(image_placeholder)
|
||||
except Exception:
|
||||
continue
|
||||
else:
|
||||
|
@ -702,7 +702,7 @@ def program_version():
|
||||
return res
|
||||
|
||||
|
||||
def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None):
|
||||
def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None, all_hr_prompts=None, all_hr_negative_prompts=None):
|
||||
if index is None:
|
||||
index = position_in_batch + iteration * p.batch_size
|
||||
|
||||
@ -745,11 +745,18 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
|
||||
"RNG": opts.randn_source if opts.randn_source != "GPU" else None,
|
||||
"NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
|
||||
"Tiling": "True" if p.tiling else None,
|
||||
"Hires prompt": None, # This is set later, insert here to keep order
|
||||
"Hires negative prompt": None, # This is set later, insert here to keep order
|
||||
**p.extra_generation_params,
|
||||
"Version": program_version() if opts.add_version_to_infotext else None,
|
||||
"User": p.user if opts.add_user_name_to_info else None,
|
||||
}
|
||||
|
||||
if all_hr_prompts := all_hr_prompts or getattr(p, 'all_hr_prompts', None):
|
||||
generation_params['Hires prompt'] = all_hr_prompts[index] if all_hr_prompts[index] != all_prompts[index] else None
|
||||
if all_hr_negative_prompts := all_hr_negative_prompts or getattr(p, 'all_hr_negative_prompts', None):
|
||||
generation_params['Hires negative prompt'] = all_hr_negative_prompts[index] if all_hr_negative_prompts[index] != all_negative_prompts[index] else None
|
||||
|
||||
generation_params_text = ", ".join([k if k == v else f'{k}: {infotext_utils.quote(v)}' for k, v in generation_params.items() if v is not None])
|
||||
|
||||
prompt_text = p.main_prompt if use_main_prompt else all_prompts[index]
|
||||
@ -896,22 +903,22 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
|
||||
if p.scripts is not None:
|
||||
p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
|
||||
|
||||
p.setup_conds()
|
||||
|
||||
p.extra_generation_params.update(model_hijack.extra_generation_params)
|
||||
|
||||
# params.txt should be saved after scripts.process_batch, since the
|
||||
# infotext could be modified by that callback
|
||||
# Example: a wildcard processed by process_batch sets an extra model
|
||||
# strength, which is saved as "Model Strength: 1.0" in the infotext
|
||||
if n == 0:
|
||||
if n == 0 and not cmd_opts.no_prompt_history:
|
||||
with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
|
||||
processed = Processed(p, [])
|
||||
file.write(processed.infotext(p, 0))
|
||||
|
||||
p.setup_conds()
|
||||
|
||||
for comment in model_hijack.comments:
|
||||
p.comment(comment)
|
||||
|
||||
p.extra_generation_params.update(model_hijack.extra_generation_params)
|
||||
|
||||
if p.n_iter > 1:
|
||||
shared.state.job = f"Batch {n+1} out of {p.n_iter}"
|
||||
|
||||
@ -1194,12 +1201,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
|
||||
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 tuple(self.hr_negative_prompt) != tuple(self.negative_prompt):
|
||||
self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt
|
||||
|
||||
self.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")
|
||||
if self.enable_hr and self.latent_scale_mode is None:
|
||||
if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers):
|
||||
|
@ -26,6 +26,13 @@ class ScriptStripComments(scripts.Script):
|
||||
p.main_prompt = strip_comments(p.main_prompt)
|
||||
p.main_negative_prompt = strip_comments(p.main_negative_prompt)
|
||||
|
||||
if getattr(p, 'enable_hr', False):
|
||||
p.all_hr_prompts = [strip_comments(x) for x in p.all_hr_prompts]
|
||||
p.all_hr_negative_prompts = [strip_comments(x) for x in p.all_hr_negative_prompts]
|
||||
|
||||
p.hr_prompt = strip_comments(p.hr_prompt)
|
||||
p.hr_negative_prompt = strip_comments(p.hr_negative_prompt)
|
||||
|
||||
|
||||
def before_token_counter(params: script_callbacks.BeforeTokenCounterParams):
|
||||
if not shared.opts.enable_prompt_comments:
|
||||
|
@ -34,7 +34,7 @@ def randn_local(seed, shape):
|
||||
|
||||
|
||||
def randn_like(x):
|
||||
"""Generate a tensor with random numbers from a normal distribution using the previously initialized genrator.
|
||||
"""Generate a tensor with random numbers from a normal distribution using the previously initialized generator.
|
||||
|
||||
Use either randn() or manual_seed() to initialize the generator."""
|
||||
|
||||
@ -48,7 +48,7 @@ def randn_like(x):
|
||||
|
||||
|
||||
def randn_without_seed(shape, generator=None):
|
||||
"""Generate a tensor with random numbers from a normal distribution using the previously initialized genrator.
|
||||
"""Generate a tensor with random numbers from a normal distribution using the previously initialized generator.
|
||||
|
||||
Use either randn() or manual_seed() to initialize the generator."""
|
||||
|
||||
|
@ -1,13 +1,14 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
import inspect
|
||||
import os
|
||||
from collections import namedtuple
|
||||
from typing import Optional, Any
|
||||
|
||||
from fastapi import FastAPI
|
||||
from gradio import Blocks
|
||||
|
||||
from modules import errors, timer
|
||||
from modules import errors, timer, extensions, shared, util
|
||||
|
||||
|
||||
def report_exception(c, job):
|
||||
@ -116,7 +117,105 @@ class BeforeTokenCounterParams:
|
||||
is_positive: bool = True
|
||||
|
||||
|
||||
ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
|
||||
@dataclasses.dataclass
|
||||
class ScriptCallback:
|
||||
script: str
|
||||
callback: any
|
||||
name: str = "unnamed"
|
||||
|
||||
|
||||
def add_callback(callbacks, fun, *, name=None, category='unknown', filename=None):
|
||||
if filename is None:
|
||||
stack = [x for x in inspect.stack() if x.filename != __file__]
|
||||
filename = stack[0].filename if stack else 'unknown file'
|
||||
|
||||
extension = extensions.find_extension(filename)
|
||||
extension_name = extension.canonical_name if extension else 'base'
|
||||
|
||||
callback_name = f"{extension_name}/{os.path.basename(filename)}/{category}"
|
||||
if name is not None:
|
||||
callback_name += f'/{name}'
|
||||
|
||||
unique_callback_name = callback_name
|
||||
for index in range(1000):
|
||||
existing = any(x.name == unique_callback_name for x in callbacks)
|
||||
if not existing:
|
||||
break
|
||||
|
||||
unique_callback_name = f'{callback_name}-{index+1}'
|
||||
|
||||
callbacks.append(ScriptCallback(filename, fun, unique_callback_name))
|
||||
|
||||
|
||||
def sort_callbacks(category, unordered_callbacks, *, enable_user_sort=True):
|
||||
callbacks = unordered_callbacks.copy()
|
||||
callback_lookup = {x.name: x for x in callbacks}
|
||||
dependencies = {}
|
||||
|
||||
order_instructions = {}
|
||||
for extension in extensions.extensions:
|
||||
for order_instruction in extension.metadata.list_callback_order_instructions():
|
||||
if order_instruction.name in callback_lookup:
|
||||
if order_instruction.name not in order_instructions:
|
||||
order_instructions[order_instruction.name] = []
|
||||
|
||||
order_instructions[order_instruction.name].append(order_instruction)
|
||||
|
||||
if order_instructions:
|
||||
for callback in callbacks:
|
||||
dependencies[callback.name] = []
|
||||
|
||||
for callback in callbacks:
|
||||
for order_instruction in order_instructions.get(callback.name, []):
|
||||
for after in order_instruction.after:
|
||||
if after not in callback_lookup:
|
||||
continue
|
||||
|
||||
dependencies[callback.name].append(after)
|
||||
|
||||
for before in order_instruction.before:
|
||||
if before not in callback_lookup:
|
||||
continue
|
||||
|
||||
dependencies[before].append(callback.name)
|
||||
|
||||
sorted_names = util.topological_sort(dependencies)
|
||||
callbacks = [callback_lookup[x] for x in sorted_names]
|
||||
|
||||
if enable_user_sort:
|
||||
for name in reversed(getattr(shared.opts, 'prioritized_callbacks_' + category, [])):
|
||||
index = next((i for i, callback in enumerate(callbacks) if callback.name == name), None)
|
||||
if index is not None:
|
||||
callbacks.insert(0, callbacks.pop(index))
|
||||
|
||||
return callbacks
|
||||
|
||||
|
||||
def ordered_callbacks(category, unordered_callbacks=None, *, enable_user_sort=True):
|
||||
if unordered_callbacks is None:
|
||||
unordered_callbacks = callback_map.get('callbacks_' + category, [])
|
||||
|
||||
if not enable_user_sort:
|
||||
return sort_callbacks(category, unordered_callbacks, enable_user_sort=False)
|
||||
|
||||
callbacks = ordered_callbacks_map.get(category)
|
||||
if callbacks is not None and len(callbacks) == len(unordered_callbacks):
|
||||
return callbacks
|
||||
|
||||
callbacks = sort_callbacks(category, unordered_callbacks)
|
||||
|
||||
ordered_callbacks_map[category] = callbacks
|
||||
return callbacks
|
||||
|
||||
|
||||
def enumerate_callbacks():
|
||||
for category, callbacks in callback_map.items():
|
||||
if category.startswith('callbacks_'):
|
||||
category = category[10:]
|
||||
|
||||
yield category, callbacks
|
||||
|
||||
|
||||
callback_map = dict(
|
||||
callbacks_app_started=[],
|
||||
callbacks_model_loaded=[],
|
||||
@ -141,14 +240,18 @@ callback_map = dict(
|
||||
callbacks_before_token_counter=[],
|
||||
)
|
||||
|
||||
ordered_callbacks_map = {}
|
||||
|
||||
|
||||
def clear_callbacks():
|
||||
for callback_list in callback_map.values():
|
||||
callback_list.clear()
|
||||
|
||||
ordered_callbacks_map.clear()
|
||||
|
||||
|
||||
def app_started_callback(demo: Optional[Blocks], app: FastAPI):
|
||||
for c in callback_map['callbacks_app_started']:
|
||||
for c in ordered_callbacks('app_started'):
|
||||
try:
|
||||
c.callback(demo, app)
|
||||
timer.startup_timer.record(os.path.basename(c.script))
|
||||
@ -157,7 +260,7 @@ def app_started_callback(demo: Optional[Blocks], app: FastAPI):
|
||||
|
||||
|
||||
def app_reload_callback():
|
||||
for c in callback_map['callbacks_on_reload']:
|
||||
for c in ordered_callbacks('on_reload'):
|
||||
try:
|
||||
c.callback()
|
||||
except Exception:
|
||||
@ -165,7 +268,7 @@ def app_reload_callback():
|
||||
|
||||
|
||||
def model_loaded_callback(sd_model):
|
||||
for c in callback_map['callbacks_model_loaded']:
|
||||
for c in ordered_callbacks('model_loaded'):
|
||||
try:
|
||||
c.callback(sd_model)
|
||||
except Exception:
|
||||
@ -175,7 +278,7 @@ def model_loaded_callback(sd_model):
|
||||
def ui_tabs_callback():
|
||||
res = []
|
||||
|
||||
for c in callback_map['callbacks_ui_tabs']:
|
||||
for c in ordered_callbacks('ui_tabs'):
|
||||
try:
|
||||
res += c.callback() or []
|
||||
except Exception:
|
||||
@ -185,7 +288,7 @@ def ui_tabs_callback():
|
||||
|
||||
|
||||
def ui_train_tabs_callback(params: UiTrainTabParams):
|
||||
for c in callback_map['callbacks_ui_train_tabs']:
|
||||
for c in ordered_callbacks('ui_train_tabs'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -193,7 +296,7 @@ def ui_train_tabs_callback(params: UiTrainTabParams):
|
||||
|
||||
|
||||
def ui_settings_callback():
|
||||
for c in callback_map['callbacks_ui_settings']:
|
||||
for c in ordered_callbacks('ui_settings'):
|
||||
try:
|
||||
c.callback()
|
||||
except Exception:
|
||||
@ -201,7 +304,7 @@ def ui_settings_callback():
|
||||
|
||||
|
||||
def before_image_saved_callback(params: ImageSaveParams):
|
||||
for c in callback_map['callbacks_before_image_saved']:
|
||||
for c in ordered_callbacks('before_image_saved'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -209,7 +312,7 @@ def before_image_saved_callback(params: ImageSaveParams):
|
||||
|
||||
|
||||
def image_saved_callback(params: ImageSaveParams):
|
||||
for c in callback_map['callbacks_image_saved']:
|
||||
for c in ordered_callbacks('image_saved'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -217,7 +320,7 @@ def image_saved_callback(params: ImageSaveParams):
|
||||
|
||||
|
||||
def extra_noise_callback(params: ExtraNoiseParams):
|
||||
for c in callback_map['callbacks_extra_noise']:
|
||||
for c in ordered_callbacks('extra_noise'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -225,7 +328,7 @@ def extra_noise_callback(params: ExtraNoiseParams):
|
||||
|
||||
|
||||
def cfg_denoiser_callback(params: CFGDenoiserParams):
|
||||
for c in callback_map['callbacks_cfg_denoiser']:
|
||||
for c in ordered_callbacks('cfg_denoiser'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -233,7 +336,7 @@ def cfg_denoiser_callback(params: CFGDenoiserParams):
|
||||
|
||||
|
||||
def cfg_denoised_callback(params: CFGDenoisedParams):
|
||||
for c in callback_map['callbacks_cfg_denoised']:
|
||||
for c in ordered_callbacks('cfg_denoised'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -241,7 +344,7 @@ def cfg_denoised_callback(params: CFGDenoisedParams):
|
||||
|
||||
|
||||
def cfg_after_cfg_callback(params: AfterCFGCallbackParams):
|
||||
for c in callback_map['callbacks_cfg_after_cfg']:
|
||||
for c in ordered_callbacks('cfg_after_cfg'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -249,7 +352,7 @@ def cfg_after_cfg_callback(params: AfterCFGCallbackParams):
|
||||
|
||||
|
||||
def before_component_callback(component, **kwargs):
|
||||
for c in callback_map['callbacks_before_component']:
|
||||
for c in ordered_callbacks('before_component'):
|
||||
try:
|
||||
c.callback(component, **kwargs)
|
||||
except Exception:
|
||||
@ -257,7 +360,7 @@ def before_component_callback(component, **kwargs):
|
||||
|
||||
|
||||
def after_component_callback(component, **kwargs):
|
||||
for c in callback_map['callbacks_after_component']:
|
||||
for c in ordered_callbacks('after_component'):
|
||||
try:
|
||||
c.callback(component, **kwargs)
|
||||
except Exception:
|
||||
@ -265,7 +368,7 @@ def after_component_callback(component, **kwargs):
|
||||
|
||||
|
||||
def image_grid_callback(params: ImageGridLoopParams):
|
||||
for c in callback_map['callbacks_image_grid']:
|
||||
for c in ordered_callbacks('image_grid'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
@ -273,7 +376,7 @@ def image_grid_callback(params: ImageGridLoopParams):
|
||||
|
||||
|
||||
def infotext_pasted_callback(infotext: str, params: dict[str, Any]):
|
||||
for c in callback_map['callbacks_infotext_pasted']:
|
||||
for c in ordered_callbacks('infotext_pasted'):
|
||||
try:
|
||||
c.callback(infotext, params)
|
||||
except Exception:
|
||||
@ -281,7 +384,7 @@ def infotext_pasted_callback(infotext: str, params: dict[str, Any]):
|
||||
|
||||
|
||||
def script_unloaded_callback():
|
||||
for c in reversed(callback_map['callbacks_script_unloaded']):
|
||||
for c in reversed(ordered_callbacks('script_unloaded')):
|
||||
try:
|
||||
c.callback()
|
||||
except Exception:
|
||||
@ -289,7 +392,7 @@ def script_unloaded_callback():
|
||||
|
||||
|
||||
def before_ui_callback():
|
||||
for c in reversed(callback_map['callbacks_before_ui']):
|
||||
for c in reversed(ordered_callbacks('before_ui')):
|
||||
try:
|
||||
c.callback()
|
||||
except Exception:
|
||||
@ -299,7 +402,7 @@ def before_ui_callback():
|
||||
def list_optimizers_callback():
|
||||
res = []
|
||||
|
||||
for c in callback_map['callbacks_list_optimizers']:
|
||||
for c in ordered_callbacks('list_optimizers'):
|
||||
try:
|
||||
c.callback(res)
|
||||
except Exception:
|
||||
@ -311,7 +414,7 @@ def list_optimizers_callback():
|
||||
def list_unets_callback():
|
||||
res = []
|
||||
|
||||
for c in callback_map['callbacks_list_unets']:
|
||||
for c in ordered_callbacks('list_unets'):
|
||||
try:
|
||||
c.callback(res)
|
||||
except Exception:
|
||||
@ -321,20 +424,13 @@ def list_unets_callback():
|
||||
|
||||
|
||||
def before_token_counter_callback(params: BeforeTokenCounterParams):
|
||||
for c in callback_map['callbacks_before_token_counter']:
|
||||
for c in ordered_callbacks('before_token_counter'):
|
||||
try:
|
||||
c.callback(params)
|
||||
except Exception:
|
||||
report_exception(c, 'before_token_counter')
|
||||
|
||||
|
||||
def add_callback(callbacks, fun):
|
||||
stack = [x for x in inspect.stack() if x.filename != __file__]
|
||||
filename = stack[0].filename if stack else 'unknown file'
|
||||
|
||||
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 stack else 'unknown file'
|
||||
@ -351,24 +447,24 @@ def remove_callbacks_for_function(callback_func):
|
||||
callback_list.remove(callback_to_remove)
|
||||
|
||||
|
||||
def on_app_started(callback):
|
||||
def on_app_started(callback, *, name=None):
|
||||
"""register a function to be called when the webui started, the gradio `Block` component and
|
||||
fastapi `FastAPI` object are passed as the arguments"""
|
||||
add_callback(callback_map['callbacks_app_started'], callback)
|
||||
add_callback(callback_map['callbacks_app_started'], callback, name=name, category='app_started')
|
||||
|
||||
|
||||
def on_before_reload(callback):
|
||||
def on_before_reload(callback, *, name=None):
|
||||
"""register a function to be called just before the server reloads."""
|
||||
add_callback(callback_map['callbacks_on_reload'], callback)
|
||||
add_callback(callback_map['callbacks_on_reload'], callback, name=name, category='on_reload')
|
||||
|
||||
|
||||
def on_model_loaded(callback):
|
||||
def on_model_loaded(callback, *, name=None):
|
||||
"""register a function to be called when the stable diffusion model is created; the model is
|
||||
passed as an argument; this function is also called when the script is reloaded. """
|
||||
add_callback(callback_map['callbacks_model_loaded'], callback)
|
||||
add_callback(callback_map['callbacks_model_loaded'], callback, name=name, category='model_loaded')
|
||||
|
||||
|
||||
def on_ui_tabs(callback):
|
||||
def on_ui_tabs(callback, *, name=None):
|
||||
"""register a function to be called when the UI is creating new tabs.
|
||||
The function must either return a None, which means no new tabs to be added, or a list, where
|
||||
each element is a tuple:
|
||||
@ -378,71 +474,71 @@ def on_ui_tabs(callback):
|
||||
title is tab text displayed to user in the UI
|
||||
elem_id is HTML id for the tab
|
||||
"""
|
||||
add_callback(callback_map['callbacks_ui_tabs'], callback)
|
||||
add_callback(callback_map['callbacks_ui_tabs'], callback, name=name, category='ui_tabs')
|
||||
|
||||
|
||||
def on_ui_train_tabs(callback):
|
||||
def on_ui_train_tabs(callback, *, name=None):
|
||||
"""register a function to be called when the UI is creating new tabs for the train tab.
|
||||
Create your new tabs with gr.Tab.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_ui_train_tabs'], callback)
|
||||
add_callback(callback_map['callbacks_ui_train_tabs'], callback, name=name, category='ui_train_tabs')
|
||||
|
||||
|
||||
def on_ui_settings(callback):
|
||||
def on_ui_settings(callback, *, name=None):
|
||||
"""register a function to be called before UI settings are populated; add your settings
|
||||
by using shared.opts.add_option(shared.OptionInfo(...)) """
|
||||
add_callback(callback_map['callbacks_ui_settings'], callback)
|
||||
add_callback(callback_map['callbacks_ui_settings'], callback, name=name, category='ui_settings')
|
||||
|
||||
|
||||
def on_before_image_saved(callback):
|
||||
def on_before_image_saved(callback, *, name=None):
|
||||
"""register a function to be called before an image is saved to a file.
|
||||
The callback is called with one argument:
|
||||
- params: ImageSaveParams - parameters the image is to be saved with. You can change fields in this object.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_before_image_saved'], callback)
|
||||
add_callback(callback_map['callbacks_before_image_saved'], callback, name=name, category='before_image_saved')
|
||||
|
||||
|
||||
def on_image_saved(callback):
|
||||
def on_image_saved(callback, *, name=None):
|
||||
"""register a function to be called after an image is saved to a file.
|
||||
The callback is called with one argument:
|
||||
- params: ImageSaveParams - parameters the image was saved with. Changing fields in this object does nothing.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_image_saved'], callback)
|
||||
add_callback(callback_map['callbacks_image_saved'], callback, name=name, category='image_saved')
|
||||
|
||||
|
||||
def on_extra_noise(callback):
|
||||
def on_extra_noise(callback, *, name=None):
|
||||
"""register a function to be called before adding extra noise in img2img or hires fix;
|
||||
The callback is called with one argument:
|
||||
- params: ExtraNoiseParams - contains noise determined by seed and latent representation of image
|
||||
"""
|
||||
add_callback(callback_map['callbacks_extra_noise'], callback)
|
||||
add_callback(callback_map['callbacks_extra_noise'], callback, name=name, category='extra_noise')
|
||||
|
||||
|
||||
def on_cfg_denoiser(callback):
|
||||
def on_cfg_denoiser(callback, *, name=None):
|
||||
"""register a function to be called in the kdiffussion cfg_denoiser method after building the inner model inputs.
|
||||
The callback is called with one argument:
|
||||
- params: CFGDenoiserParams - parameters to be passed to the inner model and sampling state details.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_cfg_denoiser'], callback)
|
||||
add_callback(callback_map['callbacks_cfg_denoiser'], callback, name=name, category='cfg_denoiser')
|
||||
|
||||
|
||||
def on_cfg_denoised(callback):
|
||||
def on_cfg_denoised(callback, *, name=None):
|
||||
"""register a function to be called in the kdiffussion cfg_denoiser method after building the inner model inputs.
|
||||
The callback is called with one argument:
|
||||
- params: CFGDenoisedParams - parameters to be passed to the inner model and sampling state details.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_cfg_denoised'], callback)
|
||||
add_callback(callback_map['callbacks_cfg_denoised'], callback, name=name, category='cfg_denoised')
|
||||
|
||||
|
||||
def on_cfg_after_cfg(callback):
|
||||
def on_cfg_after_cfg(callback, *, name=None):
|
||||
"""register a function to be called in the kdiffussion cfg_denoiser method after cfg calculations are completed.
|
||||
The callback is called with one argument:
|
||||
- params: AfterCFGCallbackParams - parameters to be passed to the script for post-processing after cfg calculation.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_cfg_after_cfg'], callback)
|
||||
add_callback(callback_map['callbacks_cfg_after_cfg'], callback, name=name, category='cfg_after_cfg')
|
||||
|
||||
|
||||
def on_before_component(callback):
|
||||
def on_before_component(callback, *, name=None):
|
||||
"""register a function to be called before a component is created.
|
||||
The callback is called with arguments:
|
||||
- component - gradio component that is about to be created.
|
||||
@ -451,61 +547,61 @@ def on_before_component(callback):
|
||||
Use elem_id/label fields of kwargs to figure out which component it is.
|
||||
This can be useful to inject your own components somewhere in the middle of vanilla UI.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_before_component'], callback)
|
||||
add_callback(callback_map['callbacks_before_component'], callback, name=name, category='before_component')
|
||||
|
||||
|
||||
def on_after_component(callback):
|
||||
def on_after_component(callback, *, name=None):
|
||||
"""register a function to be called after a component is created. See on_before_component for more."""
|
||||
add_callback(callback_map['callbacks_after_component'], callback)
|
||||
add_callback(callback_map['callbacks_after_component'], callback, name=name, category='after_component')
|
||||
|
||||
|
||||
def on_image_grid(callback):
|
||||
def on_image_grid(callback, *, name=None):
|
||||
"""register a function to be called before making an image grid.
|
||||
The callback is called with one argument:
|
||||
- params: ImageGridLoopParams - parameters to be used for grid creation. Can be modified.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_image_grid'], callback)
|
||||
add_callback(callback_map['callbacks_image_grid'], callback, name=name, category='image_grid')
|
||||
|
||||
|
||||
def on_infotext_pasted(callback):
|
||||
def on_infotext_pasted(callback, *, name=None):
|
||||
"""register a function to be called before applying an infotext.
|
||||
The callback is called with two arguments:
|
||||
- infotext: str - raw infotext.
|
||||
- result: dict[str, any] - parsed infotext parameters.
|
||||
"""
|
||||
add_callback(callback_map['callbacks_infotext_pasted'], callback)
|
||||
add_callback(callback_map['callbacks_infotext_pasted'], callback, name=name, category='infotext_pasted')
|
||||
|
||||
|
||||
def on_script_unloaded(callback):
|
||||
def on_script_unloaded(callback, *, name=None):
|
||||
"""register a function to be called before the script is unloaded. Any hooks/hijacks/monkeying about that
|
||||
the script did should be reverted here"""
|
||||
|
||||
add_callback(callback_map['callbacks_script_unloaded'], callback)
|
||||
add_callback(callback_map['callbacks_script_unloaded'], callback, name=name, category='script_unloaded')
|
||||
|
||||
|
||||
def on_before_ui(callback):
|
||||
def on_before_ui(callback, *, name=None):
|
||||
"""register a function to be called before the UI is created."""
|
||||
|
||||
add_callback(callback_map['callbacks_before_ui'], callback)
|
||||
add_callback(callback_map['callbacks_before_ui'], callback, name=name, category='before_ui')
|
||||
|
||||
|
||||
def on_list_optimizers(callback):
|
||||
def on_list_optimizers(callback, *, name=None):
|
||||
"""register a function to be called when UI is making a list of cross attention optimization options.
|
||||
The function will be called with one argument, a list, and shall add objects of type modules.sd_hijack_optimizations.SdOptimization
|
||||
to it."""
|
||||
|
||||
add_callback(callback_map['callbacks_list_optimizers'], callback)
|
||||
add_callback(callback_map['callbacks_list_optimizers'], callback, name=name, category='list_optimizers')
|
||||
|
||||
|
||||
def on_list_unets(callback):
|
||||
def on_list_unets(callback, *, name=None):
|
||||
"""register a function to be called when UI is making a list of alternative options for unet.
|
||||
The function will be called with one argument, a list, and shall add objects of type modules.sd_unet.SdUnetOption to it."""
|
||||
|
||||
add_callback(callback_map['callbacks_list_unets'], callback)
|
||||
add_callback(callback_map['callbacks_list_unets'], callback, name=name, category='list_unets')
|
||||
|
||||
|
||||
def on_before_token_counter(callback):
|
||||
def on_before_token_counter(callback, *, name=None):
|
||||
"""register a function to be called when UI is counting tokens for a prompt.
|
||||
The function will be called with one argument of type BeforeTokenCounterParams, and should modify its fields if necessary."""
|
||||
|
||||
add_callback(callback_map['callbacks_before_token_counter'], callback)
|
||||
add_callback(callback_map['callbacks_before_token_counter'], callback, name=name, category='before_token_counter')
|
||||
|
@ -7,7 +7,9 @@ from dataclasses import dataclass
|
||||
|
||||
import gradio as gr
|
||||
|
||||
from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing, errors, timer
|
||||
from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing, errors, timer, util
|
||||
|
||||
topological_sort = util.topological_sort
|
||||
|
||||
AlwaysVisible = object()
|
||||
|
||||
@ -92,7 +94,7 @@ class Script:
|
||||
"""If true, the script setup will only be run in Gradio UI, not in API"""
|
||||
|
||||
controls = None
|
||||
"""A list of controls retured by the ui()."""
|
||||
"""A list of controls returned by the ui()."""
|
||||
|
||||
def title(self):
|
||||
"""this function should return the title of the script. This is what will be displayed in the dropdown menu."""
|
||||
@ -109,7 +111,7 @@ class Script:
|
||||
|
||||
def show(self, is_img2img):
|
||||
"""
|
||||
is_img2img is True if this function is called for the img2img interface, and Fasle otherwise
|
||||
is_img2img is True if this function is called for the img2img interface, and False otherwise
|
||||
|
||||
This function should return:
|
||||
- False if the script should not be shown in UI at all
|
||||
@ -138,7 +140,6 @@ class Script:
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
def before_process(self, p, *args):
|
||||
"""
|
||||
This function is called very early during processing begins for AlwaysVisible scripts.
|
||||
@ -369,29 +370,6 @@ scripts_data = []
|
||||
postprocessing_scripts_data = []
|
||||
ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"])
|
||||
|
||||
def topological_sort(dependencies):
|
||||
"""Accepts a dictionary mapping name to its dependencies, returns a list of names ordered according to dependencies.
|
||||
Ignores errors relating to missing dependeencies or circular dependencies
|
||||
"""
|
||||
|
||||
visited = {}
|
||||
result = []
|
||||
|
||||
def inner(name):
|
||||
visited[name] = True
|
||||
|
||||
for dep in dependencies.get(name, []):
|
||||
if dep in dependencies and dep not in visited:
|
||||
inner(dep)
|
||||
|
||||
result.append(name)
|
||||
|
||||
for depname in dependencies:
|
||||
if depname not in visited:
|
||||
inner(depname)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class ScriptWithDependencies:
|
||||
@ -562,6 +540,25 @@ class ScriptRunner:
|
||||
self.paste_field_names = []
|
||||
self.inputs = [None]
|
||||
|
||||
self.callback_map = {}
|
||||
self.callback_names = [
|
||||
'before_process',
|
||||
'process',
|
||||
'before_process_batch',
|
||||
'after_extra_networks_activate',
|
||||
'process_batch',
|
||||
'postprocess',
|
||||
'postprocess_batch',
|
||||
'postprocess_batch_list',
|
||||
'post_sample',
|
||||
'on_mask_blend',
|
||||
'postprocess_image',
|
||||
'postprocess_maskoverlay',
|
||||
'postprocess_image_after_composite',
|
||||
'before_component',
|
||||
'after_component',
|
||||
]
|
||||
|
||||
self.on_before_component_elem_id = {}
|
||||
"""dict of callbacks to be called before an element is created; key=elem_id, value=list of callbacks"""
|
||||
|
||||
@ -600,6 +597,8 @@ class ScriptRunner:
|
||||
self.scripts.append(script)
|
||||
self.selectable_scripts.append(script)
|
||||
|
||||
self.callback_map.clear()
|
||||
|
||||
self.apply_on_before_component_callbacks()
|
||||
|
||||
def apply_on_before_component_callbacks(self):
|
||||
@ -769,8 +768,42 @@ class ScriptRunner:
|
||||
|
||||
return processed
|
||||
|
||||
def list_scripts_for_method(self, method_name):
|
||||
if method_name in ('before_component', 'after_component'):
|
||||
return self.scripts
|
||||
else:
|
||||
return self.alwayson_scripts
|
||||
|
||||
def create_ordered_callbacks_list(self, method_name, *, enable_user_sort=True):
|
||||
script_list = self.list_scripts_for_method(method_name)
|
||||
category = f'script_{method_name}'
|
||||
callbacks = []
|
||||
|
||||
for script in script_list:
|
||||
if getattr(script.__class__, method_name, None) == getattr(Script, method_name, None):
|
||||
continue
|
||||
|
||||
script_callbacks.add_callback(callbacks, script, category=category, name=script.__class__.__name__, filename=script.filename)
|
||||
|
||||
return script_callbacks.sort_callbacks(category, callbacks, enable_user_sort=enable_user_sort)
|
||||
|
||||
def ordered_callbacks(self, method_name, *, enable_user_sort=True):
|
||||
script_list = self.list_scripts_for_method(method_name)
|
||||
category = f'script_{method_name}'
|
||||
|
||||
scrpts_len, callbacks = self.callback_map.get(category, (-1, None))
|
||||
|
||||
if callbacks is None or scrpts_len != len(script_list):
|
||||
callbacks = self.create_ordered_callbacks_list(method_name, enable_user_sort=enable_user_sort)
|
||||
self.callback_map[category] = len(script_list), callbacks
|
||||
|
||||
return callbacks
|
||||
|
||||
def ordered_scripts(self, method_name):
|
||||
return [x.callback for x in self.ordered_callbacks(method_name)]
|
||||
|
||||
def before_process(self, p):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('before_process'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.before_process(p, *script_args)
|
||||
@ -778,7 +811,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running before_process: {script.filename}", exc_info=True)
|
||||
|
||||
def process(self, p):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('process'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.process(p, *script_args)
|
||||
@ -786,7 +819,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running process: {script.filename}", exc_info=True)
|
||||
|
||||
def before_process_batch(self, p, **kwargs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('before_process_batch'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.before_process_batch(p, *script_args, **kwargs)
|
||||
@ -794,7 +827,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running before_process_batch: {script.filename}", exc_info=True)
|
||||
|
||||
def after_extra_networks_activate(self, p, **kwargs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('after_extra_networks_activate'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.after_extra_networks_activate(p, *script_args, **kwargs)
|
||||
@ -802,7 +835,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running after_extra_networks_activate: {script.filename}", exc_info=True)
|
||||
|
||||
def process_batch(self, p, **kwargs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('process_batch'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.process_batch(p, *script_args, **kwargs)
|
||||
@ -810,7 +843,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running process_batch: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess(self, p, processed):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess(p, processed, *script_args)
|
||||
@ -818,7 +851,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running postprocess: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess_batch(self, p, images, **kwargs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess_batch'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess_batch(p, *script_args, images=images, **kwargs)
|
||||
@ -826,7 +859,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess_batch_list'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess_batch_list(p, pp, *script_args, **kwargs)
|
||||
@ -834,7 +867,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running postprocess_batch_list: {script.filename}", exc_info=True)
|
||||
|
||||
def post_sample(self, p, ps: PostSampleArgs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('post_sample'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.post_sample(p, ps, *script_args)
|
||||
@ -842,7 +875,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running post_sample: {script.filename}", exc_info=True)
|
||||
|
||||
def on_mask_blend(self, p, mba: MaskBlendArgs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('on_mask_blend'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.on_mask_blend(p, mba, *script_args)
|
||||
@ -850,7 +883,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running post_sample: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess_image(self, p, pp: PostprocessImageArgs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess_image'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess_image(p, pp, *script_args)
|
||||
@ -858,7 +891,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running postprocess_image: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess_maskoverlay(self, p, ppmo: PostProcessMaskOverlayArgs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess_maskoverlay'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess_maskoverlay(p, ppmo, *script_args)
|
||||
@ -866,7 +899,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running postprocess_image: {script.filename}", exc_info=True)
|
||||
|
||||
def postprocess_image_after_composite(self, p, pp: PostprocessImageArgs):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('postprocess_image_after_composite'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.postprocess_image_after_composite(p, pp, *script_args)
|
||||
@ -880,7 +913,7 @@ class ScriptRunner:
|
||||
except Exception:
|
||||
errors.report(f"Error running on_before_component: {script.filename}", exc_info=True)
|
||||
|
||||
for script in self.scripts:
|
||||
for script in self.ordered_scripts('before_component'):
|
||||
try:
|
||||
script.before_component(component, **kwargs)
|
||||
except Exception:
|
||||
@ -893,7 +926,7 @@ class ScriptRunner:
|
||||
except Exception:
|
||||
errors.report(f"Error running on_after_component: {script.filename}", exc_info=True)
|
||||
|
||||
for script in self.scripts:
|
||||
for script in self.ordered_scripts('after_component'):
|
||||
try:
|
||||
script.after_component(component, **kwargs)
|
||||
except Exception:
|
||||
@ -921,7 +954,7 @@ class ScriptRunner:
|
||||
self.scripts[si].args_to = args_to
|
||||
|
||||
def before_hr(self, p):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('before_hr'):
|
||||
try:
|
||||
script_args = p.script_args[script.args_from:script.args_to]
|
||||
script.before_hr(p, *script_args)
|
||||
@ -929,7 +962,7 @@ class ScriptRunner:
|
||||
errors.report(f"Error running before_hr: {script.filename}", exc_info=True)
|
||||
|
||||
def setup_scrips(self, p, *, is_ui=True):
|
||||
for script in self.alwayson_scripts:
|
||||
for script in self.ordered_scripts('setup'):
|
||||
if not is_ui and script.setup_for_ui_only:
|
||||
continue
|
||||
|
||||
|
@ -35,7 +35,7 @@ class EmphasisIgnore(Emphasis):
|
||||
|
||||
class EmphasisOriginal(Emphasis):
|
||||
name = "Original"
|
||||
description = "the orginal emphasis implementation"
|
||||
description = "the original emphasis implementation"
|
||||
|
||||
def after_transformers(self):
|
||||
original_mean = self.z.mean()
|
||||
@ -48,7 +48,7 @@ class EmphasisOriginal(Emphasis):
|
||||
|
||||
class EmphasisOriginalNoNorm(EmphasisOriginal):
|
||||
name = "No norm"
|
||||
description = "same as orginal, but without normalization (seems to work better for SDXL)"
|
||||
description = "same as original, but without normalization (seems to work better for SDXL)"
|
||||
|
||||
def after_transformers(self):
|
||||
self.z = self.z * self.multipliers.reshape(self.multipliers.shape + (1,)).expand(self.z.shape)
|
||||
|
@ -23,7 +23,7 @@ class PromptChunk:
|
||||
|
||||
PromptChunkFix = namedtuple('PromptChunkFix', ['offset', 'embedding'])
|
||||
"""An object of this type is a marker showing that textual inversion embedding's vectors have to placed at offset in the prompt
|
||||
chunk. Thos objects are found in PromptChunk.fixes and, are placed into FrozenCLIPEmbedderWithCustomWordsBase.hijack.fixes, and finally
|
||||
chunk. Those objects are found in PromptChunk.fixes and, are placed into FrozenCLIPEmbedderWithCustomWordsBase.hijack.fixes, and finally
|
||||
are applied by sd_hijack.EmbeddingsWithFixes's forward function."""
|
||||
|
||||
|
||||
@ -66,7 +66,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
|
||||
|
||||
def encode_with_transformers(self, tokens):
|
||||
"""
|
||||
converts a batch of token ids (in python lists) into a single tensor with numeric respresentation of those tokens;
|
||||
converts a batch of token ids (in python lists) into a single tensor with numeric representation of those tokens;
|
||||
All python lists with tokens are assumed to have same length, usually 77.
|
||||
if input is a list with B elements and each element has T tokens, expected output shape is (B, T, C), where C depends on
|
||||
model - can be 768 and 1024.
|
||||
@ -136,7 +136,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
|
||||
if token == self.comma_token:
|
||||
last_comma = len(chunk.tokens)
|
||||
|
||||
# this is when we are at the end of alloted 75 tokens for the current chunk, and the current token is not a comma. opts.comma_padding_backtrack
|
||||
# this is when we are at the end of allotted 75 tokens for the current chunk, and the current token is not a comma. opts.comma_padding_backtrack
|
||||
# is a setting that specifies that if there is a comma nearby, the text after the comma should be moved out of this chunk and into the next.
|
||||
elif opts.comma_padding_backtrack != 0 and len(chunk.tokens) == self.chunk_length and last_comma != -1 and len(chunk.tokens) - last_comma <= opts.comma_padding_backtrack:
|
||||
break_location = last_comma + 1
|
||||
@ -206,7 +206,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
|
||||
be a multiple of 77; and C is dimensionality of each token - for SD1 it's 768, for SD2 it's 1024, and for SDXL it's 1280.
|
||||
An example shape returned by this function can be: (2, 77, 768).
|
||||
For SDXL, instead of returning one tensor avobe, it returns a tuple with two: the other one with shape (B, 1280) with pooled values.
|
||||
Webui usually sends just one text at a time through this function - the only time when texts is an array with more than one elemenet
|
||||
Webui usually sends just one text at a time through this function - the only time when texts is an array with more than one element
|
||||
is when you do prompt editing: "a picture of a [cat:dog:0.4] eating ice cream"
|
||||
"""
|
||||
|
||||
@ -230,7 +230,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
|
||||
for fixes in self.hijack.fixes:
|
||||
for _position, embedding in fixes:
|
||||
used_embeddings[embedding.name] = embedding
|
||||
|
||||
devices.torch_npu_set_device()
|
||||
z = self.process_tokens(tokens, multipliers)
|
||||
zs.append(z)
|
||||
|
||||
|
@ -784,7 +784,7 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer):
|
||||
If it is loaded, returns that (moving it to GPU if necessary, and moving the currently loadded model to CPU if necessary).
|
||||
If not, returns the model that can be used to load weights from checkpoint_info's file.
|
||||
If no such model exists, returns None.
|
||||
Additionaly deletes loaded models that are over the limit set in settings (sd_checkpoints_limit).
|
||||
Additionally deletes loaded models that are over the limit set in settings (sd_checkpoints_limit).
|
||||
"""
|
||||
|
||||
already_loaded = None
|
||||
|
@ -13,8 +13,8 @@ def get_learned_conditioning(self: sgm.models.diffusion.DiffusionEngine, batch:
|
||||
for embedder in self.conditioner.embedders:
|
||||
embedder.ucg_rate = 0.0
|
||||
|
||||
width = getattr(batch, 'width', 1024)
|
||||
height = getattr(batch, 'height', 1024)
|
||||
width = getattr(batch, 'width', 1024) or 1024
|
||||
height = getattr(batch, 'height', 1024) or 1024
|
||||
is_negative_prompt = getattr(batch, 'is_negative_prompt', False)
|
||||
aesthetic_score = shared.opts.sdxl_refiner_low_aesthetic_score if is_negative_prompt else shared.opts.sdxl_refiner_high_aesthetic_score
|
||||
|
||||
|
@ -152,7 +152,7 @@ class CFGDenoiser(torch.nn.Module):
|
||||
if state.interrupted or state.skipped:
|
||||
raise sd_samplers_common.InterruptedException
|
||||
|
||||
if sd_samplers_common.apply_refiner(self):
|
||||
if sd_samplers_common.apply_refiner(self, sigma):
|
||||
cond = self.sampler.sampler_extra_args['cond']
|
||||
uncond = self.sampler.sampler_extra_args['uncond']
|
||||
|
||||
|
@ -155,8 +155,19 @@ def replace_torchsde_browinan():
|
||||
replace_torchsde_browinan()
|
||||
|
||||
|
||||
def apply_refiner(cfg_denoiser):
|
||||
def apply_refiner(cfg_denoiser, sigma=None):
|
||||
if opts.refiner_switch_by_sample_steps or sigma is None:
|
||||
completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
|
||||
cfg_denoiser.p.extra_generation_params["Refiner switch by sampling steps"] = True
|
||||
|
||||
else:
|
||||
# torch.max(sigma) only to handle rare case where we might have different sigmas in the same batch
|
||||
try:
|
||||
timestep = torch.argmin(torch.abs(cfg_denoiser.inner_model.sigmas - torch.max(sigma)))
|
||||
except AttributeError: # for samplers that don't use sigmas (DDIM) sigma is actually the timestep
|
||||
timestep = torch.max(sigma).to(dtype=int)
|
||||
completed_ratio = (999 - timestep) / 1000
|
||||
|
||||
refiner_switch_at = cfg_denoiser.p.refiner_switch_at
|
||||
refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
|
||||
|
||||
|
12
modules/sd_samplers_custom_schedulers.py
Normal file
12
modules/sd_samplers_custom_schedulers.py
Normal file
@ -0,0 +1,12 @@
|
||||
import torch
|
||||
|
||||
|
||||
def sgm_uniform(n, sigma_min, sigma_max, inner_model, device):
|
||||
start = inner_model.sigma_to_t(torch.tensor(sigma_max))
|
||||
end = inner_model.sigma_to_t(torch.tensor(sigma_min))
|
||||
sigs = [
|
||||
inner_model.t_to_sigma(ts)
|
||||
for ts in torch.linspace(start, end, n)[:-1]
|
||||
]
|
||||
sigs += [0.0]
|
||||
return torch.FloatTensor(sigs).to(device)
|
@ -3,6 +3,7 @@ import inspect
|
||||
import k_diffusion.sampling
|
||||
from modules import sd_samplers_common, sd_samplers_extra, sd_samplers_cfg_denoiser
|
||||
from modules.sd_samplers_cfg_denoiser import CFGDenoiser # noqa: F401
|
||||
from modules.sd_samplers_custom_schedulers import sgm_uniform
|
||||
from modules.script_callbacks import ExtraNoiseParams, extra_noise_callback
|
||||
|
||||
from modules.shared import opts
|
||||
@ -62,7 +63,8 @@ k_diffusion_scheduler = {
|
||||
'Automatic': None,
|
||||
'karras': k_diffusion.sampling.get_sigmas_karras,
|
||||
'exponential': k_diffusion.sampling.get_sigmas_exponential,
|
||||
'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential
|
||||
'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential,
|
||||
'sgm_uniform' : sgm_uniform,
|
||||
}
|
||||
|
||||
|
||||
@ -121,6 +123,11 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
|
||||
if opts.k_sched_type != 'exponential' and opts.rho != 0 and opts.rho != default_rho:
|
||||
sigmas_kwargs['rho'] = opts.rho
|
||||
p.extra_generation_params["Schedule rho"] = opts.rho
|
||||
if opts.k_sched_type == 'sgm_uniform':
|
||||
# Ensure the "step" will be target step + 1
|
||||
steps += 1 if not discard_next_to_last_sigma else 0
|
||||
sigmas_kwargs['inner_model'] = self.model_wrap
|
||||
sigmas_kwargs.pop('rho', None)
|
||||
|
||||
sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device)
|
||||
elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
|
||||
|
@ -6,6 +6,10 @@ import gradio as gr
|
||||
from modules import shared_cmd_options, shared_gradio_themes, options, shared_items, sd_models_types
|
||||
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 modules import util
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from modules import shared_state, styles, interrogate, shared_total_tqdm, memmon
|
||||
|
||||
cmd_opts = shared_cmd_options.cmd_opts
|
||||
parser = shared_cmd_options.parser
|
||||
@ -16,11 +20,11 @@ styles_filename = cmd_opts.styles_file = cmd_opts.styles_file if len(cmd_opts.st
|
||||
config_filename = cmd_opts.ui_settings_file
|
||||
hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
|
||||
|
||||
demo = None
|
||||
demo: gr.Blocks = None
|
||||
|
||||
device = None
|
||||
device: str = None
|
||||
|
||||
weight_load_location = None
|
||||
weight_load_location: str = None
|
||||
|
||||
xformers_available = False
|
||||
|
||||
@ -28,22 +32,22 @@ hypernetworks = {}
|
||||
|
||||
loaded_hypernetworks = []
|
||||
|
||||
state = None
|
||||
state: 'shared_state.State' = None
|
||||
|
||||
prompt_styles = None
|
||||
prompt_styles: 'styles.StyleDatabase' = None
|
||||
|
||||
interrogator = None
|
||||
interrogator: 'interrogate.InterrogateModels' = None
|
||||
|
||||
face_restorers = []
|
||||
|
||||
options_templates = None
|
||||
opts = None
|
||||
restricted_opts = None
|
||||
options_templates: dict = None
|
||||
opts: options.Options = None
|
||||
restricted_opts: set[str] = None
|
||||
|
||||
sd_model: sd_models_types.WebuiSdModel = None
|
||||
|
||||
settings_components = None
|
||||
"""assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings"""
|
||||
settings_components: dict = None
|
||||
"""assigned from ui.py, a mapping on setting names to gradio components repsponsible for those settings"""
|
||||
|
||||
tab_names = []
|
||||
|
||||
@ -65,9 +69,9 @@ progress_print_out = sys.stdout
|
||||
|
||||
gradio_theme = gr.themes.Base()
|
||||
|
||||
total_tqdm = None
|
||||
total_tqdm: 'shared_total_tqdm.TotalTQDM' = None
|
||||
|
||||
mem_mon = None
|
||||
mem_mon: 'memmon.MemUsageMonitor' = None
|
||||
|
||||
options_section = options.options_section
|
||||
OptionInfo = options.OptionInfo
|
||||
|
@ -1,5 +1,8 @@
|
||||
import html
|
||||
import sys
|
||||
|
||||
from modules import script_callbacks, scripts, ui_components
|
||||
from modules.options import OptionHTML, OptionInfo
|
||||
from modules.shared_cmd_options import cmd_opts
|
||||
|
||||
|
||||
@ -118,6 +121,45 @@ def ui_reorder_categories():
|
||||
yield "scripts"
|
||||
|
||||
|
||||
def callbacks_order_settings():
|
||||
options = {
|
||||
"sd_vae_explanation": OptionHTML("""
|
||||
For categories below, callbacks added to dropdowns happen before others, in order listed.
|
||||
"""),
|
||||
|
||||
}
|
||||
|
||||
callback_options = {}
|
||||
|
||||
for category, _ in script_callbacks.enumerate_callbacks():
|
||||
callback_options[category] = script_callbacks.ordered_callbacks(category, enable_user_sort=False)
|
||||
|
||||
for method_name in scripts.scripts_txt2img.callback_names:
|
||||
callback_options["script_" + method_name] = scripts.scripts_txt2img.create_ordered_callbacks_list(method_name, enable_user_sort=False)
|
||||
|
||||
for method_name in scripts.scripts_img2img.callback_names:
|
||||
callbacks = callback_options.get("script_" + method_name, [])
|
||||
|
||||
for addition in scripts.scripts_img2img.create_ordered_callbacks_list(method_name, enable_user_sort=False):
|
||||
if any(x.name == addition.name for x in callbacks):
|
||||
continue
|
||||
|
||||
callbacks.append(addition)
|
||||
|
||||
callback_options["script_" + method_name] = callbacks
|
||||
|
||||
for category, callbacks in callback_options.items():
|
||||
if not callbacks:
|
||||
continue
|
||||
|
||||
option_info = OptionInfo([], f"{category} callback priority", ui_components.DropdownMulti, {"choices": [x.name for x in callbacks]})
|
||||
option_info.needs_restart()
|
||||
option_info.html("<div class='info'>Default order: <ol>" + "".join(f"<li>{html.escape(x.name)}</li>\n" for x in callbacks) + "</ol></div>")
|
||||
options['prioritized_callbacks_' + category] = option_info
|
||||
|
||||
return options
|
||||
|
||||
|
||||
class Shared(sys.modules[__name__].__class__):
|
||||
"""
|
||||
this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than
|
||||
|
@ -101,6 +101,7 @@ options_templates.update(options_section(('upscaling', "Upscaling", "postprocess
|
||||
"DAT_tile": OptionInfo(192, "Tile size for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
|
||||
"DAT_tile_overlap": OptionInfo(8, "Tile overlap for DAT upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
|
||||
"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}),
|
||||
"set_scale_by_when_changing_upscaler": OptionInfo(False, "Automatically set the Scale by factor based on the name of the selected Upscaler."),
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('face-restoration', "Face restoration", "postprocessing"), {
|
||||
@ -213,7 +214,7 @@ options_templates.update(options_section(('optimizations', "Optimizations", "sd"
|
||||
"pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt", infotext='Pad conds').info("improves performance when prompt and negative prompt have different lengths; changes seeds"),
|
||||
"pad_cond_uncond_v0": OptionInfo(False, "Pad prompt/negative prompt (v0)", infotext='Pad conds v0').info("alternative implementation for the above; used prior to 1.6.0 for DDIM sampler; overrides the above if set; WARNING: truncates negative prompt if it's too long; changes seeds"),
|
||||
"persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("do not recalculate conds from prompts if prompts have not changed since previous calculation"),
|
||||
"batch_cond_uncond": OptionInfo(True, "Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond comandline argument"),
|
||||
"batch_cond_uncond": OptionInfo(True, "Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond commandline argument"),
|
||||
"fp8_storage": OptionInfo("Disable", "FP8 weight", gr.Radio, {"choices": ["Disable", "Enable for SDXL", "Enable"]}).info("Use FP8 to store Linear/Conv layers' weight. Require pytorch>=2.1.0."),
|
||||
"cache_fp16_weight": OptionInfo(False, "Cache FP16 weight for LoRA").info("Cache fp16 weight when enabling FP8, will increase the quality of LoRA. Use more system ram."),
|
||||
}))
|
||||
@ -227,7 +228,8 @@ options_templates.update(options_section(('compatibility', "Compatibility", "sd"
|
||||
"dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."),
|
||||
"hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."),
|
||||
"use_old_scheduling": OptionInfo(False, "Use old prompt editing timelines.", infotext="Old prompt editing timelines").info("For [red:green:N]; old: If N < 1, it's a fraction of steps (and hires fix uses range from 0 to 1), if N >= 1, it's an absolute number of steps; new: If N has a decimal point in it, it's a fraction of steps (and hires fix uses range from 1 to 2), othewrwise it's an absolute number of steps"),
|
||||
"use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod")
|
||||
"use_downcasted_alpha_bar": OptionInfo(False, "Downcast model alphas_cumprod to fp16 before sampling. For reproducing old seeds.", infotext="Downcast alphas_cumprod"),
|
||||
"refiner_switch_by_sample_steps": OptionInfo(False, "Switch to refiner by sampling steps instead of model timesteps. Old behavior for refiner.", infotext="Refiner switch by sampling steps")
|
||||
}))
|
||||
|
||||
options_templates.update(options_section(('interrogate', "Interrogate"), {
|
||||
@ -257,7 +259,9 @@ options_templates.update(options_section(('extra_networks', "Extra Networks", "s
|
||||
"extra_networks_card_description_is_html": OptionInfo(False, "Treat card description as HTML"),
|
||||
"extra_networks_card_order_field": OptionInfo("Path", "Default order field for Extra Networks cards", gr.Dropdown, {"choices": ['Path', 'Name', 'Date Created', 'Date Modified']}).needs_reload_ui(),
|
||||
"extra_networks_card_order": OptionInfo("Ascending", "Default order for Extra Networks cards", gr.Dropdown, {"choices": ['Ascending', 'Descending']}).needs_reload_ui(),
|
||||
"extra_networks_tree_view_default_enabled": OptionInfo(False, "Enables the Extra Networks directory tree view by default").needs_reload_ui(),
|
||||
"extra_networks_tree_view_style": OptionInfo("Dirs", "Extra Networks directory view style", gr.Radio, {"choices": ["Tree", "Dirs"]}).needs_reload_ui(),
|
||||
"extra_networks_tree_view_default_enabled": OptionInfo(True, "Show the Extra Networks directory view by default").needs_reload_ui(),
|
||||
"extra_networks_tree_view_default_width": OptionInfo(180, "Default width for the Extra Networks directory tree view", gr.Number).needs_reload_ui(),
|
||||
"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_reload_ui(),
|
||||
"textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"),
|
||||
@ -311,6 +315,8 @@ options_templates.update(options_section(('ui', "User interface", "ui"), {
|
||||
"show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
|
||||
"send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
|
||||
"send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
|
||||
"enable_reloading_ui_scripts": OptionInfo(False, "Reload UI scripts when using Reload UI option").info("useful for developing: if you make changes to UI scripts code, it is applied when the UI is reloded."),
|
||||
|
||||
}))
|
||||
|
||||
|
||||
@ -362,13 +368,13 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
|
||||
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}, infotext='Sigma tmin').info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'),
|
||||
's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}, infotext='Sigma tmax').info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"),
|
||||
's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}, infotext='Sigma noise').info('amount of additional noise to counteract loss of detail during sampling'),
|
||||
'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}, infotext='Schedule type').info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"),
|
||||
'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential", "sgm_uniform"]}, infotext='Schedule type').info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"),
|
||||
'sigma_min': OptionInfo(0.0, "sigma min", gr.Number, infotext='Schedule min sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"),
|
||||
'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule max sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"),
|
||||
'rho': OptionInfo(0.0, "rho", gr.Number, infotext='Schedule rho').info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"),
|
||||
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}, infotext='ENSD').info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"),
|
||||
'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma", infotext='Discard penultimate sigma').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"),
|
||||
'sgm_noise_multiplier': OptionInfo(False, "SGM noise multiplier", infotext='SGM noise multplier').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12818").info("Match initial noise to official SDXL implementation - only useful for reproducing images"),
|
||||
'sgm_noise_multiplier': OptionInfo(False, "SGM noise multiplier", infotext='SGM noise multiplier').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12818").info("Match initial noise to official SDXL implementation - only useful for reproducing images"),
|
||||
'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}, infotext='UniPC variant'),
|
||||
'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}, infotext='UniPC skip type'),
|
||||
'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"),
|
||||
|
@ -157,10 +157,12 @@ class State:
|
||||
self.current_image_sampling_step = self.sampling_step
|
||||
|
||||
except Exception:
|
||||
# when switching models during genration, VAE would be on CPU, so creating an image will fail.
|
||||
# when switching models during generation, VAE would be on CPU, so creating an image will fail.
|
||||
# we silently ignore this error
|
||||
errors.record_exception()
|
||||
|
||||
def assign_current_image(self, image):
|
||||
if shared.opts.live_previews_image_format == 'jpeg' and image.mode == 'RGBA':
|
||||
image = image.convert('RGB')
|
||||
self.current_image = image
|
||||
self.id_live_preview += 1
|
||||
|
@ -1,3 +1,4 @@
|
||||
from __future__ import annotations
|
||||
from pathlib import Path
|
||||
from modules import errors
|
||||
import csv
|
||||
@ -42,7 +43,7 @@ def extract_style_text_from_prompt(style_text, prompt):
|
||||
stripped_style_text = style_text.strip()
|
||||
|
||||
if "{prompt}" in stripped_style_text:
|
||||
left, right = stripped_style_text.split("{prompt}", 2)
|
||||
left, _, right = stripped_style_text.partition("{prompt}")
|
||||
if stripped_prompt.startswith(left) and stripped_prompt.endswith(right):
|
||||
prompt = stripped_prompt[len(left):len(stripped_prompt)-len(right)]
|
||||
return True, prompt
|
||||
|
@ -65,7 +65,7 @@ def crop_image(im, settings):
|
||||
rect[3] -= 1
|
||||
d.rectangle(rect, outline=GREEN)
|
||||
results.append(im_debug)
|
||||
if settings.destop_view_image:
|
||||
if settings.desktop_view_image:
|
||||
im_debug.show()
|
||||
|
||||
return results
|
||||
@ -341,5 +341,5 @@ class Settings:
|
||||
self.entropy_points_weight = entropy_points_weight
|
||||
self.face_points_weight = face_points_weight
|
||||
self.annotate_image = annotate_image
|
||||
self.destop_view_image = False
|
||||
self.desktop_view_image = False
|
||||
self.dnn_model_path = dnn_model_path
|
||||
|
@ -2,7 +2,6 @@ import os
|
||||
import numpy as np
|
||||
import PIL
|
||||
import torch
|
||||
from PIL import Image
|
||||
from torch.utils.data import Dataset, DataLoader, Sampler
|
||||
from torchvision import transforms
|
||||
from collections import defaultdict
|
||||
@ -10,7 +9,7 @@ from random import shuffle, choices
|
||||
|
||||
import random
|
||||
import tqdm
|
||||
from modules import devices, shared
|
||||
from modules import devices, shared, images
|
||||
import re
|
||||
|
||||
from ldm.modules.distributions.distributions import DiagonalGaussianDistribution
|
||||
@ -61,7 +60,7 @@ class PersonalizedBase(Dataset):
|
||||
if shared.state.interrupted:
|
||||
raise Exception("interrupted")
|
||||
try:
|
||||
image = Image.open(path)
|
||||
image = images.read(path)
|
||||
#Currently does not work for single color transparency
|
||||
#We would need to read image.info['transparency'] for that
|
||||
if use_weight and 'A' in image.getbands():
|
||||
|
@ -193,11 +193,11 @@ if __name__ == '__main__':
|
||||
|
||||
embedded_image = insert_image_data_embed(cap_image, test_embed)
|
||||
|
||||
retrived_embed = extract_image_data_embed(embedded_image)
|
||||
retrieved_embed = extract_image_data_embed(embedded_image)
|
||||
|
||||
assert str(retrived_embed) == str(test_embed)
|
||||
assert str(retrieved_embed) == str(test_embed)
|
||||
|
||||
embedded_image2 = insert_image_data_embed(cap_image, retrived_embed)
|
||||
embedded_image2 = insert_image_data_embed(cap_image, retrieved_embed)
|
||||
|
||||
assert embedded_image == embedded_image2
|
||||
|
||||
|
@ -172,7 +172,7 @@ class EmbeddingDatabase:
|
||||
if data:
|
||||
name = data.get('name', name)
|
||||
else:
|
||||
# if data is None, means this is not an embeding, just a preview image
|
||||
# if data is None, means this is not an embedding, just a preview image
|
||||
return
|
||||
elif ext in ['.BIN', '.PT']:
|
||||
data = torch.load(path, map_location="cpu")
|
||||
|
@ -269,6 +269,9 @@ def create_ui():
|
||||
|
||||
parameters_copypaste.reset()
|
||||
|
||||
settings = ui_settings.UiSettings()
|
||||
settings.register_settings()
|
||||
|
||||
scripts.scripts_current = scripts.scripts_txt2img
|
||||
scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
|
||||
|
||||
@ -1116,7 +1119,6 @@ def create_ui():
|
||||
loadsave = ui_loadsave.UiLoadsave(cmd_opts.ui_config_file)
|
||||
ui_settings_from_file = loadsave.ui_settings.copy()
|
||||
|
||||
settings = ui_settings.UiSettings()
|
||||
settings.create_ui(loadsave, dummy_component)
|
||||
|
||||
interfaces = [
|
||||
|
@ -105,7 +105,7 @@ def save_files(js_data, images, do_make_zip, index):
|
||||
logfile_path = os.path.join(shared.opts.outdir_save, "log.csv")
|
||||
|
||||
# NOTE: ensure csv integrity when fields are added by
|
||||
# updating headers and padding with delimeters where needed
|
||||
# updating headers and padding with delimiters where needed
|
||||
if os.path.exists(logfile_path):
|
||||
update_logfile(logfile_path, fields)
|
||||
|
||||
|
@ -88,7 +88,7 @@ class DropdownEditable(FormComponent, gr.Dropdown):
|
||||
class InputAccordion(gr.Checkbox):
|
||||
"""A gr.Accordion that can be used as an input - returns True if open, False if closed.
|
||||
|
||||
Actaully just a hidden checkbox, but creates an accordion that follows and is followed by the state of the checkbox.
|
||||
Actually just a hidden checkbox, but creates an accordion that follows and is followed by the state of the checkbox.
|
||||
"""
|
||||
|
||||
global_index = 0
|
||||
|
@ -380,7 +380,7 @@ def install_extension_from_url(dirname, url, branch_name=None):
|
||||
except OSError as err:
|
||||
if err.errno == errno.EXDEV:
|
||||
# Cross device link, typical in docker or when tmp/ and extensions/ are on different file systems
|
||||
# Since we can't use a rename, do the slower but more versitile shutil.move()
|
||||
# Since we can't use a rename, do the slower but more versatile shutil.move()
|
||||
shutil.move(tmpdir, target_dir)
|
||||
else:
|
||||
# Something else, not enough free space, permissions, etc. rethrow it so that it gets handled.
|
||||
|
@ -151,6 +151,7 @@ def quote_js(s):
|
||||
s = s.replace('"', '\\"')
|
||||
return f'"{s}"'
|
||||
|
||||
|
||||
class ExtraNetworksPage:
|
||||
def __init__(self, title):
|
||||
self.title = title
|
||||
@ -164,6 +165,8 @@ class ExtraNetworksPage:
|
||||
self.lister = util.MassFileLister()
|
||||
# HTML Templates
|
||||
self.pane_tpl = shared.html("extra-networks-pane.html")
|
||||
self.pane_content_tree_tpl = shared.html("extra-networks-pane-tree.html")
|
||||
self.pane_content_dirs_tpl = shared.html("extra-networks-pane-dirs.html")
|
||||
self.card_tpl = shared.html("extra-networks-card.html")
|
||||
self.btn_tree_tpl = shared.html("extra-networks-tree-button.html")
|
||||
self.btn_copy_path_tpl = shared.html("extra-networks-copy-path-button.html")
|
||||
@ -236,7 +239,7 @@ class ExtraNetworksPage:
|
||||
)
|
||||
onclick = html.escape(onclick)
|
||||
|
||||
btn_copy_path = self.btn_copy_path_tpl.format(**{"filename": item["filename"]})
|
||||
btn_copy_path = self.btn_copy_path_tpl.format(**{"filename": quote_js(item["filename"])})
|
||||
btn_metadata = ""
|
||||
metadata = item.get("metadata")
|
||||
if metadata:
|
||||
@ -474,6 +477,47 @@ class ExtraNetworksPage:
|
||||
|
||||
return f"<ul class='tree-list tree-list--tree'>{res}</ul>"
|
||||
|
||||
def create_dirs_view_html(self, tabname: str) -> str:
|
||||
"""Generates HTML for displaying folders."""
|
||||
|
||||
subdirs = {}
|
||||
for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]:
|
||||
for root, dirs, _ in sorted(os.walk(parentdir, followlinks=True), key=lambda x: shared.natural_sort_key(x[0])):
|
||||
for dirname in sorted(dirs, key=shared.natural_sort_key):
|
||||
x = os.path.join(root, dirname)
|
||||
|
||||
if not os.path.isdir(x):
|
||||
continue
|
||||
|
||||
subdir = os.path.abspath(x)[len(parentdir):]
|
||||
|
||||
if shared.opts.extra_networks_dir_button_function:
|
||||
if not subdir.startswith(os.path.sep):
|
||||
subdir = os.path.sep + subdir
|
||||
else:
|
||||
while subdir.startswith(os.path.sep):
|
||||
subdir = subdir[1:]
|
||||
|
||||
is_empty = len(os.listdir(x)) == 0
|
||||
if not is_empty and not subdir.endswith(os.path.sep):
|
||||
subdir = subdir + os.path.sep
|
||||
|
||||
if (os.path.sep + "." in subdir or subdir.startswith(".")) and not shared.opts.extra_networks_show_hidden_directories:
|
||||
continue
|
||||
|
||||
subdirs[subdir] = 1
|
||||
|
||||
if subdirs:
|
||||
subdirs = {"": 1, **subdirs}
|
||||
|
||||
subdirs_html = "".join([f"""
|
||||
<button class='lg secondary gradio-button custom-button{" search-all" if subdir == "" else ""}' onclick='extraNetworksSearchButton("{tabname}", "{self.extra_networks_tabname}", event)'>
|
||||
{html.escape(subdir if subdir != "" else "all")}
|
||||
</button>
|
||||
""" for subdir in subdirs])
|
||||
|
||||
return subdirs_html
|
||||
|
||||
def create_card_view_html(self, tabname: str, *, none_message) -> str:
|
||||
"""Generates HTML for the network Card View section for a tab.
|
||||
|
||||
@ -487,15 +531,15 @@ class ExtraNetworksPage:
|
||||
Returns:
|
||||
HTML formatted string.
|
||||
"""
|
||||
res = ""
|
||||
res = []
|
||||
for item in self.items.values():
|
||||
res += self.create_item_html(tabname, item, self.card_tpl)
|
||||
res.append(self.create_item_html(tabname, item, self.card_tpl))
|
||||
|
||||
if res == "":
|
||||
if not res:
|
||||
dirs = "".join([f"<li>{x}</li>" for x in self.allowed_directories_for_previews()])
|
||||
res = none_message or shared.html("extra-networks-no-cards.html").format(dirs=dirs)
|
||||
res = [none_message or shared.html("extra-networks-no-cards.html").format(dirs=dirs)]
|
||||
|
||||
return res
|
||||
return "".join(res)
|
||||
|
||||
def create_html(self, tabname, *, empty=False):
|
||||
"""Generates an HTML string for the current pane.
|
||||
@ -524,28 +568,28 @@ class ExtraNetworksPage:
|
||||
if "user_metadata" not in item:
|
||||
self.read_user_metadata(item)
|
||||
|
||||
data_sortdir = shared.opts.extra_networks_card_order
|
||||
data_sortmode = shared.opts.extra_networks_card_order_field.lower().replace("sort", "").replace(" ", "_").rstrip("_").strip()
|
||||
data_sortkey = f"{data_sortmode}-{data_sortdir}-{len(self.items)}"
|
||||
tree_view_btn_extra_class = ""
|
||||
tree_view_div_extra_class = "hidden"
|
||||
if shared.opts.extra_networks_tree_view_default_enabled:
|
||||
tree_view_btn_extra_class = "extra-network-control--enabled"
|
||||
tree_view_div_extra_class = ""
|
||||
show_tree = shared.opts.extra_networks_tree_view_default_enabled
|
||||
|
||||
return self.pane_tpl.format(
|
||||
**{
|
||||
page_params = {
|
||||
"tabname": tabname,
|
||||
"extra_networks_tabname": self.extra_networks_tabname,
|
||||
"data_sortmode": data_sortmode,
|
||||
"data_sortkey": data_sortkey,
|
||||
"data_sortdir": data_sortdir,
|
||||
"tree_view_btn_extra_class": tree_view_btn_extra_class,
|
||||
"tree_view_div_extra_class": tree_view_div_extra_class,
|
||||
"tree_html": self.create_tree_view_html(tabname),
|
||||
"data_sortdir": shared.opts.extra_networks_card_order,
|
||||
"sort_path_active": ' extra-network-control--enabled' if shared.opts.extra_networks_card_order_field == 'Path' else '',
|
||||
"sort_name_active": ' extra-network-control--enabled' if shared.opts.extra_networks_card_order_field == 'Name' else '',
|
||||
"sort_date_created_active": ' extra-network-control--enabled' if shared.opts.extra_networks_card_order_field == 'Date Created' else '',
|
||||
"sort_date_modified_active": ' extra-network-control--enabled' if shared.opts.extra_networks_card_order_field == 'Date Modified' else '',
|
||||
"tree_view_btn_extra_class": "extra-network-control--enabled" if show_tree else "",
|
||||
"items_html": self.create_card_view_html(tabname, none_message="Loading..." if empty else None),
|
||||
"extra_networks_tree_view_default_width": shared.opts.extra_networks_tree_view_default_width,
|
||||
"tree_view_div_default_display_class": "" if show_tree else "extra-network-dirs-hidden",
|
||||
}
|
||||
)
|
||||
|
||||
if shared.opts.extra_networks_tree_view_style == "Tree":
|
||||
pane_content = self.pane_content_tree_tpl.format(**page_params, tree_html=self.create_tree_view_html(tabname))
|
||||
else:
|
||||
pane_content = self.pane_content_dirs_tpl.format(**page_params, dirs_html=self.create_dirs_view_html(tabname))
|
||||
|
||||
return self.pane_tpl.format(**page_params, pane_content=pane_content)
|
||||
|
||||
def create_item(self, name, index=None):
|
||||
raise NotImplementedError()
|
||||
@ -691,7 +735,7 @@ def create_ui(interface: gr.Blocks, unrelated_tabs, tabname):
|
||||
return ui.pages_contents
|
||||
|
||||
button_refresh = gr.Button("Refresh", elem_id=f"{tabname}_{page.extra_networks_tabname}_extra_refresh_internal", visible=False)
|
||||
button_refresh.click(fn=refresh, inputs=[], outputs=ui.pages).then(fn=lambda: None, _js="function(){ " + f"applyExtraNetworkFilter('{tabname}_{page.extra_networks_tabname}');" + " }")
|
||||
button_refresh.click(fn=refresh, inputs=[], outputs=ui.pages).then(fn=lambda: None, _js="function(){ " + f"applyExtraNetworkFilter('{tabname}_{page.extra_networks_tabname}');" + " }").then(fn=lambda: None, _js='setupAllResizeHandles')
|
||||
|
||||
def create_html():
|
||||
ui.pages_contents = [pg.create_html(ui.tabname) for pg in ui.stored_extra_pages]
|
||||
@ -701,7 +745,7 @@ def create_ui(interface: gr.Blocks, unrelated_tabs, tabname):
|
||||
create_html()
|
||||
return ui.pages_contents
|
||||
|
||||
interface.load(fn=pages_html, inputs=[], outputs=ui.pages)
|
||||
interface.load(fn=pages_html, inputs=[], outputs=ui.pages).then(fn=lambda: None, _js='setupAllResizeHandles')
|
||||
|
||||
return ui
|
||||
|
||||
|
@ -133,8 +133,10 @@ class UserMetadataEditor:
|
||||
filename = item.get("filename", None)
|
||||
basename, ext = os.path.splitext(filename)
|
||||
|
||||
with open(basename + '.json', "w", encoding="utf8") as file:
|
||||
metadata_path = basename + '.json'
|
||||
with open(metadata_path, "w", encoding="utf8") as file:
|
||||
json.dump(metadata, file, indent=4, ensure_ascii=False)
|
||||
self.page.lister.update_file_entry(metadata_path)
|
||||
|
||||
def save_user_metadata(self, name, desc, notes):
|
||||
user_metadata = self.get_user_metadata(name)
|
||||
@ -185,7 +187,8 @@ class UserMetadataEditor:
|
||||
geninfo, items = images.read_info_from_image(image)
|
||||
|
||||
images.save_image_with_geninfo(image, geninfo, item["local_preview"])
|
||||
|
||||
self.page.lister.update_file_entry(item["local_preview"])
|
||||
item['preview'] = self.page.find_preview(item["local_preview"])
|
||||
return self.get_card_html(name), ''
|
||||
|
||||
def setup_ui(self, gallery):
|
||||
@ -200,6 +203,3 @@ class UserMetadataEditor:
|
||||
inputs=[self.edit_name_input],
|
||||
outputs=[]
|
||||
)
|
||||
|
||||
|
||||
|
||||
|
@ -104,6 +104,8 @@ class UiLoadsave:
|
||||
apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
|
||||
|
||||
if type(x) == InputAccordion:
|
||||
if hasattr(x, 'custom_script_source'):
|
||||
x.accordion.custom_script_source = x.custom_script_source
|
||||
if x.accordion.visible:
|
||||
apply_field(x.accordion, 'visible')
|
||||
apply_field(x, 'value')
|
||||
|
@ -67,7 +67,7 @@ class UiPromptStyles:
|
||||
with gr.Row():
|
||||
self.selection = gr.Dropdown(label="Styles", elem_id=f"{tabname}_styles_edit_select", choices=list(shared.prompt_styles.styles), value=[], allow_custom_value=True, info="Styles allow you to add custom text to prompt. Use the {prompt} token in style text, and it will be replaced with user's prompt when applying style. Otherwise, style's text will be added to the end of the prompt.")
|
||||
ui_common.create_refresh_button([self.dropdown, self.selection], shared.prompt_styles.reload, lambda: {"choices": list(shared.prompt_styles.styles)}, f"refresh_{tabname}_styles")
|
||||
self.materialize = ui_components.ToolButton(value=styles_materialize_symbol, elem_id=f"{tabname}_style_apply_dialog", tooltip="Apply all selected styles from the style selction dropdown in main UI to the prompt.")
|
||||
self.materialize = ui_components.ToolButton(value=styles_materialize_symbol, elem_id=f"{tabname}_style_apply_dialog", tooltip="Apply all selected styles from the style selection dropdown in main UI to the prompt.")
|
||||
self.copy = ui_components.ToolButton(value=styles_copy_symbol, elem_id=f"{tabname}_style_copy", tooltip="Copy main UI prompt to style.")
|
||||
|
||||
with gr.Row():
|
||||
|
@ -1,7 +1,8 @@
|
||||
import gradio as gr
|
||||
|
||||
from modules import ui_common, shared, script_callbacks, scripts, sd_models, sysinfo, timer
|
||||
from modules import ui_common, shared, script_callbacks, scripts, sd_models, sysinfo, timer, shared_items
|
||||
from modules.call_queue import wrap_gradio_call
|
||||
from modules.options import options_section
|
||||
from modules.shared import opts
|
||||
from modules.ui_components import FormRow
|
||||
from modules.ui_gradio_extensions import reload_javascript
|
||||
@ -98,6 +99,9 @@ class UiSettings:
|
||||
|
||||
return get_value_for_setting(key), opts.dumpjson()
|
||||
|
||||
def register_settings(self):
|
||||
script_callbacks.ui_settings_callback()
|
||||
|
||||
def create_ui(self, loadsave, dummy_component):
|
||||
self.components = []
|
||||
self.component_dict = {}
|
||||
@ -105,7 +109,11 @@ class UiSettings:
|
||||
|
||||
shared.settings_components = self.component_dict
|
||||
|
||||
script_callbacks.ui_settings_callback()
|
||||
# we add this as late as possible so that scripts have already registered their callbacks
|
||||
opts.data_labels.update(options_section(('callbacks', "Callbacks", "system"), {
|
||||
**shared_items.callbacks_order_settings(),
|
||||
}))
|
||||
|
||||
opts.reorder()
|
||||
|
||||
with gr.Blocks(analytics_enabled=False) as settings_interface:
|
||||
|
@ -20,7 +20,7 @@ class Upscaler:
|
||||
filter = None
|
||||
model = None
|
||||
user_path = None
|
||||
scalers: []
|
||||
scalers: list
|
||||
tile = True
|
||||
|
||||
def __init__(self, create_dirs=False):
|
||||
|
@ -69,10 +69,8 @@ def upscale_with_model(
|
||||
for y, h, row in grid.tiles:
|
||||
newrow = []
|
||||
for x, w, tile in row:
|
||||
logger.debug("Tile (%d, %d) %s...", x, y, tile)
|
||||
output = upscale_pil_patch(model, tile)
|
||||
scale_factor = output.width // tile.width
|
||||
logger.debug("=> %s (scale factor %s)", output, scale_factor)
|
||||
newrow.append([x * scale_factor, w * scale_factor, output])
|
||||
p.update(1)
|
||||
newtiles.append([y * scale_factor, h * scale_factor, newrow])
|
||||
|
@ -81,6 +81,17 @@ class MassFileListerCachedDir:
|
||||
self.files = {x[0].lower(): x for x in files}
|
||||
self.files_cased = {x[0]: x for x in files}
|
||||
|
||||
def update_entry(self, filename):
|
||||
"""Add a file to the cache"""
|
||||
file_path = os.path.join(self.dirname, filename)
|
||||
try:
|
||||
stat = os.stat(file_path)
|
||||
entry = (filename, stat.st_mtime, stat.st_ctime)
|
||||
self.files[filename.lower()] = entry
|
||||
self.files_cased[filename] = entry
|
||||
except FileNotFoundError as e:
|
||||
print(f'MassFileListerCachedDir.add_entry: "{file_path}" {e}')
|
||||
|
||||
|
||||
class MassFileLister:
|
||||
"""A class that provides a way to check for the existence and mtime/ctile of files without doing more than one stat call per file."""
|
||||
@ -136,3 +147,27 @@ class MassFileLister:
|
||||
def reset(self):
|
||||
"""Clear the cache of all directories."""
|
||||
self.cached_dirs.clear()
|
||||
|
||||
|
||||
def topological_sort(dependencies):
|
||||
"""Accepts a dictionary mapping name to its dependencies, returns a list of names ordered according to dependencies.
|
||||
Ignores errors relating to missing dependeencies or circular dependencies
|
||||
"""
|
||||
|
||||
visited = {}
|
||||
result = []
|
||||
|
||||
def inner(name):
|
||||
visited[name] = True
|
||||
|
||||
for dep in dependencies.get(name, []):
|
||||
if dep in dependencies and dep not in visited:
|
||||
inner(dep)
|
||||
|
||||
result.append(name)
|
||||
|
||||
for depname in dependencies:
|
||||
if depname not in visited:
|
||||
inner(depname)
|
||||
|
||||
return result
|
||||
|
@ -2,6 +2,8 @@
|
||||
|
||||
target-version = "py39"
|
||||
|
||||
[tool.ruff.lint]
|
||||
|
||||
extend-select = [
|
||||
"B",
|
||||
"C",
|
||||
@ -25,10 +27,10 @@ ignore = [
|
||||
"W605", # invalid escape sequence, messes with some docstrings
|
||||
]
|
||||
|
||||
[tool.ruff.per-file-ignores]
|
||||
[tool.ruff.lint.per-file-ignores]
|
||||
"webui.py" = ["E402"] # Module level import not at top of file
|
||||
|
||||
[tool.ruff.flake8-bugbear]
|
||||
[tool.ruff.lint.flake8-bugbear]
|
||||
# Allow default arguments like, e.g., `data: List[str] = fastapi.Query(None)`.
|
||||
extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"]
|
||||
|
||||
|
@ -4,6 +4,7 @@ accelerate
|
||||
|
||||
blendmodes
|
||||
clean-fid
|
||||
diskcache
|
||||
einops
|
||||
facexlib
|
||||
fastapi>=0.90.1
|
||||
|
@ -3,6 +3,7 @@ Pillow==9.5.0
|
||||
accelerate==0.21.0
|
||||
blendmodes==2022
|
||||
clean-fid==0.1.35
|
||||
diskcache==5.6.3
|
||||
einops==0.4.1
|
||||
facexlib==0.3.0
|
||||
fastapi==0.94.0
|
||||
|
@ -102,7 +102,7 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0
|
||||
shaped_noise_fft = _fft2(noise_rgb)
|
||||
shaped_noise_fft[:, :, :] = np.absolute(shaped_noise_fft[:, :, :]) ** 2 * (src_dist ** noise_q) * src_phase # perform the actual shaping
|
||||
|
||||
brightness_variation = 0. # color_variation # todo: temporarily tieing brightness variation to color variation for now
|
||||
brightness_variation = 0. # color_variation # todo: temporarily tying brightness variation to color variation for now
|
||||
contrast_adjusted_np_src = _np_src_image[:] * (brightness_variation + 1.) - brightness_variation * 2.
|
||||
|
||||
# scikit-image is used for histogram matching, very convenient!
|
||||
|
@ -1,10 +1,12 @@
|
||||
import re
|
||||
|
||||
from PIL import Image
|
||||
import numpy as np
|
||||
|
||||
from modules import scripts_postprocessing, shared
|
||||
import gradio as gr
|
||||
|
||||
from modules.ui_components import FormRow, ToolButton
|
||||
from modules.ui_components import FormRow, ToolButton, InputAccordion
|
||||
from modules.ui import switch_values_symbol
|
||||
|
||||
upscale_cache = {}
|
||||
@ -17,7 +19,14 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
|
||||
def ui(self):
|
||||
selected_tab = gr.Number(value=0, visible=False)
|
||||
|
||||
with gr.Column():
|
||||
with InputAccordion(True, label="Upscale", elem_id="extras_upscale") as upscale_enabled:
|
||||
with FormRow():
|
||||
extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
|
||||
|
||||
with FormRow():
|
||||
extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
|
||||
extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
|
||||
|
||||
with FormRow():
|
||||
with gr.Tabs(elem_id="extras_resize_mode"):
|
||||
with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
|
||||
@ -32,18 +41,24 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
|
||||
upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn", tooltip="Switch width/height")
|
||||
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
|
||||
|
||||
with FormRow():
|
||||
extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
|
||||
def on_selected_upscale_method(upscale_method):
|
||||
if not shared.opts.set_scale_by_when_changing_upscaler:
|
||||
return gr.update()
|
||||
|
||||
with FormRow():
|
||||
extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
|
||||
extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
|
||||
match = re.search(r'(\d)[xX]|[xX](\d)', upscale_method)
|
||||
if not match:
|
||||
return gr.update()
|
||||
|
||||
return gr.update(value=int(match.group(1) or match.group(2)))
|
||||
|
||||
upscaling_res_switch_btn.click(lambda w, h: (h, w), inputs=[upscaling_resize_w, upscaling_resize_h], outputs=[upscaling_resize_w, upscaling_resize_h], show_progress=False)
|
||||
tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab])
|
||||
tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab])
|
||||
|
||||
extras_upscaler_1.change(on_selected_upscale_method, inputs=[extras_upscaler_1], outputs=[upscaling_resize], show_progress="hidden")
|
||||
|
||||
return {
|
||||
"upscale_enabled": upscale_enabled,
|
||||
"upscale_mode": selected_tab,
|
||||
"upscale_by": upscaling_resize,
|
||||
"upscale_to_width": upscaling_resize_w,
|
||||
@ -81,7 +96,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
|
||||
|
||||
return image
|
||||
|
||||
def process_firstpass(self, pp: scripts_postprocessing.PostprocessedImage, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
|
||||
def process_firstpass(self, pp: scripts_postprocessing.PostprocessedImage, upscale_enabled=True, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
|
||||
if upscale_mode == 1:
|
||||
pp.shared.target_width = upscale_to_width
|
||||
pp.shared.target_height = upscale_to_height
|
||||
@ -89,7 +104,10 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
|
||||
pp.shared.target_width = int(pp.image.width * upscale_by)
|
||||
pp.shared.target_height = int(pp.image.height * upscale_by)
|
||||
|
||||
def process(self, pp: scripts_postprocessing.PostprocessedImage, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
|
||||
def process(self, pp: scripts_postprocessing.PostprocessedImage, upscale_enabled=True, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
|
||||
if not upscale_enabled:
|
||||
return
|
||||
|
||||
if upscaler_1_name == "None":
|
||||
upscaler_1_name = None
|
||||
|
||||
|
@ -45,7 +45,7 @@ def apply_prompt(p, x, xs):
|
||||
def apply_order(p, x, xs):
|
||||
token_order = []
|
||||
|
||||
# Initally grab the tokens from the prompt, so they can be replaced in order of earliest seen
|
||||
# Initially grab the tokens from the prompt, so they can be replaced in order of earliest seen
|
||||
for token in x:
|
||||
token_order.append((p.prompt.find(token), token))
|
||||
|
||||
|
52
style.css
52
style.css
@ -1,6 +1,6 @@
|
||||
/* temporary fix to load default gradio font in frontend instead of backend */
|
||||
|
||||
@import url('webui-assets/css/sourcesanspro.css');
|
||||
@import url('/webui-assets/css/sourcesanspro.css');
|
||||
|
||||
|
||||
/* temporary fix to hide gradio crop tool until it's fixed https://github.com/gradio-app/gradio/issues/3810 */
|
||||
@ -528,6 +528,10 @@ table.popup-table .link{
|
||||
opacity: 0.75;
|
||||
}
|
||||
|
||||
.settings-comment .info ol{
|
||||
margin: 0.4em 0 0.8em 1em;
|
||||
}
|
||||
|
||||
#sysinfo_download a.sysinfo_big_link{
|
||||
font-size: 24pt;
|
||||
}
|
||||
@ -1205,12 +1209,24 @@ body.resizing .resize-handle {
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.extra-network-pane .extra-network-pane-content {
|
||||
.extra-network-pane .extra-network-pane-content-dirs {
|
||||
display: flex;
|
||||
flex: 1;
|
||||
flex-direction: column;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.extra-network-pane .extra-network-pane-content-tree {
|
||||
display: flex;
|
||||
flex: 1;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.extra-network-dirs-hidden .extra-network-dirs{ display: none; }
|
||||
.extra-network-dirs-hidden .extra-network-tree{ display: none; }
|
||||
.extra-network-dirs-hidden .resize-handle { display: none; }
|
||||
.extra-network-dirs-hidden .resize-handle-row { display: flex !important; }
|
||||
|
||||
.extra-network-pane .extra-network-tree {
|
||||
flex: 1;
|
||||
font-size: 1rem;
|
||||
@ -1260,7 +1276,7 @@ body.resizing .resize-handle {
|
||||
|
||||
.extra-network-control {
|
||||
position: relative;
|
||||
display: grid;
|
||||
display: flex;
|
||||
width: 100%;
|
||||
padding: 0 !important;
|
||||
margin-top: 0 !important;
|
||||
@ -1277,6 +1293,12 @@ body.resizing .resize-handle {
|
||||
align-items: start;
|
||||
}
|
||||
|
||||
.extra-network-control small{
|
||||
color: var(--input-placeholder-color);
|
||||
line-height: 2.2rem;
|
||||
margin: 0 0.5rem 0 0.75rem;
|
||||
}
|
||||
|
||||
.extra-network-tree .tree-list--tree {}
|
||||
|
||||
/* Remove auto indentation from tree. Will be overridden later. */
|
||||
@ -1424,6 +1446,12 @@ body.resizing .resize-handle {
|
||||
line-height: 1rem;
|
||||
}
|
||||
|
||||
|
||||
.extra-network-control .extra-network-control--search .extra-network-control--search-text::placeholder {
|
||||
color: var(--input-placeholder-color);
|
||||
}
|
||||
|
||||
|
||||
/* <input> clear button (x on right side) styling */
|
||||
.extra-network-control .extra-network-control--search .extra-network-control--search-text::-webkit-search-cancel-button {
|
||||
-webkit-appearance: none;
|
||||
@ -1456,19 +1484,19 @@ body.resizing .resize-handle {
|
||||
background-color: var(--input-placeholder-color);
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--sort[data-sortmode="path"] .extra-network-control--sort-icon {
|
||||
.extra-network-control .extra-network-control--sort[data-sortkey="default"] .extra-network-control--sort-icon {
|
||||
mask-image: url('data:image/svg+xml,<svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 5C1 3.34315 2.34315 2 4 2H8.43845C9.81505 2 11.015 2.93689 11.3489 4.27239L11.7808 6H13.5H20C21.6569 6 23 7.34315 23 9V11C23 11.5523 22.5523 12 22 12C21.4477 12 21 11.5523 21 11V9C21 8.44772 20.5523 8 20 8H13.5H11.7808H4C3.44772 8 3 8.44772 3 9V10V19C3 19.5523 3.44772 20 4 20H9C9.55228 20 10 20.4477 10 21C10 21.5523 9.55228 22 9 22H4C2.34315 22 1 20.6569 1 19V10V9V5ZM3 6.17071C3.31278 6.06015 3.64936 6 4 6H9.71922L9.40859 4.75746C9.2973 4.3123 8.89732 4 8.43845 4H4C3.44772 4 3 4.44772 3 5V6.17071ZM20.1716 18.7574C20.6951 17.967 21 17.0191 21 16C21 13.2386 18.7614 11 16 11C13.2386 11 11 13.2386 11 16C11 18.7614 13.2386 21 16 21C17.0191 21 17.967 20.6951 18.7574 20.1716L21.2929 22.7071C21.6834 23.0976 22.3166 23.0976 22.7071 22.7071C23.0976 22.3166 23.0976 21.6834 22.7071 21.2929L20.1716 18.7574ZM13 16C13 14.3431 14.3431 13 16 13C17.6569 13 19 14.3431 19 16C19 17.6569 17.6569 19 16 19C14.3431 19 13 17.6569 13 16Z" fill="%23000000"></path></g></svg>');
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--sort[data-sortmode="name"] .extra-network-control--sort-icon {
|
||||
.extra-network-control .extra-network-control--sort[data-sortkey="name"] .extra-network-control--sort-icon {
|
||||
mask-image: url('data:image/svg+xml,<svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"><path fill-rule="evenodd" clip-rule="evenodd" d="M17.1841 6.69223C17.063 6.42309 16.7953 6.25 16.5002 6.25C16.2051 6.25 15.9374 6.42309 15.8162 6.69223L11.3162 16.6922C11.1463 17.07 11.3147 17.514 11.6924 17.6839C12.0701 17.8539 12.5141 17.6855 12.6841 17.3078L14.1215 14.1136H18.8789L20.3162 17.3078C20.4862 17.6855 20.9302 17.8539 21.308 17.6839C21.6857 17.514 21.8541 17.07 21.6841 16.6922L17.1841 6.69223ZM16.5002 8.82764L14.7965 12.6136H18.2039L16.5002 8.82764Z" fill="%231C274C"></path><path opacity="0.5" fill-rule="evenodd" clip-rule="evenodd" d="M2.25 7C2.25 6.58579 2.58579 6.25 3 6.25H13C13.4142 6.25 13.75 6.58579 13.75 7C13.75 7.41421 13.4142 7.75 13 7.75H3C2.58579 7.75 2.25 7.41421 2.25 7Z" fill="%231C274C"></path><path opacity="0.5" d="M2.25 12C2.25 11.5858 2.58579 11.25 3 11.25H10C10.4142 11.25 10.75 11.5858 10.75 12C10.75 12.4142 10.4142 12.75 10 12.75H3C2.58579 12.75 2.25 12.4142 2.25 12Z" fill="%231C274C"></path><path opacity="0.5" d="M2.25 17C2.25 16.5858 2.58579 16.25 3 16.25H8C8.41421 16.25 8.75 16.5858 8.75 17C8.75 17.4142 8.41421 17.75 8 17.75H3C2.58579 17.75 2.25 17.4142 2.25 17Z" fill="%231C274C"></path></g></svg>');
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--sort[data-sortmode="date_created"] .extra-network-control--sort-icon {
|
||||
.extra-network-control .extra-network-control--sort[data-sortkey="date_created"] .extra-network-control--sort-icon {
|
||||
mask-image: url('data:image/svg+xml,<svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"><path d="M17 11C14.2386 11 12 13.2386 12 16C12 18.7614 14.2386 21 17 21C19.7614 21 22 18.7614 22 16C22 13.2386 19.7614 11 17 11ZM17 11V9M2 9V15.8C2 16.9201 2 17.4802 2.21799 17.908C2.40973 18.2843 2.71569 18.5903 3.09202 18.782C3.51984 19 4.0799 19 5.2 19H13M2 9V8.2C2 7.0799 2 6.51984 2.21799 6.09202C2.40973 5.71569 2.71569 5.40973 3.09202 5.21799C3.51984 5 4.0799 5 5.2 5H13.8C14.9201 5 15.4802 5 15.908 5.21799C16.2843 5.40973 16.5903 5.71569 16.782 6.09202C17 6.51984 17 7.0799 17 8.2V9M2 9H17M5 3V5M14 3V5M15 16H17M17 16H19M17 16V14M17 16V18" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path></g></svg>');
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--sort[data-sortmode="date_modified"] .extra-network-control--sort-icon {
|
||||
.extra-network-control .extra-network-control--sort[data-sortkey="date_modified"] .extra-network-control--sort-icon {
|
||||
mask-image: url('data:image/svg+xml,<svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"><path d="M10 21H6.2C5.0799 21 4.51984 21 4.09202 20.782C3.71569 20.5903 3.40973 20.2843 3.21799 19.908C3 19.4802 3 18.9201 3 17.8V8.2C3 7.0799 3 6.51984 3.21799 6.09202C3.40973 5.71569 3.71569 5.40973 4.09202 5.21799C4.51984 5 5.0799 5 6.2 5H17.8C18.9201 5 19.4802 5 19.908 5.21799C20.2843 5.40973 20.5903 5.71569 20.782 6.09202C21 6.51984 21 7.0799 21 8.2V10M7 3V5M17 3V5M3 9H21M13.5 13.0001L7 13M10 17.0001L7 17M14 21L16.025 20.595C16.2015 20.5597 16.2898 20.542 16.3721 20.5097C16.4452 20.4811 16.5147 20.4439 16.579 20.399C16.6516 20.3484 16.7152 20.2848 16.8426 20.1574L21 16C21.5523 15.4477 21.5523 14.5523 21 14C20.4477 13.4477 19.5523 13.4477 19 14L14.8426 18.1574C14.7152 18.2848 14.6516 18.3484 14.601 18.421C14.5561 18.4853 14.5189 18.5548 14.4903 18.6279C14.458 18.7102 14.4403 18.7985 14.405 18.975L14 21Z" stroke="black" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path></g></svg>');
|
||||
}
|
||||
|
||||
@ -1518,13 +1546,18 @@ body.resizing .resize-handle {
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--enabled {
|
||||
background-color: rgba(0, 0, 0, 0.15);
|
||||
background-color: rgba(0, 0, 0, 0.1);
|
||||
border-radius: 0.25rem;
|
||||
}
|
||||
|
||||
.dark .extra-network-control .extra-network-control--enabled {
|
||||
background-color: rgba(255, 255, 255, 0.15);
|
||||
}
|
||||
|
||||
.extra-network-control .extra-network-control--enabled .extra-network-control--icon{
|
||||
background-color: var(--button-secondary-text-color);
|
||||
}
|
||||
|
||||
/* ==== REFRESH ICON ACTIONS ==== */
|
||||
.extra-network-control .extra-network-control--refresh {
|
||||
padding: 0.25rem;
|
||||
@ -1615,9 +1648,10 @@ body.resizing .resize-handle {
|
||||
display: inline-flex;
|
||||
visibility: hidden;
|
||||
color: var(--button-secondary-text-color);
|
||||
|
||||
width: 0;
|
||||
}
|
||||
|
||||
.extra-network-tree .tree-list-content:hover .button-row {
|
||||
visibility: visible;
|
||||
width: auto;
|
||||
}
|
||||
|
23
webui.sh
23
webui.sh
@ -130,12 +130,18 @@ case "$gpu_info" in
|
||||
if [[ -z "${TORCH_COMMAND}" ]]
|
||||
then
|
||||
pyv="$(${python_cmd} -c 'import sys; print(".".join(map(str, sys.version_info[0:2])))')"
|
||||
if [[ $(bc <<< "$pyv <= 3.10") -eq 1 ]]
|
||||
# Using an old nightly compiled against rocm 5.2 for Navi1, see https://github.com/pytorch/pytorch/issues/106728#issuecomment-1749511711
|
||||
if [[ $pyv == "3.8" ]]
|
||||
then
|
||||
# Navi users will still use torch 1.13 because 2.0 does not seem to work.
|
||||
export TORCH_COMMAND="pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm5.6"
|
||||
export TORCH_COMMAND="pip install https://download.pytorch.org/whl/nightly/rocm5.2/torch-2.0.0.dev20230209%2Brocm5.2-cp38-cp38-linux_x86_64.whl https://download.pytorch.org/whl/nightly/rocm5.2/torchvision-0.15.0.dev20230209%2Brocm5.2-cp38-cp38-linux_x86_64.whl"
|
||||
elif [[ $pyv == "3.9" ]]
|
||||
then
|
||||
export TORCH_COMMAND="pip install https://download.pytorch.org/whl/nightly/rocm5.2/torch-2.0.0.dev20230209%2Brocm5.2-cp39-cp39-linux_x86_64.whl https://download.pytorch.org/whl/nightly/rocm5.2/torchvision-0.15.0.dev20230209%2Brocm5.2-cp39-cp39-linux_x86_64.whl"
|
||||
elif [[ $pyv == "3.10" ]]
|
||||
then
|
||||
export TORCH_COMMAND="pip install https://download.pytorch.org/whl/nightly/rocm5.2/torch-2.0.0.dev20230209%2Brocm5.2-cp310-cp310-linux_x86_64.whl https://download.pytorch.org/whl/nightly/rocm5.2/torchvision-0.15.0.dev20230209%2Brocm5.2-cp310-cp310-linux_x86_64.whl"
|
||||
else
|
||||
printf "\e[1m\e[31mERROR: RX 5000 series GPUs must be using at max python 3.10, aborting...\e[0m"
|
||||
printf "\e[1m\e[31mERROR: RX 5000 series GPUs python version must be between 3.8 and 3.10, aborting...\e[0m"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
@ -143,7 +149,7 @@ case "$gpu_info" in
|
||||
*"Navi 2"*) export HSA_OVERRIDE_GFX_VERSION=10.3.0
|
||||
;;
|
||||
*"Navi 3"*) [[ -z "${TORCH_COMMAND}" ]] && \
|
||||
export TORCH_COMMAND="pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm5.7"
|
||||
export TORCH_COMMAND="pip install torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm5.7"
|
||||
;;
|
||||
*"Renoir"*) export HSA_OVERRIDE_GFX_VERSION=9.0.0
|
||||
printf "\n%s\n" "${delimiter}"
|
||||
@ -157,11 +163,10 @@ if ! echo "$gpu_info" | grep -q "NVIDIA";
|
||||
then
|
||||
if echo "$gpu_info" | grep -q "AMD" && [[ -z "${TORCH_COMMAND}" ]]
|
||||
then
|
||||
export TORCH_COMMAND="pip install torch==2.0.1+rocm5.4.2 torchvision==0.15.2+rocm5.4.2 --index-url https://download.pytorch.org/whl/rocm5.4.2"
|
||||
elif echo "$gpu_info" | grep -q "Huawei" && [[ -z "${TORCH_COMMAND}" ]]
|
||||
export TORCH_COMMAND="pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.7"
|
||||
elif npu-smi info 2>/dev/null
|
||||
then
|
||||
export TORCH_COMMAND="pip install torch==2.1.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu; pip install torch_npu"
|
||||
|
||||
export TORCH_COMMAND="pip install torch==2.1.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu; pip install torch_npu==2.1.0"
|
||||
fi
|
||||
fi
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user