diff options
| -rw-r--r-- | html/licenses.html | 219 | ||||
| -rw-r--r-- | javascript/extraNetworks.js | 2 | ||||
| -rw-r--r-- | javascript/hints.js | 1 | ||||
| -rw-r--r-- | javascript/progressbar.js | 2 | ||||
| -rw-r--r-- | launch.py | 16 | ||||
| -rw-r--r-- | modules/api/api.py | 45 | ||||
| -rw-r--r-- | modules/api/models.py | 28 | ||||
| -rw-r--r-- | modules/generation_parameters_copypaste.py | 8 | ||||
| -rw-r--r-- | modules/images.py | 2 | ||||
| -rw-r--r-- | modules/modelloader.py | 8 | ||||
| -rw-r--r-- | modules/models/diffusion/uni_pc/__init__.py | 1 | ||||
| -rw-r--r-- | modules/models/diffusion/uni_pc/sampler.py | 100 | ||||
| -rw-r--r-- | modules/models/diffusion/uni_pc/uni_pc.py | 856 | ||||
| -rw-r--r-- | modules/processing.py | 7 | ||||
| -rw-r--r-- | modules/scripts.py | 23 | ||||
| -rw-r--r-- | modules/sd_hijack.py | 12 | ||||
| -rw-r--r-- | modules/sd_hijack_optimizations.py | 70 | ||||
| -rw-r--r-- | modules/sd_samplers.py | 2 | ||||
| -rw-r--r-- | modules/sd_samplers_compvis.py | 59 | ||||
| -rw-r--r-- | modules/shared.py | 17 | ||||
| -rw-r--r-- | scripts/xyz_grid.py | 134 | ||||
| -rw-r--r-- | style.css | 2 | ||||
| -rw-r--r-- | test/basic_features/txt2img_test.py | 2 | ||||
| -rw-r--r-- | webui.py | 4 |
24 files changed, 1529 insertions, 91 deletions
diff --git a/html/licenses.html b/html/licenses.html index 570630eb..bddbf466 100644 --- a/html/licenses.html +++ b/html/licenses.html @@ -417,3 +417,222 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
</pre>
+<h2><a href="https://github.com/huggingface/diffusers/blob/c7da8fd23359a22d0df2741688b5b4f33c26df21/LICENSE">Scaled Dot Product Attention</a></h2>
+<small>Some small amounts of code borrowed and reworked.</small>
+<pre>
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\ No newline at end of file diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js index 17bf2000..5781df4f 100644 --- a/javascript/extraNetworks.js +++ b/javascript/extraNetworks.js @@ -78,7 +78,7 @@ function cardClicked(tabname, textToAdd, allowNegativePrompt){ var textarea = allowNegativePrompt ? activePromptTextarea[tabname] : gradioApp().querySelector("#" + tabname + "_prompt > label > textarea")
if(! tryToRemoveExtraNetworkFromPrompt(textarea, textToAdd)){
- textarea.value = textarea.value + " " + textToAdd
+ textarea.value = textarea.value + opts.extra_networks_add_text_separator + textToAdd
}
updateInput(textarea)
diff --git a/javascript/hints.js b/javascript/hints.js index f1199009..7f4101b2 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -6,6 +6,7 @@ titles = { "GFPGAN": "Restore low quality faces using GFPGAN neural network", "Euler a": "Euler Ancestral - very creative, each can get a completely different picture depending on step count, setting steps higher than 30-40 does not help", "DDIM": "Denoising Diffusion Implicit Models - best at inpainting", + "UniPC": "Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models", "DPM adaptive": "Ignores step count - uses a number of steps determined by the CFG and resolution", "Batch count": "How many batches of images to create (has no impact on generation performance or VRAM usage)", diff --git a/javascript/progressbar.js b/javascript/progressbar.js index ff6d757b..9ccc9da4 100644 --- a/javascript/progressbar.js +++ b/javascript/progressbar.js @@ -139,7 +139,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre var divProgress = document.createElement('div') divProgress.className='progressDiv' - divProgress.style.display = opts.show_progressbar ? "" : "none" + divProgress.style.display = opts.show_progressbar ? "block" : "none" var divInner = document.createElement('div') divInner.className='progress' @@ -161,7 +161,17 @@ def git_clone(url, dir, name, commithash=None): if commithash is not None:
run(f'"{git}" -C "{dir}" checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
-
+
+def git_pull_recursive(dir):
+ for subdir, _, _ in os.walk(dir):
+ if os.path.exists(os.path.join(subdir, '.git')):
+ try:
+ output = subprocess.check_output([git, '-C', subdir, 'pull', '--autostash'])
+ print(f"Pulled changes for repository in '{subdir}':\n{output.decode('utf-8').strip()}\n")
+ except subprocess.CalledProcessError as e:
+ print(f"Couldn't perform 'git pull' on repository in '{subdir}':\n{e.output.decode('utf-8').strip()}\n")
+
+
def version_check(commit):
try:
import requests
@@ -247,6 +257,7 @@ def prepare_environment(): args, _ = parser.parse_known_args(sys.argv)
sys.argv, _ = extract_arg(sys.argv, '-f')
+ sys.argv, update_all_extensions = extract_arg(sys.argv, '--update-all-extensions')
sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test')
sys.argv, skip_python_version_check = extract_arg(sys.argv, '--skip-python-version-check')
sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
@@ -312,6 +323,9 @@ def prepare_environment(): if update_check:
version_check(commit)
+
+ if update_all_extensions:
+ git_pull_recursive(dir_extensions)
if "--exit" in sys.argv:
print("Exiting because of --exit argument")
diff --git a/modules/api/api.py b/modules/api/api.py index 5a9ac5f1..376f7f04 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -150,6 +150,7 @@ class Api: self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse) self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse) self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse) + self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList) def add_api_route(self, path: str, endpoint, **kwargs): if shared.cmd_opts.api_auth: @@ -174,36 +175,44 @@ class Api: script_idx = script_name_to_index(script_name, script_runner.selectable_scripts) script = script_runner.selectable_scripts[script_idx] return script, script_idx + + def get_scripts_list(self): + t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] + i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] + + return ScriptsList(txt2img = t2ilist, img2img = i2ilist) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): script, script_idx = self.get_script(txt2imgreq.script_name, scripts.scripts_txt2img) - populate = txt2imgreq.copy(update={ # Override __init__ params + populate = txt2imgreq.copy(update={ # Override __init__ params "sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index), - "do_not_save_samples": True, - "do_not_save_grid": True - } - ) + "do_not_save_samples": not txt2imgreq.save_images, + "do_not_save_grid": not txt2imgreq.save_images, + }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on args = vars(populate) args.pop('script_name', None) + send_images = args.pop('send_images', True) + args.pop('save_images', None) + with self.queue_lock: p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args) + p.outpath_grids = opts.outdir_txt2img_grids + p.outpath_samples = opts.outdir_txt2img_samples shared.state.begin() if script is not None: - p.outpath_grids = opts.outdir_txt2img_grids - p.outpath_samples = opts.outdir_txt2img_samples p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args processed = scripts.scripts_txt2img.run(p, *p.script_args) else: processed = process_images(p) shared.state.end() - b64images = list(map(encode_pil_to_base64, processed.images)) + b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) @@ -218,13 +227,12 @@ class Api: if mask: mask = decode_base64_to_image(mask) - populate = img2imgreq.copy(update={ # Override __init__ params + populate = img2imgreq.copy(update={ # Override __init__ params "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index), - "do_not_save_samples": True, - "do_not_save_grid": True, - "mask": mask - } - ) + "do_not_save_samples": not img2imgreq.save_images, + "do_not_save_grid": not img2imgreq.save_images, + "mask": mask, + }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on @@ -232,21 +240,24 @@ class Api: args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine. args.pop('script_name', None) + send_images = args.pop('send_images', True) + args.pop('save_images', None) + with self.queue_lock: p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args) p.init_images = [decode_base64_to_image(x) for x in init_images] + p.outpath_grids = opts.outdir_img2img_grids + p.outpath_samples = opts.outdir_img2img_samples shared.state.begin() if script is not None: - p.outpath_grids = opts.outdir_img2img_grids - p.outpath_samples = opts.outdir_img2img_samples p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args processed = scripts.scripts_img2img.run(p, *p.script_args) else: processed = process_images(p) shared.state.end() - b64images = list(map(encode_pil_to_base64, processed.images)) + b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] if not img2imgreq.include_init_images: img2imgreq.init_images = None diff --git a/modules/api/models.py b/modules/api/models.py index cba43d3b..fa1c40df 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -14,8 +14,8 @@ API_NOT_ALLOWED = [ "outpath_samples", "outpath_grids", "sampler_index", - "do_not_save_samples", - "do_not_save_grid", + # "do_not_save_samples", + # "do_not_save_grid", "extra_generation_params", "overlay_images", "do_not_reload_embeddings", @@ -100,13 +100,29 @@ class PydanticModelGenerator: StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator( "StableDiffusionProcessingTxt2Img", StableDiffusionProcessingTxt2Img, - [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}] + [ + {"key": "sampler_index", "type": str, "default": "Euler"}, + {"key": "script_name", "type": str, "default": None}, + {"key": "script_args", "type": list, "default": []}, + {"key": "send_images", "type": bool, "default": True}, + {"key": "save_images", "type": bool, "default": False}, + ] ).generate_model() StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( "StableDiffusionProcessingImg2Img", StableDiffusionProcessingImg2Img, - [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}] + [ + {"key": "sampler_index", "type": str, "default": "Euler"}, + {"key": "init_images", "type": list, "default": None}, + {"key": "denoising_strength", "type": float, "default": 0.75}, + {"key": "mask", "type": str, "default": None}, + {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, + {"key": "script_name", "type": str, "default": None}, + {"key": "script_args", "type": list, "default": []}, + {"key": "send_images", "type": bool, "default": True}, + {"key": "save_images", "type": bool, "default": False}, + ] ).generate_model() class TextToImageResponse(BaseModel): @@ -267,3 +283,7 @@ class EmbeddingsResponse(BaseModel): class MemoryResponse(BaseModel): ram: dict = Field(title="RAM", description="System memory stats") cuda: dict = Field(title="CUDA", description="nVidia CUDA memory stats") + +class ScriptsList(BaseModel): + txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)") + img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)")
\ No newline at end of file diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 89dc23bf..cb367655 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -288,6 +288,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model settings_map = {}
+
+
infotext_to_setting_name_mapping = [
('Clip skip', 'CLIP_stop_at_last_layers', ),
('Conditional mask weight', 'inpainting_mask_weight'),
@@ -296,7 +298,11 @@ infotext_to_setting_name_mapping = [ ('Noise multiplier', 'initial_noise_multiplier'),
('Eta', 'eta_ancestral'),
('Eta DDIM', 'eta_ddim'),
- ('Discard penultimate sigma', 'always_discard_next_to_last_sigma')
+ ('Discard penultimate sigma', 'always_discard_next_to_last_sigma'),
+ ('UniPC variant', 'uni_pc_variant'),
+ ('UniPC skip type', 'uni_pc_skip_type'),
+ ('UniPC order', 'uni_pc_order'),
+ ('UniPC lower order final', 'uni_pc_lower_order_final'),
]
diff --git a/modules/images.py b/modules/images.py index 5b80c23e..7df2b08c 100644 --- a/modules/images.py +++ b/modules/images.py @@ -556,7 +556,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i elif image_to_save.mode == 'I;16':
image_to_save = image_to_save.point(lambda p: p * 0.0038910505836576).convert("RGB" if extension.lower() == ".webp" else "L")
- image_to_save.save(temp_file_path, format=image_format, quality=opts.jpeg_quality)
+ image_to_save.save(temp_file_path, format=image_format, quality=opts.jpeg_quality, lossless=opts.webp_lossless)
if opts.enable_pnginfo and info is not None:
exif_bytes = piexif.dump({
diff --git a/modules/modelloader.py b/modules/modelloader.py index fc3f6249..e351d808 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -6,7 +6,7 @@ from urllib.parse import urlparse from basicsr.utils.download_util import load_file_from_url from modules import shared -from modules.upscaler import Upscaler +from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone from modules.paths import script_path, models_path @@ -169,4 +169,8 @@ def load_upscalers(): scaler = cls(commandline_options.get(cmd_name, None)) datas += scaler.scalers - shared.sd_upscalers = datas + shared.sd_upscalers = sorted( + datas, + # 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 "" + ) diff --git a/modules/models/diffusion/uni_pc/__init__.py b/modules/models/diffusion/uni_pc/__init__.py new file mode 100644 index 00000000..e1265e3f --- /dev/null +++ b/modules/models/diffusion/uni_pc/__init__.py @@ -0,0 +1 @@ +from .sampler import UniPCSampler diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py new file mode 100644 index 00000000..bf346ff4 --- /dev/null +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -0,0 +1,100 @@ +"""SAMPLING ONLY.""" + +import torch + +from .uni_pc import NoiseScheduleVP, model_wrapper, UniPC +from modules import shared, devices + + +class UniPCSampler(object): + def __init__(self, model, **kwargs): + super().__init__() + self.model = model + to_torch = lambda x: x.clone().detach().to(torch.float32).to(model.device) + self.before_sample = None + self.after_sample = None + self.register_buffer('alphas_cumprod', to_torch(model.alphas_cumprod)) + + def register_buffer(self, name, attr): + if type(attr) == torch.Tensor: + if attr.device != devices.device: + attr = attr.to(devices.device) + setattr(self, name, attr) + + def set_hooks(self, before_sample, after_sample, after_update): + self.before_sample = before_sample + self.after_sample = after_sample + self.after_update = after_update + + @torch.no_grad() + def sample(self, + S, + batch_size, + shape, + conditioning=None, + callback=None, + normals_sequence=None, + img_callback=None, + quantize_x0=False, + eta=0., + mask=None, + x0=None, + temperature=1., + noise_dropout=0., + score_corrector=None, + corrector_kwargs=None, + verbose=True, + x_T=None, + log_every_t=100, + unconditional_guidance_scale=1., + unconditional_conditioning=None, + # this has to come in the same format as the conditioning, # e.g. as encoded tokens, ... + **kwargs + ): + if conditioning is not None: + if isinstance(conditioning, dict): + ctmp = conditioning[list(conditioning.keys())[0]] + while isinstance(ctmp, list): ctmp = ctmp[0] + cbs = ctmp.shape[0] + if cbs != batch_size: + print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") + + elif isinstance(conditioning, list): + for ctmp in conditioning: + if ctmp.shape[0] != batch_size: + print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") + + else: + if conditioning.shape[0] != batch_size: + print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}") + + # sampling + C, H, W = shape + size = (batch_size, C, H, W) + print(f'Data shape for UniPC sampling is {size}') + + device = self.model.betas.device + if x_T is None: + img = torch.randn(size, device=device) + else: + img = x_T + + ns = NoiseScheduleVP('discrete', alphas_cumprod=self.alphas_cumprod) + + # SD 1.X is "noise", SD 2.X is "v" + model_type = "v" if self.model.parameterization == "v" else "noise" + + model_fn = model_wrapper( + lambda x, t, c: self.model.apply_model(x, t, c), + ns, + model_type=model_type, + guidance_type="classifier-free", + #condition=conditioning, + #unconditional_condition=unconditional_conditioning, + guidance_scale=unconditional_guidance_scale, + ) + + uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=False, variant=shared.opts.uni_pc_variant, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=self.before_sample, after_sample=self.after_sample, after_update=self.after_update) + x = uni_pc.sample(img, steps=S, skip_type=shared.opts.uni_pc_skip_type, method="multistep", order=shared.opts.uni_pc_order, lower_order_final=shared.opts.uni_pc_lower_order_final) + + return x.to(device), None diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py new file mode 100644 index 00000000..df63d1bc --- /dev/null +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -0,0 +1,856 @@ +import torch +import torch.nn.functional as F +import math + |