diff --git a/CHANGELOG.md b/CHANGELOG.md
index 12627f6bd..829902abe 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
# Change Log for SD.Next
-## Update for 2025-09-25
+## Update for 2025-09-28
- **Models**
- [WAN 2.2 14B VACE](https://huggingface.co/alibaba-pai/Wan2.2-VACE-Fun-A14B)
@@ -53,6 +53,18 @@
- **video** support for configurable multi-stage models such as WAN-2.2-14B
- **video** new LTX model selection
- replace `pynvml` with `nvidia-ml-py` for gpu monitoring
+ - update **loopback** script with radon seed option, thanks @rabanti
+ - **vae** slicing enable for lowvram/medvram, tiling for lowvram, both disabled otherwise
+ - **attention** remove split-attention and add explicitly attention slicing enable/disable option
+ enable in *settings -> compute settings*
+ can be combined with sdp, enabling may improve stability when used on iGPU or shared memory systems
+- **Experimental**
+ - `new` command line flag enables new `pydantic` and `albumentations` packages
+ - **modular pipelines**: enable in *settings -> model options*
+ only compatible with some pipelines, invalidates preview generation
+ - **modular guiders**: automatically used for compatible pipelines when *modular pipelines* is enabled
+ allows for using many different guidance methods:
+ *CFG, CFGZero, PAG, APG, SLG, SEG, TCFG, FDG*
- **Fixes**
- ui: fix image metadata display when switching selected image in control tab
- framepack: add explicit hf-login before framepack load
diff --git a/installer.py b/installer.py
index ea7f5b496..1932a20af 100644
--- a/installer.py
+++ b/installer.py
@@ -977,10 +977,7 @@ def check_torch():
if not args.ignore:
sys.exit(1)
if rocm.is_installed:
- if sys.platform == "win32": # CPU, DirectML, ZLUDA
- rocm.conceal()
- elif rocm.is_wsl: # ROCm WSL
- rocm.preload_hsa_runtime()
+ rocm.postinstall()
if args.version:
return
if not args.skip_all:
diff --git a/javascript/guidance.js b/javascript/guidance.js
new file mode 100644
index 000000000..11c2430d3
--- /dev/null
+++ b/javascript/guidance.js
@@ -0,0 +1,20 @@
+const guiders = {
+ None: '',
+ 'LSC: LayerSkipConfig': 'https://github.com/huggingface/diffusers/blob/041501aea92919c9c7f36e189fc9cf7d865ebb96/src/diffusers/hooks/layer_skip.py#L41',
+ 'CFG: ClassifierFreeGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.ClassifierFreeGuidance',
+ 'Auto: AutoGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.AutoGuidance',
+ 'Zero: ClassifierFreeZeroStar': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.ClassifierFreeZeroStarGuidance',
+ 'PAG: PerturbedAttentionGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.PerturbedAttentionGuidance',
+ 'APG: AdaptiveProjectedGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.AdaptiveProjectedGuidance',
+ 'SLG: SkipLayerGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.SkipLayerGuidance',
+ 'SEG: SmoothedEnergyGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.SmoothedEnergyGuidance',
+ 'TCFG: TangentialClassifierFreeGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.TangentialClassifierFreeGuidance',
+ 'FDG: FrequencyDecoupledGuidance': 'https://huggingface.co/docs/diffusers/v0.35.1/en/api/modular_diffusers/guiders#diffusers.FrequencyDecoupledGuidance',
+};
+
+function getGuidanceDocs(guider) {
+ if (guider.label) guider = guider.label;
+ const url = guiders[guider];
+ log('getGuidanceDocs', guider, url);
+ if (url) window.open(url, '_blank');
+}
diff --git a/modules/control/run.py b/modules/control/run.py
index 586958a49..3f6b0f7be 100644
--- a/modules/control/run.py
+++ b/modules/control/run.py
@@ -255,6 +255,7 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
prompt: str = '', negative_prompt: str = '', styles: List[str] = [],
steps: int = 20, sampler_index: int = None,
seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1,
+ guidance_name: str = 'Default', guidance_scale: float = 6.0, guidance_rescale: float = 0.0, guidance_start: float = 0.0, guidance_stop: float = 1.0,
cfg_scale: float = 6.0, clip_skip: float = 1.0, image_cfg_scale: float = 6.0, diffusers_guidance_rescale: float = 0.7, pag_scale: float = 0.0, pag_adaptive: float = 0.5, cfg_end: float = 1.0,
vae_type: str = 'Full', tiling: bool = False, hidiffusion: bool = False,
detailer_enabled: bool = True, detailer_prompt: str = '', detailer_negative: str = '', detailer_steps: int = 10, detailer_strength: float = 0.3, detailer_resolution: int = 1024,
@@ -306,7 +307,13 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
seed_resize_from_h = seed_resize_from_h,
seed_resize_from_w = seed_resize_from_w,
denoising_strength = denoising_strength,
- # advanced
+ # modular guidance
+ guidance_name = guidance_name,
+ guidance_scale = guidance_scale,
+ guidance_rescale = guidance_rescale,
+ guidance_start = guidance_start,
+ guidance_stop = guidance_stop,
+ # legacy guidance
cfg_scale = cfg_scale,
cfg_end = cfg_end,
clip_skip = clip_skip,
@@ -314,6 +321,7 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
diffusers_guidance_rescale = diffusers_guidance_rescale,
pag_scale = pag_scale,
pag_adaptive = pag_adaptive,
+ # advanced
vae_type = vae_type,
tiling = tiling,
hidiffusion = hidiffusion,
diff --git a/modules/devices.py b/modules/devices.py
index abe979c17..a98b53d02 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -49,6 +49,10 @@ def has_xpu() -> bool:
return bool(hasattr(torch, 'xpu') and torch.xpu.is_available())
+def has_rocm() -> bool:
+ return bool(torch.version.hip is not None and torch.cuda.is_available())
+
+
def has_zluda() -> bool:
if not cuda_ok:
return False
diff --git a/modules/img2img.py b/modules/img2img.py
index 19da4b92f..4809d9fa0 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -161,10 +161,8 @@ def img2img(id_task: str, state: str, mode: int,
vae_type, tiling, hidiffusion,
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
n_iter, batch_size,
- cfg_scale, image_cfg_scale,
- diffusers_guidance_rescale,
- pag_scale, pag_adaptive,
- cfg_end,
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
+ cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
refiner_start,
clip_skip,
denoising_strength,
@@ -255,6 +253,11 @@ def img2img(id_task: str, state: str, mode: int,
batch_size=batch_size,
n_iter=n_iter,
steps=steps,
+ guidance_name=guidance_name,
+ guidance_scale=guidance_scale,
+ guidance_rescale=guidance_rescale,
+ guidance_start=guidance_start,
+ guidance_stop=guidance_stop,
cfg_scale=cfg_scale,
cfg_end=cfg_end,
clip_skip=clip_skip,
diff --git a/modules/modular_guiders.py b/modules/modular_guiders.py
new file mode 100644
index 000000000..556ad52b4
--- /dev/null
+++ b/modules/modular_guiders.py
@@ -0,0 +1,87 @@
+import diffusers
+from modules import shared, errors, processing
+
+
+# ['Default', 'CFG', 'Zero', 'PAG', 'APG', 'SLG', 'SEG', 'TCFG', 'FDG']
+guiders = {
+ # 'None': { 'cls': None, 'args': {}, },
+ 'Default': { 'cls': None, 'args': {}, },
+ 'CFG: ClassifierFreeGuidance': { 'cls': diffusers.ClassifierFreeGuidance, 'args': {} },
+ 'Auto: AutoGuidance': { 'cls': diffusers.AutoGuidance, 'args': { 'dropout': 1.0, 'auto_guidance_layers': [7, 8, 9], 'auto_guidance_config': None } },
+ 'Zero: ClassifierFreeZeroStar': { 'cls': diffusers.ClassifierFreeZeroStarGuidance, 'args': { 'zero_init_steps': 1 } },
+ 'PAG: PerturbedAttentionGuidance': { 'cls': diffusers.PerturbedAttentionGuidance, 'args': { 'perturbed_guidance_scale': 2.8, 'perturbed_guidance_start': 0.01, 'perturbed_guidance_stop': 0.2, 'perturbed_guidance_layers': [7, 8, 9], 'perturbed_guidance_config': None } },
+ 'APG: AdaptiveProjectedGuidance': { 'cls': diffusers.AdaptiveProjectedGuidance, 'args': { 'adaptive_projected_guidance_momentum': -1, 'adaptive_projected_guidance_rescale': 15.0 } },
+ 'SLG: SkipLayerGuidance': { 'cls': diffusers.SkipLayerGuidance, 'args': { 'skip_layer_guidance_scale': 2.8, 'skip_layer_guidance_start': 0.01, 'skip_layer_guidance_stop': 0.2, 'skip_layer_guidance_layers': [7, 8, 9], 'skip_layer_config': None } },
+ 'SEG: SmoothedEnergyGuidance': { 'cls': diffusers.SmoothedEnergyGuidance, 'args': { 'seg_guidance_scale': 3.0, 'seg_blur_sigma': 9999999.0, 'seg_blur_threshold_inf': 9999.0, 'seg_guidance_start': 0.0, 'seg_guidance_stop': 1.0, 'seg_guidance_layers': [7, 8, 9], 'seg_guidance_config': None } },
+ 'TCFG: TangentialClassifierFreeGuidance': { 'cls': diffusers.TangentialClassifierFreeGuidance, 'args': {} },
+ 'FDG: FrequencyDecoupledGuidance': { 'cls': diffusers.FrequencyDecoupledGuidance, 'args': { 'guidance_scales': [10.0, 5.0], 'parallel_weights': 1.0, 'guidance_rescale_space': "data" } },
+}
+base_args = {
+ 'guidance_scale': 6.0,
+ 'guidance_rescale': 0.0,
+ 'start': 0.0,
+ 'stop': 1.0,
+}
+
+
+def set_guider(p: processing.StableDiffusionProcessing):
+ guidance_name = p.guidance_name or 'Default'
+ if guidance_name not in guiders:
+ return
+
+ if guidance_name == 'Default':
+ if hasattr(shared.sd_model, 'default_guider'):
+ guider_info = shared.sd_model.default_guider
+ shared.sd_model.update_components(guider=guider_info)
+ else:
+ guider_info = shared.sd_model.get_component_spec("guider")
+ shared.sd_model.default_guider = guider_info
+ guider_cls = guider_info.type_hint
+ if guider_info is not None and guider_cls is not None and guider_info.config is not None:
+ guider_args = {k: v for k, v in guider_info.config.items() if not k.startswith('_') and v is not None}
+ else:
+ guider_args = {}
+ shared.log.info(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args}')
+ return
+ if guidance_name == 'None':
+ shared.sd_model.update_components(guider=None) # breaks the pipeline
+ shared.log.info(f'Guider: name={guidance_name}')
+ return
+
+ guider_info = guiders[guidance_name]
+ guider_cls = guider_info['cls']
+ guider_args = {}
+ for k, v in base_args.items():
+ if v is not None and v >= 0.0:
+ guider_args[k] = v
+ shared.log.warning('Guiders: partially implemented') # TODO: guiders
+ for k, v in guider_info['args'].items():
+ try:
+ if k is None:
+ pass
+ elif k.endswith('_layers') and isinstance(v, str):
+ guider_args[k] = [int(x.strip()) for x in v.split(',') if x.strip().isdigit()]
+ elif k.endswith('_config'):
+ # if lsc_enabled
+ # guider_args[k] = diffusers.LayerSkipConfig(...)
+ pass
+ elif isinstance(v, list) and len(v) > 0:
+ guider_args[k] = v
+ elif isinstance(v, int) and (v >= 0):
+ guider_args[k] = int(v)
+ elif isinstance(v, float) and (v >= 0.0):
+ guider_args[k] = float(v)
+ elif isinstance(v, str) and (len(v) > 0):
+ guider_args[k] = v
+ except Exception as e:
+ shared.log.error(f'Guiders: arg={k} value={v} error={e}')
+ errors.display(e, 'Guiders')
+ # guider_args.update(guider_info['args'])
+ if guider_cls is not None:
+ try:
+ guider_instance = guider_cls(**guider_args)
+ shared.log.info(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args}')
+ shared.sd_model.update_components(guider=guider_instance)
+ except Exception as e:
+ shared.log.error(f'Guider: name={guidance_name} cls={guider_cls.__name__} args={guider_args} {e}')
+ return
diff --git a/modules/processing_class.py b/modules/processing_class.py
index d0d634cfa..ddad4686e 100644
--- a/modules/processing_class.py
+++ b/modules/processing_class.py
@@ -36,7 +36,13 @@ class StableDiffusionProcessing:
sampler_name: str = None,
hr_sampler_name: str = None,
eta: float = None,
- # guidance
+ # modular guidance
+ guidance_name: str = 'Default',
+ guidance_scale: float = 6.0,
+ guidance_rescale: float = 0.0,
+ guidance_start: float = 0.0,
+ guidance_stop: float = 1.0,
+ # legacy guidance
cfg_scale: float = 6.0,
cfg_end: float = 1,
diffusers_guidance_rescale: float = 0.0,
@@ -247,6 +253,11 @@ class StableDiffusionProcessing:
self.do_not_save_grid = do_not_save_grid
self.override_settings_restore_afterwards = override_settings_restore_afterwards
self.eta = eta
+ self.guidance_name = guidance_name
+ self.guidance_scale = guidance_scale
+ self.guidance_rescale = guidance_rescale
+ self.guidance_start = guidance_start
+ self.guidance_stop = guidance_stop
self.cfg_scale = cfg_scale
self.cfg_end = cfg_end
self.diffusers_guidance_rescale = diffusers_guidance_rescale
diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py
index 6453516c0..277b5e1c5 100644
--- a/modules/processing_diffusers.py
+++ b/modules/processing_diffusers.py
@@ -102,6 +102,8 @@ def process_pre(p: processing.StableDiffusionProcessing):
modular_pipe = modular.convert_to_modular(shared.sd_model)
if modular_pipe is not None:
shared.sd_model = modular_pipe
+ from modules import modular_guiders
+ modular_guiders.set_guider(p)
timer.process.record('pre')
diff --git a/modules/processing_vae.py b/modules/processing_vae.py
index aca549a39..933af425f 100644
--- a/modules/processing_vae.py
+++ b/modules/processing_vae.py
@@ -173,7 +173,7 @@ def full_vae_decode(latents, model):
log_debug(f'VAE memory: {shared.mem_mon.read()}')
vae_name = os.path.splitext(os.path.basename(sd_vae.loaded_vae_file))[0] if sd_vae.loaded_vae_file is not None else "default"
vae_scale_factor = sd_vae.get_vae_scale_factor(model)
- shared.log.debug(f'Decode: vae="{vae_name}" scale={vae_scale_factor} upcast={upcast} slicing={getattr(model.vae, "use_slicing", None)} tiling={getattr(model.vae, "use_tiling", None)} latents={list(latents.shape)}:{latents.device}:{latents.dtype} time={t1-t0:.3f}')
+ shared.log.debug(f'Decode: vae="{vae_name}" scale={vae_scale_factor} upcast={upcast} slicing={getattr(model.vae, "use_slicing", None)} tiling={getattr(model.vae, "use_tiling", None)} latents={list(latents.shape)}:{latents.device} dtype={latents.dtype} time={t1-t0:.3f}')
return decoded
@@ -221,7 +221,7 @@ def taesd_vae_decode(latents):
else:
decoded = sd_vae_taesd.decode(latents)
t1 = time.time()
- shared.log.debug(f'Decode: vae="taesd" latents={latents.shape}:{latents.dtype}:{latents.device} time={t1-t0:.3f}')
+ shared.log.debug(f'Decode: vae="taesd" latents={latents.shape}:{latents.device} dtype={latents.dtype} time={t1-t0:.3f}')
return decoded
diff --git a/modules/rocm.py b/modules/rocm.py
index 3ffff069a..000eb039f 100644
--- a/modules/rocm.py
+++ b/modules/rocm.py
@@ -5,6 +5,7 @@ import shutil
import subprocess
from typing import Union, List
from enum import Enum
+from functools import wraps
def resolve_link(path_: str) -> str:
@@ -28,17 +29,6 @@ def load_library_global(path_: str):
ctypes.CDLL(path_, mode=ctypes.RTLD_GLOBAL)
-def conceal():
- os.environ.pop("ROCM_HOME", None)
- os.environ.pop("ROCM_PATH", None)
- paths = os.environ["PATH"].split(";")
- paths_no_rocm = []
- for path_ in paths:
- if "rocm" not in path_.lower():
- paths_no_rocm.append(path_)
- os.environ["PATH"] = ";".join(paths_no_rocm)
-
-
class Environment:
pass
@@ -117,7 +107,7 @@ class Agent:
return "gfx94X-dcgpu"
if self.gfx_version == 0x950:
return "gfx950-dcgpu"
- raise Exception(f"Unsupported GPU architecture: {self.name}")
+ raise RuntimeError(f"Unsupported GPU architecture: {self.name}")
def get_gfx_version(self) -> Union[str, None]:
if self.gfx_version >= 0x1100 and self.gfx_version < 0x1200:
@@ -200,10 +190,10 @@ def get_version() -> str:
return f'{arr[0]}.{arr[1]}' if len(arr) >= 2 else None
else:
# If rocm-sdk package is installed, the hip library may be used by PyTorch.
- version = ctypes.c_int()
- environment.hip.hipRuntimeGetVersion(ctypes.byref(version))
- major = version.value // 10000000
- minor = (version.value // 100000) % 100
+ ver = ctypes.c_int()
+ environment.hip.hipRuntimeGetVersion(ctypes.byref(ver))
+ major = ver.value // 10000000
+ minor = (ver.value // 100000) % 100
#patch = version.value % 100000
return f"{major}.{minor}"
@@ -240,6 +230,50 @@ if sys.platform == "win32":
del hip
return agents
+ def postinstall():
+ import torch
+ if torch.version.hip is None:
+ os.environ.pop("ROCM_HOME", None)
+ os.environ.pop("ROCM_PATH", None)
+ paths = os.environ["PATH"].split(";")
+ paths_no_rocm = []
+ for path_ in paths:
+ if "rocm" not in path_.lower():
+ paths_no_rocm.append(path_)
+ os.environ["PATH"] = ";".join(paths_no_rocm)
+ return
+
+ def rocm_init():
+ try:
+ import torch
+ import numpy as np
+
+ cholesky_ex_gpu = torch.linalg.cholesky_ex
+ @wraps(cholesky_ex_gpu)
+ def cholesky_ex(A: torch.Tensor, upper=False, check_errors=False, out=None) -> torch.return_types.linalg_cholesky_ex:
+ assert not check_errors
+ return_device = A.device
+ L = torch.from_numpy(np.linalg.cholesky(A.to("cpu").numpy(), upper=upper)).to(return_device)
+ info = torch.tensor(0, dtype=torch.int32, device=return_device)
+ if out is not None:
+ out[0].copy_(L)
+ out[1].copy_(info)
+ return torch.return_types.linalg_cholesky_ex((L, info), {})
+ torch.linalg.cholesky_ex = cholesky_ex
+
+ cholesky_gpu = torch.linalg.cholesky
+ @wraps(cholesky_gpu)
+ def cholesky(A: torch.Tensor, upper=False, out=None) -> torch.Tensor:
+ return_device = A.device
+ L = torch.from_numpy(np.linalg.cholesky(A.to("cpu").numpy(), upper=upper)).to(return_device)
+ if out is not None:
+ out.copy_(L)
+ return L
+ torch.linalg.cholesky = cholesky
+ except Exception as e:
+ return False, e
+ return True, None
+
is_wsl: bool = False
else:
def get_agents() -> List[Agent]:
@@ -251,15 +285,19 @@ else:
agents = [x.strip().split(" ")[-1] for x in agents if x.startswith(' Name:') and "CPU" not in x]
return [Agent(x) for x in agents]
- def preload_hsa_runtime():
- try:
- if shutil.which("conda") is not None:
- # Preload stdc++ library. This will bypass Anaconda stdc++ library.
- load_library_global("/lib/x86_64-linux-gnu/libstdc++.so.6")
- # Preload rocr4wsl. The user don't have to replace the library file.
- load_library_global("/opt/rocm/lib/libhsa-runtime64.so")
- except OSError:
- pass
+ def postinstall():
+ if is_wsl:
+ try:
+ if shutil.which("conda") is not None:
+ # Preload stdc++ library. This will bypass Anaconda stdc++ library.
+ load_library_global("/lib/x86_64-linux-gnu/libstdc++.so.6")
+ # Preload rocr4wsl. The user don't have to replace the library file.
+ load_library_global("/opt/rocm/lib/libhsa-runtime64.so")
+ except OSError:
+ pass
+
+ def rocm_init():
+ return True, None
is_wsl: bool = os.environ.get('WSL_DISTRO_NAME', 'unknown' if spawn('wslpath -w /') else None) is not None
environment = None
@@ -268,7 +306,7 @@ is_installed = False
version = None
def refresh():
- global environment, blaslt_tensile_libpath, is_installed, version
+ global environment, blaslt_tensile_libpath, is_installed, version # pylint: disable=global-statement
environment = find()
if environment is not None:
if isinstance(environment, ROCmEnvironment):
diff --git a/modules/sd_hijack_vae.py b/modules/sd_hijack_vae.py
index edd8427e6..2563ccfed 100644
--- a/modules/sd_hijack_vae.py
+++ b/modules/sd_hijack_vae.py
@@ -18,7 +18,7 @@ def hijack_vae_decode(*args, **kwargs):
latents = args[0].to(device=devices.device, dtype=shared.sd_model.vae.dtype) # upcast to vae dtype
res = shared.sd_model.vae.orig_decode(latents, *args[1:], **kwargs)
t1 = time.time()
- shared.log.debug(f'Decode: vae={shared.sd_model.vae.__class__.__name__} slicing={getattr(shared.sd_model.vae, "use_slicing", None)} tiling={getattr(shared.sd_model.vae, "use_tiling", None)} latents={list(latents.shape)}:{latents.device}:{latents.dtype} time={t1-t0:.3f}')
+ shared.log.debug(f'Decode: vae={shared.sd_model.vae.__class__.__name__} slicing={getattr(shared.sd_model.vae, "use_slicing", None)} tiling={getattr(shared.sd_model.vae, "use_tiling", None)} latents={list(latents.shape)}:{latents.device} dtype={latents.dtype} time={t1-t0:.3f}')
else:
res = shared.sd_model.vae.orig_decode(*args, **kwargs)
except Exception as e:
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 9b9ec7d68..e759ac56f 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -1070,17 +1070,19 @@ def set_diffusers_attention(pipe, quiet:bool=False):
pipe.enable_xformers_memory_efficient_attention()
else:
shared.log.warning(f"Attention: xFormers is not compatible with {pipe.__class__.__name__}")
- elif shared.opts.cross_attention_optimization == "Split attention":
- if hasattr(pipe, "enable_attention_slicing"):
- pipe.enable_attention_slicing()
- else:
- shared.log.warning(f"Attention: Split attention is not compatible with {pipe.__class__.__name__}")
elif shared.opts.cross_attention_optimization == "Batch matrix-matrix":
set_attn(pipe, p.AttnProcessor(), name="Batch matrix-matrix")
elif shared.opts.cross_attention_optimization == "Dynamic Attention BMM":
from modules.sd_hijack_dynamic_atten import DynamicAttnProcessorBMM
set_attn(pipe, DynamicAttnProcessorBMM(), name="Dynamic Attention BMM")
+ if shared.opts.attention_slicing != "Default" and hasattr(pipe, "enable_attention_slicing") and hasattr(pipe, "disable_attention_slicing"):
+ if shared.opts.attention_slicing:
+ pipe.enable_attention_slicing()
+ else:
+ pipe.disable_attention_slicing()
+ shared.log.debug(f"Attention: slicing={shared.opts.attention_slicing}")
+
pipe.current_attn_name = shared.opts.cross_attention_optimization
diff --git a/modules/sdnq/common.py b/modules/sdnq/common.py
index ecd06a653..783a7ab2f 100644
--- a/modules/sdnq/common.py
+++ b/modules/sdnq/common.py
@@ -44,7 +44,7 @@ allowed_types = linear_types + conv_types + conv_transpose_types
if use_torch_compile:
torch._dynamo.config.cache_size_limit = max(8192, torch._dynamo.config.cache_size_limit)
torch._dynamo.config.accumulated_recompile_limit = max(8192, torch._dynamo.config.accumulated_recompile_limit)
- compile_func = partial(torch.compile, fullgraph=True, dynamic=False)
+ compile_func = partial(torch.compile, fullgraph=True)
else:
def compile_func(fn, **kwargs): # pylint: disable=unused-argument
return fn
diff --git a/modules/shared.py b/modules/shared.py
index 78ff5ac0c..8dcf8f26d 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -83,6 +83,11 @@ elif cmd_opts.use_directml:
ok, e = directml_init()
if not ok:
log.error(f'DirectML initialization failed: {e}')
+elif cmd_opts.use_rocm or devices.has_rocm():
+ from modules.rocm import rocm_init
+ ok, e = rocm_init()
+ if not ok:
+ log.error(f'ROCm initialization failed: {e}')
devices.backend = devices.get_backend(cmd_opts)
devices.device = devices.get_optimal_device()
mem_stat = memory_stats()
@@ -251,8 +256,8 @@ options_templates.update(options_section(('vae_encoder', "Variational Auto Encod
"sd_vae": OptionInfo("Automatic", "VAE model", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
"diffusers_vae_upcast": OptionInfo("default", "VAE upcasting", gr.Radio, {"choices": ['default', 'true', 'false']}),
"no_half_vae": OptionInfo(False if not cmd_opts.use_openvino else True, "Full precision (--no-half-vae)"),
- "diffusers_vae_slicing": OptionInfo(True, "VAE slicing", gr.Checkbox),
- "diffusers_vae_tiling": OptionInfo(cmd_opts.lowvram or cmd_opts.medvram, "VAE tiling", gr.Checkbox),
+ "diffusers_vae_slicing": OptionInfo(cmd_opts.lowvram or cmd_opts.medvram, "VAE slicing", gr.Checkbox),
+ "diffusers_vae_tiling": OptionInfo(cmd_opts.lowvram, "VAE tiling", gr.Checkbox),
"diffusers_vae_tile_size": OptionInfo(0, "VAE tile size", gr.Slider, {"minimum": 0, "maximum": 4096, "step": 8 }),
"diffusers_vae_tile_overlap": OptionInfo(0.25, "VAE tile overlap", gr.Slider, {"minimum": 0, "maximum": 0.95, "step": 0.05 }),
"remote_vae_type": OptionInfo('raw', "Remote VAE image type", gr.Dropdown, {"choices": ['raw', 'jpg', 'png']}),
@@ -285,6 +290,8 @@ options_templates.update(options_section(('cuda', "Compute Settings"), {
"cross_attention_sep": OptionInfo("Cross Attention
", "", gr.HTML),
"cross_attention_optimization": OptionInfo(startup_cross_attention, "Attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention()}),
+ "attention_": OptionInfo("Cross Attention
", "", gr.HTML),
+ "attention_slicing": OptionInfo('Default', "Attention slicing", gr.CheckboxGroup, {"choices": ['Default', 'Enabled', 'Disabled']}),
"sdp_options": OptionInfo(startup_sdp_options, "SDP options", gr.CheckboxGroup, {"choices": startup_sdp_choices}),
"xformers_options": OptionInfo(['Flash attention'], "xFormers options", gr.CheckboxGroup, {"choices": ['Flash attention'] }),
"dynamic_attention_slice_rate": OptionInfo(0.5, "Dynamic Attention slicing rate in GB", gr.Slider, {"minimum": 0.01, "maximum": max(gpu_memory,4), "step": 0.01}),
diff --git a/modules/shared_items.py b/modules/shared_items.py
index 8eac5e070..f4d98e955 100644
--- a/modules/shared_items.py
+++ b/modules/shared_items.py
@@ -120,7 +120,6 @@ def list_crossattention():
"Scaled-Dot-Product",
"xFormers",
"Batch matrix-matrix",
- "Split attention",
"Dynamic Attention BMM"
]
diff --git a/modules/txt2img.py b/modules/txt2img.py
index 3397d4fe9..08d4f1bf2 100644
--- a/modules/txt2img.py
+++ b/modules/txt2img.py
@@ -14,6 +14,7 @@ def txt2img(id_task, state,
vae_type, tiling, hidiffusion,
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
n_iter, batch_size,
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
clip_skip,
seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
@@ -55,6 +56,11 @@ def txt2img(id_task, state,
batch_size=batch_size,
n_iter=n_iter,
steps=steps,
+ guidance_name=guidance_name,
+ guidance_scale=guidance_scale,
+ guidance_rescale=guidance_rescale,
+ guidance_start=guidance_start,
+ guidance_stop=guidance_stop,
cfg_scale=cfg_scale,
image_cfg_scale=image_cfg_scale,
diffusers_guidance_rescale=diffusers_guidance_rescale,
diff --git a/modules/ui_control.py b/modules/ui_control.py
index a1c77848d..3f43701af 100644
--- a/modules/ui_control.py
+++ b/modules/ui_control.py
@@ -2,7 +2,8 @@ import os
import time
import gradio as gr
from modules.control import unit
-from modules import errors, shared, progress, ui_common, ui_sections, generation_parameters_copypaste, call_queue, scripts_manager, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
+from modules import errors, shared, progress, generation_parameters_copypaste, call_queue, scripts_manager, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
+from modules import ui_common, ui_sections, ui_guidance
from modules import ui_control_helpers as helpers
@@ -156,7 +157,7 @@ def create_ui(_blocks: gr.Blocks=None):
mask_controls = masking.create_segment_ui()
- cfg_scale, image_cfg_scale, guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('control')
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('control')
vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('control')
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('control')
@@ -274,7 +275,8 @@ def create_ui(_blocks: gr.Blocks=None):
prompt, negative, styles,
steps, sampler_index,
seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
- cfg_scale, clip_skip, image_cfg_scale, guidance_rescale, pag_scale, pag_adaptive, cfg_end, vae_type, tiling, hidiffusion,
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
+ cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end, vae_type, tiling, hidiffusion,
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio,
resize_mode_before, resize_name_before, resize_context_before, width_before, height_before, scale_by_before, selected_scale_tab_before,
@@ -354,14 +356,19 @@ def create_ui(_blocks: gr.Blocks=None):
(mask_controls[4], "Mask erode"),
(mask_controls[5], "Mask dilate"),
(mask_controls[6], "Mask auto"),
+ # guidance
+ (guidance_name, "Guidance"),
+ (guidance_scale, "Guidance scale"),
+ (guidance_rescale, "Guidance rescale"),
+ (guidance_start, "Guidance start"),
+ (guidance_stop, "Guidance stop"),
# advanced
- (cfg_scale, "Guidance scale"),
(cfg_scale, "CFG scale"),
(cfg_end, "CFG end"),
(clip_skip, "Clip skip"),
(image_cfg_scale, "Image CFG scale"),
(image_cfg_scale, "Hires CFG scale"),
- (guidance_rescale, "CFG rescale"),
+ (diffusers_guidance_rescale, "CFG rescale"),
(vae_type, "VAE type"),
(tiling, "Tiling"),
(hidiffusion, "HiDiffusion"),
diff --git a/modules/ui_guidance.py b/modules/ui_guidance.py
new file mode 100644
index 000000000..3f3b3f8f3
--- /dev/null
+++ b/modules/ui_guidance.py
@@ -0,0 +1,125 @@
+import gradio as gr
+from modules import shared, modular_guiders
+from modules import ui_symbols, ui_components
+
+
+def create_guidance_inputs(tab):
+ with gr.Accordion(open=False, label='Guidance', elem_id=f"{tab}_guidance", elem_classes=["small-accordion"]):
+ with gr.Group():
+
+ with gr.Row(elem_id=f"{tab}_guider_row", elem_classes=['flexbox'], visible=shared.opts.model_modular_enable):
+ guidance_name = gr.Dropdown(choices=list(modular_guiders.guiders.keys()), value='Default', label='Guider', elem_id=f"{tab}_guider")
+ guidance_btn = ui_components.ToolButton(value=ui_symbols.book, elem_id=f"{tab}_guider_docs")
+ guidance_btn.click(fn=None, _js='getGuidanceDocs', inputs=[guidance_name], outputs=[])
+ with gr.Row(visible=shared.opts.model_modular_enable):
+ guidance_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_guidance_scale")
+ guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance rescale', value=0.0, elem_id=f"{tab}_guidance_rescale")
+ with gr.Row(visible=shared.opts.model_modular_enable):
+ guidance_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance start', value=0.0, elem_id=f"{tab}_guidance_start")
+ guidance_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance stop', value=1.0, elem_id=f"{tab}_guidance_stop")
+ guidance_args = [guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop]
+
+ lsc_group = gr.Accordion(open=False, label='Layer skip guidance', elem_classes=["small-accordion"], visible=shared.opts.model_modular_enable)
+ with lsc_group:
+ with gr.Row():
+ guidance_lsc_enabled = gr.Checkbox(label='Enable LayerSkipConfig', value=False)
+ guidance_lsc_label = gr.Label(value='LSC: LayerSkipConfig', elem_id=f"{tab}_lsc_label", visible=False)
+ guidance_lsc_btn = ui_components.ToolButton(value=ui_symbols.book, elem_id=f"{tab}_lsc_docs", elem_classes=["guidance-docs"])
+ guidance_lsc_btn.click(fn=None, _js='getGuidanceDocs', inputs=[guidance_lsc_label], outputs=[])
+ with gr.Row():
+ guidance_lsc_indices = gr.Textbox(label='LSC layer indices', value='1, 2, 3', placeholder='Comma-separated layer indices to skip')
+ with gr.Row():
+ guidance_lsc_fqn = gr.Textbox(label='LSC fully qualified name', value='transformer_blocks', placeholder='Fully qualified name of the layer stack')
+ with gr.Row():
+ guidance_lsc_skip_attention = gr.Checkbox(label='LSC skip attention blocks', value=True)
+ guidance_lsc_skip_ff = gr.Checkbox(label='LSC skip feed-forward blocks', value=True)
+ guidance_lsc_skip_attention_scores = gr.Checkbox(label='LSC skip attention scores', value=False)
+ with gr.Row():
+ guidance_lsc_dropout = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='LSC dropout rate', value=1.0)
+ lsc_args = [guidance_lsc_enabled, guidance_lsc_indices, guidance_lsc_fqn, guidance_lsc_skip_attention, guidance_lsc_skip_ff, guidance_lsc_skip_attention_scores, guidance_lsc_dropout]
+
+ auto_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with auto_group:
+ guidance_auto_dropout = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='AutoGuidance dropout', value=0.1)
+ guidance_auto_layers = gr.Textbox(label='AutoGuidance layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
+ guidance_auto_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='AutoGuidance config')
+ guidance_auto_args = [guidance_auto_dropout, guidance_auto_layers, guidance_auto_config]
+
+ zero_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with zero_group:
+ guidance_zero_init_steps = gr.Slider(minimum=0, maximum=10, step=1, label='ZeroStar init steps', value=1)
+ guidance_zero_args = [guidance_zero_init_steps]
+
+ pag_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with pag_group:
+ guidance_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='PAG scale', value=2.8)
+ guidance_pag_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='PAG start', value=0.01)
+ guidance_pag_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='PAG stop', value=0.2)
+ guidance_pag_layers = gr.Textbox(label='PAG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
+ guidance_pag_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='PAG config')
+ guidance_pag_args = [guidance_pag_scale, guidance_pag_start, guidance_pag_stop, guidance_pag_layers, guidance_pag_config]
+
+ apg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with apg_group:
+ guidance_apg_momentum = gr.Slider(minimum=-1.0, maximum=1.0, step=0.05, label='APG momentum', value=-1.0)
+ guidance_apg_rescale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='APG rescale', value=15.0)
+ guidance_apg_args = [guidance_apg_momentum, guidance_apg_rescale]
+
+ slg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with slg_group:
+ guidance_slg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='SLG scale', value=2.8)
+ guidance_slg_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SLG start', value=0.01)
+ guidance_slg_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SLG stop', value=0.2)
+ guidance_slg_layers = gr.Textbox(label='SLG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
+ guidance_slg_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='SLG config')
+ guidance_slg_args = [guidance_slg_scale, guidance_slg_start, guidance_slg_stop, guidance_slg_layers, guidance_slg_config]
+
+ seg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with seg_group:
+ guidance_seg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='SEG scale', value=3.0)
+ guidance_seg_blur_sigma = gr.Number(label='SEG blur sigma', value=9999999.0)
+ guidance_seg_blur_threshold_inf = gr.Number(label='SEG blur threshold inf', value=9999.0)
+ guidance_seg_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SEG start', value=0.0)
+ guidance_seg_stop = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='SEG stop', value=1.0)
+ guidance_seg_layers = gr.Textbox(label='SEG layers', value='7, 8, 9', placeholder='Comma-separated layer indices, e.g. 7,8,9')
+ guidance_seg_config = gr.Dropdown(choices=[None, 'config1', 'config2'], value=None, label='SEG config')
+ guidance_seg_args = [guidance_seg_scale, guidance_seg_blur_sigma, guidance_seg_blur_threshold_inf, guidance_seg_start, guidance_seg_stop, guidance_seg_layers, guidance_seg_config]
+
+ tcfg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with tcfg_group:
+ pass
+
+ fdg_group = gr.Accordion(open=True, label='Advanced guidance params', elem_classes=["small-accordion"], visible=False)
+ with fdg_group:
+ guidance_fdg_scales = gr.Textbox(label='FDG scales', value='10.0, 5.0', placeholder='Comma-separated scales, e.g. 10.0,5.0')
+ guidance_fdg_weights = gr.Textbox(label='FDG weights', value='1.0', placeholder='Single float or comma-separated weights, e.g. 1.0 or 1.0,0.5')
+ guidance_fdg_rescale_space = gr.Dropdown(choices=['data', 'freq'], value='data', label='FDG rescale space')
+ guidance_fdg_args = [guidance_fdg_scales, guidance_fdg_weights, guidance_fdg_rescale_space]
+
+ def adv_visibility(guidance_name):
+ return [
+ gr.update(visible=guidance_name.startswith('Auto')),
+ gr.update(visible=guidance_name.startswith('Zero')),
+ gr.update(visible=guidance_name.startswith('PAG')),
+ gr.update(visible=guidance_name.startswith('APG')),
+ gr.update(visible=guidance_name.startswith('SLG')),
+ gr.update(visible=guidance_name.startswith('SEG')),
+ gr.update(visible=guidance_name.startswith('TCFG')),
+ gr.update(visible=guidance_name.startswith('FDG')),
+ ]
+ guidance_name.change(fn=adv_visibility, inputs=[guidance_name], outputs=[auto_group, zero_group, pag_group, apg_group, slg_group, seg_group, tcfg_group, fdg_group])
+
+ gr.HTML(value='
Fallback guidance
', visible=shared.opts.model_modular_enable, elem_id=f"{tab}_guidance_note")
+ with gr.Row(elem_id=f"{tab}_cfg_row", elem_classes=['flexbox']):
+ cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_cfg_scale")
+ cfg_end = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance end', value=1.0, elem_id=f"{tab}_cfg_end")
+ with gr.Row():
+ image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Refine guidance', value=6.0, elem_id=f"{tab}_image_cfg_scale")
+ diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Rescale guidance', value=0.0, elem_id=f"{tab}_image_cfg_rescale")
+ with gr.Row():
+ diffusers_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='Attention guidance', value=0.0, elem_id=f"{tab}_pag_scale")
+ diffusers_pag_adaptive = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Adaptive scaling', value=0.5, elem_id=f"{tab}_pag_adaptive")
+
+ _modular_args = guidance_args + lsc_args + guidance_auto_args + guidance_zero_args + guidance_pag_args + guidance_apg_args + guidance_slg_args + guidance_seg_args + guidance_fdg_args
+ standard_args = [cfg_scale, image_cfg_scale, diffusers_guidance_rescale, diffusers_pag_scale, diffusers_pag_adaptive, cfg_end]
+ return guidance_args + standard_args
diff --git a/modules/ui_img2img.py b/modules/ui_img2img.py
index 7e7db44cb..cf1324484 100644
--- a/modules/ui_img2img.py
+++ b/modules/ui_img2img.py
@@ -1,11 +1,11 @@
-import os
-from PIL import Image
import gradio as gr
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
-from modules import timer, shared, ui_common, ui_sections, generation_parameters_copypaste, processing_vae
+from modules import timer, shared, call_queue, generation_parameters_copypaste, processing_vae
+from modules import ui_common, ui_sections, ui_guidance
def process_interrogate(mode, ii_input_files, ii_input_dir, ii_output_dir, *ii_singles):
+ import os
+ from PIL import Image
from modules.interrogate.interrogate import interrogate
mode = int(mode)
if mode in {0, 1, 3, 4}:
@@ -132,7 +132,7 @@ def create_ui():
denoising_strength = gr.Slider(minimum=0.00, maximum=0.99, step=0.01, label='Denoising strength', value=0.30, elem_id="img2img_denoising_strength")
refiner_start = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Denoise start', value=0.0, elem_id="img2img_refiner_start")
- cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('img2img')
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('img2img')
vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('img2img')
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('img2img')
enable_hr, hr_sampler_index, hr_denoising_strength, hr_resize_mode, hr_resize_context, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, hr_refiner_start, refiner_prompt, refiner_negative = ui_sections.create_hires_inputs('img2img')
@@ -177,8 +177,8 @@ def create_ui():
vae_type, tiling, hidiffusion,
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
batch_count, batch_size,
- cfg_scale, image_cfg_scale,
- diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
+ cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
refiner_start,
clip_skip,
denoising_strength,
@@ -194,7 +194,7 @@ def create_ui():
override_settings,
]
img2img_dict = dict(
- fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', ''], name='Image'),
+ fn=call_queue.wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', ''], name='Image'),
_js="submit_img2img",
inputs= img2img_args + img2img_script_inputs,
outputs=[
@@ -229,8 +229,8 @@ def create_ui():
)
interrogate_btn.click(fn=lambda *args: process_interrogate(*args), **interrogate_args)
- img2img_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_prompt], outputs=[img2img_token_counter], show_progress = False)
- img2img_negative_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_negative_prompt], outputs=[img2img_negative_token_counter], show_progress = False)
+ img2img_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_prompt], outputs=[img2img_token_counter], show_progress = False)
+ img2img_negative_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[img2img_negative_prompt], outputs=[img2img_negative_token_counter], show_progress = False)
ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery)
img2img_paste_fields = [
@@ -254,8 +254,13 @@ def create_ui():
(seed, "Seed"),
(subseed, "Variation seed"),
(subseed_strength, "Variation strength"),
+ # guidance
+ (guidance_name, "Guidance"),
+ (guidance_scale, "Guidance scale"),
+ (guidance_rescale, "Guidance rescale"),
+ (guidance_start, "Guidance start"),
+ (guidance_stop, "Guidance stop"),
# advanced
- (cfg_scale, "Guidance scale"),
(cfg_scale, "CFG scale"),
(cfg_end, "CFG end"),
(image_cfg_scale, "Image CFG scale"),
diff --git a/modules/ui_sections.py b/modules/ui_sections.py
index 829c502bd..683681cd5 100644
--- a/modules/ui_sections.py
+++ b/modules/ui_sections.py
@@ -146,21 +146,6 @@ def create_video_inputs(tab:str, show_always:bool=False):
return video_type, video_duration, video_loop, video_pad, video_interpolate
-def create_guidance_inputs(tab):
- with gr.Accordion(open=False, label="Guidance", elem_id=f"{tab}_guidance", elem_classes=["small-accordion"]):
- with gr.Group():
- with gr.Row(elem_id=f"{tab}_cfg_row", elem_classes=['flexbox']):
- cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Guidance scale', value=6.0, elem_id=f"{tab}_cfg_scale")
- cfg_end = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label='Guidance end', value=1.0, elem_id=f"{tab}_cfg_end")
- with gr.Row():
- image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Refine guidance', value=6.0, elem_id=f"{tab}_image_cfg_scale")
- diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Rescale guidance', value=0.0, elem_id=f"{tab}_image_cfg_rescale")
- with gr.Row():
- diffusers_pag_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.05, label='Attention guidance', value=0.0, elem_id=f"{tab}_pag_scale")
- diffusers_pag_adaptive = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Adaptive scaling', value=0.5, elem_id=f"{tab}_pag_adaptive")
- return cfg_scale, image_cfg_scale, diffusers_guidance_rescale, diffusers_pag_scale, diffusers_pag_adaptive, cfg_end
-
-
def create_advanced_inputs(tab):
with gr.Accordion(open=False, label="Advanced", elem_id=f"{tab}_advanced", elem_classes=["small-accordion"]):
with gr.Group():
diff --git a/modules/ui_txt2img.py b/modules/ui_txt2img.py
index 0fae0c606..6eccbdd82 100644
--- a/modules/ui_txt2img.py
+++ b/modules/ui_txt2img.py
@@ -1,7 +1,6 @@
import gradio as gr
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call
-from modules import timer, shared, ui_common, ui_sections, generation_parameters_copypaste, processing_vae, images
-from modules.ui_components import ToolButton # pylint: disable=unused-import
+from modules import timer, shared, call_queue, generation_parameters_copypaste, processing_vae, images
+from modules import ui_common, ui_sections, ui_guidance
def create_ui():
@@ -33,7 +32,7 @@ def create_ui():
with gr.Accordion(open=False, label="Samplers", elem_classes=["small-accordion"], elem_id="txt2img_sampler_group"):
ui_sections.create_sampler_options('txt2img')
seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = ui_sections.create_seed_inputs('txt2img')
- cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_sections.create_guidance_inputs('txt2img')
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop, cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end = ui_guidance.create_guidance_inputs('txt2img')
vae_type, tiling, hidiffusion, clip_skip = ui_sections.create_advanced_inputs('txt2img')
hdr_mode, hdr_brightness, hdr_color, hdr_sharpen, hdr_clamp, hdr_boundary, hdr_threshold, hdr_maximize, hdr_max_center, hdr_max_boundary, hdr_color_picker, hdr_tint_ratio = ui_sections.create_correction_inputs('txt2img')
enable_hr, hr_sampler_index, denoising_strength, hr_resize_mode, hr_resize_context, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative = ui_sections.create_hires_inputs('txt2img')
@@ -57,6 +56,7 @@ def create_ui():
vae_type, tiling, hidiffusion,
detailer_enabled, detailer_prompt, detailer_negative, detailer_steps, detailer_strength, detailer_resolution,
batch_count, batch_size,
+ guidance_name, guidance_scale, guidance_rescale, guidance_start, guidance_stop,
cfg_scale, image_cfg_scale, diffusers_guidance_rescale, pag_scale, pag_adaptive, cfg_end,
clip_skip,
seed, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
@@ -68,7 +68,7 @@ def create_ui():
override_settings,
]
txt2img_dict = dict(
- fn=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', ''], name='Text'),
+ fn=call_queue.wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', ''], name='Text'),
_js="submit_txt2img",
inputs=txt2img_args + txt2img_script_inputs,
outputs=[
@@ -106,8 +106,13 @@ def create_ui():
(seed, "Seed"),
(subseed, "Variation seed"),
(subseed_strength, "Variation strength"),
+ # guidance
+ (guidance_name, "Guidance"),
+ (guidance_scale, "Guidance scale"),
+ (guidance_rescale, "Guidance rescale"),
+ (guidance_start, "Guidance start"),
+ (guidance_stop, "Guidance stop"),
# advanced
- (cfg_scale, "Guidance scale"),
(cfg_scale, "CFG scale"),
(cfg_end, "CFG end"),
(clip_skip, "Clip skip"),
@@ -156,7 +161,7 @@ def create_ui():
txt2img_bindings = generation_parameters_copypaste.ParamBinding(paste_button=txt2img_paste, tabname="txt2img", source_text_component=txt2img_prompt, source_image_component=None)
generation_parameters_copypaste.register_paste_params_button(txt2img_bindings)
- txt2img_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_prompt], outputs=[txt2img_token_counter], show_progress = False)
- txt2img_negative_token_button.click(fn=wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_negative_prompt], outputs=[txt2img_negative_token_counter], show_progress = False)
+ txt2img_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_prompt], outputs=[txt2img_token_counter], show_progress = False)
+ txt2img_negative_token_button.click(fn=call_queue.wrap_queued_call(ui_common.update_token_counter), inputs=[txt2img_negative_prompt], outputs=[txt2img_negative_token_counter], show_progress = False)
ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
diff --git a/modules/windows_hip_ffi.py b/modules/windows_hip_ffi.py
index cc9e4a1e4..c612aa43d 100644
--- a/modules/windows_hip_ffi.py
+++ b/modules/windows_hip_ffi.py
@@ -1,6 +1,7 @@
import sys
if sys.platform == "win32":
+ import os
import ctypes
import ctypes.wintypes
@@ -15,8 +16,11 @@ if sys.platform == "win32":
def __init__(self):
ctypes.windll.kernel32.LoadLibraryA.restype = ctypes.wintypes.HMODULE
ctypes.windll.kernel32.LoadLibraryA.argtypes = [ctypes.c_char_p]
- # amdhip64.dll is a part of AMDGPU drivers
- self.handle = ctypes.windll.kernel32.LoadLibraryA(b"amdhip64.dll")
+ path = os.environ.get("windir", "C:\\Windows") + "\\System32\\amdhip64_6.dll"
+ if not os.path.isfile(path):
+ path = os.environ.get("windir", "C:\\Windows") + "\\System32\\amdhip64_7.dll"
+ assert os.path.isfile(path)
+ self.handle = ctypes.windll.kernel32.LoadLibraryA(path.encode('utf-8'))
ctypes.windll.kernel32.GetLastError.restype = ctypes.wintypes.DWORD
ctypes.windll.kernel32.GetLastError.argtypes = []
assert ctypes.windll.kernel32.GetLastError() == 0
@@ -28,10 +32,9 @@ if sys.platform == "win32":
ctypes.windll.kernel32.GetProcAddress(self.handle, b"hipGetDeviceProperties"))
def __del__(self):
- #ctypes.windll.kernel32.FreeLibrary.argtypes = [ctypes.wintypes.HMODULE]
- #ctypes.windll.kernel32.FreeLibrary(self.handle)
- # Hopefully it does not make conflicts with amdhip64_7.dll
- pass
+ # Hopefully this will prevent conflicts with amdhip64_7.dll from ROCm Python packages or HIP SDK
+ ctypes.windll.kernel32.FreeLibrary.argtypes = [ctypes.wintypes.HMODULE]
+ ctypes.windll.kernel32.FreeLibrary(self.handle)
def get_device_count(self):
count = ctypes.c_int()
diff --git a/modules/zluda_installer.py b/modules/zluda_installer.py
index 2922f196f..c6fb55c23 100644
--- a/modules/zluda_installer.py
+++ b/modules/zluda_installer.py
@@ -163,7 +163,7 @@ def load():
ctypes.windll.LoadLibrary(os.path.join(rocm.environment.path, 'bin', 'MIOpen.dll'))
ctypes.windll.LoadLibrary(os.path.join(path, 'cudnn64_9.dll'))
- def conceal():
+ def postinstall():
import torch
torch.version.hip = rocm.version
platform = sys.platform
@@ -176,4 +176,4 @@ def load():
def _join_rocm_home(*paths) -> str:
return os.path.join(cpp_extension.ROCM_HOME, *paths)
cpp_extension._join_rocm_home = _join_rocm_home # pylint: disable=protected-access
- rocm.conceal = conceal
+ rocm.postinstall = postinstall
diff --git a/scripts/loopback.py b/scripts/loopback.py
index a22b153a2..e24683ce6 100644
--- a/scripts/loopback.py
+++ b/scripts/loopback.py
@@ -1,4 +1,5 @@
import math
+import random
import gradio as gr
from modules import images, processing, scripts_manager
@@ -21,10 +22,12 @@ class Script(scripts_manager.Script):
final_denoising_strength = gr.Slider(minimum=0, maximum=1, step=0.01, label='Final strength', value=0.5, elem_id=self.elem_id("final_denoising_strength"))
with gr.Row():
denoising_curve = gr.Dropdown(label="Strength curve", choices=["Aggressive", "Linear", "Lazy"], value="Linear")
+ with gr.Row():
+ randomize_seed = gr.Checkbox(label="Randomize seed after each loop iteration", value=False)
- return [loops, final_denoising_strength, denoising_curve]
+ return [loops, final_denoising_strength, denoising_curve, randomize_seed]
- def run(self, p, loops, final_denoising_strength, denoising_curve): # pylint: disable=arguments-differ
+ def run(self, p, loops, final_denoising_strength, denoising_curve, randomize_seed): # pylint: disable=arguments-differ
processing.fix_seed(p)
initial_batch_count = p.n_iter
p.extra_generation_params['Loopback'] = final_denoising_strength
@@ -76,10 +79,14 @@ class Script(scripts_manager.Script):
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
+ if randomize_seed:
+ p.seed = random.randrange(4294967294)
+ p.all_seeds = [p.seed]
p.seed = processed.seed + 1 # why?
p.denoising_strength = calculate_denoising_strength(i + 1)
last_image = processed.images[0]
p.init_images = [last_image]
+ log.info(f'Loopback: iteration={i} seed={p.seed} curve={denoising_curve} strength={p.denoising_strength}:{final_denoising_strength}')
if initial_batch_count == 1:
history.append(last_image)
all_images.append(last_image)
diff --git a/scripts/xyz/xyz_grid_classes.py b/scripts/xyz/xyz_grid_classes.py
index 306b591f3..0836adbbf 100644
--- a/scripts/xyz/xyz_grid_classes.py
+++ b/scripts/xyz/xyz_grid_classes.py
@@ -20,6 +20,7 @@ from scripts.xyz.xyz_grid_shared import ( # pylint: disable=no-name-in-module, u
apply_lora,
apply_lora_strength,
apply_te,
+ apply_guidance,
apply_styles,
apply_upscaler,
apply_context,
@@ -223,6 +224,7 @@ axis_options = [
AxisOption("[Sampler] Shift", float, apply_setting("schedulers_shift")),
AxisOption("[Sampler] eta delta", float, apply_setting("eta_noise_seed_delta")),
AxisOption("[Sampler] eta multiplier", float, apply_setting("scheduler_eta")),
+ AxisOption("[Guidance] Guidance name", str, apply_guidance, choices=lambda: ['Default', 'CFG', 'Auto', 'Zero', 'PAG', 'APG', 'SLG', 'SEG', 'TCFG', 'FDG']),
AxisOption("[Refine] Upscaler", str, apply_field("hr_upscaler"), cost=0.3, choices=lambda: [x.name for x in shared.sd_upscalers]),
AxisOption("[Refine] Sampler", str, apply_hr_sampler_name, fmt=format_value_add_label, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
AxisOption("[Refine] Denoising strength", float, apply_field("denoising_strength")),
diff --git a/scripts/xyz/xyz_grid_shared.py b/scripts/xyz/xyz_grid_shared.py
index 0c95d14de..76d4df769 100644
--- a/scripts/xyz/xyz_grid_shared.py
+++ b/scripts/xyz/xyz_grid_shared.py
@@ -254,6 +254,13 @@ def apply_te(p, x, xs):
shared.log.debug(f'XYZ grid apply text-encoder: "{x}"')
+def apply_guidance(p, x, xs):
+ from modules.modular_guiders import guiders
+ guiders = list(guiders.keys())
+ p.guidance_name = [g for g in guiders if g.lower().startswith(x.lower())][0]
+ shared.log.debug(f'XYZ grid apply guidance: "{p.guidance_name}"')
+
+
def apply_styles(p: processing.StableDiffusionProcessingTxt2Img, x: str, _):
p.styles.extend(x.split(','))
shared.log.debug(f'XYZ grid apply style: "{x}"')
diff --git a/scripts/xyz_grid_on.py b/scripts/xyz_grid_on.py
index f79be6636..595536067 100644
--- a/scripts/xyz_grid_on.py
+++ b/scripts/xyz_grid_on.py
@@ -324,6 +324,7 @@ class Script(scripts_manager.Script):
def cell(x, y, z, ix, iy, iz):
if shared.state.interrupted:
+ shared.log.warning('XYZ grid: Interrupted')
return processing.Processed(p, [], p.seed, ""), 0
p.xyz = True
pc = copy(p)
diff --git a/wiki b/wiki
index bd9905932..77e5745f7 160000
--- a/wiki
+++ b/wiki
@@ -1 +1 @@
-Subproject commit bd990593287f36d4c76828a2db0eaa019ca0630f
+Subproject commit 77e5745f7a7b8ac2f9d029c6ebb83c954be56006