Merge branch 'main' into stalker-modular_controlnet

invokeai/backend/stable_diffusion/extensions/base.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from contextlib import contextmanager
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Callable, Dict, List
+from typing import TYPE_CHECKING, Callable, Dict, List, Optional
 
 import torch
 from diffusers import UNet2DConditionModel
@@ -56,5 +56,5 @@ class ExtensionBase:
         yield None
 
     @contextmanager
-    def patch_unet(self, state_dict: Dict[str, torch.Tensor], unet: UNet2DConditionModel):
+    def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
         yield None

invokeai/backend/stable_diffusion/extensions/freeu.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+from contextlib import contextmanager
+from typing import TYPE_CHECKING, Dict, Optional
+
+import torch
+from diffusers import UNet2DConditionModel
+
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase
+
+if TYPE_CHECKING:
+    from invokeai.app.shared.models import FreeUConfig
+
+
+class FreeUExt(ExtensionBase):
+    def __init__(
+        self,
+        freeu_config: FreeUConfig,
+    ):
+        super().__init__()
+        self._freeu_config = freeu_config
+
+    @contextmanager
+    def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
+        unet.enable_freeu(
+            b1=self._freeu_config.b1,
+            b2=self._freeu_config.b2,
+            s1=self._freeu_config.s1,
+            s2=self._freeu_config.s2,
+        )
+
+        try:
+            yield
+        finally:
+            unet.disable_freeu()

invokeai/backend/stable_diffusion/extensions/rescale_cfg.py

@@ -0,0 +1,36 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import torch
+
+from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
+
+if TYPE_CHECKING:
+    from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
+
+
+class RescaleCFGExt(ExtensionBase):
+    def __init__(self, rescale_multiplier: float):
+        super().__init__()
+        self._rescale_multiplier = rescale_multiplier
+
+    @staticmethod
+    def _rescale_cfg(total_noise_pred: torch.Tensor, pos_noise_pred: torch.Tensor, multiplier: float = 0.7):
+        """Implementation of Algorithm 2 from https://arxiv.org/pdf/2305.08891.pdf."""
+        ro_pos = torch.std(pos_noise_pred, dim=(1, 2, 3), keepdim=True)
+        ro_cfg = torch.std(total_noise_pred, dim=(1, 2, 3), keepdim=True)
+
+        x_rescaled = total_noise_pred * (ro_pos / ro_cfg)
+        x_final = multiplier * x_rescaled + (1.0 - multiplier) * total_noise_pred
+        return x_final
+
+    @callback(ExtensionCallbackType.POST_COMBINE_NOISE_PREDS)
+    def rescale_noise_pred(self, ctx: DenoiseContext):
+        if self._rescale_multiplier > 0:
+            ctx.noise_pred = self._rescale_cfg(
+                ctx.noise_pred,
+                ctx.positive_noise_pred,
+                self._rescale_multiplier,
+            )