Merge branch 'main' into refactor/model-manager-2

docker/.env.sample

@@ -11,5 +11,5 @@ INVOKEAI_ROOT=
 # HUGGING_FACE_HUB_TOKEN=
 
 ## optional variables specific to the docker setup.
-# GPU_DRIVER=cuda
+# GPU_DRIVER=cuda # or rocm
-# CONTAINER_UID=1000
+# CONTAINER_UID=1000

docker/Dockerfile

@@ -18,8 +18,8 @@ ENV INVOKEAI_SRC=/opt/invokeai
 ENV VIRTUAL_ENV=/opt/venv/invokeai
 
 ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-ARG TORCH_VERSION=2.0.1
+ARG TORCH_VERSION=2.1.0
-ARG TORCHVISION_VERSION=0.15.2
+ARG TORCHVISION_VERSION=0.16
 ARG GPU_DRIVER=cuda
 ARG TARGETPLATFORM="linux/amd64"
 # unused but available
@@ -35,7 +35,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
     if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
         extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
     elif [ "$GPU_DRIVER" = "rocm" ]; then \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.4.2"; \
+        extra_index_url_arg="--index-url https://download.pytorch.org/whl/rocm5.6"; \
     else \
         extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu121"; \
     fi &&\

docker/docker-compose.yml

@@ -15,6 +15,10 @@ services:
             - driver: nvidia
               count: 1
               capabilities: [gpu]
+    # For AMD support, comment out the deploy section above and uncomment the devices section below:
+    #devices:
+    #  - /dev/kfd:/dev/kfd
+    #  - /dev/dri:/dev/dri
     build:
       context: ..
       dockerfile: docker/Dockerfile

docker/run.sh

@@ -7,5 +7,5 @@ set -e
 SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
 cd "$SCRIPTDIR" || exit 1
 
-docker compose up --build -d
+docker compose up -d
 docker compose logs -f

installer/lib/installer.py

@@ -460,10 +460,10 @@ def get_torch_source() -> (Union[str, None], str):
             url = "https://download.pytorch.org/whl/cpu"
 
     if device == "cuda":
-        url = "https://download.pytorch.org/whl/cu118"
+        url = "https://download.pytorch.org/whl/cu121"
         optional_modules = "[xformers,onnx-cuda]"
     if device == "cuda_and_dml":
-        url = "https://download.pytorch.org/whl/cu118"
+        url = "https://download.pytorch.org/whl/cu121"
         optional_modules = "[xformers,onnx-directml]"
 
     # in all other cases, Torch wheels should be coming from PyPi as of Torch 1.13

invokeai/app/invocations/baseinvocation.py

@@ -92,6 +92,10 @@ class FieldDescriptions:
     inclusive_low = "The inclusive low value"
     exclusive_high = "The exclusive high value"
     decimal_places = "The number of decimal places to round to"
+    freeu_s1 = 'Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
+    freeu_s2 = 'Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
+    freeu_b1 = "Scaling factor for stage 1 to amplify the contributions of backbone features."
+    freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."
 
 
 class Input(str, Enum):

invokeai/app/invocations/latent.py

@@ -710,6 +710,8 @@ class DenoiseLatentsInvocation(BaseInvocation):
             )
             with (
                 ExitStack() as exit_stack,
+                ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),
+                ModelPatcher.apply_freeu(unet_info.context.model, self.unet.freeu_config),
                 set_seamless(unet_info.context.model, self.unet.seamless_axes),
                 unet_info as unet,
                 # Apply the LoRA after unet has been moved to its target device for faster patching.

invokeai/app/invocations/math.py

@@ -182,8 +182,8 @@ class IntegerMathInvocation(BaseInvocation):
     operation: INTEGER_OPERATIONS = InputField(
         default="ADD", description="The operation to perform", ui_choice_labels=INTEGER_OPERATIONS_LABELS
     )
-    a: int = InputField(default=0, description=FieldDescriptions.num_1)
+    a: int = InputField(default=1, description=FieldDescriptions.num_1)
-    b: int = InputField(default=0, description=FieldDescriptions.num_2)
+    b: int = InputField(default=1, description=FieldDescriptions.num_2)
 
     @field_validator("b")
     def no_unrepresentable_results(cls, v: int, info: ValidationInfo):
@@ -256,8 +256,8 @@ class FloatMathInvocation(BaseInvocation):
     operation: FLOAT_OPERATIONS = InputField(
         default="ADD", description="The operation to perform", ui_choice_labels=FLOAT_OPERATIONS_LABELS
     )
-    a: float = InputField(default=0, description=FieldDescriptions.num_1)
+    a: float = InputField(default=1, description=FieldDescriptions.num_1)
-    b: float = InputField(default=0, description=FieldDescriptions.num_2)
+    b: float = InputField(default=1, description=FieldDescriptions.num_2)
 
     @field_validator("b")
     def no_unrepresentable_results(cls, v: float, info: ValidationInfo):

invokeai/app/invocations/model.py

@@ -17,6 +17,22 @@ from .baseinvocation import (
     invocation_output,
 )
 
+# TODO: Permanent fix for this
+# from invokeai.app.invocations.shared import FreeUConfig
+
+
+class FreeUConfig(BaseModel):
+    """
+    Configuration for the FreeU hyperparameters.
+    - https://huggingface.co/docs/diffusers/main/en/using-diffusers/freeu
+    - https://github.com/ChenyangSi/FreeU
+    """
+
+    s1: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_s1)
+    s2: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_s2)
+    b1: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_b1)
+    b2: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_b2)
+
 
 class ModelInfo(BaseModel):
     model_name: str = Field(description="Info to load submodel")
@@ -36,6 +52,7 @@ class UNetField(BaseModel):
     scheduler: ModelInfo = Field(description="Info to load scheduler submodel")
     loras: List[LoraInfo] = Field(description="Loras to apply on model loading")
     seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
+    freeu_config: Optional[FreeUConfig] = Field(default=None, description="FreeU configuration")
 
 
 class ClipField(BaseModel):
@@ -51,15 +68,34 @@ class VaeField(BaseModel):
     seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
 
 
-@invocation_output("model_loader_output")
+@invocation_output("unet_output")
-class ModelLoaderOutput(BaseInvocationOutput):
+class UNetOutput(BaseInvocationOutput):
-    """Model loader output"""
+    """Base class for invocations that output a UNet field"""
 
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
-    clip: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP")
+
+
+@invocation_output("vae_output")
+class VAEOutput(BaseInvocationOutput):
+    """Base class for invocations that output a VAE field"""
+
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
+@invocation_output("clip_output")
+class CLIPOutput(BaseInvocationOutput):
+    """Base class for invocations that output a CLIP field"""
+
+    clip: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP")
+
+
+@invocation_output("model_loader_output")
+class ModelLoaderOutput(UNetOutput, CLIPOutput, VAEOutput):
+    """Model loader output"""
+
+    pass
+
+
 class MainModelField(BaseModel):
     """Main model field"""
 
@@ -366,13 +402,6 @@ class VAEModelField(BaseModel):
     model_config = ConfigDict(protected_namespaces=())
 
 
-@invocation_output("vae_loader_output")
-class VaeLoaderOutput(BaseInvocationOutput):
-    """VAE output"""
-
-    vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
-
-
 @invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.0")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
@@ -384,7 +413,7 @@ class VaeLoaderInvocation(BaseInvocation):
         title="VAE",
     )
 
-    def invoke(self, context: InvocationContext) -> VaeLoaderOutput:
+    def invoke(self, context: InvocationContext) -> VAEOutput:
         base_model = self.vae_model.base_model
         model_name = self.vae_model.model_name
         model_type = ModelType.Vae
@@ -395,7 +424,7 @@ class VaeLoaderInvocation(BaseInvocation):
             model_type=model_type,
         ):
             raise Exception(f"Unkown vae name: {model_name}!")
-        return VaeLoaderOutput(
+        return VAEOutput(
             vae=VaeField(
                 vae=ModelInfo(
                     model_name=model_name,
@@ -457,3 +486,24 @@ class SeamlessModeInvocation(BaseInvocation):
             vae.seamless_axes = seamless_axes_list
 
         return SeamlessModeOutput(unet=unet, vae=vae)
+
+
+@invocation("freeu", title="FreeU", tags=["freeu"], category="unet", version="1.0.0")
+class FreeUInvocation(BaseInvocation):
+    """
+    Applies FreeU to the UNet. Suggested values (b1/b2/s1/s2):
+
+    SD1.5: 1.2/1.4/0.9/0.2,
+    SD2: 1.1/1.2/0.9/0.2,
+    SDXL: 1.1/1.2/0.6/0.4,
+    """
+
+    unet: UNetField = InputField(description=FieldDescriptions.unet, input=Input.Connection, title="UNet")
+    b1: float = InputField(default=1.2, ge=-1, le=3, description=FieldDescriptions.freeu_b1)
+    b2: float = InputField(default=1.4, ge=-1, le=3, description=FieldDescriptions.freeu_b2)
+    s1: float = InputField(default=0.9, ge=-1, le=3, description=FieldDescriptions.freeu_s1)
+    s2: float = InputField(default=0.2, ge=-1, le=3, description=FieldDescriptions.freeu_s2)
+
+    def invoke(self, context: InvocationContext) -> UNetOutput:
+        self.unet.freeu_config = FreeUConfig(s1=self.s1, s2=self.s2, b1=self.b1, b2=self.b2)
+        return UNetOutput(unet=self.unet)

invokeai/app/invocations/shared.py

@@ -0,0 +1,16 @@
+from pydantic import BaseModel, Field
+
+from invokeai.app.invocations.baseinvocation import FieldDescriptions
+
+
+class FreeUConfig(BaseModel):
+    """
+    Configuration for the FreeU hyperparameters.
+    - https://huggingface.co/docs/diffusers/main/en/using-diffusers/freeu
+    - https://github.com/ChenyangSi/FreeU
+    """
+
+    s1: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_s1)
+    s2: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_s2)
+    b1: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_b1)
+    b2: float = Field(ge=-1, le=3, description=FieldDescriptions.freeu_b2)

invokeai/backend/model_management/lora.py

@@ -12,6 +12,8 @@ from diffusers.models import UNet2DConditionModel
 from safetensors.torch import load_file
 from transformers import CLIPTextModel, CLIPTokenizer
 
+from invokeai.app.invocations.shared import FreeUConfig
+
 from .models.lora import LoRAModel
 
 """
@@ -240,6 +242,25 @@ class ModelPatcher:
             while len(skipped_layers) > 0:
                 text_encoder.text_model.encoder.layers.append(skipped_layers.pop())
 
+    @classmethod
+    @contextmanager
+    def apply_freeu(
+        cls,
+        unet: UNet2DConditionModel,
+        freeu_config: Optional[FreeUConfig] = None,
+    ):
+        did_apply_freeu = False
+        try:
+            if freeu_config is not None:
+                unet.enable_freeu(b1=freeu_config.b1, b2=freeu_config.b2, s1=freeu_config.s1, s2=freeu_config.s2)
+                did_apply_freeu = True
+
+            yield
+
+        finally:
+            if did_apply_freeu:
+                unet.disable_freeu()
+
 
 class TextualInversionModel:
     embedding: torch.Tensor  # [n, 768]|[n, 1280]

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -546,11 +546,13 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         # Handle ControlNet(s) and T2I-Adapter(s)
         down_block_additional_residuals = None
         mid_block_additional_residual = None
-        if control_data is not None and t2i_adapter_data is not None:
+        down_intrablock_additional_residuals = None
-            # TODO(ryand): This is a limitation of the UNet2DConditionModel API, not a fundamental incompatibility
+        # if control_data is not None and t2i_adapter_data is not None:
-            # between ControlNets and T2I-Adapters. We will try to fix this upstream in diffusers.
+        # TODO(ryand): This is a limitation of the UNet2DConditionModel API, not a fundamental incompatibility
-            raise Exception("ControlNet(s) and T2I-Adapter(s) cannot be used simultaneously (yet).")
+        # between ControlNets and T2I-Adapters. We will try to fix this upstream in diffusers.
-        elif control_data is not None:
+        #    raise Exception("ControlNet(s) and T2I-Adapter(s) cannot be used simultaneously (yet).")
+        # elif control_data is not None:
+        if control_data is not None:
             down_block_additional_residuals, mid_block_additional_residual = self.invokeai_diffuser.do_controlnet_step(
                 control_data=control_data,
                 sample=latent_model_input,
@@ -559,7 +561,8 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                 total_step_count=total_step_count,
                 conditioning_data=conditioning_data,
             )
-        elif t2i_adapter_data is not None:
+        # elif t2i_adapter_data is not None:
+        if t2i_adapter_data is not None:
             accum_adapter_state = None
             for single_t2i_adapter_data in t2i_adapter_data:
                 # Determine the T2I-Adapter weights for the current denoising step.
@@ -584,7 +587,8 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                     for idx, value in enumerate(single_t2i_adapter_data.adapter_state):
                         accum_adapter_state[idx] += value * t2i_adapter_weight
 
-            down_block_additional_residuals = accum_adapter_state
+            # down_block_additional_residuals = accum_adapter_state
+            down_intrablock_additional_residuals = accum_adapter_state
 
         uc_noise_pred, c_noise_pred = self.invokeai_diffuser.do_unet_step(
             sample=latent_model_input,
@@ -593,8 +597,9 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             total_step_count=total_step_count,
             conditioning_data=conditioning_data,
             # extra:
-            down_block_additional_residuals=down_block_additional_residuals,
+            down_block_additional_residuals=down_block_additional_residuals,  # for ControlNet
-            mid_block_additional_residual=mid_block_additional_residual,
+            mid_block_additional_residual=mid_block_additional_residual,  # for ControlNet
+            down_intrablock_additional_residuals=down_intrablock_additional_residuals,  # for T2I-Adapter
         )
 
         guidance_scale = conditioning_data.guidance_scale

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -260,7 +260,6 @@ class InvokeAIDiffuserComponent:
                 conditioning_data,
                 **kwargs,
             )
-
         else:
             (
                 unconditioned_next_x,
@@ -410,6 +409,15 @@ class InvokeAIDiffuserComponent:
                 uncond_down_block.append(_uncond_down)
                 cond_down_block.append(_cond_down)
 
+        uncond_down_intrablock, cond_down_intrablock = None, None
+        down_intrablock_additional_residuals = kwargs.pop("down_intrablock_additional_residuals", None)
+        if down_intrablock_additional_residuals is not None:
+            uncond_down_intrablock, cond_down_intrablock = [], []
+            for down_intrablock in down_intrablock_additional_residuals:
+                _uncond_down, _cond_down = down_intrablock.chunk(2)
+                uncond_down_intrablock.append(_uncond_down)
+                cond_down_intrablock.append(_cond_down)
+
         uncond_mid_block, cond_mid_block = None, None
         mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None)
         if mid_block_additional_residual is not None:
@@ -441,6 +449,7 @@ class InvokeAIDiffuserComponent:
             cross_attention_kwargs=cross_attention_kwargs,
             down_block_additional_residuals=uncond_down_block,
             mid_block_additional_residual=uncond_mid_block,
+            down_intrablock_additional_residuals=uncond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
             **kwargs,
         )
@@ -470,6 +479,7 @@ class InvokeAIDiffuserComponent:
             cross_attention_kwargs=cross_attention_kwargs,
             down_block_additional_residuals=cond_down_block,
             mid_block_additional_residual=cond_mid_block,
+            down_intrablock_additional_residuals=cond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
             **kwargs,
         )
@@ -494,6 +504,15 @@ class InvokeAIDiffuserComponent:
                 uncond_down_block.append(_uncond_down)
                 cond_down_block.append(_cond_down)
 
+        uncond_down_intrablock, cond_down_intrablock = None, None
+        down_intrablock_additional_residuals = kwargs.pop("down_intrablock_additional_residuals", None)
+        if down_intrablock_additional_residuals is not None:
+            uncond_down_intrablock, cond_down_intrablock = [], []
+            for down_intrablock in down_intrablock_additional_residuals:
+                _uncond_down, _cond_down = down_intrablock.chunk(2)
+                uncond_down_intrablock.append(_uncond_down)
+                cond_down_intrablock.append(_cond_down)
+
         uncond_mid_block, cond_mid_block = None, None
         mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None)
         if mid_block_additional_residual is not None:
@@ -522,6 +541,7 @@ class InvokeAIDiffuserComponent:
             {"swap_cross_attn_context": cross_attn_processor_context},
             down_block_additional_residuals=uncond_down_block,
             mid_block_additional_residual=uncond_mid_block,
+            down_intrablock_additional_residuals=uncond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
             **kwargs,
         )
@@ -541,6 +561,7 @@ class InvokeAIDiffuserComponent:
             {"swap_cross_attn_context": cross_attn_processor_context},
             down_block_additional_residuals=cond_down_block,
             mid_block_additional_residual=cond_mid_block,
+            down_intrablock_additional_residuals=cond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
             **kwargs,
         )

invokeai/frontend/install/invokeai_update.py

@@ -63,8 +63,8 @@ def welcome(latest_release: str, latest_prerelease: str):
         yield "[bold yellow]Options:"
         yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
 [2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
-[2] Manually enter the [bold]tag name[/bold] for the version you wish to update to
+[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
-[3] Manually enter the [bold]branch name[/bold] for the version you wish to update to"""
+[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to"""
 
     console.rule()
     print(

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts

@@ -12,6 +12,7 @@ import { addFirstListImagesListener } from './listeners/addFirstListImagesListen
 import { addAnyEnqueuedListener } from './listeners/anyEnqueued';
 import { addAppConfigReceivedListener } from './listeners/appConfigReceived';
 import { addAppStartedListener } from './listeners/appStarted';
+import { addBatchEnqueuedListener } from './listeners/batchEnqueued';
 import { addDeleteBoardAndImagesFulfilledListener } from './listeners/boardAndImagesDeleted';
 import { addBoardIdSelectedListener } from './listeners/boardIdSelected';
 import { addCanvasCopiedToClipboardListener } from './listeners/canvasCopiedToClipboard';
@@ -71,8 +72,6 @@ import { addStagingAreaImageSavedListener } from './listeners/stagingAreaImageSa
 import { addTabChangedListener } from './listeners/tabChanged';
 import { addUpscaleRequestedListener } from './listeners/upscaleRequested';
 import { addWorkflowLoadedListener } from './listeners/workflowLoaded';
-import { addBatchEnqueuedListener } from './listeners/batchEnqueued';
-import { addControlAdapterAddedOrEnabledListener } from './listeners/controlAdapterAddedOrEnabled';
 
 export const listenerMiddleware = createListenerMiddleware();
 
@@ -200,7 +199,3 @@ addTabChangedListener();
 
 // Dynamic prompts
 addDynamicPromptsListener();
-
-// Display toast when controlnet or t2i adapter enabled
-// TODO: Remove when they can both be enabled at same time
-addControlAdapterAddedOrEnabledListener();

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterAddedOrEnabled.ts

@@ -1,87 +0,0 @@
-import { isAnyOf } from '@reduxjs/toolkit';
-import {
-  controlAdapterAdded,
-  controlAdapterAddedFromImage,
-  controlAdapterIsEnabledChanged,
-  controlAdapterRecalled,
-  selectControlAdapterAll,
-  selectControlAdapterById,
-} from 'features/controlAdapters/store/controlAdaptersSlice';
-import { ControlAdapterType } from 'features/controlAdapters/store/types';
-import { addToast } from 'features/system/store/systemSlice';
-import i18n from 'i18n';
-import { startAppListening } from '..';
-
-const isAnyControlAdapterAddedOrEnabled = isAnyOf(
-  controlAdapterAdded,
-  controlAdapterAddedFromImage,
-  controlAdapterRecalled,
-  controlAdapterIsEnabledChanged
-);
-
-/**
- * Until we can have both controlnet and t2i adapter enabled at once, they are mutually exclusive
- * This displays a toast when one is enabled and the other is already enabled, or one is added
- * with the other enabled
- */
-export const addControlAdapterAddedOrEnabledListener = () => {
-  startAppListening({
-    matcher: isAnyControlAdapterAddedOrEnabled,
-    effect: async (action, { dispatch, getOriginalState }) => {
-      const controlAdapters = getOriginalState().controlAdapters;
-
-      const hasEnabledControlNets = selectControlAdapterAll(
-        controlAdapters
-      ).some((ca) => ca.isEnabled && ca.type === 'controlnet');
-
-      const hasEnabledT2IAdapters = selectControlAdapterAll(
-        controlAdapters
-      ).some((ca) => ca.isEnabled && ca.type === 't2i_adapter');
-
-      let caType: ControlAdapterType | null = null;
-
-      if (controlAdapterAdded.match(action)) {
-        caType = action.payload.type;
-      }
-
-      if (controlAdapterAddedFromImage.match(action)) {
-        caType = action.payload.type;
-      }
-
-      if (controlAdapterRecalled.match(action)) {
-        caType = action.payload.type;
-      }
-
-      if (controlAdapterIsEnabledChanged.match(action)) {
-        const _caType = selectControlAdapterById(
-          controlAdapters,
-          action.payload.id
-        )?.type;
-        if (!_caType) {
-          return;
-        }
-        caType = _caType;
-      }
-
-      if (
-        (caType === 'controlnet' && hasEnabledT2IAdapters) ||
-        (caType === 't2i_adapter' && hasEnabledControlNets)
-      ) {
-        const title =
-          caType === 'controlnet'
-            ? i18n.t('controlnet.controlNetEnabledT2IDisabled')
-            : i18n.t('controlnet.t2iEnabledControlNetDisabled');
-
-        const description = i18n.t('controlnet.controlNetT2IMutexDesc');
-
-        dispatch(
-          addToast({
-            title,
-            description,
-            status: 'warning',
-          })
-        );
-      }
-    },
-  });
-};

invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts

@@ -88,61 +88,6 @@ export const selectValidT2IAdapters = (controlAdapters: ControlAdaptersState) =>
           (ca.processorType === 'none' && Boolean(ca.controlImage)))
     );
 
-// TODO: I think we can safely remove this?
-// const disableAllIPAdapters = (
-//   state: ControlAdaptersState,
-//   exclude?: string
-// ) => {
-//   const updates: Update<ControlAdapterConfig>[] = selectAllIPAdapters(state)
-//     .filter((ca) => ca.id !== exclude)
-//     .map((ca) => ({
-//       id: ca.id,
-//       changes: { isEnabled: false },
-//     }));
-//   caAdapter.updateMany(state, updates);
-// };
-
-const disableAllControlNets = (
-  state: ControlAdaptersState,
-  exclude?: string
-) => {
-  const updates: Update<ControlAdapterConfig>[] = selectAllControlNets(state)
-    .filter((ca) => ca.id !== exclude)
-    .map((ca) => ({
-      id: ca.id,
-      changes: { isEnabled: false },
-    }));
-  caAdapter.updateMany(state, updates);
-};
-
-const disableAllT2IAdapters = (
-  state: ControlAdaptersState,
-  exclude?: string
-) => {
-  const updates: Update<ControlAdapterConfig>[] = selectAllT2IAdapters(state)
-    .filter((ca) => ca.id !== exclude)
-    .map((ca) => ({
-      id: ca.id,
-      changes: { isEnabled: false },
-    }));
-  caAdapter.updateMany(state, updates);
-};
-
-const disableIncompatibleControlAdapters = (
-  state: ControlAdaptersState,
-  type: ControlAdapterType,
-  exclude?: string
-) => {
-  if (type === 'controlnet') {
-    // we cannot do controlnet + t2i adapter, if we are enabled a controlnet, disable all t2is
-    disableAllT2IAdapters(state, exclude);
-  }
-  if (type === 't2i_adapter') {
-    // we cannot do controlnet + t2i adapter, if we are enabled a t2i, disable controlnets
-    disableAllControlNets(state, exclude);
-  }
-};
-
 export const controlAdaptersSlice = createSlice({
   name: 'controlAdapters',
   initialState: initialControlAdapterState,
@@ -158,7 +103,6 @@ export const controlAdaptersSlice = createSlice({
       ) => {
         const { id, type, overrides } = action.payload;
         caAdapter.addOne(state, buildControlAdapter(id, type, overrides));
-        disableIncompatibleControlAdapters(state, type, id);
       },
       prepare: ({
         type,
@@ -175,8 +119,6 @@ export const controlAdaptersSlice = createSlice({
       action: PayloadAction<ControlAdapterConfig>
     ) => {
       caAdapter.addOne(state, action.payload);
-      const { type, id } = action.payload;
-      disableIncompatibleControlAdapters(state, type, id);
     },
     controlAdapterDuplicated: {
       reducer: (
@@ -196,8 +138,6 @@ export const controlAdaptersSlice = createSlice({
           isEnabled: true,
         });
         caAdapter.addOne(state, newControlAdapter);
-        const { type } = newControlAdapter;
-        disableIncompatibleControlAdapters(state, type, newId);
       },
       prepare: (id: string) => {
         return { payload: { id, newId: uuidv4() } };
@@ -217,7 +157,6 @@ export const controlAdaptersSlice = createSlice({
           state,
           buildControlAdapter(id, type, { controlImage })
         );
-        disableIncompatibleControlAdapters(state, type, id);
       },
       prepare: (payload: {
         type: ControlAdapterType;
@@ -235,12 +174,6 @@ export const controlAdaptersSlice = createSlice({
     ) => {
       const { id, isEnabled } = action.payload;
       caAdapter.updateOne(state, { id, changes: { isEnabled } });
-      if (isEnabled) {
-        // we are enabling a control adapter. due to limitations in the current system, we may need to disable other adapters
-        // TODO: disable when multiple IP adapters are supported
-        const ca = selectControlAdapterById(state, id);
-        ca && disableIncompatibleControlAdapters(state, ca.type, id);
-      }
     },
     controlAdapterImageChanged: (
       state,

invokeai/frontend/web/src/services/api/schema.d.ts

@@ -8808,11 +8808,11 @@ export type components = {
       ui_order: number | null;
     };
     /**
-     * StableDiffusionOnnxModelFormat
+     * IPAdapterModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusionOnnxModelFormat: "olive" | "onnx";
+    IPAdapterModelFormat: "invokeai";
     /**
      * IPAdapterModelFormat
      * @description An enumeration.
@@ -8832,11 +8832,11 @@ export type components = {
      */
     StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
     /**
-     * CLIPVisionModelFormat
+     * StableDiffusionOnnxModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    CLIPVisionModelFormat: "diffusers";
+    StableDiffusionOnnxModelFormat: "olive" | "onnx";
     /**
      * StableDiffusion1ModelFormat
      * @description An enumeration.

pyproject.toml

@@ -42,7 +42,7 @@ dependencies = [
   "datasets",
   # When bumping diffusers beyond 0.21, make sure to address this:
   # https://github.com/invoke-ai/InvokeAI/blob/fc09ab7e13cb7ca5389100d149b6422ace7b8ed3/invokeai/app/invocations/latent.py#L513
-  "diffusers[torch]~=0.21.0",
+  "diffusers[torch]~=0.22.0",
   "dnspython~=2.4.0",
   "dynamicprompts",
   "easing-functions",
@@ -81,8 +81,8 @@ dependencies = [
   "semver~=3.0.1",
   "send2trash",
   "test-tube~=0.7.5",
-  "torch~=2.0.1",
+  "torch~=2.1.0",
-  "torchvision~=0.15.2",
+  "torchvision~=0.16",
   "torchmetrics~=0.11.0",
   "torchsde~=0.2.5",
   "transformers~=4.31.0",
@@ -110,8 +110,8 @@ dependencies = [
   "pytest-datadir",
 ]
 "xformers" = [
-  "xformers~=0.0.19; sys_platform!='darwin'",
+  "xformers==0.0.22post7; sys_platform!='darwin'",
-  "triton; sys_platform=='linux'",
+	"triton; sys_platform=='linux'",
 ]
 "onnx" = ["onnxruntime"]
 "onnx-cuda" = ["onnxruntime-gpu"]