chore: prep for v5.9.1

Before FLUX Fill was merged, we didn't do any checks for the model variant. We always returned "normal".

To determine if a model is a FLUX Fill model, we need to check the state dict for a specific key. Initially, this logic was too strict and rejected quantized FLUX models. This issue was resolved, but it turns out there is another failure mode - some fine-tunes use a different key.

This change further reduces the strictness, handling the alternate key and also falling back to "normal" if we don't see either key. This effectively restores the previous probing behaviour for all FLUX models.

Closes #7856
Closes #7859

.github/workflows/python-checks.yml

@@ -34,6 +34,9 @@ on:
 
 jobs:
   python-checks:
+    env:
+      # uv requires a venv by default - but for this, we can simply use the system python
+      UV_SYSTEM_PYTHON: 1
     runs-on: ubuntu-latest
     timeout-minutes: 5 # expected run time: <1 min
     steps:
@@ -57,25 +60,19 @@ jobs:
               - '!invokeai/frontend/web/**'
               - 'tests/**'
 
-      - name: setup python
+      - name: setup uv
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        uses: actions/setup-python@v5
+        uses: astral-sh/setup-uv@v5
         with:
-          python-version: '3.12'
-          cache: pip
-          cache-dependency-path: pyproject.toml
-
-      - name: install ruff
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: pip install ruff==0.11.2
-        shell: bash
+          version: '0.6.10'
+          enable-cache: true
 
       - name: ruff check
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: ruff check --output-format=github .
+        run: uv tool run ruff@0.11.2 check --output-format=github .
         shell: bash
 
       - name: ruff format
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: ruff format --check .
+        run: uv tool run ruff@0.11.2 format --check .
         shell: bash

.github/workflows/python-tests.yml

@@ -40,24 +40,16 @@ jobs:
       matrix:
         python-version:
           - '3.11'
+          - '3.12'
         platform:
-          # - linux-cuda-12_6
-          # - linux-rocm-6_2
           - linux-cpu
           - macos-default
           - windows-cpu
         include:
-          # - platform: linux-cuda-12_6
-          #   os: ubuntu-24.04
-          #   github-env: $GITHUB_ENV
-          # - platform: linux-rocm-6_2
-          #   os: ubuntu-24.04
-          #   extra-index-url: 'https://download.pytorch.org/whl/rocm6.2'
-          #   github-env: $GITHUB_ENV
           - platform: linux-cpu
             os: ubuntu-24.04
-            github-env: $GITHUB_ENV
             extra-index-url: 'https://download.pytorch.org/whl/cpu'
+            github-env: $GITHUB_ENV
           - platform: macos-default
             os: macOS-14
             github-env: $GITHUB_ENV
@@ -69,6 +61,8 @@ jobs:
     timeout-minutes: 15 # expected run time: 2-6 min, depending on platform
     env:
       PIP_USE_PEP517: '1'
+      UV_SYSTEM_PYTHON: 1
+
     steps:
       - name: checkout
         # https://github.com/nschloe/action-cached-lfs-checkout
@@ -91,20 +85,25 @@ jobs:
               - '!invokeai/frontend/web/**'
               - 'tests/**'
 
+      - name: setup uv
+        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
+        uses: astral-sh/setup-uv@v5
+        with:
+          version: '0.6.10'
+          enable-cache: true
+          python-version: ${{ matrix.python-version }}
+
       - name: setup python
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: pip
-          cache-dependency-path: pyproject.toml
 
       - name: install dependencies
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
         env:
-          PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
-        run: >
-          pip3 install --editable=".[test]"
+          UV_INDEX: ${{ matrix.extra-index-url }}
+        run: uv pip install --editable ".[test]"
 
       - name: run pytest
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}

.github/workflows/typegen-checks.yml

@@ -54,17 +54,25 @@ jobs:
               - 'pyproject.toml'
               - 'invokeai/**'
 
+      - name: setup uv
+        if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
+        uses: astral-sh/setup-uv@v5
+        with:
+          version: '0.6.10'
+          enable-cache: true
+          python-version: '3.11'
+
       - name: setup python
         if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
         uses: actions/setup-python@v5
         with:
-          python-version: '3.10'
-          cache: pip
-          cache-dependency-path: pyproject.toml
+          python-version: '3.11'
 
-      - name: install python dependencies
+      - name: install dependencies
         if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
-        run: pip3 install --use-pep517 --editable="."
+        env:
+          UV_INDEX: ${{ matrix.extra-index-url }}
+        run: uv pip install --editable .
 
       - name: install frontend dependencies
         if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
@@ -77,7 +85,7 @@ jobs:
 
       - name: generate schema
         if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
-        run: make frontend-typegen
+        run: cd invokeai/frontend/web && uv run ../../../scripts/generate_openapi_schema.py | pnpm typegen
         shell: bash
 
       - name: compare files

invokeai/app/invocations/image.py

@@ -1089,7 +1089,7 @@ class CanvasV2MaskAndCropInvocation(BaseInvocation, WithMetadata, WithBoard):
 
 
 @invocation(
-    "expand_mask_with_fade", title="Expand Mask with Fade", tags=["image", "mask"], category="image", version="1.0.0"
+    "expand_mask_with_fade", title="Expand Mask with Fade", tags=["image", "mask"], category="image", version="1.0.1"
 )
 class ExpandMaskWithFadeInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Expands a mask with a fade effect. The mask uses black to indicate areas to keep from the generated image and white for areas to discard.
@@ -1147,8 +1147,21 @@ class ExpandMaskWithFadeInvocation(BaseInvocation, WithMetadata, WithBoard):
         coeffs = numpy.polyfit(x_control, y_control, 3)
         poly = numpy.poly1d(coeffs)
 
-        # Evaluate and clip the smooth mapping
-        feather = numpy.clip(poly(d_norm), 0, 1)
+        # Evaluate the polynomial
+        feather = poly(d_norm)
+
+        # The polynomial fit isn't perfect. Points beyond the fade distance are likely to be slightly less than 1.0,
+        # even though the control points indicate that they should be exactly 1.0. This is due to the nature of the
+        # polynomial fit, which is a best approximation of the control points but not an exact match.
+
+        # When this occurs, the area outside the mask and fade-out will not be 100% transparent. For example, it may
+        # have an alpha value of 1 instead of 0. So we must force pixels at or beyond the fade distance to exactly 1.0.
+
+        # Force pixels at or beyond the fade distance to exactly 1.0
+        feather = numpy.where(d_norm >= 1.0, 1.0, feather)
+
+        # Clip any other values to ensure they're in the valid range [0,1]
+        feather = numpy.clip(feather, 0, 1)
 
         # Build final image.
         np_result = numpy.where(black_mask == 1, 0, (feather * 255).astype(numpy.uint8))

invokeai/backend/flux/flux_state_dict_utils.py

@@ -0,0 +1,23 @@
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from invokeai.backend.model_manager.legacy_probe import CkptType
+
+
+def get_flux_in_channels_from_state_dict(state_dict: "CkptType") -> int | None:
+    """Gets the in channels from the state dict."""
+
+    # "Standard" FLUX models use "img_in.weight", but some community fine tunes use
+    # "model.diffusion_model.img_in.weight". Known models that use the latter key:
+    # - https://civitai.com/models/885098?modelVersionId=990775
+    # - https://civitai.com/models/1018060?modelVersionId=1596255
+    # - https://civitai.com/models/978314/ultrareal-fine-tune?modelVersionId=1413133
+
+    keys = {"img_in.weight", "model.diffusion_model.img_in.weight"}
+
+    for key in keys:
+        val = state_dict.get(key)
+        if val is not None:
+            return val.shape[1]
+
+    return None

invokeai/backend/model_manager/legacy_probe.py

@@ -14,6 +14,7 @@ from invokeai.backend.flux.controlnet.state_dict_utils import (
     is_state_dict_instantx_controlnet,
     is_state_dict_xlabs_controlnet,
 )
+from invokeai.backend.flux.flux_state_dict_utils import get_flux_in_channels_from_state_dict
 from invokeai.backend.flux.ip_adapter.state_dict_utils import is_state_dict_xlabs_ip_adapter
 from invokeai.backend.flux.redux.flux_redux_state_dict_utils import is_state_dict_likely_flux_redux
 from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS, ModelHash
@@ -564,7 +565,14 @@ class CheckpointProbeBase(ProbeBase):
         state_dict = self.checkpoint.get("state_dict") or self.checkpoint
 
         if base_type == BaseModelType.Flux:
-            in_channels = state_dict["img_in.weight"].shape[1]
+            in_channels = get_flux_in_channels_from_state_dict(state_dict)
+
+            if in_channels is None:
+                # If we cannot find the in_channels, we assume that this is a normal variant. Log a warning.
+                logger.warning(
+                    f"{self.model_path} does not have img_in.weight or model.diffusion_model.img_in.weight key. Assuming normal variant."
+                )
+                return ModelVariantType.Normal
 
             # FLUX Model variant types are distinguished by input channels:
             # - Unquantized Dev and Schnell have in_channels=64

invokeai/frontend/web/src/features/controlLayers/components/ParamDenoisingStrength.tsx

@@ -14,8 +14,9 @@ import WavyLine from 'common/components/WavyLine';
 import { selectImg2imgStrength, setImg2imgStrength } from 'features/controlLayers/store/paramsSlice';
 import { selectActiveRasterLayerEntities } from 'features/controlLayers/store/selectors';
 import { selectImg2imgStrengthConfig } from 'features/system/store/configSlice';
-import { memo, useCallback } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useSelectedModelConfig } from 'services/api/hooks/useSelectedModelConfig';
 
 const selectHasRasterLayersWithContent = createSelector(
   selectActiveRasterLayerEntities,
@@ -26,6 +27,7 @@ export const ParamDenoisingStrength = memo(() => {
   const img2imgStrength = useAppSelector(selectImg2imgStrength);
   const dispatch = useAppDispatch();
   const hasRasterLayersWithContent = useAppSelector(selectHasRasterLayersWithContent);
+  const selectedModelConfig = useSelectedModelConfig();
 
   const onChange = useCallback(
     (v: number) => {
@@ -39,8 +41,24 @@ export const ParamDenoisingStrength = memo(() => {
 
   const [invokeBlue300] = useToken('colors', ['invokeBlue.300']);
 
+  const isDisabled = useMemo(() => {
+    if (!hasRasterLayersWithContent) {
+      // Denoising strength does nothing if there are no raster layers w/ content
+      return true;
+    }
+    if (
+      selectedModelConfig?.type === 'main' &&
+      selectedModelConfig?.base === 'flux' &&
+      selectedModelConfig.variant === 'inpaint'
+    ) {
+      // Denoising strength is ignored by FLUX Fill, which is indicated by the variant being 'inpaint'
+      return true;
+    }
+    return false;
+  }, [hasRasterLayersWithContent, selectedModelConfig]);
+
   return (
-    <FormControl isDisabled={!hasRasterLayersWithContent} p={1} justifyContent="space-between" h={8}>
+    <FormControl isDisabled={isDisabled} p={1} justifyContent="space-between" h={8}>
       <Flex gap={3} alignItems="center">
         <InformationalPopover feature="paramDenoisingStrength">
           <FormLabel mr={0}>{`${t('parameters.denoisingStrength')}`}</FormLabel>
@@ -49,7 +67,7 @@ export const ParamDenoisingStrength = memo(() => {
           <WavyLine amplitude={img2imgStrength * 10} stroke={invokeBlue300} strokeWidth={1} width={40} height={14} />
         )}
       </Flex>
-      {hasRasterLayersWithContent ? (
+      {!isDisabled ? (
         <>
           <CompositeSlider
             step={config.coarseStep}

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "5.9.0"
+__version__ = "5.9.1"

pyproject.toml

@@ -117,7 +117,7 @@ dependencies = [
 ]
 "dev" = ["jurigged", "pudb", "snakeviz", "gprof2dot"]
 "test" = [
-  "ruff~=0.9.9",
+  "ruff~=0.11.2",
   "ruff-lsp~=0.0.62",
   "mypy",
   "pre-commit",

tests/backend/flux/controlnet/test_state_dict_utils.py

@@ -24,7 +24,7 @@ from tests.backend.flux.controlnet.xlabs_flux_controlnet_state_dict import xlabs
     ],
 )
 def test_is_state_dict_xlabs_controlnet(sd_shapes: dict[str, list[int]], expected: bool):
-    sd = {k: None for k in sd_shapes}
+    sd = dict.fromkeys(sd_shapes)
     assert is_state_dict_xlabs_controlnet(sd) == expected
 
 
@@ -37,7 +37,7 @@ def test_is_state_dict_xlabs_controlnet(sd_shapes: dict[str, list[int]], expecte
     ],
 )
 def test_is_state_dict_instantx_controlnet(sd_keys: list[str], expected: bool):
-    sd = {k: None for k in sd_keys}
+    sd = dict.fromkeys(sd_keys)
     assert is_state_dict_instantx_controlnet(sd) == expected
 
 

tests/backend/flux/ip_adapter/test_xlabs_ip_adapter_flux.py

@@ -19,7 +19,7 @@ from tests.backend.flux.ip_adapter.xlabs_flux_ip_adapter_v2_state_dict import xl
 @pytest.mark.parametrize("sd_shapes", [xlabs_flux_ip_adapter_sd_shapes, xlabs_flux_ip_adapter_v2_sd_shapes])
 def test_is_state_dict_xlabs_ip_adapter(sd_shapes: dict[str, list[int]]):
     # Construct a dummy state_dict.
-    sd = {k: None for k in sd_shapes}
+    sd = dict.fromkeys(sd_shapes)
 
     assert is_state_dict_xlabs_ip_adapter(sd)