{release} Update version to 3.5.0rc2

## What type of PR is this? (check all applicable)

- [ ] Refactor
- [x] Feature
- [ ] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission


## Have you discussed this change with the InvokeAI team?
- [x] Yes
- [ ] No, because:

      
## Have you updated all relevant documentation?
- [ ] Yes
- [x] No


## Description
Change CalculateImageTilesEvenSplitInvocation to have an overlap in
pixels rather than as a percentage of the tile. This makes it easier to
have predictable blending of the seams as you have a known overlap size.

## Related Tickets & Documents

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below. 

For example having the text: "closes #1234" would connect the current
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-->

- Related Issue #
- Closes #

## QA Instructions, Screenshots, Recordings

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Please provide steps on how to test changes, any hardware or 
software specifications as well as any other pertinent information. 
-->

## Merge Plan

<!--
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approved.

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- "This PR can be merged when approved"
- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
- "#dev-chat on discord needs to be advised of this change when it is
merged"

A merge plan is particularly important for large PRs or PRs that touch
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## Added/updated tests?

- [x] Yes
- [ ] No : _please replace this line with details on why tests
      have not been included_

## [optional] Are there any post deployment tasks we need to perform?

.github/workflows/lint-frontend.yml

@@ -21,16 +21,16 @@ jobs:
     if: github.event.pull_request.draft == false
     runs-on: ubuntu-22.04
     steps:
-      - name: Setup Node 20
+      - name: Setup Node 18
         uses: actions/setup-node@v4
         with:
-          node-version: '20'
+          node-version: '18'
       - name: Checkout
         uses: actions/checkout@v4
       - name: Setup pnpm
         uses: pnpm/action-setup@v2
         with:
-          version: 8
+          version: '8.12.1'
       - name: Install dependencies
         run: 'pnpm install --prefer-frozen-lockfile'
       - name: Typescript

.github/workflows/pypi-release.yml

@@ -1,13 +1,15 @@
 name: PyPI Release
 
 on:
-  push:
-    paths:
-      - 'invokeai/version/invokeai_version.py'
   workflow_dispatch:
+    inputs:
+      publish_package:
+        description: 'Publish build on PyPi? [true/false]'
+        required: true
+        default: 'false'
 
 jobs:
-  release:
+  build-and-release:
     if: github.repository == 'invoke-ai/InvokeAI'
     runs-on: ubuntu-22.04
     env:
@@ -15,33 +17,39 @@ jobs:
       TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
       TWINE_NON_INTERACTIVE: 1
     steps:
-      - name: Checkout sources
+      - name: Checkout
         uses: actions/checkout@v4
 
-      - name: Setup Node 20
+      - name: Setup Node 18
         uses: actions/setup-node@v4
         with:
-          node-version: '20'
+          node-version: '18'
 
       - name: Setup pnpm
         uses: pnpm/action-setup@v2
         with:
-          version: 8
+          version: '8.12.1'
 
-      - name: Install pnpm dependencies
+      - name: Install frontend dependencies
+        run: pnpm install --prefer-frozen-lockfile
         working-directory: invokeai/frontend/web
-        run: 'pnpm install --prefer-frozen-lockfile'
 
       - name: Build frontend
+        run: pnpm run build
         working-directory: invokeai/frontend/web
-        run: 'pnpm build'
 
-      - name: Install python deps
+      - name: Install python dependencies
         run: pip install --upgrade build twine
 
-      - name: Build wheel package
+      - name: Build python package
         run: python3 -m build
 
+      - name: Upload build as workflow artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: dist
+
       - name: Check distribution
         run: twine check dist/*
 
@@ -54,6 +62,6 @@ jobs:
           EXISTS=scripts.pypi_helper.local_on_pypi(); \
           print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
 
-      - name: Upload package
-        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
+      - name: Publish build on PyPi
+        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != '' && github.event.inputs.publish_package == 'true'
         run: twine upload dist/*

docker/README.md

@@ -23,7 +23,7 @@ This is done via Docker Desktop preferences
 1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
     a. the desired location of the InvokeAI runtime directory, or
     b. an existing, v3.0.0 compatible runtime directory.
-1. `docker compose up`
+1. Execute `run.sh`
 
 The image will be built automatically if needed.
 
@@ -39,7 +39,7 @@ The Docker daemon on the system must be already set up to use the GPU. In case o
 
 ## Customize
 
-Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `docker compose up`, your custom values will be used.
+Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `run.sh`, your custom values will be used.
 
 You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
 

docker/build.sh

@@ -1,11 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-build_args=""
-
-[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
-
-echo "docker compose build args:"
-echo $build_args
-
-docker compose build $build_args

docker/docker-compose.yml

@@ -2,23 +2,8 @@
 
 version: '3.8'
 
-services:
-  invokeai:
+x-invokeai: &invokeai
     image: "local/invokeai:latest"
-    # edit below to run on a container runtime other than nvidia-container-runtime.
-    # not yet tested with rocm/AMD GPUs
-    # Comment out the "deploy" section to run on CPU only
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - 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
@@ -50,3 +35,27 @@ services:
     #   - |
     #     invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
     #     invokeai-nodes-web --host 0.0.0.0
+
+services:
+  invokeai-nvidia:
+    <<: *invokeai
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+  invokeai-cpu:
+    <<: *invokeai
+    profiles:
+      - cpu
+
+  invokeai-rocm:
+    <<: *invokeai
+    devices:
+      - /dev/kfd:/dev/kfd
+      - /dev/dri:/dev/dri
+    profiles:
+      - rocm

docker/run.sh

@@ -1,11 +1,28 @@
 #!/usr/bin/env bash
 set -e
 
-# This script is provided for backwards compatibility with the old docker setup.
-# it doesn't do much aside from wrapping the usual docker compose CLI.
+run() {
+  local scriptdir=$(dirname "${BASH_SOURCE[0]}")
+  cd "$scriptdir" || exit 1
 
-SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
-cd "$SCRIPTDIR" || exit 1
+  local build_args=""
+  local profile=""
 
-docker compose up -d
-docker compose logs -f
+  [[ -f ".env" ]] &&
+    build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
+    profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+
+  local service_name="invokeai-$profile"
+
+  printf "%s\n" "docker compose build args:"
+  printf "%s\n" "$build_args"
+
+  docker compose build $build_args
+  unset build_args
+
+  printf "%s\n" "starting service $service_name"
+  docker compose --profile "$profile" up -d "$service_name"
+  docker compose logs -f
+}
+
+run

installer/create_installer.sh

@@ -91,9 +91,11 @@ rm -rf InvokeAI-Installer
 
 # copy content
 mkdir InvokeAI-Installer
-for f in templates lib *.txt *.reg; do
+for f in templates *.txt *.reg; do
     cp -r ${f} InvokeAI-Installer/
 done
+mkdir InvokeAI-Installer/lib
+cp lib/*.py InvokeAI-Installer/lib
 
 # Move the wheel
 mv dist/*.whl InvokeAI-Installer/lib/
@@ -111,6 +113,6 @@ cp WinLongPathsEnabled.reg InvokeAI-Installer/
 zip -r InvokeAI-installer-$VERSION.zip InvokeAI-Installer
 
 # clean up
-rm -rf InvokeAI-Installer tmp dist
+rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
 
 exit 0

invokeai/app/invocations/tiles.py

@@ -77,7 +77,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
     title="Calculate Image Tiles Even Split",
     tags=["tiles"],
     category="tiles",
-    version="1.0.0",
+    version="1.1.0",
     classification=Classification.Beta,
 )
 class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
@@ -97,11 +97,11 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
         ge=1,
         description="Number of tiles to divide image into on the y axis",
     )
-    overlap_fraction: float = InputField(
-        default=0.25,
+    overlap: int = InputField(
+        default=128,
         ge=0,
-        lt=1,
-        description="Overlap between adjacent tiles as a fraction of the tile's dimensions (0-1)",
+        multiple_of=8,
+        description="The overlap, in pixels, between adjacent tiles.",
     )
 
     def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
@@ -110,7 +110,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
             image_width=self.image_width,
             num_tiles_x=self.num_tiles_x,
             num_tiles_y=self.num_tiles_y,
-            overlap_fraction=self.overlap_fraction,
+            overlap=self.overlap,
         )
         return CalculateImageTilesOutput(tiles=tiles)
 

invokeai/backend/model_management/util.py

@@ -9,7 +9,7 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     :param checkpoint: The checkpoint
     """
 
-    def _get_shape_1(key, tensor, checkpoint):
+    def _get_shape_1(key: str, tensor, checkpoint) -> int:
         lora_token_vector_length = None
 
         if "." not in key:
@@ -57,6 +57,10 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     for key, tensor in checkpoint.items():
         if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
             lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
+        elif key.startswith("lora_unet_") and (
+            "time_emb_proj.lora_down" in key
+        ):  # recognizes format at https://civitai.com/models/224641
+            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
         elif key.startswith("lora_te") and "_self_attn_" in key:
             tmp_length = _get_shape_1(key, tensor, checkpoint)
             if key.startswith("lora_te_"):

invokeai/backend/model_manager/probe.py

@@ -400,6 +400,8 @@ class LoRACheckpointProbe(CheckpointProbeBase):
             return BaseModelType.StableDiffusion1
         elif token_vector_length == 1024:
             return BaseModelType.StableDiffusion2
+        elif token_vector_length == 1280:
+            return BaseModelType.StableDiffusionXL  # recognizes format at https://civitai.com/models/224641
         elif token_vector_length == 2048:
             return BaseModelType.StableDiffusionXL
         else:

invokeai/backend/tiles/tiles.py

@@ -102,7 +102,7 @@ def calc_tiles_with_overlap(
 
 
 def calc_tiles_even_split(
-    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap_fraction: float = 0
+    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap: int = 0
 ) -> list[Tile]:
     """Calculate the tile coordinates for a given image shape with the number of tiles requested.
 
@@ -111,31 +111,35 @@ def calc_tiles_even_split(
         image_width (int): The image width in px.
         num_x_tiles (int): The number of tile to split the image into on the X-axis.
         num_y_tiles (int): The number of tile to split the image into on the Y-axis.
-        overlap_fraction (float, optional): The target overlap as fraction of the tiles size. Defaults to 0.
+        overlap (int, optional): The overlap between adjacent tiles in pixels. Defaults to 0.
 
     Returns:
         list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
     """
-
-    # Ensure tile size is divisible by 8
+    # Ensure the image is divisible by LATENT_SCALE_FACTOR
     if image_width % LATENT_SCALE_FACTOR != 0 or image_height % LATENT_SCALE_FACTOR != 0:
         raise ValueError(f"image size (({image_width}, {image_height})) must be divisible by {LATENT_SCALE_FACTOR}")
 
-    # Calculate the overlap size based on the percentage and adjust it to be divisible by 8 (rounding up)
-    overlap_x = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_width / num_tiles_x) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-    overlap_y = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_height / num_tiles_y) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-
     # Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
+    if num_tiles_x > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_width - (LATENT_SCALE_FACTOR * (num_tiles_x - 1))
         tile_size_x = LATENT_SCALE_FACTOR * math.floor(
-        ((image_width + overlap_x * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
+            ((image_width + overlap * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
         )
+        assert overlap < tile_size_x
+    else:
+        tile_size_x = image_width
+
+    if num_tiles_y > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_height - (LATENT_SCALE_FACTOR * (num_tiles_y - 1))
         tile_size_y = LATENT_SCALE_FACTOR * math.floor(
-        ((image_height + overlap_y * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
+            ((image_height + overlap * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
         )
+        assert overlap < tile_size_y
+    else:
+        tile_size_y = image_height
 
     # tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
     tiles: list[Tile] = []
@@ -143,7 +147,7 @@ def calc_tiles_even_split(
     # Calculate tile coordinates. (Ignore overlap values for now.)
     for tile_idx_y in range(num_tiles_y):
         # Calculate the top and bottom of the row
-        top = tile_idx_y * (tile_size_y - overlap_y)
+        top = tile_idx_y * (tile_size_y - overlap)
         bottom = min(top + tile_size_y, image_height)
         # For the last row adjust bottom to be the height of the image
         if tile_idx_y == num_tiles_y - 1:
@@ -151,7 +155,7 @@ def calc_tiles_even_split(
 
         for tile_idx_x in range(num_tiles_x):
             # Calculate the left & right coordinate of each tile
-            left = tile_idx_x * (tile_size_x - overlap_x)
+            left = tile_idx_x * (tile_size_x - overlap)
             right = min(left + tile_size_x, image_width)
             # For the last tile in the row adjust right to be the width of the image
             if tile_idx_x == num_tiles_x - 1:

invokeai/frontend/web/public/locales/es.json

@@ -727,9 +727,6 @@
         "showMinimapnodes": "Mostrar el minimapa",
         "reloadNodeTemplates": "Recargar las plantillas de nodos",
         "loadWorkflow": "Cargar el flujo de trabajo",
-        "resetWorkflow": "Reiniciar e flujo de trabajo",
-        "resetWorkflowDesc": "¿Está seguro de que deseas restablecer este flujo de trabajo?",
-        "resetWorkflowDesc2": "Al reiniciar el flujo de trabajo se borrarán todos los nodos, aristas y detalles del flujo de trabajo.",
         "downloadWorkflow": "Descargar el flujo de trabajo en un archivo JSON"
     }
 }

invokeai/frontend/web/public/locales/it.json

@@ -898,11 +898,8 @@
         "zoomInNodes": "Ingrandire",
         "fitViewportNodes": "Adatta vista",
         "showGraphNodes": "Mostra sovrapposizione grafico",
-        "resetWorkflowDesc2": "Il ripristino dell'editor del flusso di lavoro cancellerà tutti i nodi, le connessioni e i dettagli del flusso di lavoro. I flussi di lavoro salvati non saranno interessati.",
         "reloadNodeTemplates": "Ricarica i modelli di nodo",
         "loadWorkflow": "Importa flusso di lavoro JSON",
-        "resetWorkflow": "Reimposta l'editor del flusso di lavoro",
-        "resetWorkflowDesc": "Sei sicuro di voler reimpostare l'editor del flusso di lavoro?",
         "downloadWorkflow": "Esporta flusso di lavoro JSON",
         "scheduler": "Campionatore",
         "addNode": "Aggiungi nodo",
@@ -1619,7 +1616,6 @@
         "saveWorkflow": "Salva flusso di lavoro",
         "openWorkflow": "Apri flusso di lavoro",
         "clearWorkflowSearchFilter": "Cancella il filtro di ricerca del flusso di lavoro",
-        "workflowEditorReset": "Reimpostazione dell'editor del flusso di lavoro",
         "workflowLibrary": "Libreria",
         "noRecentWorkflows": "Nessun flusso di lavoro recente",
         "workflowSaved": "Flusso di lavoro salvato",

invokeai/frontend/web/public/locales/nl.json

@@ -844,9 +844,6 @@
         "hideLegendNodes": "Typelegende veld verbergen",
         "reloadNodeTemplates": "Herlaad knooppuntsjablonen",
         "loadWorkflow": "Laad werkstroom",
-        "resetWorkflow": "Herstel werkstroom",
-        "resetWorkflowDesc": "Weet je zeker dat je deze werkstroom wilt herstellen?",
-        "resetWorkflowDesc2": "Herstel van een werkstroom haalt alle knooppunten, randen en werkstroomdetails weg.",
         "downloadWorkflow": "Download JSON van werkstroom",
         "booleanPolymorphicDescription": "Een verzameling Booleanse waarden.",
         "scheduler": "Planner",

invokeai/frontend/web/public/locales/ru.json

@@ -909,9 +909,6 @@
         "hideLegendNodes": "Скрыть тип поля",
         "showMinimapnodes": "Показать миникарту",
         "loadWorkflow": "Загрузить рабочий процесс",
-        "resetWorkflowDesc2": "Сброс рабочего процесса очистит все узлы, ребра и детали рабочего процесса.",
-        "resetWorkflow": "Сбросить рабочий процесс",
-        "resetWorkflowDesc": "Вы уверены, что хотите сбросить этот рабочий процесс?",
         "reloadNodeTemplates": "Перезагрузить шаблоны узлов",
         "downloadWorkflow": "Скачать JSON рабочего процесса",
         "booleanPolymorphicDescription": "Коллекция логических значений.",
@@ -1599,7 +1596,6 @@
         "saveWorkflow": "Сохранить рабочий процесс",
         "openWorkflow": "Открытый рабочий процесс",
         "clearWorkflowSearchFilter": "Очистить фильтр поиска рабочих процессов",
-        "workflowEditorReset": "Сброс редактора рабочих процессов",
         "workflowLibrary": "Библиотека",
         "downloadWorkflow": "Скачать рабочий процесс",
         "noRecentWorkflows": "Нет недавних рабочих процессов",

invokeai/frontend/web/public/locales/zh_CN.json

@@ -892,11 +892,8 @@
     },
     "nodes": {
         "zoomInNodes": "放大",
-        "resetWorkflowDesc": "是否确定要重置工作流编辑器?",
-        "resetWorkflow": "重置工作流编辑器",
         "loadWorkflow": "加载工作流",
         "zoomOutNodes": "缩小",
-        "resetWorkflowDesc2": "重置工作流编辑器将清除所有节点、边际和节点图详情。不影响已保存的工作流。",
         "reloadNodeTemplates": "重载节点模板",
         "hideGraphNodes": "隐藏节点图信息",
         "fitViewportNodes": "自适应视图",
@@ -1637,7 +1634,6 @@
         "saveWorkflow": "保存工作流",
         "openWorkflow": "打开工作流",
         "clearWorkflowSearchFilter": "清除工作流检索过滤器",
-        "workflowEditorReset": "工作流编辑器重置",
         "workflowLibrary": "工作流库",
         "downloadWorkflow": "下载工作流",
         "noRecentWorkflows": "无最近工作流",

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts

@@ -144,6 +144,7 @@ export const buildCanvasImageToImageGraph = (
         type: 'l2i',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [
@@ -255,6 +256,7 @@ export const buildCanvasImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -295,6 +297,7 @@ export const buildCanvasImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts

@@ -191,6 +191,7 @@ export const buildCanvasInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts

@@ -199,6 +199,7 @@ export const buildCanvasOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts

@@ -266,6 +266,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -306,6 +307,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts

@@ -196,6 +196,7 @@ export const buildCanvasSDXLInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts

@@ -204,6 +204,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts

@@ -258,6 +258,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -288,6 +289,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts

@@ -246,6 +246,7 @@ export const buildCanvasTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -276,6 +277,7 @@ export const buildCanvasTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts

@@ -143,6 +143,7 @@ export const buildLinearImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts

@@ -154,6 +154,7 @@ export const buildLinearSDXLImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts

@@ -127,6 +127,7 @@ export const buildLinearSDXLTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts

@@ -146,6 +146,7 @@ export const buildLinearTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "3.4.0post2"
+__version__ = "3.5.0rc2"

tests/backend/tiles/test_tiles.py

@@ -305,9 +305,7 @@ def test_calc_tiles_min_overlap_input_validation(
 
 def test_calc_tiles_even_split_single_tile():
     """Test calc_tiles_even_split() behavior when a single tile covers the image."""
-    tiles = calc_tiles_even_split(
-        image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap=64)
 
     expected_tiles = [
         Tile(
@@ -322,36 +320,34 @@ def test_calc_tiles_even_split_single_tile():
 def test_calc_tiles_even_split_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image is evenly covered by multiple tiles."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=320, left=0, right=624),
-            overlap=TBLR(top=0, bottom=72, left=0, right=136),
+            coords=TBLR(top=0, bottom=320, left=0, right=576),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=488, right=1112),
-            overlap=TBLR(top=0, bottom=72, left=136, right=136),
+            coords=TBLR(top=0, bottom=320, left=512, right=1088),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=976, right=1600),
-            overlap=TBLR(top=0, bottom=72, left=136, right=0),
+            coords=TBLR(top=0, bottom=320, left=1024, right=1600),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=248, bottom=576, left=0, right=624),
-            overlap=TBLR(top=72, bottom=0, left=0, right=136),
+            coords=TBLR(top=256, bottom=576, left=0, right=576),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=488, right=1112),
-            overlap=TBLR(top=72, bottom=0, left=136, right=136),
+            coords=TBLR(top=256, bottom=576, left=512, right=1088),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=976, right=1600),
-            overlap=TBLR(top=72, bottom=0, left=136, right=0),
+            coords=TBLR(top=256, bottom=576, left=1024, right=1600),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
     assert tiles == expected_tiles
@@ -360,36 +356,34 @@ def test_calc_tiles_even_split_evenly_divisible():
 def test_calc_tiles_even_split_not_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image requires 'uneven' overlaps to achieve proper coverage."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=224, left=0, right=464),
-            overlap=TBLR(top=0, bottom=56, left=0, right=104),
+            coords=TBLR(top=0, bottom=232, left=0, right=440),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=360, right=824),
-            overlap=TBLR(top=0, bottom=56, left=104, right=104),
+            coords=TBLR(top=0, bottom=232, left=376, right=816),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=720, right=1200),
-            overlap=TBLR(top=0, bottom=56, left=104, right=0),
+            coords=TBLR(top=0, bottom=232, left=752, right=1200),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=168, bottom=400, left=0, right=464),
-            overlap=TBLR(top=56, bottom=0, left=0, right=104),
+            coords=TBLR(top=168, bottom=400, left=0, right=440),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=360, right=824),
-            overlap=TBLR(top=56, bottom=0, left=104, right=104),
+            coords=TBLR(top=168, bottom=400, left=376, right=816),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=720, right=1200),
-            overlap=TBLR(top=56, bottom=0, left=104, right=0),
+            coords=TBLR(top=168, bottom=400, left=752, right=1200),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -399,28 +393,26 @@ def test_calc_tiles_even_split_not_evenly_divisible():
 def test_calc_tiles_even_split_difficult_size():
     """Test calc_tiles_even_split() behavior when the image is a difficult size to spilt evenly and keep div8."""
     # Parameters are a difficult size for other tile gen routines to calculate
-    tiles = calc_tiles_even_split(
-        image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=560, left=0, right=560),
-            overlap=TBLR(top=0, bottom=128, left=0, right=128),
+            coords=TBLR(top=0, bottom=528, left=0, right=528),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=560, left=432, right=1000),
-            overlap=TBLR(top=0, bottom=128, left=128, right=0),
+            coords=TBLR(top=0, bottom=528, left=464, right=1000),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=0, right=560),
-            overlap=TBLR(top=128, bottom=0, left=0, right=128),
+            coords=TBLR(top=464, bottom=1000, left=0, right=528),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=432, right=1000),
-            overlap=TBLR(top=128, bottom=0, left=128, right=0),
+            coords=TBLR(top=464, bottom=1000, left=464, right=1000),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -428,11 +420,13 @@ def test_calc_tiles_even_split_difficult_size():
 
 
 @pytest.mark.parametrize(
-    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap_fraction", "raises"],
+    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap", "raises"],
     [
-        (128, 128, 1, 1, 0.25, False),  # OK
+        (128, 128, 1, 1, 127, False),  # OK
         (128, 128, 1, 1, 0, False),  # OK
-        (128, 128, 2, 1, 0, False),  # OK
+        (128, 128, 2, 2, 0, False),  # OK
+        (128, 128, 2, 1, 120, True),  # overlap equals tile_height.
+        (128, 128, 1, 2, 120, True),  # overlap equals tile_width.
         (127, 127, 1, 1, 0, True),  # image size must be dividable by 8
     ],
 )
@@ -441,15 +435,15 @@ def test_calc_tiles_even_split_input_validation(
     image_width: int,
     num_tiles_x: int,
     num_tiles_y: int,
-    overlap_fraction: float,
+    overlap: int,
     raises: bool,
 ):
     """Test that calc_tiles_even_split() raises an exception if the inputs are invalid."""
     if raises:
-        with pytest.raises(ValueError):
-            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        with pytest.raises((AssertionError, ValueError)):
+            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
     else:
-        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
 
 
 #############################################