feat(nodes): add config to limit size of images in denoising

This serves as a relatively crude way to prevent OOM errors during denoising (and any operations downstream of the denoising step, like the VAE decode in Linear UI graphs).

- Add `max_image_size` config options - this is the total number of pixels eg the area
- Add logic to `denoise_latents` to scale the `latents` and `noise` to fit this
- Add logic to `color_correct` to scale the reference and mask to fit the image

invokeai/app/invocations/image.py

@@ -645,13 +645,19 @@ class ColorCorrectInvocation(BaseInvocation):
     mask_blur_radius: float = InputField(default=8, description="Mask blur radius")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
+        result = context.services.images.get_pil_image(self.image.image_name).convert("RGBA")
+
+        init_image = context.services.images.get_pil_image(self.reference.image_name)
+        # fit reference image to the input image
+        if init_image.size != result.size:
+            init_image = init_image.resize((result.width, result.height), Image.BILINEAR)
+
         pil_init_mask = None
         if self.mask is not None:
             pil_init_mask = context.services.images.get_pil_image(self.mask.image_name).convert("L")
-
-        init_image = context.services.images.get_pil_image(self.reference.image_name)
-
-        result = context.services.images.get_pil_image(self.image.image_name).convert("RGBA")
+            # fit mask to the input image
+            if pil_init_mask.size != result.size:
+                pil_init_mask = pil_init_mask.resize((result.width, result.height), Image.BILINEAR)
 
         # if init_image is None or init_mask is None:
         #    return result

invokeai/app/invocations/latent.py

@@ -77,6 +77,25 @@ DEFAULT_PRECISION = choose_precision(choose_torch_device())
 SAMPLER_NAME_VALUES = Literal[tuple(list(SCHEDULER_MAP.keys()))]
 
 
+def fit_latents(latents: torch.Tensor, max_latents_size: int, device: torch.device) -> torch.Tensor:
+    if max_latents_size == 0:
+        return latents
+
+    latents_area = latents.shape[2] * latents.shape[3]
+    if latents_area <= max_latents_size:
+        return latents
+
+    scale_factor = np.sqrt(max_latents_size / latents_area)
+    scaled_latents = torch.nn.functional.interpolate(
+        latents.to(device),
+        scale_factor=scale_factor,
+        mode="bilinear",
+        antialias=True,
+    )
+
+    return scaled_latents
+
+
 @invocation_output("scheduler_output")
 class SchedulerOutput(BaseInvocationOutput):
     scheduler: SAMPLER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
@@ -500,14 +519,20 @@ class DenoiseLatentsInvocation(BaseInvocation):
         with SilenceWarnings():  # this quenches NSFW nag from diffusers
             seed = None
             noise = None
+            max_image_size = context.services.configuration.max_image_size
+
             if self.noise is not None:
                 noise = context.services.latents.get(self.noise.latents_name)
                 seed = self.noise.seed
+                noise = fit_latents(latents=noise, max_latents_size=max_image_size // 64, device=choose_torch_device())
 
             if self.latents is not None:
                 latents = context.services.latents.get(self.latents.latents_name)
                 if seed is None:
                     seed = self.latents.seed
+                latents = fit_latents(
+                    latents=latents, max_latents_size=max_image_size // 64, device=choose_torch_device()
+                )
 
                 if noise is not None and noise.shape[1:] != latents.shape[1:]:
                     raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
@@ -532,8 +557,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             def _lora_loader():
                 for lora in self.unet.loras:
                     lora_info = context.services.model_manager.get_model(
-                        **lora.dict(exclude={"weight"}),
-                        context=context,
+                        **lora.dict(exclude={"weight"}), context=context
                     )
                     yield (lora_info.context.model, lora.weight)
                     del lora_info

invokeai/app/services/config/invokeai_config.py

@@ -255,6 +255,7 @@ class InvokeAIAppConfig(InvokeAISettings):
     attention_slice_size: Literal["auto", "balanced", "max", 1, 2, 3, 4, 5, 6, 7, 8] = Field(default="auto", description='Slice size, valid when attention_type=="sliced"', category="Generation", )
     force_tiled_decode  : bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty)", category="Generation",)
     force_tiled_decode: bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty)", category="Generation",)
+    max_image_size      : int = Field(default=512 * 512, description="The maximum size of images, in pixels. The maximum size for latents is inferred from this evaluating `max_image_size // 8`. If the size is exceeded during denoising, the latents will be resized.", category="Generation", )
 
     # QUEUE
     max_queue_size      : int = Field(default=10000, gt=0, description="Maximum number of items in the session queue", category="Queue", )
@@ -277,6 +278,7 @@ class InvokeAIAppConfig(InvokeAISettings):
 
     class Config:
         validate_assignment = True
+        env_prefix = "INVOKEAI"
 
     def parse_args(self, argv: Optional[list[str]] = None, conf: Optional[DictConfig] = None, clobber=False):
         """

invokeai/app/services/session_processor/session_processor_default.py

@@ -92,30 +92,34 @@ class DefaultSessionProcessor(SessionProcessorBase):
             self.__invoker.services.logger
             while not stop_event.is_set():
                 poll_now_event.clear()
+                try:
+                    # do not dequeue if there is already a session running
+                    if self.__queue_item is None and resume_event.is_set():
+                        queue_item = self.__invoker.services.session_queue.dequeue()
 
-                # do not dequeue if there is already a session running
-                if self.__queue_item is None and resume_event.is_set():
-                    queue_item = self.__invoker.services.session_queue.dequeue()
+                        if queue_item is not None:
+                            self.__invoker.services.logger.debug(f"Executing queue item {queue_item.item_id}")
+                            self.__queue_item = queue_item
+                            self.__invoker.services.graph_execution_manager.set(queue_item.session)
+                            self.__invoker.invoke(
+                                session_queue_batch_id=queue_item.batch_id,
+                                session_queue_id=queue_item.queue_id,
+                                session_queue_item_id=queue_item.item_id,
+                                graph_execution_state=queue_item.session,
+                                invoke_all=True,
+                            )
+                            queue_item = None
 
-                    if queue_item is not None:
-                        self.__invoker.services.logger.debug(f"Executing queue item {queue_item.item_id}")
-                        self.__queue_item = queue_item
-                        self.__invoker.services.graph_execution_manager.set(queue_item.session)
-                        self.__invoker.invoke(
-                            session_queue_batch_id=queue_item.batch_id,
-                            session_queue_id=queue_item.queue_id,
-                            session_queue_item_id=queue_item.item_id,
-                            graph_execution_state=queue_item.session,
-                            invoke_all=True,
-                        )
-                        queue_item = None
-
-                if queue_item is None:
-                    self.__invoker.services.logger.debug("Waiting for next polling interval or event")
+                    if queue_item is None:
+                        self.__invoker.services.logger.debug("Waiting for next polling interval or event")
+                        poll_now_event.wait(POLLING_INTERVAL)
+                        continue
+                except Exception as e:
+                    self.__invoker.services.logger.error(f"Error in session processor: {e}")
                     poll_now_event.wait(POLLING_INTERVAL)
                     continue
         except Exception as e:
-            self.__invoker.services.logger.error(f"Error in session processor: {e}")
+            self.__invoker.services.logger.error(f"Fatal Error in session processor: {e}")
             pass
         finally:
             stop_event.clear()

invokeai/frontend/web/dist/index.html

@@ -12,7 +12,7 @@
         margin: 0;
       }
     </style>
-    <script type="module" crossorigin src="./assets/index-eac60e23.js"></script>
+    <script type="module" crossorigin src="./assets/index-f6c3f475.js"></script>
   </head>
 
   <body dir="ltr">

invokeai/frontend/web/dist/locales/en.json

@@ -13,15 +13,14 @@
         "reset": "Reset",
         "rotateClockwise": "Rotate Clockwise",
         "rotateCounterClockwise": "Rotate Counter-Clockwise",
-        "showGalleryPanel": "Show Gallery Panel",
+        "showGallery": "Show Gallery",
         "showOptionsPanel": "Show Side Panel",
         "toggleAutoscroll": "Toggle autoscroll",
         "toggleLogViewer": "Toggle Log Viewer",
         "uploadImage": "Upload Image",
         "useThisParameter": "Use this parameter",
         "zoomIn": "Zoom In",
-        "zoomOut": "Zoom Out",
-        "loadMore": "Load More"
+        "zoomOut": "Zoom Out"
     },
     "boards": {
         "addBoard": "Add Board",
@@ -111,7 +110,6 @@
         "statusModelChanged": "Model Changed",
         "statusModelConverted": "Model Converted",
         "statusPreparing": "Preparing",
-        "statusProcessing": "Processing",
         "statusProcessingCanceled": "Processing Canceled",
         "statusProcessingComplete": "Processing Complete",
         "statusRestoringFaces": "Restoring Faces",
@@ -205,81 +203,6 @@
         "incompatibleModel": "Incompatible base model:",
         "noMatchingEmbedding": "No matching Embeddings"
     },
-    "queue": {
-        "queue": "Queue",
-        "queueFront": "Add to Front of Queue",
-        "queueBack": "Add to Queue",
-        "queueCountPrediction": "Add {{predicted}} to Queue",
-        "queueMaxExceeded": "Max of {{max_queue_size}} exceeded, would skip {{skip}}",
-        "queuedCount": "{{pending}} Pending",
-        "queueTotal": "{{total}} Total",
-        "queueEmpty": "Queue Empty",
-        "enqueueing": "Queueing Batch",
-        "resume": "Resume",
-        "resumeTooltip": "Resume Processor",
-        "resumeSucceeded": "Processor Resumed",
-        "resumeFailed": "Problem Resuming Processor",
-        "pause": "Pause",
-        "pauseTooltip": "Pause Processor",
-        "pauseSucceeded": "Processor Paused",
-        "pauseFailed": "Problem Pausing Processor",
-        "cancel": "Cancel",
-        "cancelTooltip": "Cancel Current Item",
-        "cancelSucceeded": "Item Canceled",
-        "cancelFailed": "Problem Canceling Item",
-        "prune": "Prune",
-        "pruneTooltip": "Prune {{item_count}} Completed Items",
-        "pruneSucceeded": "Pruned {{item_count}} Completed Items from Queue",
-        "pruneFailed": "Problem Pruning Queue",
-        "clear": "Clear",
-        "clearTooltip": "Cancel and Clear All Items",
-        "clearSucceeded": "Queue Cleared",
-        "clearFailed": "Problem Clearing Queue",
-        "cancelBatch": "Cancel Batch",
-        "cancelItem": "Cancel Item",
-        "cancelBatchSucceeded": "Batch Canceled",
-        "cancelBatchFailed": "Problem Canceling Batch",
-        "clearQueueAlertDialog": "Clearing the queue immediately cancels any processing items and clears the queue entirely.",
-        "clearQueueAlertDialog2": "Are you sure you want to clear the queue?",
-        "current": "Current",
-        "next": "Next",
-        "status": "Status",
-        "total": "Total",
-        "pending": "Pending",
-        "in_progress": "In Progress",
-        "completed": "Completed",
-        "failed": "Failed",
-        "canceled": "Canceled",
-        "completedIn": "Completed in",
-        "batch": "Batch",
-        "item": "Item",
-        "session": "Session",
-        "batchValues": "Batch Values",
-        "notReady": "Unable to Queue",
-        "batchQueued": "Batch Queued",
-        "batchQueuedDesc": "Added {{item_count}} sessions to {{direction}} of queue",
-        "front": "front",
-        "back": "back",
-        "batchFailedToQueue": "Failed to Queue Batch",
-        "graphQueued": "Graph queued",
-        "graphFailedToQueue": "Failed to queue graph"
-    },
-    "invocationCache": {
-        "invocationCache": "Invocation Cache",
-        "cacheSize": "Cache Size",
-        "maxCacheSize": "Max Cache Size",
-        "hits": "Cache Hits",
-        "misses": "Cache Misses",
-        "clear": "Clear",
-        "clearSucceeded": "Invocation Cache Cleared",
-        "clearFailed": "Problem Clearing Invocation Cache",
-        "enable": "Enable",
-        "enableSucceeded": "Invocation Cache Enabled",
-        "enableFailed": "Problem Enabling Invocation Cache",
-        "disable": "Disable",
-        "disableSucceeded": "Invocation Cache Disabled",
-        "disableFailed": "Problem Disabling Invocation Cache"
-    },
     "gallery": {
         "allImagesLoaded": "All Images Loaded",
         "assets": "Assets",
@@ -718,8 +641,7 @@
         "collectionItemDescription": "TODO",
         "colorCodeEdges": "Color-Code Edges",
         "colorCodeEdgesHelp": "Color-code edges according to their connected fields",
-        "colorCollection": "A collection of colors.",
-        "colorCollectionDescription": "TODO",
+        "colorCollectionDescription": "A collection of colors.",
         "colorField": "Color",
         "colorFieldDescription": "A RGBA color.",
         "colorPolymorphic": "Color Polymorphic",
@@ -766,8 +688,7 @@
         "imageFieldDescription": "Images may be passed between nodes.",
         "imagePolymorphic": "Image Polymorphic",
         "imagePolymorphicDescription": "A collection of images.",
-        "inputField": "Input Field",
-        "inputFields": "Input Fields",
+        "inputFields": "Input Feilds",
         "inputMayOnlyHaveOneConnection": "Input may only have one connection",
         "inputNode": "Input Node",
         "integer": "Integer",
@@ -785,7 +706,6 @@
         "latentsPolymorphicDescription": "Latents may be passed between nodes.",
         "loadingNodes": "Loading Nodes...",
         "loadWorkflow": "Load Workflow",
-        "noWorkflow": "No Workflow",
         "loRAModelField": "LoRA",
         "loRAModelFieldDescription": "TODO",
         "mainModelField": "Model",
@@ -807,15 +727,14 @@
         "noImageFoundState": "No initial image found in state",
         "noMatchingNodes": "No matching nodes",
         "noNodeSelected": "No node selected",
-        "nodeOpacity": "Node Opacity",
+        "noOpacity": "Node Opacity",
         "noOutputRecorded": "No outputs recorded",
         "noOutputSchemaName": "No output schema name found in ref object",
         "notes": "Notes",
         "notesDescription": "Add notes about your workflow",
         "oNNXModelField": "ONNX Model",
         "oNNXModelFieldDescription": "ONNX model field.",
-        "outputField": "Output Field",
-        "outputFields": "Output Fields",
+        "outputFields": "Output Feilds",
         "outputNode": "Output node",
         "outputSchemaNotFound": "Output schema not found",
         "pickOne": "Pick One",
@@ -864,7 +783,6 @@
         "unknownNode": "Unknown Node",
         "unknownTemplate": "Unknown Template",
         "unkownInvocation": "Unknown Invocation type",
-        "updateNode": "Update Node",
         "updateApp": "Update App",
         "vaeField": "Vae",
         "vaeFieldDescription": "Vae submodel.",
@@ -901,7 +819,6 @@
         },
         "cfgScale": "CFG Scale",
         "clipSkip": "CLIP Skip",
-        "clipSkipWithLayerCount": "CLIP Skip {{layerCount}}",
         "closeViewer": "Close Viewer",
         "codeformerFidelity": "Fidelity",
         "coherenceMode": "Mode",
@@ -940,7 +857,6 @@
             "noInitialImageSelected": "No initial image selected",
             "noModelForControlNet": "ControlNet {{index}} has no model selected.",
             "noModelSelected": "No model selected",
-            "noPrompts": "No prompts generated",
             "noNodesInGraph": "No nodes in graph",
             "readyToInvoke": "Ready to Invoke",
             "systemBusy": "System busy",
@@ -959,12 +875,7 @@
         "perlinNoise": "Perlin Noise",
         "positivePromptPlaceholder": "Positive Prompt",
         "randomizeSeed": "Randomize Seed",
-        "manualSeed": "Manual Seed",
-        "randomSeed": "Random Seed",
         "restoreFaces": "Restore Faces",
-        "iterations": "Iterations",
-        "iterationsWithCount_one": "{{count}} Iteration",
-        "iterationsWithCount_other": "{{count}} Iterations",
         "scale": "Scale",
         "scaleBeforeProcessing": "Scale Before Processing",
         "scaledHeight": "Scaled H",
@@ -975,17 +886,13 @@
         "seamlessTiling": "Seamless Tiling",
         "seamlessXAxis": "X Axis",
         "seamlessYAxis": "Y Axis",
-        "seamlessX": "Seamless X",
-        "seamlessY": "Seamless Y",
-        "seamlessX&Y": "Seamless X & Y",
         "seamLowThreshold": "Low",
         "seed": "Seed",
         "seedWeights": "Seed Weights",
-        "imageActions": "Image Actions",
         "sendTo": "Send to",
         "sendToImg2Img": "Send to Image to Image",
         "sendToUnifiedCanvas": "Send To Unified Canvas",
-        "showOptionsPanel": "Show Side Panel (O or T)",
+        "showOptionsPanel": "Show Options Panel",
         "showPreview": "Show Preview",
         "shuffle": "Shuffle Seed",
         "steps": "Steps",
@@ -994,13 +901,11 @@
         "tileSize": "Tile Size",
         "toggleLoopback": "Toggle Loopback",
         "type": "Type",
-        "upscale": "Upscale (Shift + U)",
+        "upscale": "Upscale",
         "upscaleImage": "Upscale Image",
         "upscaling": "Upscaling",
         "useAll": "Use All",
         "useCpuNoise": "Use CPU Noise",
-        "cpuNoise": "CPU Noise",
-        "gpuNoise": "GPU Noise",
         "useInitImg": "Use Initial Image",
         "usePrompt": "Use Prompt",
         "useSeed": "Use Seed",
@@ -1009,20 +914,11 @@
         "vSymmetryStep": "V Symmetry Step",
         "width": "Width"
     },
-    "dynamicPrompts": {
+    "prompt": {
         "combinatorial": "Combinatorial Generation",
         "dynamicPrompts": "Dynamic Prompts",
         "enableDynamicPrompts": "Enable Dynamic Prompts",
-        "maxPrompts": "Max Prompts",
-        "promptsWithCount_one": "{{count}} Prompt",
-        "promptsWithCount_other": "{{count}} Prompts",
-        "seedBehaviour": {
-            "label": "Seed Behaviour",
-            "perIterationLabel": "Seed per Iteration",
-            "perIterationDesc": "Use a different seed for each iteration",
-            "perPromptLabel": "Seed per Prompt",
-            "perPromptDesc": "Use a different seed for each prompt"
-        }
+        "maxPrompts": "Max Prompts"
     },
     "sdxl": {
         "cfgScale": "CFG Scale",
@@ -1170,136 +1066,6 @@
             "variations": "Try a variation with a value between 0.1 and 1.0 to change the result for a given seed. Interesting variations of the seed are between 0.1 and 0.3."
         }
     },
-    "popovers": {
-        "clipSkip": {
-            "heading": "CLIP Skip",
-            "paragraph": "Choose how many layers of the CLIP model to skip. Certain models are better suited to be used with CLIP Skip."
-        },
-        "compositingBlur": {
-            "heading": "Blur",
-            "paragraph": "The blur radius of the mask."
-        },
-        "compositingBlurMethod": {
-            "heading": "Blur Method",
-            "paragraph": "The method of blur applied to the masked area."
-        },
-        "compositingCoherencePass": {
-            "heading": "Coherence Pass",
-            "paragraph": "Composite the Inpainted/Outpainted images."
-        },
-        "compositingCoherenceMode": {
-            "heading": "Mode",
-            "paragraph": "The mode of the Coherence Pass."
-        },
-        "compositingCoherenceSteps": {
-            "heading": "Steps",
-            "paragraph": "Number of steps in the Coherence Pass. Similar to Denoising Steps."
-        },
-        "compositingStrength": {
-            "heading": "Strength",
-            "paragraph": "Amount of noise added for the Coherence Pass. Similar to Denoising Strength."
-        },
-        "compositingMaskAdjustments": {
-            "heading": "Mask Adjustments",
-            "paragraph": "Adjust the mask."
-        },
-        "controlNetBeginEnd": {
-            "heading": "Begin / End Step Percentage",
-            "paragraph": "Which parts of the denoising process will have the ControlNet applied. ControlNets applied at the start of the process guide composition, and ControlNets applied at the end guide details."
-        },
-        "controlNetControlMode": {
-            "heading": "Control Mode",
-            "paragraph": "Lends more weight to either the prompt or ControlNet."
-        },
-        "controlNetResizeMode": {
-            "heading": "Resize Mode",
-            "paragraph": "How the ControlNet image will be fit to the image generation Ratio"
-        },
-        "controlNetToggle": {
-            "heading": "Enable ControlNet",
-            "paragraph": "ControlNets provide guidance to the generation process, helping create images with controlled composition, structure, or style, depending on the model selected."
-        },
-        "controlNetWeight": {
-            "heading": "Weight",
-            "paragraph": "How strongly the ControlNet will impact the generated image."
-        },
-        "dynamicPromptsToggle": {
-            "heading": "Enable Dynamic Prompts",
-            "paragraph": "Dynamic prompts allow multiple options within a prompt. Dynamic prompts can be used by: {option1|option2|option3}. Combinations of prompts will be randomly generated until the “Images” number has been reached."
-        },
-        "dynamicPromptsCombinatorial": {
-            "heading": "Combinatorial Generation",
-            "paragraph": "Generate an image for every possible combination of Dynamic Prompts until the Max Prompts is reached."
-        },
-        "infillMethod": {
-            "heading": "Infill Method",
-            "paragraph": "Method to infill the selected area."
-        },
-        "lora": {
-            "heading": "LoRA Weight",
-            "paragraph": "Weight of the LoRA. Higher weight will lead to larger impacts on the final image."
-        },
-        "noiseEnable": {
-            "heading": "Enable Noise Settings",
-            "paragraph": "Advanced control over noise generation."
-        },
-        "noiseUseCPU": {
-            "heading": "Use CPU Noise",
-            "paragraph": "Uses the CPU to generate random noise."
-        },
-        "paramCFGScale": {
-            "heading": "CFG Scale",
-            "paragraph": "Controls how much your prompt influences the generation process."
-        },
-        "paramDenoisingStrength": {
-            "heading": "Denoising Strength",
-            "paragraph": "How much noise is added to the input image. 0 will result in an identical image, while 1 will result in a completely new image."
-        },
-        "paramIterations": {
-            "heading": "Iterations",
-            "paragraph": "The number of images to generate. If Dynamic Prompts is enabled, each of the prompts will be generated this many times."
-        },
-        "paramModel": {
-            "heading": "Model",
-            "paragraph": "Model used for the denoising steps. Different models are trained to specialize in producing different aesthetic results and content."
-        },
-        "paramNegativeConditioning": {
-            "heading": "Negative Prompt",
-            "paragraph": "The generation process avoids the concepts in the negative prompt. Use this to exclude qualities or objects from the output. Supports Compel syntax and embeddings."
-        },
-        "paramPositiveConditioning": {
-            "heading": "Positive Prompt",
-            "paragraph": "Guides the generation process. You may use any words or phrases. Supports Compel and Dynamic Prompts syntaxes and embeddings."
-        },
-        "paramRatio": {
-            "heading": "Ratio",
-            "paragraph": "The ratio of the dimensions of the image generated. An image size (in number of pixels) equivalent to 512x512 is recommended for SD1.5 models and a size equivalent to 1024x1024 is recommended for SDXL models."
-        },
-        "paramScheduler": {
-            "heading": "Scheduler",
-            "paragraph": "Scheduler defines how to iteratively add noise to an image or how to update a sample based on a model's output."
-        },
-        "paramSeed": {
-            "heading": "Seed",
-            "paragraph": "Controls the starting noise used for generation. Disable “Random Seed” to produce identical results with the same generation settings."
-        },
-        "paramSteps": {
-            "heading": "Steps",
-            "paragraph": "Number of steps that will be performed in each generation. Higher step counts will typically create better images but will require more generation time."
-        },
-        "paramVAE": {
-            "heading": "VAE",
-            "paragraph": "Model used for translating AI output into the final image."
-        },
-        "paramVAEPrecision": {
-            "heading": "VAE Precision",
-            "paragraph": "The precision used during VAE encoding and decoding. Fp16/Half precision is more efficient, at the expense of minor image variations."
-        },
-        "scaleBeforeProcessing": {
-            "heading": "Scale Before Processing",
-            "paragraph": "Scales the selected area to the size best suited for the model before the image generation process."
-        }
-    },
     "ui": {
         "hideProgressImages": "Hide Progress Images",
         "lockRatio": "Lock Ratio",

invokeai/frontend/web/src/app/components/App.tsx

@@ -36,7 +36,8 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
 
   const logger = useLogger('system');
   const dispatch = useAppDispatch();
-  const { handlePreselectedImage } = usePreselectedImage();
+  const { handleSendToCanvas, handleSendToImg2Img, handleUseAllMetadata } =
+    usePreselectedImage(selectedImage?.imageName);
   const handleReset = useCallback(() => {
     localStorage.clear();
     location.reload();
@@ -59,8 +60,22 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   }, [dispatch]);
 
   useEffect(() => {
-    handlePreselectedImage(selectedImage);
-  }, [handlePreselectedImage, selectedImage]);
+    if (selectedImage && selectedImage.action === 'sendToCanvas') {
+      handleSendToCanvas();
+    }
+  }, [selectedImage, handleSendToCanvas]);
+
+  useEffect(() => {
+    if (selectedImage && selectedImage.action === 'sendToImg2Img') {
+      handleSendToImg2Img();
+    }
+  }, [selectedImage, handleSendToImg2Img]);
+
+  useEffect(() => {
+    if (selectedImage && selectedImage.action === 'useAllParameters') {
+      handleUseAllMetadata();
+    }
+  }, [selectedImage, handleUseAllMetadata]);
 
   const headerComponent = useStore($headerComponent);
 

invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts

@@ -1,7 +1,7 @@
 import { skipToken } from '@reduxjs/toolkit/dist/query';
 import { CoreMetadata } from 'features/nodes/types/types';
 import { t } from 'i18next';
-import { useCallback, useState } from 'react';
+import { useCallback } from 'react';
 import { useAppToaster } from '../../../app/components/Toaster';
 import { useAppDispatch } from '../../../app/store/storeHooks';
 import {
@@ -13,70 +13,46 @@ import { setActiveTab } from '../../ui/store/uiSlice';
 import { initialImageSelected } from '../store/actions';
 import { useRecallParameters } from './useRecallParameters';
 
-type SelectedImage = {
-  imageName: string;
-  action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
-};
-
-export const usePreselectedImage = () => {
+export const usePreselectedImage = (imageName?: string) => {
   const dispatch = useAppDispatch();
-  const [imageNameForDto, setImageNameForDto] = useState<string | undefined>();
-  const [imageNameForMetadata, setImageNameForMetadata] = useState<
-    string | undefined
-  >();
+
   const { recallAllParameters } = useRecallParameters();
   const toaster = useAppToaster();
 
   const { currentData: selectedImageDto } = useGetImageDTOQuery(
-    imageNameForDto ?? skipToken
+    imageName ?? skipToken
   );
 
   const { currentData: selectedImageMetadata } = useGetImageMetadataQuery(
-    imageNameForMetadata ?? skipToken
+    imageName ?? skipToken
   );
 
-  const handlePreselectedImage = useCallback(
-    (selectedImage?: SelectedImage) => {
-      if (!selectedImage) {
-        return;
-      }
+  const handleSendToCanvas = useCallback(() => {
+    if (selectedImageDto) {
+      dispatch(setInitialCanvasImage(selectedImageDto));
+      dispatch(setActiveTab('unifiedCanvas'));
+      toaster({
+        title: t('toast.sentToUnifiedCanvas'),
+        status: 'info',
+        duration: 2500,
+        isClosable: true,
+      });
+    }
+  }, [dispatch, toaster, selectedImageDto]);
 
-      if (selectedImage.action === 'sendToCanvas') {
-        setImageNameForDto(selectedImage?.imageName);
-        if (selectedImageDto) {
-          dispatch(setInitialCanvasImage(selectedImageDto));
-          dispatch(setActiveTab('unifiedCanvas'));
-          toaster({
-            title: t('toast.sentToUnifiedCanvas'),
-            status: 'info',
-            duration: 2500,
-            isClosable: true,
-          });
-        }
-      }
+  const handleSendToImg2Img = useCallback(() => {
+    if (selectedImageDto) {
+      dispatch(initialImageSelected(selectedImageDto));
+    }
+  }, [dispatch, selectedImageDto]);
 
-      if (selectedImage.action === 'sendToImg2Img') {
-        setImageNameForDto(selectedImage?.imageName);
-        if (selectedImageDto) {
-          dispatch(initialImageSelected(selectedImageDto));
-        }
-      }
+  const handleUseAllMetadata = useCallback(() => {
+    if (selectedImageMetadata) {
+      recallAllParameters(selectedImageMetadata.metadata as CoreMetadata);
+    }
+    // disabled because `recallAllParameters` changes the model, but its dep to prepare LoRAs has model as a dep. this introduces circular logic that causes infinite re-renders
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [selectedImageMetadata]);
 
-      if (selectedImage.action === 'useAllParameters') {
-        setImageNameForMetadata(selectedImage?.imageName);
-        if (selectedImageMetadata) {
-          recallAllParameters(selectedImageMetadata.metadata as CoreMetadata);
-        }
-      }
-    },
-    [
-      dispatch,
-      selectedImageDto,
-      selectedImageMetadata,
-      recallAllParameters,
-      toaster,
-    ]
-  );
-
-  return { handlePreselectedImage };
+  return { handleSendToCanvas, handleSendToImg2Img, handleUseAllMetadata };
 };

invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts

@@ -21,7 +21,7 @@ import {
   loraModelsAdapter,
   useGetLoRAModelsQuery,
 } from '../../../services/api/endpoints/models';
-import { loraRecalled } from '../../lora/store/loraSlice';
+import { loraRecalled, lorasCleared } from '../../lora/store/loraSlice';
 import { initialImageSelected, modelSelected } from '../store/actions';
 import {
   setCfgScale,
@@ -509,6 +509,7 @@ export const useRecallParameters = () => {
         dispatch(setRefinerStart(refiner_start));
       }
 
+      dispatch(lorasCleared());
       loras?.forEach((lora) => {
         const result = prepareLoRAMetadataItem(lora);
         if (result.lora) {

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "3.2.0rc2"
+__version__ = "3.1.1"

tests/test_config.py

@@ -121,6 +121,12 @@ def test_env_override(patch_rootdir):
     conf.parse_args(conf=init1, argv=[])
     assert conf.max_cache_size == 20
 
+    # make sure that prefix is respected
+    del os.environ["INVOKEAI_always_use_cpu"]
+    os.environ["always_use_cpu"] = "True"
+    conf.parse_args(conf=init1, argv=[])
+    assert conf.always_use_cpu is False
+
 
 def test_root_resists_cwd(patch_rootdir):
     from invokeai.app.services.config import InvokeAIAppConfig