fix(ui): CA processor cancellation

When a control adapter processor config is changed, if we were already processing an image, that batch is immediately canceled. This prevents the processed image from getting stuck in a weird state if you change or reset the processor at the right (err, wrong?) moment.

- Update internal state for control adapters to track processor batches, instead of just having a flag indicating if the image is processing. Add a slice migration to not break the user's existing app state.
- Update preprocessor listener with more sophisticated logic to handle canceling the batch and resetting the processed image when the config changes or is reset.
- Fixed error handling that erroneously showed "failed to queue graph" errors when an active listener instance is canceled, need to check the abort signal.
This commit is contained in:
psychedelicious 2024-05-10 09:52:00 +10:00
parent da61396b1c
commit 2656f13a4a
6 changed files with 119 additions and 91 deletions

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@ -1,13 +1,14 @@
import { isAnyOf } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { AppDispatch } from 'app/store/store';
import { parseify } from 'common/util/serialize';
import {
caLayerImageChanged,
caLayerIsProcessingImageChanged,
caLayerModelChanged,
caLayerProcessedImageChanged,
caLayerProcessorConfigChanged,
caLayerProcessorPendingBatchIdChanged,
caLayerRecalled,
isControlAdapterLayer,
} from 'features/controlLayers/store/controlLayersSlice';
@ -15,47 +16,39 @@ import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
import { isImageOutput } from 'features/nodes/types/common';
import { addToast } from 'features/system/store/systemSlice';
import { t } from 'i18next';
import { isEqual } from 'lodash-es';
import { imagesApi } from 'services/api/endpoints/images';
import { getImageDTO } from 'services/api/endpoints/images';
import { queueApi } from 'services/api/endpoints/queue';
import type { BatchConfig, ImageDTO } from 'services/api/types';
import type { BatchConfig } from 'services/api/types';
import { socketInvocationComplete } from 'services/events/actions';
import { assert } from 'tsafe';
const matcher = isAnyOf(caLayerImageChanged, caLayerProcessorConfigChanged, caLayerModelChanged, caLayerRecalled);
const DEBOUNCE_MS = 300;
const log = logger('session');
/**
* Simple helper to cancel a batch and reset the pending batch ID
*/
const cancelProcessorBatch = async (dispatch: AppDispatch, layerId: string, batchId: string) => {
const req = dispatch(queueApi.endpoints.cancelByBatchIds.initiate({ batch_ids: [batchId] }));
log.trace({ batchId }, 'Cancelling existing preprocessor batch');
try {
await req.unwrap();
} catch {
// no-op
} finally {
req.reset();
// Always reset the pending batch ID - the cancel req could fail if the batch doesn't exist
dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: null }));
}
};
export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
startAppListening({
matcher,
effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take }) => {
effect: async (action, { dispatch, getState, cancelActiveListeners, delay, take, signal }) => {
const layerId = caLayerRecalled.match(action) ? action.payload.id : action.payload.layerId;
const precheckLayerOriginal = getOriginalState()
.controlLayers.present.layers.filter(isControlAdapterLayer)
.find((l) => l.id === layerId);
const precheckLayer = getState()
.controlLayers.present.layers.filter(isControlAdapterLayer)
.find((l) => l.id === layerId);
// Conditions to bail
const layerDoesNotExist = !precheckLayer;
const layerHasNoImage = !precheckLayer?.controlAdapter.image;
const layerHasNoProcessorConfig = !precheckLayer?.controlAdapter.processorConfig;
const layerIsAlreadyProcessingImage = precheckLayer?.controlAdapter.isProcessingImage;
const areImageAndProcessorUnchanged =
isEqual(precheckLayer?.controlAdapter.image, precheckLayerOriginal?.controlAdapter.image) &&
isEqual(precheckLayer?.controlAdapter.processorConfig, precheckLayerOriginal?.controlAdapter.processorConfig);
if (
layerDoesNotExist ||
layerHasNoImage ||
layerHasNoProcessorConfig ||
areImageAndProcessorUnchanged ||
layerIsAlreadyProcessingImage
) {
return;
}
// Cancel any in-progress instances of this listener
cancelActiveListeners();
@ -63,19 +56,31 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
// Delay before starting actual work
await delay(DEBOUNCE_MS);
dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: true }));
// Double-check that we are still eligible for processing
const state = getState();
const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
const image = layer?.controlAdapter.image;
const config = layer?.controlAdapter.processorConfig;
// If we have no image or there is no processor config, bail
if (!layer || !image || !config) {
if (!layer) {
return;
}
const image = layer.controlAdapter.image;
const config = layer.controlAdapter.processorConfig;
if (!image || !config) {
// The user has reset the image or config, so we should clear the processed image
dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null }));
}
// At this point, the user has stopped fiddling with the processor settings and there is a processor selected.
// If there is a pending processor batch, cancel it.
if (layer.controlAdapter.processorPendingBatchId) {
cancelProcessorBatch(dispatch, layerId, layer.controlAdapter.processorPendingBatchId);
}
// @ts-expect-error: TS isn't able to narrow the typing of buildNode and `config` will error...
const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config);
const enqueueBatchArg: BatchConfig = {
@ -83,7 +88,11 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
batch: {
graph: {
nodes: {
[processorNode.id]: { ...processorNode, is_intermediate: true },
[processorNode.id]: {
...processorNode,
// Control images are always intermediate - do not save to gallery
is_intermediate: true,
},
},
edges: [],
},
@ -91,16 +100,21 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
},
};
// Kick off the processor batch
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
fixedCacheKey: 'enqueueBatch',
})
);
try {
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
fixedCacheKey: 'enqueueBatch',
})
);
const enqueueResult = await req.unwrap();
req.reset();
// TODO(psyche): Update the pydantic models, pretty sure we will _always_ have a batch_id here, but the model says it's optional
assert(enqueueResult.batch.batch_id, 'Batch ID not returned from queue');
dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: enqueueResult.batch.batch_id }));
log.debug({ enqueueResult: parseify(enqueueResult) }, t('queue.graphQueued'));
// Wait for the processor node to complete
const [invocationCompleteAction] = await take(
(action): action is ReturnType<typeof socketInvocationComplete> =>
socketInvocationComplete.match(action) &&
@ -109,47 +123,52 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
);
// We still have to check the output type
if (isImageOutput(invocationCompleteAction.payload.data.result)) {
const { image_name } = invocationCompleteAction.payload.data.result.image;
assert(
isImageOutput(invocationCompleteAction.payload.data.result),
`Processor did not return an image output, got: ${invocationCompleteAction.payload.data.result}`
);
const { image_name } = invocationCompleteAction.payload.data.result.image;
// Wait for the ImageDTO to be received
const [{ payload }] = await take(
(action) =>
imagesApi.endpoints.getImageDTO.matchFulfilled(action) && action.payload.image_name === image_name
);
const imageDTO = await getImageDTO(image_name);
assert(imageDTO, "Failed to fetch processor output's image DTO");
const imageDTO = payload as ImageDTO;
log.debug({ layerId, imageDTO }, 'ControlNet image processed');
// Update the processed image in the store
dispatch(
caLayerProcessedImageChanged({
layerId,
imageDTO,
})
);
dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
}
// Whew! We made it. Update the layer with the processed image
log.debug({ layerId, imageDTO }, 'ControlNet image processed');
dispatch(caLayerProcessedImageChanged({ layerId, imageDTO }));
dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: null }));
} catch (error) {
log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
if (signal.aborted) {
// The listener was canceled - we need to cancel the pending processor batch, if there is one (could have changed by now).
const pendingBatchId = getState()
.controlLayers.present.layers.filter(isControlAdapterLayer)
.find((l) => l.id === layerId)?.controlAdapter.processorPendingBatchId;
if (pendingBatchId) {
cancelProcessorBatch(dispatch, layerId, pendingBatchId);
}
log.trace('Control Adapter preprocessor cancelled');
} else {
// Some other error condition...
console.log(error);
log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
if (error instanceof Object) {
if ('data' in error && 'status' in error) {
if (error.status === 403) {
dispatch(caLayerImageChanged({ layerId, imageDTO: null }));
return;
if (error instanceof Object) {
if ('data' in error && 'status' in error) {
if (error.status === 403) {
dispatch(caLayerImageChanged({ layerId, imageDTO: null }));
return;
}
}
}
}
dispatch(
addToast({
title: t('queue.graphFailedToQueue'),
status: 'error',
})
);
dispatch(
addToast({
title: t('queue.graphFailedToQueue'),
status: 'error',
})
);
}
} finally {
req.reset();
}
},
});

View File

@ -124,7 +124,7 @@ export const ControlAdapterImagePreview = memo(
controlImage &&
processedControlImage &&
!isMouseOverImage &&
!controlAdapter.isProcessingImage &&
!controlAdapter.processorPendingBatchId &&
controlAdapter.processorConfig !== null;
useEffect(() => {
@ -190,7 +190,7 @@ export const ControlAdapterImagePreview = memo(
/>
</>
{controlAdapter.isProcessingImage && (
{controlAdapter.processorPendingBatchId !== null && (
<Flex
position="absolute"
top={0}

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@ -27,7 +27,7 @@ import { modelChanged } from 'features/parameters/store/generationSlice';
import type { ParameterAutoNegative } from 'features/parameters/types/parameterSchemas';
import { getIsSizeOptimal, getOptimalDimension } from 'features/parameters/util/optimalDimension';
import type { IRect, Vector2d } from 'konva/lib/types';
import { isEqual, partition } from 'lodash-es';
import { isEqual, partition, unset } from 'lodash-es';
import { atom } from 'nanostores';
import type { RgbColor } from 'react-colorful';
import type { UndoableOptions } from 'redux-undo';
@ -49,7 +49,7 @@ import type {
} from './types';
export const initialControlLayersState: ControlLayersState = {
_version: 2,
_version: 3,
selectedLayerId: null,
brushSize: 100,
layers: [],
@ -334,13 +334,13 @@ export const controlLayersSlice = createSlice({
const layer = selectCALayerOrThrow(state, layerId);
layer.opacity = opacity;
},
caLayerIsProcessingImageChanged: (
caLayerProcessorPendingBatchIdChanged: (
state,
action: PayloadAction<{ layerId: string; isProcessingImage: boolean }>
action: PayloadAction<{ layerId: string; batchId: string | null }>
) => {
const { layerId, isProcessingImage } = action.payload;
const { layerId, batchId } = action.payload;
const layer = selectCALayerOrThrow(state, layerId);
layer.controlAdapter.isProcessingImage = isProcessingImage;
layer.controlAdapter.processorPendingBatchId = batchId;
},
//#endregion
@ -800,7 +800,7 @@ export const {
caLayerProcessorConfigChanged,
caLayerIsFilterEnabledChanged,
caLayerOpacityChanged,
caLayerIsProcessingImageChanged,
caLayerProcessorPendingBatchIdChanged,
// IPA Layers
ipaLayerAdded,
ipaLayerRecalled,
@ -857,7 +857,16 @@ export const selectControlLayersSlice = (state: RootState) => state.controlLayer
const migrateControlLayersState = (state: any): any => {
if (state._version === 1) {
// Reset state for users on v1 (e.g. beta users), some changes could cause
return deepClone(initialControlLayersState);
state = deepClone(initialControlLayersState);
}
if (state._version === 2) {
// The CA `isProcessingImage` flag was replaced with a `processorPendingBatchId` property, fix up CA layers
for (const layer of (state as ControlLayersState).layers) {
if (layer.type === 'control_adapter_layer') {
layer.controlAdapter.processorPendingBatchId = null;
unset(layer.controlAdapter, 'isProcessingImage');
}
}
}
return state;
};

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@ -113,7 +113,7 @@ export const zLayer = z.discriminatedUnion('type', [
export type Layer = z.infer<typeof zLayer>;
export type ControlLayersState = {
_version: 2;
_version: 3;
selectedLayerId: string | null;
layers: Layer[];
brushSize: number;

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@ -198,8 +198,8 @@ const zControlAdapterBase = z.object({
weight: z.number().gte(0).lte(1),
image: zImageWithDims.nullable(),
processedImage: zImageWithDims.nullable(),
isProcessingImage: z.boolean(),
processorConfig: zProcessorConfig.nullable(),
processorPendingBatchId: z.string().nullable().default(null),
beginEndStepPct: zBeginEndStepPct,
});
@ -521,8 +521,8 @@ export const initialControlNetV2: Omit<ControlNetConfigV2, 'id'> = {
controlMode: 'balanced',
image: null,
processedImage: null,
isProcessingImage: false,
processorConfig: CA_PROCESSOR_DATA.canny_image_processor.buildDefaults(),
processorPendingBatchId: null,
};
export const initialT2IAdapterV2: Omit<T2IAdapterConfigV2, 'id'> = {
@ -532,8 +532,8 @@ export const initialT2IAdapterV2: Omit<T2IAdapterConfigV2, 'id'> = {
beginEndStepPct: [0, 1],
image: null,
processedImage: null,
isProcessingImage: false,
processorConfig: CA_PROCESSOR_DATA.canny_image_processor.buildDefaults(),
processorPendingBatchId: null,
};
export const initialIPAdapterV2: Omit<IPAdapterConfigV2, 'id'> = {

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@ -587,7 +587,7 @@ const parseControlNetToControlAdapterLayer: MetadataParseFunc<ControlAdapterLaye
image: imageDTO ? imageDTOToImageWithDims(imageDTO) : null,
processedImage: processedImageDTO ? imageDTOToImageWithDims(processedImageDTO) : null,
processorConfig,
isProcessingImage: false,
processorPendingBatchId: null,
},
};
@ -651,7 +651,7 @@ const parseT2IAdapterToControlAdapterLayer: MetadataParseFunc<ControlAdapterLaye
image: imageDTO ? imageDTOToImageWithDims(imageDTO) : null,
processedImage: processedImageDTO ? imageDTOToImageWithDims(processedImageDTO) : null,
processorConfig,
isProcessingImage: false,
processorPendingBatchId: null,
},
};