mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
tidy(ui): remove unused graph helper
This commit is contained in:
psychedelicious
@ -1,518 +0,0 @@
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import { getStore } from 'app/store/nanostores/store';
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import type { RootState } from 'app/store/store';
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import { deepClone } from 'common/util/deepClone';
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import {
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isControlAdapterLayer,
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isInitialImageLayer,
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isIPAdapterLayer,
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isRegionalGuidanceLayer,
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rgLayerMaskImageUploaded,
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} from 'features/controlLayers/store/controlLayersSlice';
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import type { InitialImageLayer, Layer, RegionalGuidanceLayer } from 'features/controlLayers/store/types';
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import type {
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ControlNetConfigV2,
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ImageWithDims,
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IPAdapterConfigV2,
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ProcessorConfig,
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T2IAdapterConfigV2,
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} from 'features/controlLayers/util/controlAdapters';
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import { getRegionalPromptLayerBlobs } from 'features/controlLayers/util/getLayerBlobs';
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import type { ImageField } from 'features/nodes/types/common';
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import {
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CONTROL_NET_COLLECT,
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IMAGE_TO_LATENTS,
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IP_ADAPTER_COLLECT,
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PROMPT_REGION_INVERT_TENSOR_MASK_PREFIX,
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PROMPT_REGION_MASK_TO_TENSOR_PREFIX,
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PROMPT_REGION_NEGATIVE_COND_PREFIX,
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PROMPT_REGION_POSITIVE_COND_INVERTED_PREFIX,
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PROMPT_REGION_POSITIVE_COND_PREFIX,
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RESIZE,
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T2I_ADAPTER_COLLECT,
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} from 'features/nodes/util/graph/constants';
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import type { Graph } from 'features/nodes/util/graph/Graph';
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import { MetadataUtil } from 'features/nodes/util/graph/MetadataUtil';
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import { size } from 'lodash-es';
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import { getImageDTO, imagesApi } from 'services/api/endpoints/images';
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import type { BaseModelType, ImageDTO, Invocation } from 'services/api/types';
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import { assert } from 'tsafe';
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export const addControlLayersToGraph = async (
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state: RootState,
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g: Graph,
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denoise: Invocation<'denoise_latents'>,
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posCond: Invocation<'compel'> | Invocation<'sdxl_compel_prompt'>,
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negCond: Invocation<'compel'> | Invocation<'sdxl_compel_prompt'>,
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posCondCollect: Invocation<'collect'>,
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negCondCollect: Invocation<'collect'>,
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noise: Invocation<'noise'>
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): Promise<Layer[]> => {
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const mainModel = state.generation.model;
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assert(mainModel, 'Missing main model when building graph');
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const isSDXL = mainModel.base === 'sdxl';
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// Filter out layers with incompatible base model, missing control image
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const validLayers = state.controlLayers.present.layers.filter((l) => isValidLayer(l, mainModel.base));
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const validControlAdapters = validLayers.filter(isControlAdapterLayer).map((l) => l.controlAdapter);
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for (const ca of validControlAdapters) {
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addGlobalControlAdapterToGraph(ca, g, denoise);
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}
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const validIPAdapters = validLayers.filter(isIPAdapterLayer).map((l) => l.ipAdapter);
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for (const ipAdapter of validIPAdapters) {
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addGlobalIPAdapterToGraph(ipAdapter, g, denoise);
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}
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const initialImageLayers = validLayers.filter(isInitialImageLayer);
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assert(initialImageLayers.length <= 1, 'Only one initial image layer allowed');
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if (initialImageLayers[0]) {
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addInitialImageLayerToGraph(state, g, denoise, noise, initialImageLayers[0]);
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}
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// TODO: We should probably just use conditioning collectors by default, and skip all this fanagling with re-routing
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// the existing conditioning nodes.
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const validRGLayers = validLayers.filter(isRegionalGuidanceLayer);
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const layerIds = validRGLayers.map((l) => l.id);
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const blobs = await getRegionalPromptLayerBlobs(layerIds);
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assert(size(blobs) === size(layerIds), 'Mismatch between layer IDs and blobs');
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for (const layer of validRGLayers) {
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const blob = blobs[layer.id];
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assert(blob, `Blob for layer ${layer.id} not found`);
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// Upload the mask image, or get the cached image if it exists
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const { image_name } = await getMaskImage(layer, blob);
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// The main mask-to-tensor node
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const maskToTensor = g.addNode({
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id: `${PROMPT_REGION_MASK_TO_TENSOR_PREFIX}_${layer.id}`,
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type: 'alpha_mask_to_tensor',
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image: {
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image_name,
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},
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});
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if (layer.positivePrompt) {
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// The main positive conditioning node
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const regionalPosCond = g.addNode(
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isSDXL
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? {
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type: 'sdxl_compel_prompt',
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id: `${PROMPT_REGION_POSITIVE_COND_PREFIX}_${layer.id}`,
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prompt: layer.positivePrompt,
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style: layer.positivePrompt, // TODO: Should we put the positive prompt in both fields?
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}
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: {
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type: 'compel',
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id: `${PROMPT_REGION_POSITIVE_COND_PREFIX}_${layer.id}`,
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prompt: layer.positivePrompt,
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}
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);
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// Connect the mask to the conditioning
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g.addEdge(maskToTensor, 'mask', regionalPosCond, 'mask');
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// Connect the conditioning to the collector
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g.addEdge(regionalPosCond, 'conditioning', posCondCollect, 'item');
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// Copy the connections to the "global" positive conditioning node to the regional cond
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for (const edge of g.getEdgesTo(posCond)) {
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console.log(edge);
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if (edge.destination.field !== 'prompt') {
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// Clone the edge, but change the destination node to the regional conditioning node
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const clone = deepClone(edge);
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clone.destination.node_id = regionalPosCond.id;
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g.addEdgeFromObj(clone);
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}
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}
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}
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if (layer.negativePrompt) {
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// The main negative conditioning node
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const regionalNegCond = g.addNode(
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isSDXL
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? {
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type: 'sdxl_compel_prompt',
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id: `${PROMPT_REGION_NEGATIVE_COND_PREFIX}_${layer.id}`,
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prompt: layer.negativePrompt,
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style: layer.negativePrompt,
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}
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: {
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type: 'compel',
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id: `${PROMPT_REGION_NEGATIVE_COND_PREFIX}_${layer.id}`,
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prompt: layer.negativePrompt,
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}
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);
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// Connect the mask to the conditioning
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g.addEdge(maskToTensor, 'mask', regionalNegCond, 'mask');
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// Connect the conditioning to the collector
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g.addEdge(regionalNegCond, 'conditioning', negCondCollect, 'item');
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// Copy the connections to the "global" negative conditioning node to the regional cond
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for (const edge of g.getEdgesTo(negCond)) {
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if (edge.destination.field !== 'prompt') {
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// Clone the edge, but change the destination node to the regional conditioning node
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const clone = deepClone(edge);
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clone.destination.node_id = regionalNegCond.id;
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g.addEdgeFromObj(clone);
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}
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}
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}
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// If we are using the "invert" auto-negative setting, we need to add an additional negative conditioning node
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if (layer.autoNegative === 'invert' && layer.positivePrompt) {
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// We re-use the mask image, but invert it when converting to tensor
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const invertTensorMask = g.addNode({
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id: `${PROMPT_REGION_INVERT_TENSOR_MASK_PREFIX}_${layer.id}`,
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type: 'invert_tensor_mask',
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});
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// Connect the OG mask image to the inverted mask-to-tensor node
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g.addEdge(maskToTensor, 'mask', invertTensorMask, 'mask');
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// Create the conditioning node. It's going to be connected to the negative cond collector, but it uses the positive prompt
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const regionalPosCondInverted = g.addNode(
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isSDXL
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? {
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type: 'sdxl_compel_prompt',
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id: `${PROMPT_REGION_POSITIVE_COND_INVERTED_PREFIX}_${layer.id}`,
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prompt: layer.positivePrompt,
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style: layer.positivePrompt,
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}
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: {
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type: 'compel',
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id: `${PROMPT_REGION_POSITIVE_COND_INVERTED_PREFIX}_${layer.id}`,
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prompt: layer.positivePrompt,
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}
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);
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// Connect the inverted mask to the conditioning
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g.addEdge(invertTensorMask, 'mask', regionalPosCondInverted, 'mask');
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// Connect the conditioning to the negative collector
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g.addEdge(regionalPosCondInverted, 'conditioning', negCondCollect, 'item');
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// Copy the connections to the "global" positive conditioning node to our regional node
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for (const edge of g.getEdgesTo(posCond)) {
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if (edge.destination.field !== 'prompt') {
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// Clone the edge, but change the destination node to the regional conditioning node
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const clone = deepClone(edge);
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clone.destination.node_id = regionalPosCondInverted.id;
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g.addEdgeFromObj(clone);
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}
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}
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}
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const validRegionalIPAdapters: IPAdapterConfigV2[] = layer.ipAdapters.filter((ipa) =>
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isValidIPAdapter(ipa, mainModel.base)
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);
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for (const ipAdapterConfig of validRegionalIPAdapters) {
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const ipAdapterCollect = addIPAdapterCollectorSafe(g, denoise);
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const { id, weight, model, clipVisionModel, method, beginEndStepPct, image } = ipAdapterConfig;
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assert(model, 'IP Adapter model is required');
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assert(image, 'IP Adapter image is required');
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const ipAdapter = g.addNode({
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id: `ip_adapter_${id}`,
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type: 'ip_adapter',
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is_intermediate: true,
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weight,
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method,
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ip_adapter_model: model,
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clip_vision_model: clipVisionModel,
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begin_step_percent: beginEndStepPct[0],
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end_step_percent: beginEndStepPct[1],
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image: {
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image_name: image.name,
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},
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});
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// Connect the mask to the conditioning
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g.addEdge(maskToTensor, 'mask', ipAdapter, 'mask');
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g.addEdge(ipAdapter, 'ip_adapter', ipAdapterCollect, 'item');
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}
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}
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MetadataUtil.add(g, { control_layers: { layers: validLayers, version: state.controlLayers.present._version } });
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return validLayers;
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};
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const getMaskImage = async (layer: RegionalGuidanceLayer, blob: Blob): Promise<ImageDTO> => {
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if (layer.uploadedMaskImage) {
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const imageDTO = await getImageDTO(layer.uploadedMaskImage.name);
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if (imageDTO) {
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return imageDTO;
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}
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}
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const { dispatch } = getStore();
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// No cached mask, or the cached image no longer exists - we need to upload the mask image
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const file = new File([blob], `${layer.id}_mask.png`, { type: 'image/png' });
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const req = dispatch(
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imagesApi.endpoints.uploadImage.initiate({ file, image_category: 'mask', is_intermediate: true })
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);
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req.reset();
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const imageDTO = await req.unwrap();
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dispatch(rgLayerMaskImageUploaded({ layerId: layer.id, imageDTO }));
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return imageDTO;
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};
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const buildControlImage = (
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image: ImageWithDims | null,
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processedImage: ImageWithDims | null,
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processorConfig: ProcessorConfig | null
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): ImageField => {
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if (processedImage && processorConfig) {
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// We've processed the image in the app - use it for the control image.
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return {
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image_name: processedImage.name,
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};
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} else if (image) {
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// No processor selected, and we have an image - the user provided a processed image, use it for the control image.
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return {
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image_name: image.name,
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};
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}
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assert(false, 'Attempted to add unprocessed control image');
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};
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const addGlobalControlAdapterToGraph = (
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controlAdapterConfig: ControlNetConfigV2 | T2IAdapterConfigV2,
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g: Graph,
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denoise: Invocation<'denoise_latents'>
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): void => {
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if (controlAdapterConfig.type === 'controlnet') {
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addGlobalControlNetToGraph(controlAdapterConfig, g, denoise);
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}
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if (controlAdapterConfig.type === 't2i_adapter') {
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addGlobalT2IAdapterToGraph(controlAdapterConfig, g, denoise);
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}
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};
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const addControlNetCollectorSafe = (g: Graph, denoise: Invocation<'denoise_latents'>): Invocation<'collect'> => {
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try {
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// Attempt to retrieve the collector
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const controlNetCollect = g.getNode(CONTROL_NET_COLLECT);
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assert(controlNetCollect.type === 'collect');
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return controlNetCollect;
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} catch {
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// Add the ControlNet collector
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const controlNetCollect = g.addNode({
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id: CONTROL_NET_COLLECT,
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type: 'collect',
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});
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g.addEdge(controlNetCollect, 'collection', denoise, 'control');
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return controlNetCollect;
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}
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};
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|
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const addGlobalControlNetToGraph = (
|
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||||||
controlNetConfig: ControlNetConfigV2,
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g: Graph,
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||||||
denoise: Invocation<'denoise_latents'>
|
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||||||
) => {
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||||||
const { id, beginEndStepPct, controlMode, image, model, processedImage, processorConfig, weight } = controlNetConfig;
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||||||
assert(model, 'ControlNet model is required');
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||||||
const controlImage = buildControlImage(image, processedImage, processorConfig);
|
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const controlNetCollect = addControlNetCollectorSafe(g, denoise);
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||||||
|
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const controlNet = g.addNode({
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||||||
id: `control_net_${id}`,
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||||||
type: 'controlnet',
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||||||
is_intermediate: true,
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begin_step_percent: beginEndStepPct[0],
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||||||
end_step_percent: beginEndStepPct[1],
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control_mode: controlMode,
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||||||
resize_mode: 'just_resize',
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control_model: model,
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control_weight: weight,
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image: controlImage,
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||||||
});
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g.addEdge(controlNet, 'control', controlNetCollect, 'item');
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||||||
};
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|
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const addT2IAdapterCollectorSafe = (g: Graph, denoise: Invocation<'denoise_latents'>): Invocation<'collect'> => {
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||||||
try {
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||||||
// You see, we've already got one!
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||||||
const t2iAdapterCollect = g.getNode(T2I_ADAPTER_COLLECT);
|
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||||||
assert(t2iAdapterCollect.type === 'collect');
|
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||||||
return t2iAdapterCollect;
|
|
||||||
} catch {
|
|
||||||
const t2iAdapterCollect = g.addNode({
|
|
||||||
id: T2I_ADAPTER_COLLECT,
|
|
||||||
type: 'collect',
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||||||
});
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||||||
|
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||||||
g.addEdge(t2iAdapterCollect, 'collection', denoise, 't2i_adapter');
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||||||
|
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||||||
return t2iAdapterCollect;
|
|
||||||
}
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|
||||||
};
|
|
||||||
|
|
||||||
const addGlobalT2IAdapterToGraph = (
|
|
||||||
t2iAdapterConfig: T2IAdapterConfigV2,
|
|
||||||
g: Graph,
|
|
||||||
denoise: Invocation<'denoise_latents'>
|
|
||||||
) => {
|
|
||||||
const { id, beginEndStepPct, image, model, processedImage, processorConfig, weight } = t2iAdapterConfig;
|
|
||||||
assert(model, 'T2I Adapter model is required');
|
|
||||||
const controlImage = buildControlImage(image, processedImage, processorConfig);
|
|
||||||
const t2iAdapterCollect = addT2IAdapterCollectorSafe(g, denoise);
|
|
||||||
|
|
||||||
const t2iAdapter = g.addNode({
|
|
||||||
id: `t2i_adapter_${id}`,
|
|
||||||
type: 't2i_adapter',
|
|
||||||
is_intermediate: true,
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|
||||||
begin_step_percent: beginEndStepPct[0],
|
|
||||||
end_step_percent: beginEndStepPct[1],
|
|
||||||
resize_mode: 'just_resize',
|
|
||||||
t2i_adapter_model: model,
|
|
||||||
weight: weight,
|
|
||||||
image: controlImage,
|
|
||||||
});
|
|
||||||
|
|
||||||
g.addEdge(t2iAdapter, 't2i_adapter', t2iAdapterCollect, 'item');
|
|
||||||
};
|
|
||||||
|
|
||||||
const addIPAdapterCollectorSafe = (g: Graph, denoise: Invocation<'denoise_latents'>): Invocation<'collect'> => {
|
|
||||||
try {
|
|
||||||
// You see, we've already got one!
|
|
||||||
const ipAdapterCollect = g.getNode(IP_ADAPTER_COLLECT);
|
|
||||||
assert(ipAdapterCollect.type === 'collect');
|
|
||||||
return ipAdapterCollect;
|
|
||||||
} catch {
|
|
||||||
const ipAdapterCollect = g.addNode({
|
|
||||||
id: IP_ADAPTER_COLLECT,
|
|
||||||
type: 'collect',
|
|
||||||
});
|
|
||||||
g.addEdge(ipAdapterCollect, 'collection', denoise, 'ip_adapter');
|
|
||||||
return ipAdapterCollect;
|
|
||||||
}
|
|
||||||
};
|
|
||||||
|
|
||||||
const addGlobalIPAdapterToGraph = (
|
|
||||||
ipAdapterConfig: IPAdapterConfigV2,
|
|
||||||
g: Graph,
|
|
||||||
denoise: Invocation<'denoise_latents'>
|
|
||||||
) => {
|
|
||||||
const { id, weight, model, clipVisionModel, method, beginEndStepPct, image } = ipAdapterConfig;
|
|
||||||
assert(image, 'IP Adapter image is required');
|
|
||||||
assert(model, 'IP Adapter model is required');
|
|
||||||
const ipAdapterCollect = addIPAdapterCollectorSafe(g, denoise);
|
|
||||||
|
|
||||||
const ipAdapter = g.addNode({
|
|
||||||
id: `ip_adapter_${id}`,
|
|
||||||
type: 'ip_adapter',
|
|
||||||
is_intermediate: true,
|
|
||||||
weight,
|
|
||||||
method,
|
|
||||||
ip_adapter_model: model,
|
|
||||||
clip_vision_model: clipVisionModel,
|
|
||||||
begin_step_percent: beginEndStepPct[0],
|
|
||||||
end_step_percent: beginEndStepPct[1],
|
|
||||||
image: {
|
|
||||||
image_name: image.name,
|
|
||||||
},
|
|
||||||
});
|
|
||||||
g.addEdge(ipAdapter, 'ip_adapter', ipAdapterCollect, 'item');
|
|
||||||
};
|
|
||||||
|
|
||||||
const addInitialImageLayerToGraph = (
|
|
||||||
state: RootState,
|
|
||||||
g: Graph,
|
|
||||||
denoise: Invocation<'denoise_latents'>,
|
|
||||||
noise: Invocation<'noise'>,
|
|
||||||
layer: InitialImageLayer
|
|
||||||
) => {
|
|
||||||
const { vaePrecision, model } = state.generation;
|
|
||||||
const { refinerModel, refinerStart } = state.sdxl;
|
|
||||||
const { width, height } = state.controlLayers.present.size;
|
|
||||||
assert(layer.isEnabled, 'Initial image layer is not enabled');
|
|
||||||
assert(layer.image, 'Initial image layer has no image');
|
|
||||||
|
|
||||||
const isSDXL = model?.base === 'sdxl';
|
|
||||||
const useRefinerStartEnd = isSDXL && Boolean(refinerModel);
|
|
||||||
|
|
||||||
const { denoisingStrength } = layer;
|
|
||||||
denoise.denoising_start = useRefinerStartEnd ? Math.min(refinerStart, 1 - denoisingStrength) : 1 - denoisingStrength;
|
|
||||||
denoise.denoising_end = useRefinerStartEnd ? refinerStart : 1;
|
|
||||||
|
|
||||||
const i2l = g.addNode({
|
|
||||||
type: 'i2l',
|
|
||||||
id: IMAGE_TO_LATENTS,
|
|
||||||
is_intermediate: true,
|
|
||||||
use_cache: true,
|
|
||||||
fp32: vaePrecision === 'fp32',
|
|
||||||
});
|
|
||||||
|
|
||||||
g.addEdge(i2l, 'latents', denoise, 'latents');
|
|
||||||
|
|
||||||
if (layer.image.width !== width || layer.image.height !== height) {
|
|
||||||
// The init image needs to be resized to the specified width and height before being passed to `IMAGE_TO_LATENTS`
|
|
||||||
|
|
||||||
// Create a resize node, explicitly setting its image
|
|
||||||
const resize = g.addNode({
|
|
||||||
id: RESIZE,
|
|
||||||
type: 'img_resize',
|
|
||||||
image: {
|
|
||||||
image_name: layer.image.name,
|
|
||||||
},
|
|
||||||
is_intermediate: true,
|
|
||||||
width,
|
|
||||||
height,
|
|
||||||
});
|
|
||||||
|
|
||||||
// The `RESIZE` node then passes its image to `IMAGE_TO_LATENTS`
|
|
||||||
g.addEdge(resize, 'image', i2l, 'image');
|
|
||||||
// The `RESIZE` node also passes its width and height to `NOISE`
|
|
||||||
g.addEdge(resize, 'width', noise, 'width');
|
|
||||||
g.addEdge(resize, 'height', noise, 'height');
|
|
||||||
} else {
|
|
||||||
// We are not resizing, so we need to set the image on the `IMAGE_TO_LATENTS` node explicitly
|
|
||||||
i2l.image = {
|
|
||||||
image_name: layer.image.name,
|
|
||||||
};
|
|
||||||
|
|
||||||
// Pass the image's dimensions to the `NOISE` node
|
|
||||||
g.addEdge(i2l, 'width', noise, 'width');
|
|
||||||
g.addEdge(i2l, 'height', noise, 'height');
|
|
||||||
}
|
|
||||||
|
|
||||||
MetadataUtil.add(g, { generation_mode: isSDXL ? 'sdxl_img2img' : 'img2img' });
|
|
||||||
};
|
|
||||||
|
|
||||||
const isValidControlAdapter = (ca: ControlNetConfigV2 | T2IAdapterConfigV2, base: BaseModelType): boolean => {
|
|
||||||
// Must be have a model that matches the current base and must have a control image
|
|
||||||
const hasModel = Boolean(ca.model);
|
|
||||||
const modelMatchesBase = ca.model?.base === base;
|
|
||||||
const hasControlImage = Boolean(ca.image || (ca.processedImage && ca.processorConfig));
|
|
||||||
return hasModel && modelMatchesBase && hasControlImage;
|
|
||||||
};
|
|
||||||
|
|
||||||
const isValidIPAdapter = (ipa: IPAdapterConfigV2, base: BaseModelType): boolean => {
|
|
||||||
// Must be have a model that matches the current base and must have a control image
|
|
||||||
const hasModel = Boolean(ipa.model);
|
|
||||||
const modelMatchesBase = ipa.model?.base === base;
|
|
||||||
const hasImage = Boolean(ipa.image);
|
|
||||||
return hasModel && modelMatchesBase && hasImage;
|
|
||||||
};
|
|
||||||
|
|
||||||
const isValidLayer = (layer: Layer, base: BaseModelType) => {
|
|
||||||
if (!layer.isEnabled) {
|
|
||||||
return false;
|
|
||||||
}
|
|
||||||
if (isControlAdapterLayer(layer)) {
|
|
||||||
return isValidControlAdapter(layer.controlAdapter, base);
|
|
||||||
}
|
|
||||||
if (isIPAdapterLayer(layer)) {
|
|
||||||
return isValidIPAdapter(layer.ipAdapter, base);
|
|
||||||
}
|
|
||||||
if (isInitialImageLayer(layer)) {
|
|
||||||
if (!layer.image) {
|
|
||||||
return false;
|
|
||||||
}
|
|
||||||
return true;
|
|
||||||
}
|
|
||||||
if (isRegionalGuidanceLayer(layer)) {
|
|
||||||
if (layer.maskObjects.length === 0) {
|
|
||||||
// Layer has no mask, meaning any guidance would be applied to an empty region.
|
|
||||||
return false;
|
|
||||||
}
|
|
||||||
const hasTextPrompt = Boolean(layer.positivePrompt) || Boolean(layer.negativePrompt);
|
|
||||||
const hasIPAdapter = layer.ipAdapters.filter((ipa) => isValidIPAdapter(ipa, base)).length > 0;
|
|
||||||
return hasTextPrompt || hasIPAdapter;
|
|
||||||
}
|
|
||||||
return false;
|
|
||||||
};
|
|
||||||
Reference in New Issue
Block a user