DemonGatanjieuandClaude Opus 5.5
9f72cfce83
run_workflow(base_only) queues the first pass alone (base_only.js cuts each queued prompt; save nodes become previews, the canvas stays). When it ends, ai_bases.py shows the previews on a picks panel; the picked one is copied into the output folder and its seed held. The next run takes the kept picture where the rest takes the base's picture, so the base is not drawn again; a base handed on as a latent (mid-way switch) is drawn again from its seed and compared with the kept one. Drawn again from the same seed, a base once came out grainy on a 6 GB card, hence the kept picture. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
93 lines
6.1 KiB
JavaScript
93 lines
6.1 KiB
JavaScript
import assert from 'node:assert/strict';
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import { baseOnly, onKeptBase } from '../web/modules/base_only.js';
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const loaders = {
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1: { class_type: 'UNETLoader', inputs: { unet_name: 'a.safetensors', weight_dtype: 'default' } },
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5: { class_type: 'CLIPLoader', inputs: { clip_name: 'te.safetensors', type: 'stable_diffusion' } },
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8: { class_type: 'VAELoader', inputs: { vae_name: 'vae.safetensors' } },
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2: { class_type: 'CLIPTextEncode', inputs: { text: 'a lake', clip: ['5', 0] } },
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3: { class_type: 'CLIPTextEncode', inputs: { text: '', clip: ['5', 0] } },
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6: { class_type: 'EmptyLatentImage', inputs: { width: 832, height: 1216, batch_size: 1 } },
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};
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const advanced = (model, latent, start, end, leftover) => ({
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class_type: 'KSamplerAdvanced', inputs: {
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model: [model, 0], positive: ['2', 0], negative: ['3', 0], latent_image: [latent, 0], add_noise: 'enable',
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noise_seed: 7, steps: 35, start_at_step: start, end_at_step: end, return_with_leftover_noise: leftover,
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},
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});
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// The two-pass card: the base is decoded and saved, then encoded, enlarged and redrawn by a second model under Tile.
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{
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const output = {
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...loaders, 30: { class_type: 'UNETLoader', inputs: { unet_name: 'b.safetensors', weight_dtype: 'default' } },
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32: advanced('1', '6', 0, 35, 'disable'),
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7: { class_type: 'VAEDecodeTiled', inputs: { samples: ['32', 0], vae: ['8', 0], tile_size: 512 } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'two_pass/base' } },
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10: { class_type: 'VAEEncodeTiled', inputs: { pixels: ['7', 0], vae: ['8', 0] } },
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11: { class_type: 'LatentUpscaleBy', inputs: { samples: ['10', 0], scale_by: 1.5 } },
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18: { class_type: 'AnimaLLLiteApply', inputs: { model: ['30', 0], image: ['7', 0] } },
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19: { class_type: 'KSampler', inputs: { model: ['18', 0], positive: ['2', 0], negative: ['3', 0], latent_image: ['11', 0], seed: 3, denoise: 0.85 } },
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20: { class_type: 'VAEDecodeTiled', inputs: { samples: ['19', 0], vae: ['8', 0] } },
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21: { class_type: 'ColorMatch', inputs: { image_ref: ['7', 0], image_target: ['20', 0] } },
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22: { class_type: 'SaveImage', inputs: { images: ['21', 0], filename_prefix: 'two_pass/upscaled' } },
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};
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const before = JSON.stringify(output);
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const got = baseOnly(output);
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assert.equal(JSON.stringify(output), before, 'the queued prompt is cut down in a copy');
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assert.deepEqual(got.bases, [{ node: '32', type: 'KSamplerAdvanced', names: ['noise_seed'] }]);
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assert.deepEqual(got.shows, ['9']);
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assert.deepEqual(got.saved, ['9'], 'the full run saves this base again: it can be compared');
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assert.equal(got.prefix, 'two_pass/base');
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assert.deepEqual(Object.keys(got.output).sort(), ['1', '2', '3', '32', '5', '6', '7', '8', '9']);
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assert.deepEqual(got.output[9], { class_type: 'PreviewImage', inputs: { images: ['7', 0] } });
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assert.equal(got.output[32], output[32], 'a base that finishes on its own runs as it is: the same picture');
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// The run after the pick: the second pass takes the kept picture wherever it took the base's, the base is not drawn again.
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const kept = onKeptBase(output, 'anomalous_reference_abc.png');
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assert.deepEqual(kept[33], { class_type: 'LoadImage', inputs: { image: 'anomalous_reference_abc.png' } });
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assert.deepEqual([kept[10].inputs.pixels, kept[18].inputs.image, kept[21].inputs.image_ref], [['33', 0], ['33', 0], ['33', 0]]);
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assert.deepEqual(kept[21].inputs.image_target, ['20', 0]);
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assert.deepEqual(Object.keys(kept).sort(), ['10', '11', '18', '19', '2', '20', '21', '22', '3', '30', '33', '5', '8'], 'the base model and its empty latent are not loaded');
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assert.equal(JSON.stringify(output), before, 'the queued prompt is changed in a copy');
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}
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// The mid-way switch: the first model hands its unfinished latent to the second; the base is finished and decoded to show.
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{
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const output = {
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...loaders, 30: { class_type: 'UNETLoader', inputs: { unet_name: 'b.safetensors', weight_dtype: 'default' } },
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32: advanced('1', '6', 0, 21, 'enable'), 33: { ...advanced('30', '32', 21, 10000, 'disable') },
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7: { class_type: 'VAEDecodeTiled', inputs: { samples: ['33', 0], vae: ['8', 0], tile_size: 512 } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'relay' } },
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};
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output[33].inputs.add_noise = 'disable';
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const got = baseOnly(output);
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assert.deepEqual(got.bases.map(base => base.node), ['32']);
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assert.deepEqual(got.shows, ['35']);
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assert.deepEqual(got.saved, [], 'the full run never shows this base');
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assert.equal(got.prefix, '');
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assert.deepEqual(got.output[34], { class_type: 'VAEDecodeTiled', inputs: { samples: ['32', 0], vae: ['8', 0], tile_size: 512 } },
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'decoded as the canvas decodes');
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assert.deepEqual(got.output[35], { class_type: 'PreviewImage', inputs: { images: ['34', 0] } });
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assert.equal(got.output[32].inputs.end_at_step, 10000);
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assert.equal(got.output[32].inputs.return_with_leftover_noise, 'disable');
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assert.equal(output[32].inputs.end_at_step, 21, 'the canvas prompt keeps its switch');
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assert.equal(onKeptBase(output, 'kept.png'), null, 'a latent handed on cannot come from a picture: drawn again from its seed');
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assert.deepEqual(Object.keys(got.output).sort(), ['1', '2', '3', '32', '34', '35', '5', '6', '8']);
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}
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// One pass only: the whole picture, shown and not saved.
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{
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const output = {
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...loaders, 4: { class_type: 'KSampler', inputs: { model: ['1', 0], positive: ['2', 0], negative: ['3', 0], latent_image: ['6', 0], seed: 1 } },
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7: { class_type: 'VAEDecode', inputs: { samples: ['4', 0], vae: ['8', 0] } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'ComfyUI' } },
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};
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const got = baseOnly(output);
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assert.deepEqual(got.bases, [{ node: '4', type: 'KSampler', names: ['seed'] }]);
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assert.equal(got.output[9].class_type, 'PreviewImage');
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assert.equal(onKeptBase(output, 'kept.png'), null, 'nothing after the base');
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}
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assert.throws(() => baseOnly({ ...loaders }), /No sampler/);
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console.log('base_only: ok');
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