dakenf/diffusers.js

Node example -> Class CoreMLExecution is implemented in both

Opened this issue · 3 comments

zaqqaz commented

Just tried node example (with node v20.10.0)

import { DiffusionPipeline } from '@aislamov/diffusers.js'
import { PNG } from 'pngjs'

const pipe = DiffusionPipeline.fromPretrained('aislamov/stable-diffusion-2-1-base-onnx')
const images = pipe.run({
  prompt: "an astronaut running a horse",
  numInferenceSteps: 30,
})

const data = await images[0].mul(255).round().clipByValue(0, 255).transpose(0, 2, 3, 1)

const p = new PNG({ width: 512, height: 512, inputColorType: 2 })
p.data = Buffer.from(data.data)
p.pack().pipe(fs.createWriteStream('output.png')).on('finish', () => {
  console.log('Image saved as output.png');
})

and got such error

objc[63467]: Class CoreMLExecution is implemented in both  node_modules/@aislamov/diffusers.js/node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.16.1.dylib (0x118318cb8) and node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.14.0.dylib (0x11abbceb0). One of the two will be used. Which one is undefined.

file:///***/test.mjs:5
const images = pipe.run({
                    ^

TypeError: pipe.run is not a function
    at file:///***/test.mjs:5:21
zaqqaz commented

Building for source and using examples seem to be working fine, so likely an issue with dependencies in published version, haven't investigated it further yet.

rbourgeat commented 
objc[63467]: Class CoreMLExecution is implemented in both  node_modules/@aislamov/diffusers.js/node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.16.1.dylib (0x118318cb8) and node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.14.0.dylib (0x11abbceb0). One of the two will be used. Which one is undefined.

file:///***/test.mjs:5
const images = pipe.run({
                    ^

TypeError: pipe.run is not a function
    at file:///***/test.mjs:5:21

Same error:

Tab1.tsx:14 Uncaught (in promise) TypeError: pipe.run is not a function
    at generateImage (Tab1.tsx:14:25)
    at Tab1.tsx:32:5

My code:

  const generateImage = async () => {
    const pipe = DiffusionPipeline.fromPretrained('aislamov/stable-diffusion-2-1-base-onnx', { revision: 'cpu' })
    const images = pipe.run({
      prompt: "an astronaut running a horse",
      numInferenceSteps: 30,
    });

    const data = await images[0].mul(255).round().clipByValue(0, 255).transpose(0, 2, 3, 1);

    const p = new PNG({ width: 512, height: 512, inputColorType: 2 });
    p.data = Buffer.from(data.data);
    p.pack().pipe(fs.createWriteStream('output.png')).on('finish', () => {
      console.log('Image saved as output.png');
    });

    setImageData(p.data);
  };
go-dev-space commented 
objc[63467]: Class CoreMLExecution is implemented in both  node_modules/@aislamov/diffusers.js/node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.16.1.dylib (0x118318cb8) and node_modules/onnxruntime-node/bin/napi-v3/darwin/arm64/libonnxruntime.1.14.0.dylib (0x11abbceb0). One of the two will be used. Which one is undefined.

file:///***/test.mjs:5
const images = pipe.run({
                    ^

TypeError: pipe.run is not a function
    at file:///***/test.mjs:5:21

Same error:

Tab1.tsx:14 Uncaught (in promise) TypeError: pipe.run is not a function
    at generateImage (Tab1.tsx:14:25)
    at Tab1.tsx:32:5

My code:

  const generateImage = async () => {
    const pipe = DiffusionPipeline.fromPretrained('aislamov/stable-diffusion-2-1-base-onnx', { revision: 'cpu' })
    const images = pipe.run({
      prompt: "an astronaut running a horse",
      numInferenceSteps: 30,
    });

    const data = await images[0].mul(255).round().clipByValue(0, 255).transpose(0, 2, 3, 1);

    const p = new PNG({ width: 512, height: 512, inputColorType: 2 });
    p.data = Buffer.from(data.data);
    p.pack().pipe(fs.createWriteStream('output.png')).on('finish', () => {
      console.log('Image saved as output.png');
    });

    setImageData(p.data);
  };

Hey,

its a promise, u have to call "await":

const pipe = await DiffusionPipeline.fromPretrained('aislamov/stable-diffusion-2-1-base-onnx', { revision: 'cpu' })

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