[Javascript ] inferenceSession on WebGL

[shimaamorsy]

Describe the issue

When i tried to inferenceSession on WebGL , I encountered this error

To reproduce

1. Download Yolov8n onnx model here MODEL
2. Run this HTML page in a webserver (LiveServer in Visual Studio Code fi): `

   
   <script src="https://cdn.jsdelivr.net/npm/onnxruntime-web/dist/ort.webgl.min.js"></script>

let model = await ort.InferenceSession.create("yolov8n.onnx", { executionProviders: ['webgl'] }); const tensor = new ort.Tensor("float32",new Float32Array(modelInputShape.reduce((a, b) => a * b)),modelInputShape); await model.run({ images: tensor })

### Urgency

Yes , i should solve this error immediately

### Platform

Windows

### OS Version

10 

### ONNX Runtime Installation

Built from Source

### ONNX Runtime Version or Commit ID

1.17.1

### ONNX Runtime API

Python

### Architecture

X64

### Execution Provider

Default CPU

### Execution Provider Library Version

Webgl

### Model File

_No response_

### Is this a quantized model?

No

[EmmaNingMS]

Hi there, WebGL will be deprecated in ORT Web soon. Pls use WebGPU for GPU inference with ORT Web. Here are the doc: https://onnxruntime.ai/docs/tutorials/web/ep-webgpu.html and example: https://github.com/microsoft/onnxruntime-inference-examples/tree/main/js/segment-anything

[shimaamorsy]

Thank you very much for your response.

I'm having another problem and I'm struggling to find the material to help me for solving my task. I'm trying to speed up the performance of YOLOv5-segmentation using static quantization. I have followed the ONNX Runtime official tutorial on how to apply static quantization

However, I encountered an error when i tried to preprocess the library If you know of another material to help me with my task, I would be very grateful to you.

[yufenglee]

Thank you very much for your response.

I'm having another problem and I'm struggling to find the material to help me for solving my task. I'm trying to speed up the performance of YOLOv5-segmentation using static quantization. I have followed the ONNX Runtime official tutorial on how to apply static quantization

However, I encountered an error when i tried to preprocess the library If you know of another material to help me with my task, I would be very grateful to you.

you can skip the preprocess to unblock yourself. As for the failure in the shape inference, does your model have non-standard onnx ops?

[shimaamorsy]

Thank you for replying .

No ,

These are the models I am trying to quantize: yolov5n-seg.onnx

yolov8n-seg.onnx

[github-actions[bot]]

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