Yulong Wang

It seems that for operator `Pad`, if the type variance T is float16, the operator's 3rd input (input[2]) will be of float16 as well, and our code read the scalar...

could you share what exact input data that you feed into the model, so that I can try to reproduce the problem

I can reproduce the problem. And I checked the session options. If I remove `use_ort_model_bytes_for_initializers: "1"`, the output value will be correct. It takes a while for me to figure...

This error means that one ArrayBuffer is used in a detached state. I may need to take a look at your code to figure out the detail.

The root cause if figured out. When using proxy, input tensors' underlying buffer is transferred from main thread into worker thread to avoid memcpy. This will invalidate any object in...

@nezaBacar could you help to verify if the PR fixes the issue by consuming package built here: https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=1306843&view=artifacts&pathAsName=false&type=publishedArtifacts

Considering recent issues/PRs about WebNN, here is a summary of requirements: - User may want to create an instance of `MLContext` using different combinations of options when trying to initialize...

There may be a difference between the proposed `ort.env.webnn.context` and `ort.env.webgpu.adaptor`: in WebGPU, the adaptor is used as a global unique object (singleton), while in WebNN, it is possible that...

> > while in WebNN, it is possible that multiple sessions uses different MLContext > > This is a valid scenario. For example, developers may want to run encoder on...

> > However, it's just one line of code, right? Should not be a problem to any one > > That's true. However I suppose the concern is this is...