Set correct NPU backend and distributed_type when using transfer_to_npu

[ArthurinRUC]

What does this PR do?

When running from torch_npu.contrib import transfer_to_npu, we will find torch.cuda.is_available() is True which leads to incorrect backend and distributed_type. This PR fixes the problem to make sure npu envs check is before CUDA.

Fixes #3020

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@muellerzr

[BenjaminBossan]

Let's add a comment that NPU has to be checked before CUDA and why (a reference to the issue). Also, any idea if the same can also happen with other devices, i.e. CUDA should always be the last check?

[ArthurinRUC]

Let's add a comment that NPU has to be checked before CUDA and why (a reference to the issue). Also, any idea if the same can also happen with other devices, i.e. CUDA should always be the last check?

Sure, I will add a brief description to my fix. Also I've already open an issue here #3020 :)

[BenjaminBossan]

Sure, I will add a brief description to my fix. Also I've already open an issue here #3020 :)

Thanks. Yeah, I meant that the comment can reference said issue.

[muellerzr]

agreed with @BenjaminBossan, let's add a comment here and during torch.device("npu") that clarifies (in the code) that these must be done before the cuda check

[HuggingFaceDocBuilderDev]

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

[ArthurinRUC]

All right I got it! Thanks :)

[muellerzr]

Great! Thanks for fixing this!

[BenjaminBossan]

Thanks!