Adding EGT Model for Graph Classification
Author: rudongyu
Pull request: yes

# What does this PR do?

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Add the graph transformer model EGT for the graph classification task.


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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## Who can review?

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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @sgugger

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam

Documentation: @sgugger, @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: @sgugger
- TensorFlow: @Rocketknight1

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Comments:
Hey! Thanks a lot for wanting to contribute! I would recommend you to push your model on the hub following[ this tutorial](https://huggingface.co/docs/transformers/custom_models) as it will be a lot easier and doesn't require you to go through all the CI and should be easier to do! Feel free to then share the huggingface repository were you added it! 

> Hey! Thanks a lot for wanting to contribute! I would recommend you to push your model on the hub following[ this tutorial](https://huggingface.co/docs/transformers/custom_models) as it will be a lot easier and doesn't require you to go through all the CI and should be easier to do! Feel free to then share the huggingface repository were you added it!

Thanks for your suggestions! I have pushed our model on the hub and [this](https://huggingface.co/Zhiteng/dgl-egt/tree/main) is the huggingface repository where I added it.

> Hey! Thanks a lot for wanting to contribute! I would recommend you to push your model on the hub following[ this tutorial](https://huggingface.co/docs/transformers/custom_models) as it will be a lot easier and doesn't require you to go through all the CI and should be easier to do! Feel free to then share the huggingface repository were you added it!

Thanks for your kind reminder! I went through the tutorial and found two potential barriers to directly sharing models in that manner:
1. HF transformers doesn't have a definition for AutoModelForGraphClassification.
2. The tutorial doesn't include a way for sharing the data collating method. However, it could be a critical part for users conveniently applying the model for graph classification.

So, maybe providing the model in the library is still a better way in this case? @clefourrier for awareness.

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.