Add ONNX export for BeiT
# What does this PR do?

Based on the fantastic work by @lewtun in https://github.com/huggingface/transformers/pull/15658, I added ONNX export support for the Microsoft BeiT model.

# Usage
```
import requests
import numpy as np
from PIL import Image
from onnxruntime import InferenceSession
from transformers import AutoConfig, AutoFeatureExtractor, AutoModelForImageClassification

# Export ViT checkpoint with image classification head
model_ckpt = "microsoft/beit-base-patch16-224"
!python -m transformers.onnx --model={model_ckpt} --feature=image-classification onnx/

# Download an image of two cute cats - naturally ;-)
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)

# Instantiate config and feature extractor
config = AutoConfig.from_pretrained(model_ckpt)
feature_extractor = AutoFeatureExtractor.from_pretrained(model_ckpt)
inputs = feature_extractor(image, return_tensors="np")

# Create ONNX Runtime session
session = InferenceSession("onnx/model.onnx", providers=["CPUExecutionProvider"])
outputs = session.run(["logits"], dict(inputs))
predicted_class_idx = np.argmax(outputs[0])
# Returns Predicted class: Egyptian cat
print("Predicted class:", config.id2label[predicted_class_idx])
```

_The documentation is not available anymore as the PR was closed or merged._<|||||>Thanks for your PR, super cool!