Add Audio Spectogram Transformer
# What does this PR do?

Fixes #16383 

This PR adds the [Audio Spectogram Transformer (AST)](https://arxiv.org/abs/2104.01778) model from MIT.

Similar to Whisper (actually prior to Whisper), the model treats audio as an image and applies a Vision Transformer on it.

The model gets SOTA results on audio classification benchmarks. 
_The documentation is not available anymore as the PR was closed or merged._<|||||>Hey, how can I use it already? I installed the branch, but unsure how to load the model. I'm new with huggingface :D<|||||>Hey @FrankFundel - hoping @NielsRogge adds a nice example as part of this PR documenting just that 🤞 In the mean time, you can try adapting the example from https://huggingface.co/docs/transformers/tasks/audio_classification

You'll need to change the repo names from `facebook/wav2vec2-base` to the appropriate Audio Spectrogram Transformer repo name. You'll also need to change the preprocess function (https://huggingface.co/docs/transformers/tasks/audio_classification#preprocess) to something like:

```python
def preprocess_function(examples):
    audio_arrays = [x["array"] for x in examples["audio"]]
    input_features = feature_extractor(audio_array, sampling_rate=feature_extractor.sampling_rate)
    return input_features
```
This is all currently untested, so might require some playing around to make it work.<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_19981). All of your documentation changes will be reflected on that endpoint.<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_19981). All of your documentation changes will be reflected on that endpoint.<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_19981). All of your documentation changes will be reflected on that endpoint.