Time Series Transformer - Dynamic Categorical Features
### Feature request

I would like to have a Dynamic Categorical Feature Embedding option in TimeSeriesTransformerConfig 

### Motivation

I didn't see any option in the TimeSeriesTransformerConfig where I could define an embedding of a Dynamic Categorical Feature. I'm working with sales data and holiday is an important element of sales, so all of my models handle the holidays with a dynamic embedding. Is it the case in Time Series Transformer too, and I'm just missing something?

### Your contribution

Happy to help, but would need some guidance on how it's handled currently.
cc @kashif <|||||>@guyko81  yes sure! I would be happy to help you get this done. I never found a good example of dynamic categorical features, so if you have some sample example that would be really helpful. 

We can assume that the dataset has a key  e.g. 

```py
dynamic_static_categorical  = [ [0, 2, 555], [23, 5, 66], ... [33, 4, 54]]
```

where we have a list of categories for each time point where the len of this array will be the length of the target values array in the time dim.

Next we will need to specify the number of dynamic cat. features (3) in the example above and the cardinalities and dims of the corresponding features:

```
dynamic_cat_card = [50, 10, 1000]
dynamic_cat_dimns = [12, 16, 32]
```

Once we have that done on the config side we can just add a corresponding `nn.Embedding` and concat the outputs to the input vector. If you open a PR please CC me and then i can help out! 

Thank you!
<|||||>@kashif I have created a pull request https://github.com/huggingface/transformers/pull/24712
Still need to test it first, but I wanted you to have a look