LongformerEmbeddings "position_embedding_type"  parameter are not used.
### System Info

- `transformers` version: 4.28.1
- Platform: Linux-5.4.0-144-generic-x86_64-with-glibc2.28
- Python version: 3.9.7
- Huggingface_hub version: 0.13.4
- Safetensors version: not installed
- PyTorch version (GPU?): 2.0.0+cu117 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help?

@sgugger 
@ArthurZucker 
@younesbelkada 

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

In transformers.models.longformer.modeling_longformer.py file:
```python
class LongformerEmbeddings(nn.Module):
    """
    Same as BertEmbeddings with a tiny tweak for positional embeddings indexing.
    """

    def __init__(self, config):
        super().__init__()
        self.word_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, padding_idx=config.pad_token_id)
        self.position_embeddings = nn.Embedding(config.max_position_embeddings, config.hidden_size)
        self.token_type_embeddings = nn.Embedding(config.type_vocab_size, config.hidden_size)

        # self.LayerNorm is not snake-cased to stick with TensorFlow model variable name and be able to load
        # any TensorFlow checkpoint file
        self.LayerNorm = nn.LayerNorm(config.hidden_size, eps=config.layer_norm_eps)
        self.dropout = nn.Dropout(config.hidden_dropout_prob)

        self.position_embedding_type = getattr(config, "position_embedding_type", "absolute")

        self.padding_idx = config.pad_token_id
        self.position_embeddings = nn.Embedding(
            config.max_position_embeddings, config.hidden_size, padding_idx=self.padding_idx
        )
```

"position_embedding_type" are not work. By the way, self.position_embeddings has redundant initialization

### Expected behavior

Add support for “position_embedding_type”
Hey! Thanks for reporting this. I'm opening a PR to remove the unused parts, however I don't think it has to support the `position_embedding_type` as the model did not use it. 