Fix VisualBert Embeddings
# What does this PR do?
This PR addresses the issue mentioned in #13001. The `self.input_embeds` has been replaced with `self.position_ids` as suggested by @NielsRogge.
Did you verify that it fixes the error mentioned in the issue?

i.e. does the following work:

```
from transformers import BertTokenizer, VisualBertModel
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = VisualBertModel.from_pretrained('uclanlp/visualbert-vqa-coco-pre')
inputs = tokenizer("The capital of France is Paris.", return_tensors="pt")
visual_embeds =  torch.zeros((1,36,2048)) #example of ROI features
visual_token_type_ids = torch.ones(visual_embeds.shape[:-1], dtype=torch.long) #example
visual_attention_mask = torch.ones(visual_embeds.shape[:-1], dtype=torch.float)
inputs.update({{
    "visual_embeds": visual_embeds,
    "visual_token_type_ids": visual_token_type_ids,
    "visual_attention_mask": visual_attention_mask
}})
outputs = model(**inputs)
```<|||||>@NielsRogge

Yes. I tried it for the example and it works fine.<|||||>@NielsRogge Does this look okay?<|||||>Idont understand