[TFBart-like models] Problem with tf saving
## Context

Usually, encoder-decoder models require both `input_ids` and `decoder_input_ids` in order to do one forward pass. If one *e.g.* only passes the `input_ids` to TFT5 -> the model will complain:

```python
from transformers import TFT5ForConditionalGeneration
import tensorflow as tf
model = TFT5ForConditionalGeneration.from_pretrained("t5-small")

model(input_ids=tf.convert_to_tensor([10 * [2]])) # => will result in error saying `decoder_input_ids` have to be provided which is expected and correct
```

Now TFBart is a bit special in that it automatically generates the `decoder_input_ids` if they are not passed -> so that the above example would not throw an error for TFBartForConditionalGeneration.

The reason for this is this line: https://github.com/huggingface/transformers/blob/61443cd7d917ef323a799ee27bb4abc4344f0d11/src/transformers/models/bart/modeling_tf_bart.py#L1053

-> it automatically creates the `decoder_input_ids` from the `input_ids` if they are not provided. This is however more a hack than a good solution IMO. Soon we want to decouple the Bart-like models from each other and it would be good to delete this line from at least new Bart-like models. Now the problem.

## Problem:

The problem is now that if we delete these lines from Bart, then the `tf.saved_model.save(model, tmpdirname)` function does not work anymore. To reproduce: 
Go into master and comment out this if statement in TFBart: https://github.com/huggingface/transformers/blob/61443cd7d917ef323a799ee27bb4abc4344f0d11/src/transformers/models/bart/modeling_tf_bart.py#L1053. 

Then run the following code:

```python
from transformers import TFBartForConditionalGeneration
import tempfile
import tensorflow as tf

model = TFBartForConditionalGeneration.from_pretrained("sshleifer/bart-tiny-random")

input_ids = tf.convert_to_tensor([10 * [1]])
decoder_input_ids = tf.convert_to_tensor([10 * [8]])
inputs_dict = {"input_ids": input_ids, "decoder_input_ids": decoder_input_ids}


logits = model(inputs_dict).logits

model._saved_model_inputs_spec = None
model._set_save_spec(inputs_dict)

with tempfile.TemporaryDirectory() as tmpdirname:
    tf.saved_model.save(model, tmpdirname)
    model = tf.keras.models.load_model(tmpdirname)
    logits_2 = model(inputs_dict)["logits"]
```

=> the code will throw an error, but it should not! It seems like there is a weird naming mismatch between `input_ids` of `TFBartDecoder` and the `decoder_input_ids` in `TFBartModel`...@jplu I'd be thrilled if you could take a look at this and see how it can be solved.
This bug forced me to disable the corresponding test in the new `TFLed` model for now, see: https://github.com/huggingface/transformers/pull/9278/files#r549042909<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.