[`TF`] Fix Tensorflow XLA Generation on limited seq_len models
Author: vasqu
Pull request: yes
Labels: name: run-slow

# What does this PR do?
Fixes xla generation with models with a limited seq_len that they can generate. It has been recently (re)discovered in #33298, which results in slow runs to fail as we have indexing issues based on absolute positional embeddings (i.e., an index out-of-bounds error). The issue can only be observed on CPUs and not on GPUs (idk why but the error is just silently swallowed). 

The solution is to extend the embedding not only by `max_new_tokens` but also by the current `seq_len` at hand. Atm, `seq_len` hasn't been considered yet.

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No fixes but a ref to #33298
(possibly adding an issue if wanted)


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Comments:
@vasqu I suspect the reason that these errors are silent on GPU is that `tf.gather()` [does not do bounds checking on GPU](https://www.tensorflow.org/api_docs/python/tf/gather):

> Caution: On CPU, if an out of bound index is found, an error is raised. On GPU, if an out of bound index is found, a 0 is stored in the corresponding output value. 

`tf.gather()` is the underlying mechanism used for a lot of things like embedding layers and other index lookups, so this affects a lot of layers.

Either way, reviewing the rest of this now!


@vasqu can you push another empty commit with the `[run-slow] opt` message to trigger the slow CI there?

Oh wow, thanks for the insights into this. This is rather counter-intuitive to me tho :D Even some archaic cuda / gpu errors would suffice for me but it is what it is.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_33903). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

tests pass :) gentle ping @Rocketknight1