more fixes for post-training llama4
Author: winglian
Pull request: yes
Labels: name: for patch

# What does this PR do?

Along with the changes in #37319 , these are also needed to train llama4.

The guard on the `past_key_values` cache is because that will be None during training.

this is a LoRA training on Scout
<img width="1787" alt="Screenshot 2025-04-06 at 11 59 57 PM" src="https://github.com/user-attachments/assets/a44b5826-d255-475f-9f86-08dea837246e" />

Fixes # (issue)


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I'll fix the last issue should be alright

The last issue is because when you are training you should set `use_cache=False` if you don't want to use the cache. If you have it set to `True`, it will create a dynamic cache, which then has not max length, which means key len is the same as input sequence length

The issue was in the `chunked_mask` @winglian not the attention mask now

I think the cache isn't the issue in this case. It's the chunked attention (as you also point out to) which is why I opened #37351 originally

I added some debugging code and this guard (which follows eager for example):
https://github.com/vasqu/transformers/blob/5f9b6589fe852a14887d9108dffd3426616cff57/src/transformers/models/llama4/modeling_llama4.py#L786

(which doesn't solve the issue imo, but is good enough for now ig)