Optimize rope_deltas propagation logic in Qwen2.5-VL
Author: Xqle
Pull request: yes

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This PR fixes the propagation of `rope_deltas` in the Qwen2.5-VL model during generation. 

Currently, the `forward()` method of `Qwen2_5_VLForConditionalGeneration` accepts `rope_deltas` as an argument, but the value is never passed to the underlying `Qwen2_5_VLModel`. As a result, users providing `rope_deltas` directly to `forward()` would see no effect. 

**Modifications**

1. `Qwen2_5_VLForConditionalGeneration.forward()` now passes `rope_deltas` to `Qwen2_5_VLModel.forward()`.
2. `Qwen2_5_VLModel.forward()` now accepts `rope_deltas` and updates its internal state accordingly.
3. Updates `prepare_inputs_for_generation()` to store calculated rope_deltas
in model_inputs, aligning its handling with position_ids.

**Impact**

- Users can now explicitly provide `rope_deltas` during generation and have them correctly applied.
- Ensures consistency between prefill and decoding phases in multi-modal generation.
- Aligns the API behavior with documentation.


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Comments:
cc @zucchini-nlp for VLMs, @ArthurZucker for rope

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: qwen2_5_vl

Btw could this influence https://github.com/huggingface/transformers/issues/41180 ? If the rope_deltas state is never modified in the forward

LMK if you have bandwidth to apply the changes, otherwise I will add it to my TODO so we don't forget adding it in the future :)