Update rewritings for qwen

[RunningLeon]

Motivation

update rewritings for the latest modeling_qwen.py as in huggingface

Modification

Please briefly describe what modification is made in this PR.

BC-breaking (Optional)

None

Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues.
2. The modification is covered by complete unit tests. If not, please add more unit tests to ensure the correctness.
3. If the modification has a dependency on downstream projects of a newer version, this PR should be tested with all supported versions of downstream projects.
4. The documentation has been modified accordingly, like docstring or example tutorials.

[lvhan028]

why?

[RunningLeon]

for these reasons, we could postpone the support of the feature for now and see if users really need it:

1. dynamic_ntk only works on prefilling phase where input_len is greater than seq_lenth in config.json, which is 8192 for qwen7b
2. dynamic_ntk should assign different ntk_alphas for different sequences in a batch, which is complicated to implement in pytorch engine
3. Qwen2 has remove dynamic_ntk, which means it is not so important.
4. Evaluations results with opencompass suggests that it won't change the results too much:

[jjjjohnson]

But seq_lenth for Qwen-14B is 2048
https://huggingface.co/Qwen/Qwen-14B/blob/main/config.json

[RunningLeon]

But seq_lenth for Qwen-14B is 2048 https://huggingface.co/Qwen/Qwen-14B/blob/main/config.json

Yes. you are right. How do you use lmdeploy with Qwen-14B on pytorch engine? is dynamic ntk useful for you ? Why not use Qwen2?