[Feature][Optimization] Qwen Support Dynamic block_wise_fp8 cache

[ckl117]

Motivation

Qwen support dynamic block_wise_fp8 cache

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Modifications

Add append_decode_cache_T_int8_neox_rope_kernel

Usage or Command

python -m fastdeploy.entrypoints.openai.api_server \
    --model Qwen2-7B-Instruct \
    --tensor-parallel-size $1 \
    --port 8212 \
    --quantization '{"quantization":"mix_quant","kv_cache_quant_type":"block_wise_fp8"}'

Accuracy Tests

Checklist

• Add at least a tag in the PR title.
  • Tag list: [[FDConfig],[APIServer],[Engine], [Scheduler], [PD Disaggregation], [Executor], [Graph Optimization], [Speculative Decoding], [RL], [Models], [Quantization], [Loader], [OP], [KVCache], [DataProcessor], [BugFix], [Docs], [CI], [Optimization], [Feature], [Benchmark], [Others], [XPU], [HPU], [GCU], [DCU], [Iluvatar], [Metax]]
  • You can add new tags based on the PR content, but the semantics must be clear.
• Format your code, run pre-commit before commit.
• Add unit tests. Please write the reason in this PR if no unit tests.
• Provide accuracy results.
• If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

[paddle-bot]

Thanks for your contribution!

[codecov-commenter]

Codecov Report

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