feat(fm9g): integrate fused FFN op into csrc decoder layer

[ZhouBencheng]

Substitute the post-attention rms_norm + MLP block on FM9G with the InfiniCore fused-FFN op. The substitution is gated per forward() call by the INFINILM_USE_FUSED_FFN env var so a single process can interleave fused and non-fused passes — required for clean benchmarks. When MuP scaling on down_proj is active (alpha != 1.0), the per-op path is taken so the multiplier the fused kernel does not model is preserved.

The fused kernel accepts only rank-2 [ntok, hidden] tensors, while the engine carries hidden_states as [batch, seq_len, hidden]; the call site views to 2-D and back.

Expose gate_up_weight(), down_weight(), and down_alpha() on the shared MLP module so the FM9G decoder layer no longer needs to reach into protected members.

Add test/bench/bench_fused_ffn_csrc.py: meaningful Chinese prompts, interleaved NF/F rounds, time.perf_counter window around engine.generate(), optional correctness verification, markdown report, and a --no-chat-template flag for the very-short-input regime where the fused path matters most.

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[wooway777]

麻烦先提供以下截图：

1. 正常说话
2. 分布式
3. 性能对比

另外this->mlp_->down_alpha() != 1.0f这个条件九格能满足么？九格应该大多不是1.0

代码怎么调整后面再看看。感觉应该可以做成通用模块，最好在text decoder layers里完成判断。

以及建议用xmake参数作为开关，参考kv caching。而非读取环境变量。