fix: 12 bug fixes from comprehensive review — 51 tok/s verified on RTX 5090
P0 fixes (blocking usability): - FIX-01: thread-local cuBLAS handle (was creating/destroying per matmul) - FIX-16: EOS token no longer leaks into API responses - FIX-17: max_seq_len configurable via --max-seq-len (default 2048, was hardcoded 256) - FIX-18: max_tokens clamped to available seq space, prompt overflow returns 400 P1 fixes (bugs & performance): - FIX-07: CachingAllocator wired into all hot paths (to_device, embedding, rope, concat) - FIX-08: CudaDeviceProp buffer increased to 32KB for CUDA 12.9 safety - FIX-09: tokenizer byte_fallback graceful degradation (was panic) - FIX-19: causal mask uses -INFINITY instead of -1e9 (BF16 supports inf) - FIX-20: LayerNorm rewritten to numerically stable two-pass algorithm - FIX-21: min block size guard (32 threads) for LayerNorm/RMSNorm launches P2 fixes (improvements): - FIX-22: Option<GpuKVCache> + take() eliminates dummy KV cache allocations - FIX-23: RoPE cache no longer artificially capped at 8192 positions Verified on dash5 (RTX 5090): 51 tok/s batch=1, 74 tok/s 2-concurrent, 1.7-3.3x HF transformers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -42,7 +42,7 @@ impl Qwen3 {
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let lm_head_raw = take(&mut w, "lm_head.weight");
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let rope_cache = RopeCache::new(
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config.max_seq_len().min(8192), // limit for memory
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config.max_seq_len(),
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config.head_dim(),
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config.rope_theta.unwrap_or(1_000_000.0) as f32,
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);
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@@ -453,7 +453,7 @@ fn concat_rows(rows: &[Tensor]) -> Tensor {
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// Allocate output [B, cols] and copy each row into it
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let total_bytes = batch * row_bytes;
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let mut out_buf = xserv_cuda::GpuBuffer::alloc(total_bytes).expect("alloc concat_rows");
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let mut out_buf = xserv_cuda::allocator::cached_alloc(total_bytes).expect("alloc concat_rows");
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for (b, row) in rows.iter().enumerate() {
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assert_eq!(row.shape(), &[1, cols]);
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