Split forward_decode_paged into host bookkeeping (decode_prepare +
ids/pos upload + advance_seq_len) and a pure-GPU decode_core. The
paged-KV and sparse-MoE designs already read every per-step variable
(block table, context lens, expert ids) from stable-address device
buffers, so decode_core captures as-is.
GptOssDecodeGraph captures lazily on the second decode step (the
first eager step warms cuBLAS) after a "retained warmup": the step
runs once with the allocator quarantine on, stocking the pool with a
dedicated block for every allocation so the capture itself never
pool-misses (a cudaMalloc while capturing is illegal — and the
capture's own quarantine is what would otherwise starve the pool).
NCCL all-reduces capture cleanly; TP=2 replays in lockstep.
Wired into tp_engine, bench-gpt-oss, and xserv-chat via
GraphedGptOssDecoder (batch>1 falls back to eager;
XSERV_DECODE_GRAPH=0 disables). Greedy tokens identical to eager.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Close the <think> block when EOS or max_tokens interrupts an analysis
channel, and flush stdout after each analysis token so --think streams
smoothly instead of dumping in buffer-sized chunks.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The gpt-oss harmony `analysis` channel is the model's reasoning, analogous
to Qwen3's <think>. With --think, wrap it in a `<think>\n…\n</think>\n\n`
block (gray when color is on, like Qwen3) and then print the final-channel
answer; without --think, suppress the analysis and show only the answer.
Replaces the previous color-gated behavior (analysis shown gray only on a
TTY, with no markers). Analysis is still excluded from the multi-turn
history (answer_ids), so re-prefill drops CoT as before.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Re-render the whole conversation each turn and re-prefill into a freshly
cleared slot, with past assistant messages rendered as completed `final`
channels (analysis dropped, terminated with <|end|> not the <|return|>
stop token) — matching the model's training format and the server's
builder. The previous incremental cache kept every turn's chain-of-thought
plus <|return|> in context, which is out of distribution for harmony
multi-turn. The generator now returns the final-channel text to feed back
as history. Qwen3 keeps the incremental cache (its ChatML format is
unaffected); reset_slot factors out the free+re-register.
NOTE: this corrects the multi-turn *format* but does NOT cure the
long-context collapse on some inputs. That is a forward-pass numerical bug
(NaN / degenerate logits) reproducible in clean bench-gpt-oss independent
of the chat layer — the collapse token is vocab_size-1 (201087), the
all-NaN argmax tie-break. Tracked separately.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The hand-rolled gpt-oss system message dropped the canonical harmony
structure (identity / knowledge cutoff / current date / Reasoning level),
putting the model out of distribution — greedy decoding then flipped into
garbage or analysis loops on ~half of single-turn requests. Emit the
canonical system message (matching the model's chat_template.jinja
build_system_message macro) with Reasoning: low, plus a today_ymd() date
helper.
Also:
- Default the repetition penalty to off (1.0). Penalizing the harmony
control tokens (<|channel|>/<|message|>/<|start|>) that must repeat to
open the final channel made gpt-oss stop right after analysis, emitting
nothing.
- Suppress the literal "assistant" role header emitted between the
analysis and final channels (only print in the final channel, moe only;
non-moe Qwen3 stays in Normal and prints as before).
Verified on dash5 (TP=2): single-turn "capital of France" is now stable
across runs with a clean final answer; Qwen3 chat unaffected.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- Let the model generate its own <|channel|> routing instead of forcing
<|channel|>final<|message|> — matches the GGUF chat template behavior.
- State machine tracks harmony channels: analysis channel rendered gray,
final channel printed normally, <|end|> stops on final channel only.
- Add repetition penalty (default 1.3 for MoE, 1.0 for Qwen) with 512
token window to prevent greedy decode loops. Configurable via
XSERV_REP_PENALTY and XSERV_REP_WINDOW env vars.
- Fix Length path: use <|end|> instead of <|im_end|> for gpt-oss to
avoid poisoning the KV cache with garbage tokens on truncation.
- Server api.rs: append <|channel|>final<|message|> to the hardcoded
gpt-oss prompt (server expects to post-process the JSON output).
- Add startswith filter to minijinja for harmony template compatibility.
Known issue: gpt-oss multi-turn NaN when total context exceeds ~256
tokens — likely a flash_attention_sinks kernel bug with sliding window
layers at large kv_len + small q_len. Single-turn and short multi-turn
conversations work correctly.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The gpt-oss harmony format generates internal control tokens
(<|channel|>, <|start|>, <|end|>, <|message|>) that should not appear
in the user-facing output. Additionally, <|end|> marks the end of a
response segment but was not in the model's EOS list, causing the
model to self-prompt into analysis channels and loop.
Fix: treat <|end|> as a stop token, skip all harmony special tokens
from the output stream.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add ChatModel enum dispatching between Qwen3 and GptOss based on
config.is_moe(), following the TP engine pattern.
- Add --tp N flag for tensor-parallel inference (required for 39GB
gpt-oss-20b which doesn't fit on a single 32GB GPU).
- Add gpt-oss harmony chat template with channel/message format.
- Replace hardcoded is_stop_token() with tokenizer.is_eos() for
multi-model EOS support.
- Restore gpt-oss hardcoded prompt template in server api.rs, lost
during the Jinja template refactor.
- Fix GEMV race condition: the K-split kernel zeroed the FP32
accumulator inside the kernel (block k=0) while other blocks
atomicAdd'd concurrently. Pre-zero with cudaMemsetAsync instead.
- Update benchmark docs with post-fix results.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Cooked-mode read_line() left line editing to the terminal, so Backspace on a
multi-byte 汉字/かな/한글 deleted a byte (or behaved inconsistently across TTYs).
Replace with a raw-mode reader (libc termios): Backspace pops a whole char,
multi-byte input is reassembled from its continuation bytes, and a full-line
redraw renders double-width glyphs correctly. Non-TTY input falls back to a
plain read; raw mode is restored after each line. libc is already a locked
transitive dep, so this builds offline.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- paged_kv_cache: new block-paged KV cache; adds a pinned-host swap pool with
a second BlockAllocator, per-sequence Location {Gpu,Cpu}, and lossless
swap_out/swap_in (block-granular D2H/H2D) for vLLM-style preemption.
bytes_per_block helper exposes per-block cost for VRAM-based sizing.
- decode_graph: CUDA-graph decode path.
- qwen3/gpt2/kv_cache: paged prefill/decode forward + related updates.
- tokenizer/bins: BPE updates, new xserv-chat CLI, bench-qwen3 tweaks.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
