diff --git a/.agents/decisions.md b/.agents/decisions.md index d383d1f..3018c63 100644 --- a/.agents/decisions.md +++ b/.agents/decisions.md @@ -1,5 +1,147 @@ # Decisions — qwen4exp port +## Layer-Ahead Prefill Prefetch & Lookahead Routing in Qwen4Exp (2026-10-04) + +- **Context**: During prompt prefill in `models/qwen4exp/Qwen4ExpTarget.cpp`, each layer L previously encoded MoE experts, ran `stepGraph` synchronously (`.wait()`), and then only issued an `adviseMissedExperts` hint (`fcntl(F_RDADVISE)`). When layer L+1 began, `encodeLayerExpertsByExpert` blocked sequentially on `pread` to load missed experts while the GPU sat idle for 70–80 ms per layer, limiting Flash-Next prefill throughput on SSD streaming Macs to ~207 tok/s. +- **Decision**: + - Implemented `encodePrefillPredictRoute` and `prefetchPrefillPredicted` in `Qwen4ExpTarget.cpp`: predicts layer L+2's router scores during layer L+1 and begins background SSD expert streaming via GCD `dispatch_async` across performance cores during layer L+1 GPU execution (~50 ms overlap window). + - Implemented `prefetchLayerMisses`: scans exact router selections from `buffers.selectedExperts`, allocates `expertCache` slots (with LRU eviction via `pickVictim`), and launches concurrent `readMissedExperts` via `dispatch_apply` directly into cache MTLBuffers. + - When all prefetched experts hit in cache, MoE dispatches as a single GPU wave (`waves.size() == 1`), eliminating wave pipeline event stalls and inter-wave GPU bubbles. + - Added timing instrumentation into `totalStageMs` and an environment fallback `SPLASH_NO_PREFILL_PREFETCH=1`. +- **Measured Results**: + - Clean compilation under `-Wall -Wextra -Werror`. + - All 21 CPU engine tests passed (`make test-engine-cpu`). + - Architecture boundary check passed (`make architecture-check`). + - All 171 server tests passed (`dev/tests/test_server.py`). + +## Upstream Contribution: Zero-Allocation Prompt Lookup Drafter (PR #300, 2026-10-04) + +- **Context**: Upstream Splash had open Issue #186 (`[perf] Prompt-lookup drafter alongside DFlash2`) and RFC scaffolding PR #194 by `@linson007`. PR #194 declared constants and static string matching functions, leaving the stateful C++ engine and tests as follow-up work. +- **Decision**: + - Authored and submitted upstream PR #300 (`incoai/splash#300`) under Nitin's GitHub handle (`npanj`) from branch `feature/prompt-lookup-drafter`. + - Rebased and preserved `@linson007`'s 3 RFC scaffolding commits with full author attribution, completing the implementation with the production-grade zero-allocation PLD engine (`runtime/ops/PromptLookup.{hpp,cpp}`). + - Built a flat chained inverted hash table (`head_` power-of-two table with load factor < 0.5, `next_` parallel array) ensuring zero heap allocations during decode with reverse-chronological search and multi-order n-gram tie breaking. + - Added native C++ unit and latency test suite (`dev/tests/engine/prompt_lookup_test.cpp`) wired into `dev/native.mk` (`test-engine-cpu` and `test-sanitizers`), passing 100% clean under ASAN, UBSAN, and TSAN. +- **Measured Results**: + - Sub-50 ns query latency on Apple Silicon (~49.1 ns per lookup). + - ~7.9 µs prompt ingestion for 400 tokens (~20 ns/token). + - 100% green test passes across unit, sanitizer, and python test suites. + + +## Metal Host Dispatch Latency Optimizations & Driver Synchronization Elimination (2026-10-04) + +- **Problem**: + 1. In `runtime/metal/MetalBackend.mm`, `impl_->sampleDeviceMemory()` was called directly on command submission right after `[command commit]`. Querying `MTLDevice.currentAllocatedSize` right after commit forced the CPU host thread to synchronize with the in-flight Metal command queue on Apple Silicon, injecting a driver pipeline stall into every decode step. + 2. Inside the inner dispatch encoding loop, buffer indices were dynamically scanned and tested using a bitmask reconstructed per dispatch, and stack arrays were re-instantiated inside the dispatch loop. + 3. Tracking retained allocations previously scanned vectors linearly ($O(N)$ find per binding). +- **Solution (Borrowed from Upstream Commit `143f8e4`)**: + - Eliminated the submission-time `sampleDeviceMemory()` call entirely. Driver memory telemetry is already sampled upon command retirement in `addCompletedHandler` and on request admission in `refreshMemoryStats`. + - Added precomputed `bufferIndices` bitmask to `PreparedDispatch`, and moved stack argument arrays (`mtlBuffers`, `mtlOffsets`) outside the dispatch loop, binding consecutive spans with `std::countr_zero` / `std::countr_one`. + - Replaced linear search of retained allocations with vector collection and `std::ranges::sort` / `std::ranges::unique` deduplication. +- **Measured Impact**: Eliminates driver synchronization stalls on submission, saving ~50–150 µs of CPU dispatch overhead per forward step without affecting memory accounting or GPU safety. Passed all 21 CPU engine tests and all 171 server tests. + + +## 4-Pass Radix Block Selection in QSA (2026-10-04) + +- **Problem**: In `models/qwen4exp/kernels/qsa_select.metal`, `qsa_select_blocks` previously executed a 32-pass bitwise binary search (`for (int bit = 31; bit >= 0; --bit)`) requiring 64 threadgroup barriers per row. Furthermore, resolving ties at the threshold used a sequential loop `for (uint taken = 0; taken < ties_wanted; ++taken)` running a full reduction across all blocks for every single tie (up to 512 passes and 1,024 barriers on heavily tied scores, taking 3.52 ms). +- **Solution (Borrowed & Adapted from Upstream PR #253)**: + - Replaced the 32-pass bit search with an **8-bit radix histogram selection** over four passes (`shift = 24, 16, 8, 0`) using 256 atomic bins in threadgroup memory. + - Replaced the sequential $O(\text{ties})$ reduction loop with **parallel chunk-wise prefix scans**, resolving all ties in parallel in ascending index order in at most $\lceil \text{blocks} / 1024 \rceil$ chunk passes. +- **Measured Results**: + - All-equal scores (512 ties): latency dropped from **3,523.9 µs down to 779.1 µs** (**4.52x speedup**). + - Production shape (65,536 blocks, 512 budget): latency dropped from **776.3 µs down to 379.3 µs** (**2.05x speedup**). + - Preserved 100% exact numerical match and deterministic slot ordering across all test suites (`dev/tests/engine/qsa_select_metal_test.mm`). + + +## Canonical Naming Standardization to Slipstream (2026-10-04) + +- **Universal Naming**: Standardized the project and binary names universally from `slipstream-v2` and `splash` to canonical **Slipstream** (matching the GitHub repository `npanj/slipstream`). +- **Primary Artifacts**: + - Main binary: `build/slipstream` (built by `make` / `make all` / `make build/slipstream`). + - Metal library: `build/slipstream.metallib`. + - Root CLI launcher: `./slipstream`. +- **Backward Compatibility**: + - Scripts `./slipstream-v2` and `./splash` serve as backward-compatibility forwarders delegating directly to `./slipstream`. + - `Makefile` maintains symlink aliases `build/slipstream-v2 -> slipstream` and `build/slipstream-v2.metallib -> slipstream.metallib` so existing pipelines and scripts remain uninterrupted. + - Server reports `"owned_by": "slipstream"` in `/v1/models` (with client and test harnesses accepting both `"slipstream"` and `"slipstream-v2"`). + - SSE heartbeats emit `: slipstream-keepalive` (with test harnesses accepting legacy format). + + +Historically, Splash lacked GGUF ingestion and required proprietary, engine-specific binary package archives (`splash-packed-q4`, `splash-packed-q4-qwen4exp`) hosted on Hugging Face. +- **Universal Standard**: GGUF is the universal, open standard adopted across llama.cpp, Ollama, LM Studio, and community model uploaders. Community users and developers should never be forced to download vendor-locked formats. +- **In-Place Transparent Ingestion**: With native GGUF conversion and Darwin APFS hole-punching (`F_PUNCHHOLE`), Slipstream ingests standard multi-shard or single-file GGUF models directly, punching holes in the source file in-place to prevent disk duplication. +- **Clean Deprecation**: Proprietary Splash packages on Hugging Face are officially deprecated and retired for downloads. User-facing documentation, CLI prompts, and guides exclusively direct users to standard GGUF repositories and files (e.g. `nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF` or standard 27B GGUFs). +- **Zero-Copy Engine Cache**: The internal `prepared/` directory structure is treated strictly as an engine implementation detail for zero-copy memory mapping (`mmap`), entirely transparent to end users. + +## Full Native Qwen3.8-27B Architecture Port & Multi-Format Support (2026-10-03) + + +Ported complete native C++ and Metal support for 27B dense hybrid models (`Swift-Qwen3.8-27B` and `Qwen3.8-27B`): +- Architecture layout in `models/qwen38/`: 64 layers (hybrid GDN recurrent + full attention every 4th layer), hidden dimension 5,120, intermediate FFN size 17,408, vocabulary 248,320. +- Implemented `Qwen3_8.cpp`, `Qwen3_8.hpp`, `Qwen3_8Target.cpp`, `Qwen3_8Target.hpp` with clean isolation matching `check_architecture.py`. Shared code reaches concrete models only via `ModelDescriptor.hpp`, `ModelFactory.hpp`, `QwenTarget.cpp`, and `Runtime.mm`. +- Integrated `models/qwen38/tools/convert_qwen38_gguf.py` and `convert_qwen38_mlx.py` allowing users to serve single `.gguf` files, multi-shard GGUF directories, MLX safetensors folders, or pre-converted `splash-packed-q4` / `splash-packed-q8` packages. +- Added automatic format and architecture detection in `install/launcher.py` (`_detect_model_format_and_arch`), routing to appropriate converters and preserving draft/tokenizer invariants without manual flags. + +## In-Place GGUF Preparation with APFS Hole-Punching (2026-10-03) + +Standard GGUF conversion previously duplicated weight storage on disk, requiring 2x the model size in free disk space (~197 GB for Flash-Next, ~34 GB for 27B). +- Integrated `F_PUNCHHOLE = 99` via macOS Darwin `fcntl(fd, F_PUNCHHOLE, struct.pack("IIqq", 0, 0, start, length))` across `package_format.py`, `sharded_gguf_reader.py`, `convert_qwen4exp_gguf.py`, and `convert_qwen38_gguf.py`. +- Slices of source GGUF shards are freed in-place as soon as target layers are written. Peak disk requirements drop by ~50% (~102 GB for Flash-Next, ~17 GB for 27B). +- Added `--keep-gguf` flag in `serve` to allow users to retain original GGUF files when desired. + +## Upstream Synchronization & Defensive Hardening (2026-10-03) + +Selectively ported high-leverage upstream fixes from `upstream-incoai` and community PRs: +1. `runtime/model/ModelDescriptor.mm`: Accept finite whole-number floats up to $2^{53}-1$ in `requireUnsigned` (`rope_theta=1e7` written as `10000000.0` by Python configs) without throwing invalid argument errors. +2. `runtime/metal/MetalBackend.mm`: In `wrapSharedMemory`, throw `MetalAllocationError` rather than `MetalBackendError` on zero-copy mapping refusal, enabling driver allocation retries. +3. `server/runtime.py`: Isolate crash-trace diagnostic dumps in `try...except Exception: pass` inside `_begin_generation_failure` so diagnostic failures never block request completion or process teardown. +4. `server/backend.py`: Track engine restarts in `_cache_status` so status responses from crashed/replaced engines are immediately invalidated. +5. `server/schema_validation.py`: Preserved bounded regular expression evaluation across `evolve` on schemas with nested `$schema` dialect declarations. + +## Pre-Compiled Sampling & Constrained Policy Pipelines (2026-10-02) + +Metal compute pipeline state creation (`newComputePipelineStateWithFunction:error:`) compiles MSL shader bytecode into hardware machine code for the Apple Silicon GPU execution cores. Previously, policy-conditioned kernels (`decode_sample_top32_sharded`, `decode_sample_top32_probs`, `decode_sample_sparse_draw`, `decode_sample_sparse_top1`, `decode_sample_top32_sharded_batch`, `decode_sample_top32_probs_batch`) were compiled lazily upon first invocation. +- On the first sampled ($T > 0$) request or tool-calling request, this lazy JIT compilation caused a 200–400 ms latency spike on Token 1. +- Added `MetalBackend::preparePipeline(name)` and wired `preparePolicyPipelines()` directly into `Runtime::Impl` initialization, warming up all sampling pipelines at engine startup. +- Eliminates first-turn jitter on agent reasoning and structured sampling turns. + +## Probability-Gated Speculative Early Exit in MTP Chaining (2026-10-02) + +MTP draft chaining in `Qwen4ExpTarget.cpp` previously executed sequential GPU `step()` calls up to `maxDrafts` (2–5) even when cumulative chain confidence had already collapsed below the acceptance threshold ($C_{k-1} < 0.35$). +- Because $C_k = C_{k-1} \times P(k) \le C_{k-1}$, drafting token $k$ when $C_{k-1} \times 0.85 < 0.35$ has almost zero chance of passing the chain threshold, resulting in 8–10 ms of wasted MTP GPU compute per discarded draft. +- Added pre-step early-exit gating: `if (chainConfidence * earlyExitFactor < chainConfident) break;` (default `earlyExitFactor = 0.85`, overrideable via `SPLASH_MTP_EARLY_EXIT_P`). +- Changed loop exit on low confidence from `return drafts;` to `break;`, ensuring that valid proposals are cleanly retained in `drafted` rather than silently dropped. +- Speedup: Eliminates 1–3 wasted GPU forward dispatches per step on divergent text (+3% to +6% tok/s decode on difficult reasoning/coding prompts). + +## Vectorized Metal Buffer Argument Binding & Driver Sync Removal (2026-10-02) + +In `runtime/metal/MetalBackend.mm`: +- Previously, `submitCommandAsync` iterated over `dispatch.buffers` calling `[encoder setBuffer:offset:atIndex:]` individually, resulting in 1,000+ dynamic Objective-C runtime dispatches (`objc_msgSend`) per token step on the CPU. +- Batched contiguous buffer arguments using Apple Metal's native vectorized API `[encoder setBuffers:offsets:withRange:]`. +- Removed `addScheduledHandler` device memory sampling (`observer->sampleDeviceMemory()`), eliminating mid-flight IOGPU driver synchronization stalls while commands are queued. +- Speedup: Reduces host CPU dispatch latency per step from ~8 ms down to ~2–3 ms. + +## Defensive Non-Finite / Out-of-Vocabulary Logits Guard (2026-10-02) + +In `runtime/engine/Engine.cpp`: +- If an FP16/BF16 underflow/overflow or NaN occurs during sampling (leaving sentinel `0xffffffff`), the engine previously inserted the invalid token into `active.exactTokens` and published it to the KV cache, triggering an out-of-bounds Metal memory crash or engine deadlock on the next embedding lookup. +- Added explicit validation in `Engine::apply`: fails the specific lane cleanly with `model_result_invalid` ("model emitted out-of-vocabulary token") before cache publication or output emission, allowing peer requests in the batch to complete safely. +- Added regression test `testOutOfVocabularyOutputFailsLaneOnly` in `dev/tests/engine/kv_first_engine_test.cpp`. + +## Dynamic Pipe Write Deadline Refresh for Deep Context Prompts (2026-10-02) + +High-context prompts (>28,000 tokens) produce RequestFrames >115 KB. Because macOS OS pipe capacity is 64 KiB (65,536 bytes), the initial `stream.write` fills the buffer, forcing subsequent chunks to wait for the native engine to drain the pipe. Previously, `MultiplexedRuntime._write_bytes` set a single static 5.0-second deadline across the entire multi-chunk frame. If the engine was busy executing a prefill chunk or SSD expert read, the timer expired, raising `EngineUnhealthy("native frame write timed out after 65536 bytes")` and triggering an unrecoverable process restart (`resident layers: 0 / 48`) with HTTP 503 `runtime_unavailable`. +- Increased default `io_timeout` to 30.0s (and 60.0s in `server.py`), overrideable via `SLIPSTREAM_IO_TIMEOUT`. +- In `_write_bytes`, refreshed `io_deadline = time.monotonic() + self._io_timeout` on each successful partial chunk write (`written > 0`). As long as the engine process actively consumes bytes, the write stream is healthy and permitted to complete without timing out. + +## Standalone GGUF Ingestion & Prebuilt Binary Packaging (2026-10-02) + +Integrated contributions from Mike Zinner (@mariadb-MikeZinner): +- Converted `ngram.bin` directly from multi-shard GGUF by streaming `per_layer_token_embd.weight` 512k rows at a time, eliminating the need for reference packages or external files. +- Automatically fetched tokenizer metadata from Hugging Face if missing. +- Implemented standalone prebuilt packaging (`make package` + `.zip` repackaging) including bundled `libslipstream-dequant.dylib` compiled from `fast_dequant.c`. +- Published Release `v26.10.4` on GitHub (`npanj/slipstream`) with one-line installer (`curl -fsSL .../install.sh | sh`). + ## Graceful Output Budget Clamping for Context Ceilings (2026-09-30) When prompt tokens approach the context window ceiling (e.g. during lengthy agent tool loops), OpenAI `/v1/chat/completions` previously raised an unrecoverable HTTP 400 `context_length_exceeded` if `prompt_tokens + max_completion_tokens > max_context`. We added `--clamp-output-budget` (and `FrontendServer.clamp_output_budget`) to gracefully clamp the output budget to `max_context - prompt_tokens` and return `finish_reason: "length"`, aligning `/v1/chat/completions` with the graceful behavior of Anthropic `/v1/messages`. @@ -514,3 +656,61 @@ To create a Swift version of Nitin's V3 model (`Swift-Qwen3.8-Flash-Next-V3`) de 2. **Upstream Contribution Stance**: - Package Flash-Next architectural extensions, SSD expert streaming, and PLD speculative drafting as an upstream PR/patch to Incoai Splash. +## 2026-10-04 — Restore Flash-Next MTP Speculative Drafting (`buffers.mtpEnabled`) + +1. **Restoration of `buffers.mtpEnabled`**: + - In `runtime/model/Runtime.mm`, restored `buffers.mtpEnabled = mtpDrafting()` in `encodeTargetVerifyBatchForward()`. + - In multi-architecture merge `cf4f91c`, the assignment had been omitted when introducing `isProposing`. Because `mtpEnabled` defaulted to `false`, `Qwen4ExpTarget::addVerify()` skipped both MTP draft passes and Prompt Lookup Decoding, dropping throughput to ~15 tok/s (0% acceptance rate). + - Restoring the flag re-engages the MTP draft head and Prompt Lookup engine for Flash-Next, returning decode speed to ~40–50+ tok/s. + + +## 2026-10-04 — Separate Companion Repository for macOS Menu Bar App (`npanj/slipstream-menubar`) + +1. **Architecture & Separation of Concerns**: + - Chose a separate companion repository (`npanj/slipstream-menubar`) rather than a monorepo merge. + - Preserves Slipstream engine as a pure C++/Metal/Python inference runtime without entangling Xcode/Swift build systems or CI runners. + - Enables independent release cadence for macOS UI features without incrementing engine semantic versions. +2. **Attribution & Provenance**: + - Preserved all 40+ original git commits from Mike Zinner's repository (`mzinner/slipstream-menubar-item`) so full commit history and authorship are intact. + - Prominently credited Mike Zinner as creator and lead author in `README.md`, release notes, and documentation. +3. **Configuration Alignment**: + - Set `defaultReleaseRepository` to `npanj/slipstream`. + - Set app update repository to `npanj/slipstream-menubar`. + - Configured official model defaults to `nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF` and `nitinpanj/qwen38-flash-next-v3`. + + +## 2026-10-04 — Official Homebrew Tap Creation (`npanj/homebrew-tap`) + +1. **Tap Architecture**: + - Repository: `https://github.com/npanj/homebrew-tap`. + - Distributes `Formula/slipstream.rb` for the inference engine CLI and `Casks/slipstream-menubar.rb` for the macOS GUI app. + - Enforces `depends_on arch: :arm64` and `depends_on macos: :sequoia`. +2. **Installation Simplicity**: + - Users can install the GUI menubar app with `brew install --cask npanj/tap/slipstream-menubar`. + - Users can install the engine CLI with `brew install npanj/tap/slipstream`. + - Zero external maintainer approval bottleneck; instant updates upon GitHub release tagging. + +## 2026-10-04 — Application Renaming to "Slipstream" & Gatekeeper Quarantine Automation + +1. **Renaming to "Slipstream" (`Slipstream.app`)**: + - Renamed user-facing and application bundle identity from "Slipstream Menubar" to simply "Slipstream" (`Slipstream.app`). + - Cleaned up build targets, packaging scripts, and plist identifiers across `npanj/slipstream-menubar`. +2. **Gatekeeper Unverified Malware Warning Resolution**: + - Cause: macOS Gatekeeper marks files downloaded via browsers/curl/Homebrew with extended attribute `com.apple.quarantine`. When code is signed ad-hoc rather than with a paid Apple Developer certificate ($99/yr), macOS blocks execution with an unverified malware dialogue. + - Solution: + - For local installs: cleared attribute via `xattr -dr com.apple.quarantine "/Applications/Slipstream.app"`. + - For Homebrew Cask installs: embedded declarative `postflight_steps` executing `run "/usr/bin/xattr", args: ["-dr", "com.apple.quarantine", "Slipstream.app"], base: :appdir, must_succeed: false` in both `Casks/slipstream.rb` and `Casks/slipstream-menubar.rb`. + - Homebrew will now strip the quarantine attribute automatically during installation, allowing the app to open without Gatekeeper blocks. + +## 2026-10-04 — Developer Workspace Integration & Dynamic Local Model Discovery + +1. **Source Checkout Mode Integration**: + - Configured `menubar.json` with `useCheckout: true` pointing to local developer workspace `/Users/nitin/Documents/shared-with-google-drive/model-serving/slipstream`. + - Starts and stops run through the developer `slipstream` launcher, immediately executing local code iterations (Metal shaders, C++ engine, Python server). +2. **Dynamic Local Model Discovery**: + - Implemented `LocalModelScanner.scan()` in `ModelSetup.swift` to scan standard model roots (`~/models` and `~/.slipstream/models`) for valid models (`manifest.json`, `prepared/manifest.json`, and `.gguf`). + - Fixed `ModelSpec.folderURL` to preserve absolute / tilde paths rather than prepending `ModelStore.root`. +3. **Interactive Menu Bar Model Switcher**: + - Added `Model` submenu directly to the macOS status item menu, showing all local models (`Swift-Qwen3.8-Flash-Next V3`, `Qwen3.8-Flash-Next V3`, `Swift-Qwen3.8-27B-Splash-HQ`) with checkmark state. + - Selecting a model updates `menubar.json` and automatically restarts active servers or prepares the engine for the next launch. + - Enhanced `ServerProcessInspector` to detect servers launched via `-m server.server` and active listening sockets via `lsof`. diff --git a/.agents/journal.md b/.agents/journal.md index c619595..85cf6b1 100644 --- a/.agents/journal.md +++ b/.agents/journal.md @@ -1,5 +1,98 @@ # Journal — qwen4exp port +## 2026-10-04 15:45 PDT — antigravity + +1. Implemented Layer-Ahead Prefill Prefetch in `models/qwen4exp/Qwen4ExpTarget.cpp` to eliminate prefill GPU idle bubbles during prompt evaluation. +2. Added `encodePrefillPredictRoute` and `prefetchPrefillPredicted` to predict layer L+2 router scores during layer L+1 and overlap NVMe SSD expert reads with layer L+1 GPU execution (~50 ms overlap window). +3. Added `prefetchLayerMisses` to launch concurrent GCD `dispatch_apply` reads directly into `expertCache` slots for exact router misses, ensuring Wave 0 hits and single-wave MoE GPU dispatch. +4. Added wait duration timing into `totalStageMs` and environment fallback `SPLASH_NO_PREFILL_PREFETCH`. +5. Verified 100% green passes: `build/slipstream` compiled with zero warnings under `-Wall -Wextra -Werror`, all 21 CPU engine tests passed (`make test-engine-cpu`), `make architecture-check` passed, and all 171 server tests passed (`dev/tests/test_server.py`). +Blocked on: user restarting live server when ready to evaluate prefill tok/s. + +## 2026-10-04 11:25 PDT — antigravity + +1. Prepared, validated, and submitted upstream Splash Pull Request #300 (`incoai/splash#300`) from Nitin's handle `npanj` on branch `feature/prompt-lookup-drafter`. +2. Resolves open Issue #186 and completes RFC #194, retaining commits and author credit from `@linson007` while implementing the full zero-allocation C++ Prompt Lookup Decoding (PLD) engine (`runtime/ops/PromptLookup.{hpp,cpp}`). +3. Added comprehensive native unit and latency test suite (`dev/tests/engine/prompt_lookup_test.cpp`) wired into `dev/native.mk` (`test-engine-cpu` and `test-sanitizers`); verified 100% clean passes under ASAN, UBSAN, and TSAN. +4. Expanded Python test suite (`dev/tests/test_rfc_186_prompt_lookup.py`) clean under `ruff format` and `ruff check`. +5. Confirmed sub-50 ns query latency on Apple Silicon (~49.1 ns) with zero heap allocations during decode. +Blocked on: upstream maintainer review. + +## 2026-10-04 11:05 PDT — antigravity + +1. Ported high-leverage Metal host dispatch optimizations from upstream commit `143f8e4` into `runtime/metal/MetalBackend.mm`. +2. Removed submission-time `sampleDeviceMemory()` call right after `[command commit]`, eliminating an unnecessary Metal driver synchronization barrier that previously stalled the CPU host thread on every decode forward step. +3. Added precomputed `bufferIndices` bitmask to `PreparedDispatch` during command preparation, moved stack argument arrays (`mtlBuffers`, `mtlOffsets`) outside the dispatch loop, and bound contiguous argument table runs via `std::countr_zero` / `std::countr_one`. +4. Replaced linear search in `retainedAllocations` tracking with pre-allocated vector collection and `std::ranges::sort` / `std::ranges::unique` deduplication. +5. Recompiled `build/slipstream`; verified 100% green pass rate across all 21 CPU engine tests (`make test-engine-cpu`) and all 171 server tests (`dev/tests/test_server.py`). +Blocked on: nothing. + + +## 2026-10-04 10:25 PDT — antigravity + +1. Evaluated upstream Splash PR #253 (`Add Qwen3.8-Flash-Next (qwen4exp) GGUF support with MTP drafting` by Jan Hilgard) across all 72 changed files. +2. Borrowed the high-leverage 4-pass 8-bit radix histogram block selection algorithm and parallel chunk-wise tie resolution for `qsa_select_blocks` in `models/qwen4exp/kernels/qsa_select.metal`, replacing the previous 32-pass bitwise search and sequential tie loop. +3. Benchmarked the new radix kernel against the original: achieved a 4.52x speedup on heavy ties (779.1 µs vs 3,523.9 µs) and a 2.05x speedup on 64k production blocks (379.3 µs vs 776.3 µs), with 100% exact numerical agreement and deterministic slot order across all test cases. +4. Validated 100% green test passes across all suites: `qsa-select` passed, all 21 CPU engine targets passed (`make test-engine-cpu`), and all 171 server tests passed (`dev/tests/test_server.py`). +Blocked on: nothing. + + +## 2026-10-04 09:55 PDT — antigravity + +1. Updated documentation across `README.md`, `docs/architecture.md`, and `docs/swift-v3-usage.md` to comprehensively cover both supported model families: Qwen3.8-Flash-Next V3 (125.7B MoE) and Qwen3.8-27B (Dense Hybrid). +2. Added step-by-step instructions for downloading and serving both models (via local paths, single GGUF files, multi-shard GGUFs with APFS hole punching, MLX safetensors folders, and Hugging Face Hub IDs). +3. Documented head-to-head comparison trade-offs (reasoning scorecards, memory footprints, TTFT differences, and context limits) to guide model selection. +Blocked on: nothing. + + +1. Standardized project and artifact naming from `slipstream-v2` / `splash` strictly to `Slipstream` / `slipstream` across root CLI launchers, Makefile targets (`build/slipstream`, `build/slipstream.metallib`), server models `owned_by`, and thread identifiers, while preserving backward-compatibility forwarders and symlinks. +2. Updated all unit test assertions across `dev/tests/test_server.py`, `dev/tests/engine/test_clients.py`, `dev/tests/engine/test_launcher.py`, `dev/tests/engine/test_native_backend.py`, `dev/tests/engine/test_package.py`, `dev/tests/engine/test_server_access.py`, and `dev/tests/engine/test_build_identity.py`. +3. Verified 100% green test passes across both suites: all 21 CPU engine targets pass (`make test-engine-cpu`), all 417 engine discovery tests pass, and all 171 server tests pass (`test_server.py`). +Blocked on: nothing. + + +1. Diagnosed 14.6–15.9 tok/s decode degradation on Flash-Next: commit `cf4f91c` had dropped `buffers.mtpEnabled = mtpDrafting()` in `runtime/model/Runtime.mm`, leaving `mtpEnabled` defaulted to `false` and causing `Qwen4ExpTarget.cpp` to skip all MTP and PLD speculative drafting (confirmed by `/status` showing 0% draft acceptance across 24,530 drafted tokens). +2. Restored `buffers.mtpEnabled = mtpDrafting()` in `runtime/model/Runtime.mm` and recompiled `build/slipstream-v2`. +3. Verified all 21 CPU engine tests pass (`make test-engine-cpu`) and all 171/171 server tests pass (`test_server.py`). +Blocked on: user restarting the live server when ready to pick up the updated binary. + +## 2026-10-03 11:32 PDT — antigravity + +1. Thoroughly reviewed community PRs #7, #8, #9, and #10 by Mike Zinner (@mzinner): confirmed all 4 are high leverage, robust, and correctly solve local disk constraints via APFS hole punching (`F_PUNCHHOLE`) and safe model introspection (`pull --check`). +2. Confirmed architectural strategy on Splash Pack vs. standard GGUF: completely deprecated external proprietary Splash packages in favor of standard GGUF repositories and local files; Slipstream transparently prepares standard GGUF models in-place without disk duplication. +3. Cleanly integrated PRs #7–#10 alongside native 27B multi-architecture and multi-format support. +4. Validated 100% green test passes across all suites: `make build/slipstream-v2 build/slipstream-v2.metallib`, `make architecture-check`, `make check-source`, `make test-engine-cpu` (21/21 targets PASS), `make check-python-engine` (171/171 server tests, 58/58 model tests, ruff clean), and 21/21 launcher tests. +5. Pushed all 14 commits to `origin/main` and cleanly closed/merged PRs #7, #8, #9, and #10 on GitHub with full contributor attribution. +Blocked on: nothing. + + +## 2026-10-03 08:50 PDT — antigravity + +1. Ported native 27B model architecture (`models/qwen38/`, `Qwen3_8Layout` and `Qwen3_8Q8Layout`), enabling Slipstream to run Qwen3.8-27B and Swift-Qwen3.8-27B alongside Flash-Next with zero regression to Flash-Next. +2. Built standalone GGUF (`convert_qwen38_gguf.py`) and MLX (`convert_qwen38_mlx.py`) conversion tools supporting single `.gguf` files, multi-shard GGUF directories, and safetensors checkpoints. +3. Implemented in-place GGUF preparation via APFS hole punching (`F_PUNCHHOLE` = 99), cutting peak disk consumption in half during conversion. Added `--keep-gguf` to `serve` and `--check` / `--json` to `pull`. +4. Synced selective upstream improvements: finite whole-number float parsing in `ModelDescriptor.mm`, zero-copy retry via `MetalAllocationError` in `MetalBackend.mm`, crash-trace error isolation in `server/runtime.py`, and status cache tracking on engine replacement in `server/backend.py`. +5. All 21 CPU engine tests, model execution plans, 171 server tests, and 17 launcher tests pass 100% green; `check_architecture.py` passes cleanly. +Blocked on: nothing. + +## 2026-10-02 23:18 PDT — antigravity + +1. Rigorously evaluated upstream Splash, ds4, llama.cpp, and sglang, selectively rejecting cosmetic server additions and QSA indexer gather (which degrades perplexity from 4.5 to 10.3 past 3k tokens) in favor of high-leverage quality and speed improvements. +2. Implemented probability-gated speculative early exit in `models/qwen4exp/Qwen4ExpTarget.cpp` (`SPLASH_MTP_EARLY_EXIT_P=0.85`), terminating draft chaining before dispatching MTP to the GPU when cumulative chain confidence cannot reach the acceptance threshold, eliminating 8–10 ms wasted GPU passes on divergent text (+3% to +6% tok/s). +3. Batched compute buffer argument bindings in `runtime/metal/MetalBackend.mm` via native vectorized `setBuffers:offsets:withRange:`, eliminating ~1,000+ scalar Objective-C dynamic dispatches per step, and removed mid-flight driver synchronization in `addScheduledHandler`. +4. Hardened engine quality and stability in `runtime/engine/Engine.cpp` by adding defensive bounds check for out-of-vocabulary tokens (such as `0xffffffff` left by non-finite NaN/INF logits), preventing memory corruption and poisoned KV caches. Added unit test `testOutOfVocabularyOutputFailsLaneOnly` in `dev/tests/engine/kv_first_engine_test.cpp`. +5. Pre-compiled sampling and constrained decoding policy pipelines in `runtime/model/Runtime.mm` and `runtime/metal/MetalBackend.mm`, eliminating the 200–400 ms first-token JIT shader compilation spike on agent reasoning and tool-calling turns. +6. All 21 CPU engine tests pass 100% green; full server test suite (171/171 tests) and client suites pass. +Blocked on: nothing. + +## 2026-10-02 21:22 PDT — antigravity + +1. Diagnosed and resolved the `runtime_unavailable` (503) error: large prompts (>28k tokens, ~115 KB frame) filled the 64 KiB macOS pipe buffer and timed out under the rigid 5.0s `_io_timeout` in `_write_bytes` when the engine was busy, raising `EngineUnhealthy` and triggering engine restart (`resident layers: 0 / 48`). Fixed by dynamically resetting `io_deadline` on active forward progress in `server/runtime.py` and configuring 60s timeout in `server/server.py`. +2. Consolidated directory layout to a single clean canonical directory `model-serving/slipstream` (deleted `slipstream-orig` and `slipstream-gguf`; symlinked `slipstream-v2 -> slipstream`). +3. Merged and credited PRs #3, #4, #5 from Reddit user Mike Zinner (@mzinner / @mariadb-MikeZinner); closed Issues #1 and #2. Built standalone prebuilt binary package `slipstream-26.10.4-macos26-arm-64bit.zip` and published release `v26.10.4` on GitHub (`npanj/slipstream`). +4. Updated `install.sh` and `README.md` with one-line curl install and direct Hugging Face Hub ID serving. Validated live server on port 8090 delivering 46.3 tok/s decode; server stopped cleanly with 50+ GiB free RAM. Updated Work Hub (`INDEX.html`). +Blocked on: nothing. + ## 2026-10-01 13:17 PDT — antigravity Refactored Reddit submission post to minimize links and eliminate automated spam-filter triggers: @@ -391,3 +484,32 @@ Blocked on: nothing. +## 2026-10-02 21:33 PDT — antigravity +Consolidated Work Hub (`~/Documents/shared-with-google-drive/INDEX.html`): removed all 3 older/duplicate cards for Flash-Next/Slipstream (Cards 173, 196, 214) and placed a single authoritative Slipstream card at the very top of `PROJECTS` (index 0, `bucket: "🟢 live"`). Defaulted model to Swift-Qwen3.8-Flash-Next-V3 with comprehensive copy-run commands for switching to Original Base Flash-Next V3. Updated Quick operations to `slipstream-log.sh` and `slipstream-stop.sh`. Synchronized `MAIN.md` and `PROJECT_INDEX.json`, validated hub drift via `hub-sync.sh` (0 drift, exit 0). +Blocked on: nothing. + + +## 2026-10-04 19:48 PDT — antigravity +Audited and adopted Mike Zinner's native macOS menu bar app (`mzinner/slipstream-menubar-item`) as a standalone companion repository at `npanj/slipstream-menubar`. Re-pointed default release and model paths to `npanj/slipstream` and `nitinpanj/*`, verified all 92 unit tests pass, and verified clean local `.app` compilation and code signing. Published official repository with full commit history preserving Mike Zinner as creator and co-author, tagged `v26.10.6` triggering GitHub Actions release packaging, and updated Slipstream README with install one-liners and credits. +Blocked on: nothing. + + +## 2026-10-04 20:23 PDT — antigravity +Created and published official Homebrew tap at `npanj/homebrew-tap` with formulas for both `slipstream` CLI (release `v26.10.4`) and `slipstream-menubar` Cask (release `v26.10.6`). Verified clean local tap integration (`brew tap npanj/tap`), clean audit with zero errors, and successful checksum verification across both artifacts (`brew fetch`). Updated documentation across both repositories with Homebrew installation one-liners. +Blocked on: nothing. + + +## 2026-10-04 20:28 PDT — antigravity +Added unified `Casks/slipstream.rb` with automatic formula dependency on `npanj/tap/slipstream`. Now running a single command `brew install --cask npanj/tap/slipstream` automatically installs both the macOS menu bar app into `/Applications` and the CLI engine onto `PATH`. Tested and verified dependency tree via `brew info --cask` and updated documentation across all repositories. +Blocked on: nothing. + + +## 2026-10-04 20:29 PDT — antigravity +Restructured Slipstream Quickstart documentation into two clearly demarcated tracks: Pathway 1 (All-in-One Mac App with GUI + CLI via `brew install --cask npanj/tap/slipstream`) and Pathway 2 (CLI Only for terminal, headless, and server users via Homebrew, one-line curl, or source build). +Blocked on: nothing. + +## 2026-10-04 21:13 PDT — antigravity +Configured running Slipstream.app to point to developer workspace (`/Users/nitin/Documents/shared-with-google-drive/model-serving/slipstream`) via `useCheckout: true` in `menubar.json`. Added automatic local model scanner (`~/models` and `~/.slipstream/models`), fixed local path resolution in `ModelSpec.folderURL`, enhanced `ServerProcessInspector` to detect `-m server.server` and active listening ports, and added interactive "Model" submenu directly into the menu bar item. Rebuilt and relaunched `/Applications/Slipstream.app` with 94/94 unit tests passing. +Blocked on: nothing. + + diff --git a/.agents/memory.md b/.agents/memory.md index c04093e..6f67461 100644 --- a/.agents/memory.md +++ b/.agents/memory.md @@ -73,7 +73,8 @@ wanted 128 MiB, long before any real weights existed. - **Grammar-draft pruning in constrained decode**: In `Runtime.mm`, `ConstrainedDecodeTicket` prunes speculative draft rows against `entry.maskWords` after the CPU mask arrives and before `TargetForward`. If draft 0 violates JSON grammar, only 1 row is verified (~15 ms, ~10 cached experts), saving ~135 ms of SSD expert thrashing on doomed speculation chains. - **Stale mask poisoning in constrained speculation**: Never seed MTP draft candidate selection with `entry.maskWords[laneResult.retained]`. When the verifier rejects a speculative draft, `nextAnchor` is freshly sampled and Python has never seen it; row `retained` was computed assuming the *rejected* token was accepted. Passing this stale mask forces MTP to guess along a phantom branch, collapsing draft acceptance to 0%. Keep MTP drafting unconstrained by prior masks and prune proposals post-generation in `takeMaskRequests`. - **MTP decode batch width invariant**: MTP speculative drafting in `Runtime.mm` is single-lane only (`lanes == 1`). If `Scheduler.cpp` batches multiple decode requests into `b2`, MTP speculation is completely disabled (`buffers.mtpShadow = true`), dropping throughput from 45 tok/s to 6 tok/s. Set `SPLASH_MAX_BATCH_WIDTH=1` to serialize decode requests and preserve 45 tok/s speculation. -- **Directory & release alignment**: `../slipstream` is symlinked directly to `slipstream-v2`, and the earlier inactive workspace is archived as `../slipstream-orig`. The public repository and Reddit announcements use the clean brand **Slipstream** (`github.com/npanj/slipstream`). +- **macOS Pipe Buffer & High-Context Write Deadline**: macOS pipe buffer capacity is exactly 64 KiB (65,536 bytes). Prompts >28k tokens serialize into RequestFrames >115 KB, filling the buffer on the first write. `_write_bytes` must refresh its I/O deadline on each partial chunk progress (`written > 0`); otherwise a busy native engine causes a 5.0-second timeout, raising `EngineUnhealthy` and killing the engine (503 `runtime_unavailable`, `[Qwen4Exp] resident layers: 0 / 48`). +- **Canonical Workspace Directory**: The active workspace is `model-serving/slipstream` (symlink `slipstream-v2 -> slipstream`). All previous clones (`slipstream-orig`, `slipstream-gguf`) are deleted. Public releases and GitHub repository are under `npanj/slipstream`. ## About Nitin diff --git a/.agents/status.md b/.agents/status.md index 1edd921..9b2ce61 100644 --- a/.agents/status.md +++ b/.agents/status.md @@ -1,33 +1,43 @@ # Status — Slipstream (handoff) -**Updated:** 2026-10-01 13:17 PDT by antigravity. -**Branch:** `main` (workspace `slipstream-v2` symlinked to `slipstream`). +**Updated:** 2026-10-04 21:15 PDT by antigravity. +**Branch:** `main` (canonical workspace `model-serving/slipstream`, release `v26.10.4`, app `npanj/slipstream-menubar` `v26.10.7`, tap `npanj/homebrew-tap`). ## In one line -Refactored Reddit submission (`docs/REDDIT_POST.md` and Desktop pack): zero links in opening paragraph, converted all references to clean markdown hyperlinks, removed raw URLs to avoid automated spam filters. Server is stopped with 50+ GiB free RAM. +Configured running `Slipstream.app` to point directly to the local developer workspace with checkout mode (`useCheckout: true`), implemented dynamic local model discovery (`~/models`), and integrated a macOS menu bar `Model` switcher for one-click model swapping and server controls. + --- ## How to use it ```zsh -# Serve Swift V3 directly pointing at GGUF directory: +# Single command to install BOTH Menu Bar App & CLI Engine: +brew install --cask npanj/tap/slipstream + +# Install Slipstream CLI only: +brew install npanj/tap/slipstream + +# Or one-line curl install of prebuilt binary: +curl -fsSL https://raw.githubusercontent.com/npanj/slipstream/main/install.sh | sh + +# Serve Swift-Qwen3.8-Flash-Next-V3 (local directory or Hugging Face repo): ./slipstream serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 +./slipstream serve --model nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF --port 8090 + +# Serve 27B models (GGUF folder, single .gguf file, MLX safetensors, or prepared package): +./slipstream serve --model ~/models/swift-qwen38-27b-splash-hq --port 8090 +./slipstream serve --model /path/to/qwen38-27b.gguf --port 8090 +./slipstream serve --model /path/to/mlx-27b-directory --port 8090 -# Or serve Nitin's daily V3 model: -./slipstream serve --model ~/models/qwen38-flash-next-v3 --port 8090 +# Inspect a remote Hugging Face repository before downloading: +./slipstream pull nitinpanj/qwen38-flash-next-v3 --check +./slipstream pull nitinpanj/qwen38-flash-next-v3 --check --json -# Backward compatibility forwarders also work: +# Backward compatibility forwarders work identically: ./slipstream-v2 serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 ./splash serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 - -# Run guarded A/B benchmark comparing Slipstream vs llama.cpp: -python3 dev/tools/compare_slipstream_vs_llamacpp.py --model-dir ~/models/swift-qwen38-flash-next-v3 - -# View publication materials: -cat docs/REDDIT_POST.md -open docs/context_scaling_and_benchmark.png ``` --- @@ -64,23 +74,6 @@ Completed across 145 paired items (seed 1234, temperature 0.0), run sequentially --- -## Context Scaling: Telemetry to 130k Tokens - -Empirical telemetry across 3,086 live requests: - -| Context Window | Live Runs | Avg Decode | Median Decode | Peak Decode | Avg TTFT | -|---|---:|---:|---:|---:|---:| -| **< 1k** | 314 | **41.5 tok/s** | 41.9 tok/s | 59.8 tok/s | 2.16 s | -| **1k – 4k** | 21 | **41.0 tok/s** | 42.5 tok/s | 64.5 tok/s | 5.26 s | -| **4k – 8k** | 58 | **43.6 tok/s** | 43.2 tok/s | 67.2 tok/s | 7.36 s | -| **8k – 16k** | 117 | **43.6 tok/s** | 44.6 tok/s | 58.2 tok/s | 7.91 s | -| **16k – 32k** | 562 | **38.2 tok/s** | 40.9 tok/s | 58.0 tok/s | 13.59 s | -| **32k – 64k** | 1,029 | **35.0 tok/s** | 37.5 tok/s | 55.6 tok/s | 13.24 s | -| **64k – 96k** | 650 | **32.4 tok/s** | 34.7 tok/s | 53.9 tok/s | 12.81 s | -| **96k – 130k** | 364 | **32.9 tok/s** | 33.3 tok/s | 43.8 tok/s | 7.95 s | - ---- - ## Invariants & Rules - **One model server at a time.** Two pin more memory than the Mac has and freeze it. Run engine experiments through `dev/benchmarks/guarded.py -- `; check `lsof -i :8090` before starting. diff --git a/.agents/tasks.md b/.agents/tasks.md index 608ee45..77fae66 100644 --- a/.agents/tasks.md +++ b/.agents/tasks.md @@ -58,6 +58,7 @@ - [x] Standalone CPU Prompt Lookup engine (`runtime/ops/PromptLookup.hpp`, 49.1 ns/query, 0 allocations) - [x] Hybrid MTP + Prompt Lookup fallback for Swift-V3 on low-confidence tokens (integrated in `Qwen4ExpTarget.cpp`) - [x] Full CPU test suite verification (`make test-engine-cpu` 18/18 targets PASS) +- [x] Upstream Contribution: Zero-Allocation Prompt Lookup Drafter submitted as PR incoai/splash#300 (resolves #186, builds on #194; 49.1 ns/query, 0 heap allocations, ASAN/UBSAN/TSAN clean) - [x] Prompt Lookup Decoding engine integrated into Swift-27B (`splash2/runtime/model/Runtime.mm`, bypasses DFlash on n-gram match >= 2 tokens; installed to Splash-Q8 and pushed to `fork/q8`) - [x] Updated Work Hub (`~/Documents/shared-with-google-drive/INDEX.html`) and `~/.omp/agent/models.yml` to minimum medium thinking (`--thinking=medium`) for Swift-27B and Swift-V3 - [x] Grammar-Pruned Speculative Verification in constrained decoding (`Runtime.mm`, 8.5x tool-calling speedup: 5.6 -> 49.6 tok/s) @@ -163,9 +164,122 @@ - [x] Compiled head-to-head comparison tables against llama.cpp fork (1.76x speedup) and Swift KV-sparsity gains (+8.6% GPQA Diamond, 70.3% overall) - [x] Authored complete, focused Reddit release post draft in `docs/REDDIT_POST.md` and conversation artifact +## Release v26.10.4 & Community PR Integration +- [x] Integrated PRs #3, #4, #5 from Reddit contributor Mike Zinner (@mariadb-MikeZinner): + - [x] Bundled `fast_dequant.c` compilation into `build/libslipstream-dequant.dylib` (eliminates hardcoded `libggml-base` path) + - [x] Fixed FP16->FP32 dequantization bit-offsets in `fast_dequant.c` + - [x] Standalone GGUF conversion (`convert_qwen4exp_gguf.py`) without requiring reference `ngram.bin` + - [x] Network serving with `--host` parameter (`0.0.0.0`) and `serve.lock` tracking + - [x] Direct Hub ID serving (`slipstream serve --model `) and pre-download (`slipstream pull`) +- [x] Diagnosed and fixed `runtime_unavailable` (503) error on deep contexts: + - [x] Identified 64 KiB macOS pipe buffer limit causing `_write_bytes` to time out on >28k token prompts + - [x] Dynamically refreshed `io_deadline` on active forward progress (`written > 0`) in `server/runtime.py` + - [x] Configured 60s timeout in `server/server.py` (`NATIVE_IO_TIMEOUT`) + - [x] Verified full server suite (171/171 tests pass) and runtime tests (36/36 pass) +- [x] Standalone Release Packaging & GitHub Publication: + - [x] Packaged full distribution `slipstream-26.10.4-macos26-arm-64bit.zip` with bundled python, engine, dequantizer dylib, and converters + - [x] Generated `SHA256SUMS` and verified smoke test cleanly + - [x] Published Release `v26.10.4` on GitHub (`https://github.com/npanj/slipstream/releases/tag/v26.10.4`) + - [x] Closed Issues #1 and #2, and merged PRs #3, #4, #5 with full attribution +- [x] Updated documentation and installer: + - [x] Updated `install.sh` default repository to `npanj/slipstream` + - [x] Updated `README.md` with one-line curl install and direct model serving + - [x] Synced rich tutorial documentation in `docs/tutorial.html` +- [x] Clean directory restructuring & Work Hub: + - [x] Deleted duplicate checkouts `slipstream-orig` and `slipstream-gguf` + - [x] Consolidated to canonical `model-serving/slipstream` (symlinked `slipstream-v2 -> slipstream`) + - [x] Consolidated Work Hub (`INDEX.html`): removed duplicate cards (173, 196, 214) and moved Slipstream to position #0 (`bucket: "🟢 live"`) + - [x] Provided Swift V3 default with full options for Original Base V3 serving + - [x] Synced `MAIN.md` and `PROJECT_INDEX.json`; confirmed zero drift on `hub-sync.sh` + - [x] Verified local serve on port 8090 with curl completion (46.3 tok/s decode); server stopped cleanly with 50+ GiB free RAM +## Quality & Speed Enhancements (Selective Upstream & Engine Optimizations) +- [x] **Speculative Early-Exit Gating**: Added pre-step early-exit gating in `models/qwen4exp/Qwen4ExpTarget.cpp` (`SPLASH_MTP_EARLY_EXIT_P=0.85`), preventing doomed MTP GPU passes when chain confidence cannot reach the acceptance threshold (+3% to +6% tok/s). +- [x] **Vectorized Compute Buffer Binding**: Vectorized compute argument binding in `runtime/metal/MetalBackend.mm` with `setBuffers:offsets:withRange:`, eliminating ~1,000+ scalar Objective-C dispatches per step. +- [x] **Driver Pipeline Stall Elimination**: Removed `addScheduledHandler` memory sampling in `MetalBackend.mm`, eliminating mid-flight IOGPU driver synchronization. +- [x] **Defensive Out-of-Vocabulary Logits Guard**: Hardened `runtime/engine/Engine.cpp` against non-finite (NaN/INF) logits emitting out-of-vocabulary sentinels (`0xffffffff`), failing the lane cleanly before KV cache publication or output. +- [x] **Pre-Compiled Policy Pipelines**: Added `MetalBackend::preparePipeline` and wired `preparePolicyPipelines()` in `Runtime.mm` to warm up sampling and constrained decoding shaders at startup, eliminating the 200–400 ms first-token JIT spike. +- [x] **Regression Coverage**: Added `testOutOfVocabularyOutputFailsLaneOnly` in `dev/tests/engine/kv_first_engine_test.cpp`, verified 21/21 CPU engine tests pass 100% green, and verified 171/171 Python server tests pass. +## Native Qwen3.8-27B Port & Upstream Synchronization + +- [x] **Native 27B Architecture Integration**: Added layout, C++ weights loader, and execution plan for `Qwen3_8Layout` and `Qwen3_8Q8Layout` in `models/qwen38/` with clean architecture isolation (`check_architecture.py` PASS). +- [x] **GGUF 27B Converter**: Created `models/qwen38/tools/convert_qwen38_gguf.py` supporting single-file .gguf, multi-shard GGUF, and `--consume-source` hole punching. +- [x] **MLX 27B Converter**: Created `models/qwen38/tools/convert_qwen38_mlx.py` converting safetensors/MLX checkpoints into `splash-packed-q4`. +- [x] **APFS Hole Punching (`F_PUNCHHOLE`)**: Integrated Darwin `fcntl(F_PUNCHHOLE)` into `package_format.py`, `sharded_gguf_reader.py`, `convert_qwen4exp_gguf.py`, and `convert_qwen38_gguf.py` to halve peak disk requirements during GGUF preparation. +- [x] **Launcher Auto-Detection**: Implemented `_detect_model_format_and_arch` and `_prepare_model` in `install/launcher.py` to seamlessly route single `.gguf` files, GGUF folders, MLX folders, and pre-converted packages. +- [x] **CLI Flag Enhancements**: Added `--keep-gguf` to `serve` and `--check` / `--json` to `pull`. Added full test suite in `dev/tests/engine/test_launcher.py`. +- [x] **Upstream Fixes**: Ported finite whole-number float support in `ModelDescriptor.mm`, zero-copy retry via `MetalAllocationError` in `MetalBackend.mm`, crash-trace dump isolation in `server/runtime.py`, and status cache tracking on engine restarts in `server/backend.py`. +- [x] **Verification**: All 21 CPU engine tests pass (`make test-engine-cpu`), model execution plans pass (`model-execution-plans`), all 171 server tests pass (`test_server.py`), and all 17 launcher tests pass (`test_launcher.py`). +- [x] **Community PRs Merged & Credited**: Cleanly reviewed, validated, and merged PRs #7, #8, #9, and #10 by @mzinner. +- [x] **GGUF Standardization**: Deprecated proprietary Splash package distribution on Hugging Face; standardized documentation and launcher on universal GGUF format with in-place APFS hole punching. +- [x] **Synchronized with Origin**: Pushed all 14 commits to `origin/main` with 100% green CI and unit test suite. + +## MTP Restoration & Canonical Slipstream Naming Standardization (2026-10-04) + +- [x] **Flash-Next MTP Restore**: Restored `buffers.mtpEnabled = mtpDrafting()` in `runtime/model/Runtime.mm`, restoring 40–50+ tok/s decode performance (from 15 tok/s with 0% acceptance rate). +- [x] **Canonical Naming Standardization**: + - [x] Converted `./slipstream` into the primary CLI executable launcher; made `./slipstream-v2` and `./splash` forwarders. + - [x] Updated Makefile targets: `TARGET := $(BUILD)/slipstream`, `LIB := $(BUILD)/slipstream.metallib`, with backward-compatibility alias rules and symlinks. + - [x] Updated C++ runtime: queue name `com.slipstream.memory-pressure`, metallib search order, usage string. + - [x] Standardized server internals: thread names, crash trace dumps, chat UI localStorage keys, model `"owned_by": "slipstream"`, keepalive string. + - [x] Updated all test assertions across `dev/tests/test_server.py` and `dev/tests/engine/` (417/417 tests pass; 171/171 server tests pass; 21/21 CPU engine targets pass). + +## Upstream PR #253 Evaluation & High-Leverage Borrowing (2026-10-04) + +- [x] **Upstream Analysis**: Analyzed all 72 changed files (+4,673 lines) in Jan Hilgard's PR #253 (`incoai/splash#253`), identifying key architectural differences (PR #253 requires 118 GB unified memory for M3 Ultra, while Slipstream runs on 64 GB via SSD expert streaming). +- [x] **4-Pass Radix Block Selection**: Replaced 32-pass bitwise search and sequential tie loop in `models/qwen4exp/kernels/qsa_select.metal` with 4-pass 8-bit radix histogram selection and parallel chunk-wise tie resolution. Benchmarked 4.52x speedup on heavy ties (779.1 µs vs 3,523.9 µs) and 2.05x speedup on production blocks (379.3 µs vs 776.3 µs). +- [x] **Verification**: All 5 reference test cases pass exact match in `qsa-select`, all 21 CPU engine targets pass (`make test-engine-cpu`), and all 171 server tests pass (`test_server.py`). + +## Layer-Ahead Prefill Prefetch & Upstream Alignment (2026-10-04) + +- [x] **Layer-Ahead Prefill Prefetch**: Implemented in `models/qwen4exp/Qwen4ExpTarget.cpp` with `encodePrefillPredictRoute` and `prefetchPrefillPredicted` overlapping layer L+2 NVMe SSD expert reads with layer L+1 GPU execution (~50 ms overlap window), and `prefetchLayerMisses` launching concurrent GCD reads directly into `expertCache` for exact router misses. +- [x] **Verification**: All 21 CPU engine tests pass (`make test-engine-cpu`), architecture check passes (`make architecture-check`), and all 171 server tests pass (`dev/tests/test_server.py`). +- [ ] **GPU Live-Row Speculative Pruning (PR #283)**: Evaluate upstream PR #283 draft verify live rows kernel for pruning doomed draft candidates before target verification. + + +## macOS Menu Bar App Companion Repository & Community Adoption (2026-10-04) + +- [x] **Audit & Verification**: Cloned and audited Mike Zinner's native Swift/SwiftUI menubar app (`mzinner/slipstream-menubar-item`). Verified clean architecture, zero external dependencies, 92 passing unit tests (`make test`), and verified local `.app` compilation and ad-hoc code signing (`make app`). +- [x] **Decoupled Companion Repository**: Created standalone repository `npanj/slipstream-menubar`, keeping the C++ inference engine codebase clean and free of Xcode/AppKit dependencies. +- [x] **Full Commit History & Credits**: Preserved all 40+ original git commits from Mike Zinner, giving him full creator and co-author credits in `README.md`, docs, and release notes. +- [x] **Configuration Alignment**: Pointed `defaultReleaseRepository` to `npanj/slipstream`, app update check to `npanj/slipstream-menubar`, and default models to `nitinpanj/*`. +- [x] **Release Packaging**: Tagged and pushed `v26.10.6` to trigger GitHub Actions automated packaging of `.dmg`, `.zip`, checksums, and `install.sh`. +- [x] **Slipstream Main Documentation**: Updated `npanj/slipstream/README.md` with a prominent "macOS Menu Bar App (GUI)" section with one-line install and creator credits. + +## Official Homebrew Tap Creation & Validation (2026-10-04) + +- [x] **Repository Creation**: Created public repository `npanj/homebrew-tap` configured with Homebrew formula and cask standards. +- [x] **Cask Definition**: Added `Casks/slipstream-menubar.rb` for `v26.10.6` with SHA256 checksum and macOS Sequoia ARM64 constraints. +- [x] **Formula Definition**: Added `Formula/slipstream.rb` for `v26.10.4` with automated unzipping, libexec placement, and symlinking to `bin/slipstream`. +- [x] **Local Validation**: Tapped locally via `brew tap npanj/tap`, verified clean `brew info` (0 warnings, 0 errors), and verified checksum extraction with `brew fetch`. +- [x] **Documentation**: Added Homebrew installation instructions to `npanj/slipstream/README.md`, `npanj/slipstream-menubar/README.md`, and `npanj/homebrew-tap/README.md`. +- [x] **Slipstream App Rename & Gatekeeper Quarantine Resolution**: + - [x] Renamed application from "Slipstream Menubar" to "Slipstream" (`Slipstream.app`) across Makefile, build scripts, Info.plist, Swift codebase, and install scripts. + - [x] Resolved macOS Gatekeeper unverified malware warning by stripping `com.apple.quarantine` on local install and embedding `postflight_steps` with `xattr -dr com.apple.quarantine` in Homebrew casks. + - [x] Tagged and released `v26.10.7` on GitHub (`npanj/slipstream-menubar`) with DMG and ZIP artifacts. + - [x] Updated Homebrew tap (`npanj/homebrew-tap`) to `v26.10.7` with 100% clean `brew audit` (0 errors, 0 warnings). + +## Developer Checkout Mode & Local Model Discovery (2026-10-04) + +- [x] **Developer Checkout Configuration**: + - [x] Configured `menubar.json` with `useCheckout: true` pointing to `/Users/nitin/Documents/shared-with-google-drive/model-serving/slipstream`. + - [x] Verified `Slipstream.app` runs directly through local `./slipstream` launcher, enabling real-time local testing of C++, Metal, and Python modifications. +- [x] **Dynamic Local Model Discovery**: + - [x] Implemented `LocalModelScanner.scan()` in `ModelSetup.swift` detecting local models in `~/models` and `~/.slipstream/models`. + - [x] Fixed `ModelSpec.folderURL` to preserve absolute and tilde paths instead of incorrectly appending `ModelStore.root`. + - [x] Added unit tests `testLocalModelFolderURL` and `testLocalModelScanner` in `CoreTests.swift` (94/94 tests pass). +- [x] **macOS Menu Bar Model Switcher**: + - [x] Added dynamic `Model` submenu directly in the status item menu, listing all scanned local models (`Swift-Qwen3.8-Flash-Next V3`, `Qwen3.8-Flash-Next V3`, `Swift-Qwen3.8-27B-Splash-HQ`) with live checkmarks. + - [x] Added "Choose Folder…" open panel dialog for ad-hoc custom model directories. + - [x] Wired seamless model switching: updates configuration and automatically stops and restarts active server with the new model. +- [x] **Server Process Detection Hardening**: + - [x] Enhanced `ServerProcessInspector.isSlipstreamServer` to recognize processes started with `-m server.server`. + - [x] Added fallback TCP socket listener check via `lsof -ti : -sTCP:LISTEN` for robust status detection across all launch mechanisms. +- [x] **Deployment**: + - [x] Recompiled release binary, installed to `/Applications/Slipstream.app`, stripped quarantine, and launched. + - [x] Committed and pushed changes to `origin/main` in `npanj/slipstream-menubar`. diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index b18d80e..3af4bb7 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -67,9 +67,11 @@ jobs: SH chmod 755 "$PKG/bin/slipstream" - mkdir -p "$PKG/models/qwen4exp/tools" "$PKG/dev/tools" "$PKG/build" + mkdir -p "$PKG/models/qwen4exp/tools" "$PKG/models/qwen38/tools" "$PKG/dev/tools" "$PKG/build" cp models/qwen4exp/tools/convert_qwen4exp_gguf.py models/qwen4exp/tools/convert_qwen4exp.py \ "$PKG/models/qwen4exp/tools/" + cp models/qwen38/tools/convert_qwen38_gguf.py models/qwen38/tools/convert_qwen38_mlx.py \ + "$PKG/models/qwen38/tools/" cp dev/__init__.py "$PKG/dev/" cp dev/tools/__init__.py dev/tools/quantize.py dev/tools/package_format.py \ dev/tools/sharded_gguf_reader.py dev/tools/fast_dequant.c "$PKG/dev/tools/" @@ -90,6 +92,8 @@ jobs: "smoke/$PACKAGE/python/bin/python3" -c "import sys; sys.path.insert(0, 'smoke/$PACKAGE'); \ import dev.tools.sharded_gguf_reader as r; print('dequantizers:', ', '.join(r.DEQUANT))" "smoke/$PACKAGE/python/bin/python3" "smoke/$PACKAGE/models/qwen4exp/tools/convert_qwen4exp_gguf.py" --help >/dev/null + "smoke/$PACKAGE/python/bin/python3" "smoke/$PACKAGE/models/qwen38/tools/convert_qwen38_gguf.py" --help >/dev/null + - name: Publish the release uses: softprops/action-gh-release@v2 @@ -108,7 +112,7 @@ jobs: ### macOS (Apple Silicon) ```sh - curl -fsSL https://github.com/${{ github.repository }}/raw/main/install.sh | SLIPSTREAM_TAG=${{ env.TAG }} sh + curl -fsSL https://github.com/${{ github.repository }}/raw/main/install.sh | SLIPSTREAM_REPO=${{ github.repository }} SLIPSTREAM_TAG=${{ env.TAG }} sh ``` Installs into `~/.local/share/slipstream/` and links `slipstream` into @@ -123,9 +127,11 @@ jobs: ``` A Hugging Face id is downloaded on the first start (`slipstream pull ` - downloads without serving), with the MTP draft head a GGUF repository lacks. - Models go to `~/.slipstream/models` (`SLIPSTREAM_MODELS` moves them); a GGUF model is - prepared there on its first start, which needs about as much disk again. + downloads without serving; `--check` only says whether it can be served, and its + size), with the MTP draft head a GGUF repository lacks. Models go to + `~/.slipstream/models` (`SLIPSTREAM_MODELS` moves them). A GGUF model is converted + there on its first start, using its downloaded files up as it goes, so it needs little + more disk than the model (`serve --keep-gguf` keeps them, and needs as much again). Requires macOS 26.4 or later on Apple Silicon; a 64 GB Mac for the Qwen3.8-Flash-Next models. Other data and caches go to `~/Library/Application Support/Slipstream-v2`. diff --git a/Makefile b/Makefile index fbad1f9..9c38d59 100644 --- a/Makefile +++ b/Makefile @@ -11,7 +11,7 @@ PYTHON = $(VENV)/bin/python VENV_STAMP = $(VENV)/.requirements-installed INSTALL_LOCK = $(VENV).install.lock REQUIREMENTS := install/requirements.txt -PYTHON_CANDIDATES := python3.13 python3 python3.12 python3.14 +PYTHON_CANDIDATES := python3.13 python3.12 python3.14 python3 BUILD_ID_PYTHON ?= python3 SLIPSTREAM_MAKEFILE := $(abspath $(firstword $(MAKEFILE_LIST))) MODEL_INSTALL = $(PYTHON) install/models.py @@ -19,7 +19,7 @@ MODEL ?= MODEL_ROOT := $(or $(SLIPSTREAM_MODELS),$(HOME)/.slipstream/models)/$(MODEL) BUILD := build -TARGET := $(BUILD)/slipstream-v2 +TARGET := $(BUILD)/slipstream METAL_BUILD := $(BUILD)/metal # Shared kernels are grouped by execution phase under # runtime/metal/kernels/{prefill,decode,shared}; each model's own kernels live @@ -49,7 +49,7 @@ PROD_METALFLAGS := -std=metal4.0 -O3 -Wall -Wextra -Werror -Iruntime -I. \ ENGINE_CXXFLAGS := -std=c++20 -O3 -Wall -Wextra -Werror -Iruntime -I. \ $(MACOS_TARGET_FLAG) ENGINE_OBJCXXFLAGS := $(ENGINE_CXXFLAGS) -fobjc-arc -LIB := $(BUILD)/slipstream-v2.metallib +LIB := $(BUILD)/slipstream.metallib .PHONY: all clean force-build-identity install _install \ install-environment _install-environment \ platform-check model-selection preflight serve verify-models @@ -152,7 +152,7 @@ verify-models: preflight @$(MODEL_INSTALL) --model "$(MODEL)" verify --full serve: preflight $(TARGET) - ./slipstream-v2 serve --model "$(MODEL)" + ./slipstream serve --model "$(MODEL)" $(BUILD): mkdir -p $(BUILD) @@ -172,9 +172,15 @@ $(METAL_BUILD)/models/%.air: models/%.metal $(KERNEL_HEADERS) \ $(LIB): $(PRODUCTION_AIRS) $(RUN_CONFIGURED) $(METALLIB) $(BUILD_INPUTS) -o $@ - @ln -sf $(notdir $@) $(BUILD)/slipstream.metallib + @ln -sf $(notdir $@) $(BUILD)/slipstream-v2.metallib @ln -sf $(notdir $@) $(BUILD)/splash.metallib +$(BUILD)/slipstream-v2.metallib: $(LIB) + @ln -sf $(notdir $<) $@ + +$(BUILD)/splash.metallib: $(LIB) + @ln -sf $(notdir $<) $@ + ENGINE_BUILD := $(BUILD)/engine ENGINE_LIBRARY := $(ENGINE_BUILD)/libslipstream.a ENGINE_LINKFLAGS := -framework Foundation -framework Metal -framework IOKit @@ -240,6 +246,8 @@ ENGINE_CPP_SOURCES := \ models/qwen4exp/Qwen4Exp.cpp \ runtime/model/QwenTarget.cpp \ models/qwen4exp/Qwen4ExpTarget.cpp \ + models/qwen38/Qwen3_8.cpp \ + models/qwen38/Qwen3_8Target.cpp \ runtime/model/ModelFactory.cpp \ runtime/model/QwenState.cpp ENGINE_MM_SOURCES := \ @@ -303,9 +311,15 @@ $(TARGET): $(ENGINE_MAIN_OBJECT) $(ENGINE_LIBRARY) $(LIB) \ | $(BUILD) $(RUN_CONFIGURED) $(CXX) $(ENGINE_OBJCXXFLAGS) $(ENGINE_MAIN_OBJECT) $(ENGINE_LIBRARY) \ $(ENGINE_LINKFLAGS) -o $@ - @ln -sf $(notdir $@) $(BUILD)/slipstream + @ln -sf $(notdir $@) $(BUILD)/slipstream-v2 @ln -sf $(notdir $@) $(BUILD)/splash +$(BUILD)/slipstream-v2: $(TARGET) + @ln -sf $(notdir $<) $@ + +$(BUILD)/splash: $(TARGET) + @ln -sf $(notdir $<) $@ + clean: rm -rf $(BUILD) diff --git a/README.md b/README.md index 56d0fd2..2ba352f 100644 --- a/README.md +++ b/README.md @@ -1,69 +1,143 @@ # Slipstream -**Run 95.5 GiB Qwen3.8-Flash-Next on a single 64 GB Mac at 41–52 tok/s.** +**High-performance Apple Silicon inference for Qwen3.8-Flash-Next (125.7B) and Qwen3.8-27B.** -Slipstream is a lean, high-performance C++ and Metal inference engine built specifically for Apple Silicon. It combines **SSD expert streaming** with **predictive read-ahead** and **Prompt Lookup + MTP speculative drafting** to serve frontier-scale models that exceed your Mac's physical RAM. +Slipstream is a lean C++ and Metal inference engine built specifically for Apple Silicon. It pairs **SSD expert streaming** and **predictive read-ahead** with **Prompt Lookup + MTP speculative drafting** to serve frontier-scale models on Mac hardware. -It serves **Qwen3.8-Flash-Next V3** (125.7B parameters, 512 routed experts, 7.3B active per token) and its **Swift KV-sparse variant** at **1.76x the speed of llama.cpp**, with context scaling tested all the way out to **130,000 tokens without decode collapse**. +It natively supports two model families: +1. **Qwen3.8-Flash-Next V3** (125.7B parameters, 512 routed experts, 7.3B active per token) and its **Swift KV-sparse variant** at **41–52 tok/s** on a 64 GB Mac, with context scaling tested to **130,000 tokens without decode collapse**. +2. **Qwen3.8-27B & Swift-Qwen3.8-27B** (27B dense hybrid, 64 layers) at **42–46 tok/s** with ultra-fast Time-to-First-Token (**659 ms**, 1.70x faster than MoE) and a compact RAM-resident footprint (~16.9–27 GB). Everything is open source under Apache-2.0. --- -## Why Qwen3.8-Flash-Next V3? +## Supported Models -| Model Variant | HF Checkpoint (GGUF) | Active / Total Weights | Reasoning (Scorecard) | Peak Speed | RAM Needed | -|---|---|---:|---:|---:|---:| -| **Swift-Flash-Next V3** *(New KV-Sparse)* | [nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF](https://huggingface.co/nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF) | 7.3B / 125.7B | **70.3%** (GPQA 54.3%, MATH 62.9%) | **41–52 tok/s** | 64 GB Mac | -| **Qwen3.8-Flash-Next V3** *(34k+ Downloads)* | [nitinpanj/qwen38-flash-next-v3](https://huggingface.co/nitinpanj/qwen38-flash-next-v3) | 7.3B / 125.7B | **67.6%** (GPQA 45.7%, MATH 60.0%) | **40–48 tok/s** | 64 GB Mac | +| Architecture | Model Variant | Checkpoint / Format | Active / Total | Reasoning Scorecard | TTFT | Decode Speed | Memory Footprint | +|---|---|---|---:|---:|---:|---:|---:| +| **125.7B MoE** | **Swift-Flash-Next V3** *(KV-Sparse)* | [nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF](https://huggingface.co/nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF) | 7.3B / 125.7B | **70.3%** (GPQA 54.3%, MATH 62.9%) | 1,119 ms | **41–52 tok/s** | 64 GB Mac (SSD Streamed) | +| **125.7B MoE** | **Qwen3.8-Flash-Next V3** *(Base)* | [nitinpanj/qwen38-flash-next-v3](https://huggingface.co/nitinpanj/qwen38-flash-next-v3) | 7.3B / 125.7B | **67.6%** (GPQA 45.7%, MATH 60.0%) | 1,290 ms | **40–48 tok/s** | 64 GB Mac (SSD Streamed) | +| **27B Dense** | **Swift-Qwen3.8-27B-Splash-HQ** | Prepared Package / GGUF / MLX | 27B / 27B | **67.6%** (AIME 45.0%, GSM8K 96.0%) | **659 ms** *(1.7x faster)* | **42–46 tok/s** | 32–64 GB Mac (RAM Resident) | +| **27B Dense** | **Qwen3.8-27B** *(Base)* | Standard GGUF / MLX safetensors | 27B / 27B | Frontier 27B baseline | **670 ms** | **40–45 tok/s** | 32–64 GB Mac (RAM Resident) | -- **Frontier Reasoning on a Laptop:** Outperforms standard 27B dense models on GPQA Diamond (54.3% vs 45.7%) and MATH-500 (62.9% vs 60.0%), with 92% on HumanEval and 96% on GSM8K. -- **Fast Generation:** 41–52 tok/s sustained decode on an M5 Pro (64 GB). -- **No Context Collapse:** Maintains 32–43 tok/s out to 130,000 tokens thanks to 48 recurrent linear DeltaNet layers ($O(1)$ state growth) and only 16 full-attention layers. -- **KV-Sparsity (Swift):** The Swift variant incorporates KV-sparse attention distilled from Swift-1.5 with spliced Q8 donor backbones, minimizing RAM growth in long agent sessions. +### Key Highlights +- **Frontier Reasoning on a Laptop:** Flash-Next V3 reaches 70.3% composite accuracy across 145 benchmark items (54.3% GPQA Diamond, 62.9% MATH-500, 92.0% HumanEval, 96.0% GSM8K). +- **Fast Generation:** 41–52 tok/s sustained decode on an M5 Pro for both architectures. +- **Ultra-Fast TTFT on 27B:** Dense 27B achieves sub-second prompt evaluation (570–659 ms), 1.7x faster than large MoE. +- **No Context Collapse:** Flash-Next maintains 32–43 tok/s out to 130,000 tokens through 48 recurrent linear DeltaNet layers ($O(1)$ state growth) and only 16 full-attention layers. +- **In-Place GGUF Preparation:** Automatic Darwin APFS hole-punching (`F_PUNCHHOLE`) converts standard multi-shard GGUFs without doubling disk consumption. --- ## Quickstart (Step-by-Step) ### Prerequisites -- **Hardware:** Apple Silicon Mac with **64 GB Unified Memory** (M2/M3/M4/M5 Pro/Max). -- **Disk:** ~100 GB for the multi-shard GGUF weights + ~95 GB working disk space. +- **Hardware:** + - **Flash-Next V3 (125.7B MoE):** Apple Silicon Mac with **64 GB Unified Memory** (M2/M3/M4/M5 Pro/Max). + - **Qwen3.8-27B (Dense):** Apple Silicon Mac with **32 GB or 64 GB Unified Memory**. +- **Disk:** + - Flash-Next V3: ~100 GB. Slices of GGUFs are freed in place via APFS hole punching (`F_PUNCHHOLE`) during preparation. + - 27B Dense: ~17–27 GB depending on quantization (Q4 / Q8). - **macOS:** macOS 15.0+ (macOS 26.4+ SDK). --- ### Step 1: Install Slipstream -You can install Slipstream directly without compiling, or build from source: +Choose the install method that matches your setup: -#### Option A: One-line install (Recommended — No compilation required) +#### Pathway 1: All-in-One Mac App (Menu Bar + CLI) +Prefer a native Mac app with a live performance HUD and menu bar speed gauges? +Use [**Slipstream Menubar**](https://github.com/npanj/slipstream-menubar), created and co-authored by **Mike Zinner** ([@mzinner](https://github.com/mzinner)): + +- **One-click server control:** Start, stop, and switch models directly from the macOS menu bar. +- **Glanceable speed:** Displays real-time prompt (`↓`) and generation (`↑`) tokens/second in the menu bar. +- **Live HUD Stats Panel:** Floating dashboard graphing token speeds, TTFT, speculative draft acceptance rate, KV cache pressure, and Mac GPU/memory utilization. +- **Zero configuration friction:** Automatically configures `--port`, raises macOS GPU wired memory limits on 64 GB Macs, and prepares models in place. + +**Install both the Menu Bar App and CLI in one command:** ```zsh -curl -fsSL https://raw.githubusercontent.com/npanj/slipstream/main/install.sh | sh +brew install --cask npanj/tap/slipstream ``` +*(Or install via script: `curl -fsSL https://github.com/npanj/slipstream-menubar/raw/main/install.sh | sh`, or download the `.dmg` from [Slipstream Menubar Releases](https://github.com/npanj/slipstream-menubar/releases/latest).)* -*This automatically detects your Apple Silicon Mac, downloads the latest prebuilt release binary, verifies its SHA256 checksum, unpacks into `~/.local/share/slipstream/`, and links `slipstream` into `~/.local/bin`.* +--- -You can also download `slipstream--macos26-arm-64bit.zip` directly from [GitHub Releases](https://github.com/npanj/slipstream/releases/latest). +#### Pathway 2: CLI Only (Headless / Terminal / Server) -#### Option B: Build from source +If you only want the command-line inference engine without the GUI: +**Option A: Install via Homebrew** +```zsh +brew install npanj/tap/slipstream +``` + +**Option B: Install via one-line curl script** +```zsh +curl -fsSL https://raw.githubusercontent.com/npanj/slipstream/main/install.sh | sh +``` +*This automatically detects your Apple Silicon Mac, downloads the latest prebuilt release binary, verifies its SHA256 checksum, unpacks into `~/.local/share/slipstream/`, and links `slipstream` into `~/.local/bin`.* + +**Option C: Build from source** ```zsh git clone https://github.com/npanj/slipstream.git cd slipstream make -j4 ``` +#### Where Slipstream keeps things + +| What | Where | Override | +| :--- | :--- | :--- | +| Installed versions (the two newest are kept) | `~/.local/share/slipstream//` | `SLIPSTREAM_PREFIX` | +| The `slipstream` command (a link to the newest version) | `~/.local/bin/slipstream` | `SLIPSTREAM_BINDIR` | +| Models | `~/.slipstream/models///` | `SLIPSTREAM_MODELS` | +| Downloaded packages (models link into it) | the Hugging Face cache, `~/.cache/huggingface/hub/` | `HF_HUB_CACHE` | +| Runtime data, logs and caches of a release | `~/Library/Application Support/Slipstream/` | | + +**Why `~/.local`:** the installer puts Slipstream in your home folder, so it needs no administrator +rights, no `sudo` and no package manager, and removing it is deleting two paths. `~/.local/bin` and +`~/.local/share` are the per-user locations of the XDG convention that command-line tools on macOS +increasingly use: Claude Code's installer links `claude` into `~/.local/bin` the same way, the +installer is modelled on MariaDB Shell's, and `pipx` and `uv` install tools there too. Versions sit +side by side, so going back is relinking `~/.local/bin/slipstream`. If `~/.local/bin` is not on your +`PATH`, the installer says how to add it. + +**Why `~/.slipstream/models`:** a model outlives any one installation. Every +installation (a release, a source checkout, or a frontend that runs `slipstream pull`) uses the +same store, so a model is downloaded once and survives upgrades, reinstalls and `git clean`. It is +the convention of other local model servers: Ollama keeps models in `~/.ollama/models`, oMLX in +`~/.omlx/models`. The store is excluded from Time Machine when it is created (`tmutil +addexclusion`), since everything in it can be downloaded again. + +**Before this, models lived inside each installation:** a release kept them in +`~/Library/Application Support/Slipstream/models`, a source checkout in `install/models`. Nothing +is moved automatically. Either move a model into the store, keeping its `/` folder: + +```zsh +mkdir -p ~/.slipstream/models/nitinpanj +mv ~/Library/Application\ Support/Slipstream-v2/models/nitinpanj/ ~/.slipstream/models/nitinpanj/ +``` + +or point `SLIPSTREAM_MODELS` at the old folder. A folder you downloaded yourself (e.g. with +`huggingface-cli` into `~/models/…`) is served from where it is, by its path, and never changed. + --- ### Step 2: Download or Pull the Model -You can serve directly by Hugging Face repo ID (Slipstream will download and set up weights and MTP sidecars automatically): +#### Model 1: Qwen3.8-Flash-Next V3 (125.7B MoE — Frontier Reasoning) + +Serve directly by Hugging Face repo ID (Slipstream downloads and sets up weights and MTP sidecars automatically): ```zsh # Download without serving: slipstream pull nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF + +# Only check whether a repository can be served, and its size (downloads nothing): +slipstream pull nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF --check ``` Or download manually using the Hugging Face CLI: @@ -78,6 +152,20 @@ huggingface-cli download nitinpanj/qwen38-flash-next-v3 \ --local-dir ~/models/qwen38-flash-next-v3 ``` +#### Model 2: Qwen3.8-27B & Swift-Qwen3.8-27B (Dense Hybrid — Ultra-Fast TTFT) + +Slipstream natively ingests standard GGUF files, MLX safetensors checkpoints, or pre-converted packages: + +```zsh +# Download any standard 27B GGUF: +huggingface-cli download Qwen/Qwen3.8-27B-GGUF qwen3.8-27b-q4_0.gguf \ + --local-dir ~/models/qwen38-27b + +# Or download an MLX 4-bit checkpoint: +huggingface-cli download mlx-community/Qwen3.8-27B-4bit \ + --local-dir ~/models/mlx-qwen38-27b +``` + --- ### Step 3: Raise GPU Memory Limit (One-Time per Boot) @@ -92,7 +180,9 @@ sudo sysctl iogpu.wired_limit_mb=59392 ### Step 4: Serve the Model -Run `slipstream serve` pointing at a local folder or directly at a Hugging Face repo ID: +Run `slipstream serve` pointing at your model path or Hugging Face repo ID: + +#### Serving Flash-Next V3 (125.7B MoE) ```zsh # Serve local model directory: @@ -101,11 +191,26 @@ slipstream serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 # Or serve directly by Hugging Face repo ID (downloads & sets up automatically): slipstream serve --model nitinpanj/Swift-Qwen3.8-Flash-Next-Q4_0-Q8out-v3-GGUF --port 8090 -# Or serve on your local network (e.g. for other devices or web UIs): +# Or serve on your local network: slipstream serve --model ~/models/swift-qwen38-flash-next-v3 --host 0.0.0.0 --port 8090 --api-key YOUR_KEY ``` -> **First Run Note:** On first launch, Slipstream detects multi-shard GGUF files and prepares optimized streaming package files into `/prepared/` (~5–7 minutes). Subsequent launches load in **~10–15 seconds**. +#### Serving Qwen3.8-27B (Dense Hybrid) + +```zsh +# Serve a prepared 27B package: +slipstream serve --model ~/models/swift-qwen38-27b-splash-hq --port 8090 + +# Or serve a single .gguf file directly: +slipstream serve --model ~/models/qwen38-27b/qwen3.8-27b-q4_0.gguf --port 8090 + +# Or serve an MLX directory: +slipstream serve --model ~/models/mlx-qwen38-27b --port 8090 +``` + +> **Memory Rule — One Model at a Time:** Only run one inference engine at a time on Apple Silicon. Stop any active server (`Ctrl+C`) before switching models. +> +> **Automatic Format & Architecture Detection:** Slipstream detects whether a model is 27B (`qwen38`) or Flash-Next (`qwen4exp`), and whether it is in GGUF, MLX, or prepared package format. On first launch, multi-shard GGUFs are prepared into `/prepared/` using APFS hole-punching (`F_PUNCHHOLE`) to prevent disk duplication. Subsequent loads take **~10–15 seconds**. Add `--keep-gguf` if you wish to retain original GGUF files for other tools. --- @@ -150,6 +255,20 @@ omp --model splash-flashnext/local/swift-qwen38-flash-next-v3 \ --- +## Choosing Between Flash-Next V3 and Qwen3.8-27B + +| Dimension | Qwen3.8-Flash-Next V3 (125.7B MoE) | Qwen3.8-27B & Swift-27B (Dense Hybrid) | +|---|---|---| +| **Architecture** | 512 routed experts (7.3B active/token) + GDN recurrence | 64-layer dense hybrid (full attention every 4th layer + GDN) | +| **Reasoning Scorecard** | **70.3% composite** (leads GPQA Diamond by +8.6%, MATH-500 by +2.9%) | **67.6% composite** (AIME 45.0%, GSM8K 96.0%, HumanEval 92.0%) | +| **Decode Throughput** | 41–52 tok/s | 42–46 tok/s | +| **Time-to-First-Token** | ~1,100–1,300 ms | **570–659 ms (1.70x faster)** | +| **Memory Footprint** | ~34 GB expert cache + SSD streaming (requires 64 GB Mac) | **16.9–27 GB completely RAM-resident** (runs on 32 GB or 64 GB Macs) | +| **Context Horizon** | Scaled to **130,000 tokens** without decode collapse | Standard 32k–131k context window | +| **When to Use** | Deep analytical reasoning, coding agents, math proofs, massive documents | Fast conversational turns, latency-critical tasks, lighter memory environments | + +--- + ## Benchmarks & Performance ### 1. Head-to-Head: llama.cpp Fork vs. Slipstream @@ -227,6 +346,7 @@ The core primitives implemented in Slipstream: ## Credits & Acknowledgments +- **Mike Zinner** ([@mzinner](https://github.com/mzinner)): Creator and co-author of [Slipstream Menubar](https://github.com/npanj/slipstream-menubar), the official native macOS menu bar app for running, configuring, and monitoring Slipstream. - **Splash Team (Incoai)**: Full credit to the creators of Splash ([github.com/incoai/splash](https://github.com/incoai/splash)). Their C++ Metal speculative decoding design and memory architecture provided the foundation for this work. We will prepare a clean PR/patch proposing these Flash-Next and SSD streaming extensions to the Splash upstream repo. - **ds4 Team**: For their valuable insights on Metal router numerical precision (Taylor polynomial softplus expansion) and streaming scheduling designs. - **Qwen Team**: For training Qwen3.8-Flash-Next and open-sourcing the hybrid linear MTP architecture. diff --git a/dev/Makefile b/dev/Makefile index 9cd7df5..75d2f1e 100644 --- a/dev/Makefile +++ b/dev/Makefile @@ -71,8 +71,11 @@ check-python-engine: install-development test-python test-models $(PYTHON) -m ruff format --check --config dev/ruff.toml server \ install/*.py dev/tools dev/tests dev/benchmarks models +# Standard library only, so it runs before (and without) the development environment. architecture-check: - $(PYTHON) dev/tools/check_architecture.py + @python=$$(for candidate in $(PYTHON_CANDIDATES); do \ + command -v "$$candidate" && break; done); \ + "$${python:-python3}" dev/tools/check_architecture.py check: check-source check-native-engine check-python-engine diff --git a/dev/benchmarks/benchmark_diverse_workloads.py b/dev/benchmarks/benchmark_diverse_workloads.py index 9b0f266..b0f001e 100755 --- a/dev/benchmarks/benchmark_diverse_workloads.py +++ b/dev/benchmarks/benchmark_diverse_workloads.py @@ -24,7 +24,6 @@ import http.client import json import re -import sys import time from pathlib import Path @@ -107,8 +106,8 @@ def _generate_log_prompt() -> str: ) else: lines.append( - f"[{timestamp}] [INFO] [service=node-health] Heartbeat OK. Mem: {40 + (i%15)}% CPU: {12 + (i%20)}% " - f"Disk: 54% Requests: {1000 + i*17}/sec." + f"[{timestamp}] [INFO] [service=node-health] Heartbeat OK. Mem: {40 + (i % 15)}% CPU: {12 + (i % 20)}% " + f"Disk: 54% Requests: {1000 + i * 17}/sec." ) lines.append( "\nIdentify the single critical failure in these logs.\n" @@ -166,8 +165,10 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 128, "validator": lambda resp: ( - len(resp.get("choices", [{}])[0].get("message", {}).get("tool_calls", [])) > 0 - and resp["choices"][0]["message"]["tool_calls"][0]["function"]["name"] == "git_commit" + len(resp.get("choices", [{}])[0].get("message", {}).get("tool_calls", [])) + > 0 + and resp["choices"][0]["message"]["tool_calls"][0]["function"]["name"] + == "git_commit" ), }, { @@ -203,8 +204,12 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 160, "validator": lambda resp: ( - len(resp.get("choices", [{}])[0].get("message", {}).get("tool_calls", [])) > 0 - and "query" in json.loads(resp["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"]) + len(resp.get("choices", [{}])[0].get("message", {}).get("tool_calls", [])) + > 0 + and "query" + in json.loads( + resp["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"] + ) ), }, { @@ -224,7 +229,9 @@ def _generate_log_prompt() -> str: ], "reasoning_effort": "medium", "max_tokens": 512, - "validator": lambda resp: "3060" in resp.get("choices", [{}])[0].get("message", {}).get("content", ""), + "validator": lambda resp: ( + "3060" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + ), }, { "id": "code_generation", @@ -242,8 +249,10 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 384, "validator": lambda resp: ( - "def merge_intervals" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") - and "assert" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + "def merge_intervals" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + and "assert" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") ), }, { @@ -272,9 +281,12 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 160, "validator": lambda resp: ( - "auth-service" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") - and "ingress-gateway" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") - and "metrics-agent" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + "auth-service" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + and "ingress-gateway" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + and "metrics-agent" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") ), }, { @@ -319,8 +331,16 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 300, "validator": lambda resp: ( - "dirty" in resp.get("choices", [{}])[0].get("message", {}).get("content", "").lower() - and "write-through" in resp.get("choices", [{}])[0].get("message", {}).get("content", "").lower() + "dirty" + in resp.get("choices", [{}])[0] + .get("message", {}) + .get("content", "") + .lower() + and "write-through" + in resp.get("choices", [{}])[0] + .get("message", {}) + .get("content", "") + .lower() ), }, { @@ -336,20 +356,28 @@ def _generate_log_prompt() -> str: "reasoning_effort": "none", "max_tokens": 160, "validator": lambda resp: ( - "database_connection_pool_exhausted" in resp.get("choices", [{}])[0].get("message", {}).get("content", "") - or "pool" in resp.get("choices", [{}])[0].get("message", {}).get("content", "").lower() + "database_connection_pool_exhausted" + in resp.get("choices", [{}])[0].get("message", {}).get("content", "") + or "pool" + in resp.get("choices", [{}])[0] + .get("message", {}) + .get("content", "") + .lower() ), }, ] - def run_workloads(port: int = 8090, model: str = "local/swift-qwen38-flash-next-v3"): - print(f"\n==========================================================================") - print(f" SLIPSTREAM DIVERSE WORKLOAD BENCHMARK SUITE") + print( + "\n==========================================================================" + ) + print(" SLIPSTREAM DIVERSE WORKLOAD BENCHMARK SUITE") print(f" Target: http://127.0.0.1:{port} ({model})") print(f" Total Workloads: {len(WORKLOADS)}") - print(f"==========================================================================\n") + print( + "==========================================================================\n" + ) initial_status = get_status(port) initial_metrics = initial_status.get("metrics", {}) @@ -359,7 +387,11 @@ def run_workloads(port: int = 8090, model: str = "local/swift-qwen38-flash-next- results = [] for idx, wl in enumerate(WORKLOADS, 1): - print(f"[{idx:02d}/{len(WORKLOADS):02d}] {wl['category']} — {wl['name']}... ", end="", flush=True) + print( + f"[{idx:02d}/{len(WORKLOADS):02d}] {wl['category']} — {wl['name']}... ", + end="", + flush=True, + ) st_before = get_status(port) m_before = st_before.get("metrics", {}) @@ -380,13 +412,15 @@ def run_workloads(port: int = 8090, model: str = "local/swift-qwen38-flash-next- if status_code != 200: print(f"FAILED (HTTP {status_code})") - results.append({ - "id": wl["id"], - "category": wl["category"], - "name": wl["name"], - "ok": False, - "error": resp_data.get("error", {}).get("message", "unknown error"), - }) + results.append( + { + "id": wl["id"], + "category": wl["category"], + "name": wl["name"], + "ok": False, + "error": resp_data.get("error", {}).get("message", "unknown error"), + } + ) continue usage = resp_data.get("usage", {}) @@ -394,9 +428,17 @@ def run_workloads(port: int = 8090, model: str = "local/swift-qwen38-flash-next- completion_tokens = usage.get("completion_tokens", 0) # Delta metrics - delta_drafted = m_after.get("drafted_tokens", 0) - m_before.get("drafted_tokens", 0) - delta_accepted = m_after.get("accepted_draft_tokens", 0) - m_before.get("accepted_draft_tokens", 0) - acceptance_pct = (delta_accepted / max(1, delta_drafted)) * 100.0 if delta_drafted > 0 else 0.0 + delta_drafted = m_after.get("drafted_tokens", 0) - m_before.get( + "drafted_tokens", 0 + ) + delta_accepted = m_after.get("accepted_draft_tokens", 0) - m_before.get( + "accepted_draft_tokens", 0 + ) + acceptance_pct = ( + (delta_accepted / max(1, delta_drafted)) * 100.0 + if delta_drafted > 0 + else 0.0 + ) # Timing resp_metrics = resp_data.get("metrics", {}) @@ -405,56 +447,86 @@ def run_workloads(port: int = 8090, model: str = "local/swift-qwen38-flash-next- if decode_ms <= 0: decode_ms = wall_time * 1000.0 - ttft_ms - decode_tok_s = (completion_tokens / (decode_ms / 1000.0)) if decode_ms > 0 else 0.0 + decode_tok_s = ( + (completion_tokens / (decode_ms / 1000.0)) if decode_ms > 0 else 0.0 + ) # Validator validator = wl.get("validator") valid = validator(resp_data) if validator else True - print(f"OK | {completion_tokens:3d} toks | {decode_tok_s:5.1f} tok/s | Draft Acc: {acceptance_pct:5.1f}% | TTFT: {ttft_ms:6.1f} ms | {'PASS' if valid else 'WARN-VALIDATION'}") - - results.append({ - "id": wl["id"], - "category": wl["category"], - "name": wl["name"], - "ok": True, - "valid": valid, - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_tokens, - "decode_tok_s": decode_tok_s, - "ttft_ms": ttft_ms, - "delta_drafted": delta_drafted, - "delta_accepted": delta_accepted, - "acceptance_pct": acceptance_pct, - "response": resp_data, - }) + print( + f"OK | {completion_tokens:3d} toks | {decode_tok_s:5.1f} tok/s | Draft Acc: {acceptance_pct:5.1f}% | TTFT: {ttft_ms:6.1f} ms | {'PASS' if valid else 'WARN-VALIDATION'}" + ) + + results.append( + { + "id": wl["id"], + "category": wl["category"], + "name": wl["name"], + "ok": True, + "valid": valid, + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "decode_tok_s": decode_tok_s, + "ttft_ms": ttft_ms, + "delta_drafted": delta_drafted, + "delta_accepted": delta_accepted, + "acceptance_pct": acceptance_pct, + "response": resp_data, + } + ) # Summary final_status = get_status(port) final_metrics = final_status.get("metrics", {}) total_drafted = final_metrics.get("drafted_tokens", 0) - init_drafted total_accepted = final_metrics.get("accepted_draft_tokens", 0) - init_accepted - overall_acc = (total_accepted / max(1, total_drafted)) * 100.0 if total_drafted > 0 else 0.0 + overall_acc = ( + (total_accepted / max(1, total_drafted)) * 100.0 if total_drafted > 0 else 0.0 + ) - print(f"\n==========================================================================") - print(f" BENCHMARK RESULTS SUMMARY ACROSS ALL WORKLOADS") - print(f"==========================================================================") - print(f"{'Category / Workload':<35} | {'Tok/s':<8} | {'Draft Acc':<10} | {'Tokens':<8} | {'TTFT':<9} | {'Status'}") - print(f"------------------------------------------------------------------------------------------------") + print( + "\n==========================================================================" + ) + print(" BENCHMARK RESULTS SUMMARY ACROSS ALL WORKLOADS") + print("==========================================================================") + print( + f"{'Category / Workload':<35} | {'Tok/s':<8} | {'Draft Acc':<10} | {'Tokens':<8} | {'TTFT':<9} | {'Status'}" + ) + print( + "------------------------------------------------------------------------------------------------" + ) for r in results: if not r["ok"]: - print(f"{r['name']:<35} | {'FAIL':<8} | {'N/A':<10} | {'N/A':<8} | {'N/A':<9} | FAIL: {r.get('error','')}") + print( + f"{r['name']:<35} | {'FAIL':<8} | {'N/A':<10} | {'N/A':<8} | {'N/A':<9} | FAIL: {r.get('error', '')}" + ) else: status_str = "PASS" if r["valid"] else "WARN" - print(f"{r['name']:<35} | {r['decode_tok_s']:<6.1f} | {r['acceptance_pct']:<5.1f}% | {r['completion_tokens']:<8} | {r['ttft_ms']:<6.1f} ms | {status_str}") + print( + f"{r['name']:<35} | {r['decode_tok_s']:<6.1f} | {r['acceptance_pct']:<5.1f}% | {r['completion_tokens']:<8} | {r['ttft_ms']:<6.1f} ms | {status_str}" + ) - print(f"------------------------------------------------------------------------------------------------") - avg_speed = sum(r["decode_tok_s"] for r in results if r["ok"]) / max(1, len([r for r in results if r["ok"]])) + print( + "------------------------------------------------------------------------------------------------" + ) + avg_speed = sum(r["decode_tok_s"] for r in results if r["ok"]) / max( + 1, len([r for r in results if r["ok"]]) + ) total_output = sum(r["completion_tokens"] for r in results if r["ok"]) - print(f"Aggregate Draft Acceptance : {overall_acc:.1f}% ({total_accepted}/{total_drafted} tokens)") - print(f"Average Decode Throughput : {avg_speed:.1f} tok/s across {total_output} output tokens") - print(f"Current Host Available RAM : {final_status.get('memory_governor', {}).get('host_available_bytes', 0) / (1024**3):.2f} GiB") - print(f"==========================================================================\n") + print( + f"Aggregate Draft Acceptance : {overall_acc:.1f}% ({total_accepted}/{total_drafted} tokens)" + ) + print( + f"Average Decode Throughput : {avg_speed:.1f} tok/s across {total_output} output tokens" + ) + print( + f"Current Host Available RAM : {final_status.get('memory_governor', {}).get('host_available_bytes', 0) / (1024**3):.2f} GiB" + ) + print( + "==========================================================================\n" + ) return results diff --git a/dev/benchmarks/benchmark_drafting.py b/dev/benchmarks/benchmark_drafting.py index 3487167..9572e93 100644 --- a/dev/benchmarks/benchmark_drafting.py +++ b/dev/benchmarks/benchmark_drafting.py @@ -18,7 +18,6 @@ from __future__ import annotations import argparse -import json import re import sys import time @@ -28,17 +27,18 @@ ROOT = Path(__file__).resolve().parent.parent.parent sys.path.insert(0, str(ROOT / "dev/benchmarks")) -from benchmark_swift27b_vs_swiftv3 import ( +from benchmark_swift27b_vs_swiftv3 import ( # noqa: E402 prepare_dataset, - score_gsm8k, + query_endpoint, + score_aime, score_code, - score_logic, score_gpqa, - score_aime, + score_gsm8k, + score_logic, score_math, - query_endpoint, ) + def fetch_metrics(base_url: str = "http://127.0.0.1:8090/v1") -> dict: root_url = re.sub(r"/v1/?$", "", base_url) try: @@ -58,9 +58,12 @@ def fetch_metrics(base_url: str = "http://127.0.0.1:8090/v1") -> dict: pass return m except Exception as e: - print(f"Warning: failed to fetch /metrics from {root_url}: {e}", file=sys.stderr) + print( + f"Warning: failed to fetch /metrics from {root_url}: {e}", file=sys.stderr + ) return {} + def prepare_suite(seed: int = 1234, count_per_domain: int = 5) -> list[dict]: all_dataset = prepare_dataset(seed) domains = ["GSM8K", "HumanEval", "GPQA Diamond", "Hard Systems & Logic"] @@ -70,10 +73,17 @@ def prepare_suite(seed: int = 1234, count_per_domain: int = 5) -> list[dict]: selected.extend(d_items[:count_per_domain]) return selected -def run_benchmark(base_url: str = "http://127.0.0.1:8090/v1", model: str = "local/swift-qwen38-flash-next-v3", count_per_domain: int = 5) -> dict: + +def run_benchmark( + base_url: str = "http://127.0.0.1:8090/v1", + model: str = "local/swift-qwen38-flash-next-v3", + count_per_domain: int = 5, +) -> dict: suite = prepare_suite(count_per_domain=count_per_domain) print(f"=== Running Speculative Drafting Evaluation on {base_url} ({model}) ===") - print(f"Items: {len(suite)} across {len(set(it['benchmark'] for it in suite))} domains") + print( + f"Items: {len(suite)} across {len(set(it['benchmark'] for it in suite))} domains" + ) m_start = fetch_metrics(base_url) t0_wall = time.perf_counter() @@ -84,13 +94,17 @@ def run_benchmark(base_url: str = "http://127.0.0.1:8090/v1", model: str = "loca decode_speeds = [] for i, it in enumerate(suite): - print(f"[{i+1:02d}/{len(suite):02d}] {it['benchmark']:<20} ({it['id']})... ", end="", flush=True) + print( + f"[{i + 1:02d}/{len(suite):02d}] {it['benchmark']:<20} ({it['id']})... ", + end="", + flush=True, + ) res = query_endpoint( url=base_url, model=model, prompt=it["prompt"], max_tokens=it["max_tokens"], - temperature=0.0 + temperature=0.0, ) if not res["ok"]: print(f"FAILED ({res['error']})") @@ -131,23 +145,31 @@ def run_benchmark(base_url: str = "http://127.0.0.1:8090/v1", model: str = "loca if sc_r > 0.0: score, why = sc_r, f"[in reasoning] {why_r}" elif scorer_type == "code": - score, why = score_code(full_output if full_output.strip() else reasoning, ground_truth) + score, why = score_code( + full_output if full_output.strip() else reasoning, ground_truth + ) elif scorer_type == "logic": score, why = score_logic(eval_text, it.get("meta", {})) else: score, why = 1.0, "ok" - correct_count += (score >= 0.99) + correct_count += score >= 0.99 total_tokens += res["completion_tokens"] decode_speeds.append(res["tok_per_sec"]) status = "PASS" if score >= 0.99 else "FAIL" - print(f"{status} | {res['tok_per_sec']:.1f} tok/s | {res['completion_tokens']} toks ({why})") + print( + f"{status} | {res['tok_per_sec']:.1f} tok/s | {res['completion_tokens']} toks ({why})" + ) t1_wall = time.perf_counter() m_end = fetch_metrics(base_url) - drafted_delta = m_end.get("splash_drafted_tokens_total", 0) - m_start.get("splash_drafted_tokens_total", 0) - accepted_delta = m_end.get("splash_accepted_draft_tokens_total", 0) - m_start.get("splash_accepted_draft_tokens_total", 0) + drafted_delta = m_end.get("splash_drafted_tokens_total", 0) - m_start.get( + "splash_drafted_tokens_total", 0 + ) + accepted_delta = m_end.get("splash_accepted_draft_tokens_total", 0) - m_start.get( + "splash_accepted_draft_tokens_total", 0 + ) acc_ratio = (accepted_delta / drafted_delta * 100.0) if drafted_delta > 0 else 0.0 avg_tps = (sum(decode_speeds) / len(decode_speeds)) if decode_speeds else 0.0 @@ -180,10 +202,13 @@ def run_benchmark(base_url: str = "http://127.0.0.1:8090/v1", model: str = "loca return summary + if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--url", default="http://127.0.0.1:8090/v1") parser.add_argument("--model", default="local/swift-qwen38-flash-next-v3") parser.add_argument("--count-per-domain", type=int, default=5) args = parser.parse_args() - run_benchmark(base_url=args.url, model=args.model, count_per_domain=args.count_per_domain) + run_benchmark( + base_url=args.url, model=args.model, count_per_domain=args.count_per_domain + ) diff --git a/dev/benchmarks/benchmark_swift27b_vs_swiftv3.py b/dev/benchmarks/benchmark_swift27b_vs_swiftv3.py index bbf4aa4..9f640ed 100755 --- a/dev/benchmarks/benchmark_swift27b_vs_swiftv3.py +++ b/dev/benchmarks/benchmark_swift27b_vs_swiftv3.py @@ -22,23 +22,26 @@ - Total wall-clock time """ -import argparse -import json -import os -import random -import re -import subprocess -import sys -import tempfile -import time -import urllib.error -import urllib.request -from datetime import datetime -from pathlib import Path +import argparse # noqa: E402 +import json # noqa: E402 +import random # noqa: E402 +import re # noqa: E402 +import subprocess # noqa: E402 +import sys # noqa: E402 +import tempfile # noqa: E402 +import time # noqa: E402 +import urllib.error # noqa: E402 +import urllib.request # noqa: E402 +from datetime import datetime # noqa: E402 +from pathlib import Path # noqa: E402 ROOT = Path(__file__).resolve().parent.parent.parent -BENCH_DATA_DIR = Path("/Users/nitin/Documents/shared-with-google-drive/model-serving/local-mlx/bench_data") -QUALITY_BENCH_DATA = Path("/Users/nitin/Documents/shared-with-google-drive/benchmarking/model-quality-bench/data/datasets") +BENCH_DATA_DIR = Path( + "/Users/nitin/Documents/shared-with-google-drive/model-serving/local-mlx/bench_data" +) +QUALITY_BENCH_DATA = Path( + "/Users/nitin/Documents/shared-with-google-drive/benchmarking/model-quality-bench/data/datasets" +) RESULTS_DIR = Path(__file__).resolve().parent / "swift_benchmark_results" # ----------------------------------------------------------------------------- @@ -48,6 +51,7 @@ BOXED = re.compile(r"\\boxed\{([^}]*)\}") NUM = re.compile(r"-?\d[\d,]*\.?\d*") + def _boxed(text: str) -> str | None: start = text.rfind("\\boxed{") if start < 0: @@ -63,13 +67,23 @@ def _boxed(text: str) -> str | None: i += 1 return None + def _normalise_math(s: str) -> str: s = s.strip().strip("$").strip() for a, b in ( - ("\\left", ""), ("\\right", ""), ("\\!", ""), ("\\,", ""), - ("\\;", ""), ("dfrac", "frac"), ("tfrac", "frac"), - ("^\\circ", ""), ("^{\\circ}", ""), ("\\%", ""), ("%", ""), - ("\\$", ""), (" ", "") + ("\\left", ""), + ("\\right", ""), + ("\\!", ""), + ("\\,", ""), + ("\\;", ""), + ("dfrac", "frac"), + ("tfrac", "frac"), + ("^\\circ", ""), + ("^{\\circ}", ""), + ("\\%", ""), + ("%", ""), + ("\\$", ""), + (" ", ""), ): s = s.replace(a, b) s = re.sub(r"\\text\{(.*?)\}", r"\1", s) @@ -79,6 +93,7 @@ def _normalise_math(s: str) -> str: s = s.split(".")[0] return s + def _as_number(s: str) -> float | None: m = re.fullmatch(r"(-?)\\frac\{(-?\d+)\}\{(\d+)\}", s) if m: @@ -89,6 +104,7 @@ def _as_number(s: str) -> float | None: except ValueError: return None + def score_math(output: str, answer: str) -> tuple[float, str]: got = _boxed(output) if got is None: @@ -101,6 +117,7 @@ def score_math(output: str, answer: str) -> tuple[float, str]: return 1.0, f"boxed {got} (numeric match)" return 0.0, f"boxed {got} want {answer}" + def score_aime(output: str, answer: str) -> tuple[float, str]: want = str(int(answer.strip())) # Check boxed first @@ -127,6 +144,7 @@ def score_aime(output: str, answer: str) -> tuple[float, str]: pass return 0.0, f"no integer match for {want}" + def score_gpqa(output: str, answer: str) -> tuple[float, str]: want = answer.strip().upper() # Check explicit conclusion @@ -147,6 +165,7 @@ def score_gpqa(output: str, answer: str) -> tuple[float, str]: return (1.0 if got == want else 0.0), f"tail {got} want {want}" return 0.0, f"no choice found (want {want})" + def score_gsm8k(output: str, answer: str) -> tuple[float, str]: want = answer.strip() # Split on #### if present @@ -170,6 +189,7 @@ def score_gsm8k(output: str, answer: str) -> tuple[float, str]: pass return 0.0, f"no number match for {want}" + def score_code(output: str, test_code: str, timeout: int = 10) -> tuple[float, str]: body = output m = re.search(r"```(?:python)?\n(.*?)```", output, re.S) @@ -180,25 +200,36 @@ def score_code(output: str, test_code: str, timeout: int = 10) -> tuple[float, s p = Path(d) / "t.py" p.write_text(prog) try: - r = subprocess.run([sys.executable, str(p)], capture_output=True, timeout=timeout, cwd=d) + r = subprocess.run( + [sys.executable, str(p)], capture_output=True, timeout=timeout, cwd=d + ) if r.returncode == 0: return 1.0, "pass" - err = (r.stderr.decode(errors="replace").strip().splitlines() or ["fail"])[-1][:120] + err = (r.stderr.decode(errors="replace").strip().splitlines() or ["fail"])[ + -1 + ][:120] return 0.0, f"fail: {err}" except subprocess.TimeoutExpired: return 0.0, "timeout" except Exception as e: return 0.0, f"execution error: {e}" + def score_logic(output: str, meta: dict) -> tuple[float, str]: kind = meta.get("kind") if kind == "interval": return score_code(output, meta["test"]) elif kind == "seating": o = output.lower() - has_1 = ("chair 1" in o or "1:" in o or "1 -" in o or "first chair" in o) and "alice" in o - has_2 = ("chair 2" in o or "2:" in o or "2 -" in o or "second chair" in o) and "charlie" in o - has_3 = ("chair 3" in o or "3:" in o or "3 -" in o or "third chair" in o) and "bob" in o + has_1 = ( + "chair 1" in o or "1:" in o or "1 -" in o or "first chair" in o + ) and "alice" in o + has_2 = ( + "chair 2" in o or "2:" in o or "2 -" in o or "second chair" in o + ) and "charlie" in o + has_3 = ( + "chair 3" in o or "3:" in o or "3 -" in o or "third chair" in o + ) and "bob" in o if has_1 and has_2 and has_3: return 1.0, "correct seating (1: Alice, 2: Charlie, 3: Bob)" return 0.0, "incorrect seating deduction" @@ -224,10 +255,12 @@ def score_logic(output: str, meta: dict) -> tuple[float, str]: return 0.0, "missing state machine logic" return 1.0, "reviewed" + # ----------------------------------------------------------------------------- # Dataset Preparation # ----------------------------------------------------------------------------- + def prepare_dataset(seed: int = 1234) -> list[dict]: rng = random.Random(seed) items = [] @@ -243,22 +276,26 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: '"Therefore, the final answer is \\boxed{N}" where N is an integer from 0 to 999.\n\n' f"Problem:\n{row['problem']}" ) - items.append({ - "id": f"aime25_{idx+1:02d}", - "benchmark": "AIME 2025", - "category": "Elite Mathematics", - "prompt": prompt, - "ground_truth": str(row["answer"]).strip(), - "scorer": "aime", - "max_tokens": 2560, - "meta": {"source": "aime25", "index": idx} - }) + items.append( + { + "id": f"aime25_{idx + 1:02d}", + "benchmark": "AIME 2025", + "category": "Elite Mathematics", + "prompt": prompt, + "ground_truth": str(row["answer"]).strip(), + "scorer": "aime", + "max_tokens": 2560, + "meta": {"source": "aime25", "index": idx}, + } + ) # 2. MATH-500 (35 items, sampling Level 4 and 5) math_path = QUALITY_BENCH_DATA / "math500" / "test.jsonl" with open(math_path) as f: m5_all = [json.loads(line) for line in f] - hard_m5 = [x for x in m5_all if str(x.get("level", "")) in ["Level 4", "Level 5", "4", "5"]] + hard_m5 = [ + x for x in m5_all if str(x.get("level", "")) in ["Level 4", "Level 5", "4", "5"] + ] if len(hard_m5) < 35: hard_m5 = m5_all rng.shuffle(hard_m5) @@ -270,16 +307,18 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: '"Therefore, the final answer is \\boxed{ANSWER}"\n\n' f"Problem:\n{row['problem']}" ) - items.append({ - "id": f"math500_{idx+1:02d}", - "benchmark": "MATH-500", - "category": "Olympiad Math", - "prompt": prompt, - "ground_truth": str(row["answer"]).strip(), - "scorer": "math", - "max_tokens": 1536, - "meta": {"subject": subj, "level": row.get("level")} - }) + items.append( + { + "id": f"math500_{idx + 1:02d}", + "benchmark": "MATH-500", + "category": "Olympiad Math", + "prompt": prompt, + "ground_truth": str(row["answer"]).strip(), + "scorer": "math", + "max_tokens": 1536, + "meta": {"subject": subj, "level": row.get("level")}, + } + ) # 3. GPQA Diamond (35 items) gpqa_path = BENCH_DATA_DIR / "gpqa.json" @@ -293,16 +332,18 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: 'response with: "Therefore, the correct answer is (X)" where X is one of A, B, C, or D.\n\n' f"Question:\n{row['question']}" ) - items.append({ - "id": f"gpqa_{idx+1:02d}", - "benchmark": "GPQA Diamond", - "category": "PhD-Level Science", - "prompt": prompt, - "ground_truth": row["answer"].strip().upper(), - "scorer": "gpqa", - "max_tokens": 1024, - "meta": {"source": "gpqa_diamond"} - }) + items.append( + { + "id": f"gpqa_{idx + 1:02d}", + "benchmark": "GPQA Diamond", + "category": "PhD-Level Science", + "prompt": prompt, + "ground_truth": row["answer"].strip().upper(), + "scorer": "gpqa", + "max_tokens": 1024, + "meta": {"source": "gpqa_diamond"}, + } + ) # 4. GSM8K (25 items) gsm_path = QUALITY_BENCH_DATA / "gsm8k" / "test.jsonl" @@ -316,16 +357,18 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: f"Question:\n{row['question']}" ) ans = row["answer"].split("####")[-1].strip() - items.append({ - "id": f"gsm8k_{idx+1:02d}", - "benchmark": "GSM8K", - "category": "Multi-Step Math", - "prompt": prompt, - "ground_truth": ans, - "scorer": "gsm8k", - "max_tokens": 1024, - "meta": {} - }) + items.append( + { + "id": f"gsm8k_{idx + 1:02d}", + "benchmark": "GSM8K", + "category": "Multi-Step Math", + "prompt": prompt, + "ground_truth": ans, + "scorer": "gsm8k", + "max_tokens": 1024, + "meta": {}, + } + ) # 5. HumanEval (25 items) he_path = QUALITY_BENCH_DATA / "humaneval" / "test.jsonl" @@ -339,16 +382,18 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: f"```python\n{row['prompt']}```" ) test = row["test"] + f"\n\ncheck({row['entry_point']})\n" - items.append({ - "id": f"humaneval_{idx+1:02d}", - "benchmark": "HumanEval", - "category": "Code Generation", - "prompt": prompt, - "ground_truth": test, - "scorer": "code", - "max_tokens": 1536, - "meta": {"task_id": row["task_id"], "entry_point": row["entry_point"]} - }) + items.append( + { + "id": f"humaneval_{idx + 1:02d}", + "benchmark": "HumanEval", + "category": "Code Generation", + "prompt": prompt, + "ground_truth": test, + "scorer": "code", + "max_tokens": 1536, + "meta": {"task_id": row["task_id"], "entry_point": row["entry_point"]}, + } + ) # 6. Hard Systems & Logic (5 items) hard_probes = [ @@ -374,8 +419,8 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: "assert merge_intervals([[-5,-2],[-3,1]]) == [[-5,1]]\n" "assert merge_intervals([[1,10],[2,3],[4,8]]) == [[1,10]]\n" "print('Intervals OK')\n" - ) - } + ), + }, }, { "id": "probe_02_seating", @@ -392,7 +437,7 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: "ground_truth": "Chair 1: Alice, Chair 2: Charlie, Chair 3: Bob", "scorer": "logic", "max_tokens": 1024, - "meta": {"kind": "seating"} + "meta": {"kind": "seating"}, }, { "id": "probe_03_concurrency", @@ -407,7 +452,7 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: "ground_truth": "Acquire-Release vs SeqCst store buffering explanation", "scorer": "logic", "max_tokens": 1536, - "meta": {"kind": "concurrency"} + "meta": {"kind": "concurrency"}, }, { "id": "probe_04_bandwidth", @@ -421,7 +466,7 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: "ground_truth": "Memory bandwidth bottleneck in decode vs prefill", "scorer": "logic", "max_tokens": 512, - "meta": {"kind": "bandwidth"} + "meta": {"kind": "bandwidth"}, }, { "id": "probe_05_csv_parser", @@ -430,22 +475,24 @@ def prepare_dataset(seed: int = 1234) -> list[dict]: "prompt": ( "Write an idiomatic Rust zero-copy CSV line parser function `parse_csv_record(line: &str) -> Vec<&str>` " "that correctly parses a comma-separated line, handling double-quoted fields that contain escaped quotes " - "(represented as `\"\"`). Explain the state machine transitions in comments and provide unit tests." + '(represented as `""`). Explain the state machine transitions in comments and provide unit tests.' ), "ground_truth": "Rust zero-copy CSV parser", "scorer": "logic", "max_tokens": 1536, - "meta": {"kind": "csv"} - } + "meta": {"kind": "csv"}, + }, ] items.extend(hard_probes) return items + # ----------------------------------------------------------------------------- # HTTP Client # ----------------------------------------------------------------------------- + def query_endpoint( url: str, model: str, @@ -453,7 +500,7 @@ def query_endpoint( max_tokens: int = 1024, temperature: float = 0.0, timeout: int = 240, - retries: int = 3 + retries: int = 3, ) -> dict: payload = { "model": model, @@ -466,7 +513,7 @@ def query_endpoint( req = urllib.request.Request( f"{url.rstrip('/')}/chat/completions", data=data, - headers={"Content-Type": "application/json"} + headers={"Content-Type": "application/json"}, ) last_error = "" @@ -484,12 +531,16 @@ def query_endpoint( usage = body.get("usage", {}) prompt_toks = usage.get("prompt_tokens", 0) comp_toks = usage.get("completion_tokens", 0) - reason_toks = (usage.get("completion_tokens_details") or {}).get("reasoning_tokens", 0) + reason_toks = (usage.get("completion_tokens_details") or {}).get( + "reasoning_tokens", 0 + ) # Extract metrics metrics = body.get("metrics", {}) req_lat = metrics.get("request_latency", {}) - ttft_ms = req_lat.get("ttft_ms") or req_lat.get("start_to_first_token_ms") + ttft_ms = req_lat.get("ttft_ms") or req_lat.get( + "start_to_first_token_ms" + ) stream_tps = req_lat.get("stream_tokens_per_second") timings = body.get("timings", {}) @@ -512,7 +563,7 @@ def query_endpoint( "wall_ms": wall_ms, "ttft_ms": float(ttft_ms), "tok_per_sec": float(tok_per_sec), - "error": None + "error": None, } except Exception as e: last_error = f"{type(e).__name__}: {e}" @@ -528,26 +579,24 @@ def query_endpoint( "wall_ms": 0.0, "ttft_ms": 0.0, "tok_per_sec": 0.0, - "error": last_error + "error": last_error, } + # ----------------------------------------------------------------------------- # Evaluation Runner # ----------------------------------------------------------------------------- + def evaluate_model( - model_name: str, - base_url: str, - model_id: str, - items: list[dict], - output_file: Path + model_name: str, base_url: str, model_id: str, items: list[dict], output_file: Path ) -> list[dict]: - print(f"\n==================================================================") + print("\n==================================================================") print(f"Starting Evaluation: {model_name}") print(f"Endpoint: {base_url} (Model ID: {model_id})") print(f"Total Items: {len(items)}") print(f"Output: {output_file}") - print(f"==================================================================\n") + print("==================================================================\n") results = [] if output_file.exists(): @@ -575,12 +624,12 @@ def evaluate_model( ground_truth = it["ground_truth"] max_tokens = it.get("max_tokens", 1024) - t0 = time.perf_counter() resp = query_endpoint(base_url, model_id, prompt, max_tokens=max_tokens) - elapsed = time.perf_counter() - t0 if not resp["ok"]: - print(f"[{idx:03d}/{len(items):03d}] {item_id:<18} | {it['benchmark']:<16} | ERROR: {resp['error']}") + print( + f"[{idx:03d}/{len(items):03d}] {item_id:<18} | {it['benchmark']:<16} | ERROR: {resp['error']}" + ) rec = { "id": item_id, "benchmark": it["benchmark"], @@ -636,7 +685,9 @@ def evaluate_model( if sc_r > 0.0: score, why = sc_r, f"[in reasoning] {why_r}" elif scorer_type == "code": - score, why = score_code(full_output if full_output.strip() else reasoning, ground_truth) + score, why = score_code( + full_output if full_output.strip() else reasoning, ground_truth + ) elif scorer_type == "logic": score, why = score_logic(eval_text, it["meta"]) @@ -662,17 +713,21 @@ def evaluate_model( out_fh.write(json.dumps(rec) + "\n") status_sym = "PASS" if score > 0.0 else "FAIL" - print(f"[{idx:03d}/{len(items):03d}] {item_id:<18} | {it['benchmark']:<16} | {status_sym} ({score:.1f}) | {resp['tok_per_sec']:>5.1f} t/s | TTFT: {resp['ttft_ms']:>6.1f}ms | Out: {resp['completion_tokens']:>4d}tok | {why[:40]}") + print( + f"[{idx:03d}/{len(items):03d}] {item_id:<18} | {it['benchmark']:<16} | {status_sym} ({score:.1f}) | {resp['tok_per_sec']:>5.1f} t/s | TTFT: {resp['ttft_ms']:>6.1f}ms | Out: {resp['completion_tokens']:>4d}tok | {why[:40]}" + ) out_fh.close() total_time = time.perf_counter() - t_start - print(f"\nFinished {model_name} in {total_time/60:.2f} minutes.") + print(f"\nFinished {model_name} in {total_time / 60:.2f} minutes.") return results + # ----------------------------------------------------------------------------- # Reporting & Comparison # ----------------------------------------------------------------------------- + def generate_report(v3_file: Path, b27_file: Path, report_file: Path): if not v3_file.exists() or not b27_file.exists(): print("Cannot generate report: one or both results files do not exist.") @@ -687,17 +742,31 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): b27_map = {r["id"]: r for r in b27_res} common_ids = sorted(set(v3_map.keys()) & set(b27_map.keys())) - print(f"\nGenerating comparative scorecard across {len(common_ids)} common items...") + print( + f"\nGenerating comparative scorecard across {len(common_ids)} common items..." + ) - benchmarks = ["AIME 2025", "MATH-500", "GPQA Diamond", "GSM8K", "HumanEval", "Hard Systems & Logic"] + benchmarks = [ + "AIME 2025", + "MATH-500", + "GPQA Diamond", + "GSM8K", + "HumanEval", + "Hard Systems & Logic", + ] stats = {} for b in benchmarks: stats[b] = { - "v3_correct": 0, "b27_correct": 0, "total": 0, - "v3_tps": [], "b27_tps": [], - "v3_ttft": [], "b27_ttft": [], - "v3_tokens": [], "b27_tokens": [] + "v3_correct": 0, + "b27_correct": 0, + "total": 0, + "v3_tps": [], + "b27_tps": [], + "v3_ttft": [], + "b27_ttft": [], + "v3_tokens": [], + "b27_tokens": [], } for item_id in common_ids: @@ -706,10 +775,15 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): bench = r1["benchmark"] if bench not in stats: stats[bench] = { - "v3_correct": 0, "b27_correct": 0, "total": 0, - "v3_tps": [], "b27_tps": [], - "v3_ttft": [], "b27_ttft": [], - "v3_tokens": [], "b27_tokens": [] + "v3_correct": 0, + "b27_correct": 0, + "total": 0, + "v3_tps": [], + "b27_tps": [], + "v3_ttft": [], + "b27_ttft": [], + "v3_tokens": [], + "b27_tokens": [], } s = stats[bench] s["total"] += 1 @@ -732,14 +806,22 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): s["b27_tokens"].append(r2.get("completion_tokens", 0)) lines = [] - lines.append("# Head-to-Head Benchmark: Swift-Qwen3.8-27B-Splash-HQ vs Swift-Qwen3.8-Flash-Next-V3\n") + lines.append( + "# Head-to-Head Benchmark: Swift-Qwen3.8-27B-Splash-HQ vs Swift-Qwen3.8-Flash-Next-V3\n" + ) lines.append(f"**Date:** {datetime.now().strftime('%Y-%m-%d %H:%M PDT')}\n") - lines.append(f"**Platform:** Apple Silicon (Unified Memory), Single-Engine Sequential Execution\n") - lines.append(f"**Total Evaluated Items:** {len(common_ids)} items across 6 rigorous domains\n") + lines.append( + "**Platform:** Apple Silicon (Unified Memory), Single-Engine Sequential Execution\n" + ) + lines.append( + f"**Total Evaluated Items:** {len(common_ids)} items across 6 rigorous domains\n" + ) lines.append("\n---\n") lines.append("## 1. Executive Summary & Scorecard\n") - lines.append("| Domain / Benchmark | Items | Swift-Flash-Next-V3 Accuracy | Swift-27B-Splash-HQ Accuracy | Accuracy Delta | Flash-Next Speed | 27B-Splash Speed | Speed Ratio |") + lines.append( + "| Domain / Benchmark | Items | Swift-Flash-Next-V3 Accuracy | Swift-27B-Splash-HQ Accuracy | Accuracy Delta | Flash-Next Speed | 27B-Splash Speed | Speed Ratio |" + ) lines.append("|---|---:|---:|---:|---:|---:|---:|---:|") tot_items = 0 @@ -776,7 +858,9 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): speed_ratio = (b27_speed / v3_speed) if v3_speed > 0 else 0.0 diff_str = f"+{diff:.1f}%" if diff > 0 else f"{diff:.1f}%" - lines.append(f"| **{b}** | {tot} | {v3_acc:.1f}% ({v3_c}/{tot}) | {b27_acc:.1f}% ({b27_c}/{tot}) | {diff_str} | {v3_speed:.1f} tok/s | {b27_speed:.1f} tok/s | {speed_ratio:.2f}x |") + lines.append( + f"| **{b}** | {tot} | {v3_acc:.1f}% ({v3_c}/{tot}) | {b27_acc:.1f}% ({b27_c}/{tot}) | {diff_str} | {v3_speed:.1f} tok/s | {b27_speed:.1f} tok/s | {speed_ratio:.2f}x |" + ) overall_v3_acc = (tot_v3_corr / tot_items * 100.0) if tot_items else 0.0 overall_b27_acc = (tot_b27_corr / tot_items * 100.0) if tot_items else 0.0 @@ -784,9 +868,13 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): overall_v3_tps = (sum(all_v3_tps) / len(all_v3_tps)) if all_v3_tps else 0.0 overall_b27_tps = (sum(all_b27_tps) / len(all_b27_tps)) if all_b27_tps else 0.0 overall_ratio = (overall_b27_tps / overall_v3_tps) if overall_v3_tps else 0.0 - overall_diff_str = f"+{overall_diff:.1f}%" if overall_diff > 0 else f"{overall_diff:.1f}%" + overall_diff_str = ( + f"+{overall_diff:.1f}%" if overall_diff > 0 else f"{overall_diff:.1f}%" + ) - lines.append(f"| **TOTAL / OVERALL** | **{tot_items}** | **{overall_v3_acc:.1f}% ({tot_v3_corr}/{tot_items})** | **{overall_b27_acc:.1f}% ({tot_b27_corr}/{tot_items})** | **{overall_diff_str}** | **{overall_v3_tps:.1f} tok/s** | **{overall_b27_tps:.1f} tok/s** | **{overall_ratio:.2f}x** |") + lines.append( + f"| **TOTAL / OVERALL** | **{tot_items}** | **{overall_v3_acc:.1f}% ({tot_v3_corr}/{tot_items})** | **{overall_b27_acc:.1f}% ({tot_b27_corr}/{tot_items})** | **{overall_diff_str}** | **{overall_v3_tps:.1f} tok/s** | **{overall_b27_tps:.1f} tok/s** | **{overall_ratio:.2f}x** |" + ) lines.append("\n---\n") @@ -798,12 +886,18 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): avg_b27_ttft = (sum(all_b27_ttft) / len(all_b27_ttft)) if all_b27_ttft else 0.0 ttft_ratio = (avg_v3_ttft / avg_b27_ttft) if avg_b27_ttft else 0.0 - lines.append(f"| **Average Decode Throughput** | **{overall_v3_tps:.1f} tok/s** | **{overall_b27_tps:.1f} tok/s** | **{overall_ratio:.2f}x speed** |") - lines.append(f"| **Average Time-To-First-Token (TTFT)** | **{avg_v3_ttft:.1f} ms** | **{avg_b27_ttft:.1f} ms** | **{ttft_ratio:.2f}x faster** |") + lines.append( + f"| **Average Decode Throughput** | **{overall_v3_tps:.1f} tok/s** | **{overall_b27_tps:.1f} tok/s** | **{overall_ratio:.2f}x speed** |" + ) + lines.append( + f"| **Average Time-To-First-Token (TTFT)** | **{avg_v3_ttft:.1f} ms** | **{avg_b27_ttft:.1f} ms** | **{ttft_ratio:.2f}x faster** |" + ) v3_tot_toks = sum(r.get("completion_tokens", 0) for r in v3_map.values()) b27_tot_toks = sum(r.get("completion_tokens", 0) for r in b27_map.values()) - lines.append(f"| **Total Generated Tokens** | {v3_tot_toks:,} tokens | {b27_tot_toks:,} tokens | {((b27_tot_toks-v3_tot_toks)/v3_tot_toks*100.0 if v3_tot_toks else 0.0):+.1f}% tokens |") + lines.append( + f"| **Total Generated Tokens** | {v3_tot_toks:,} tokens | {b27_tot_toks:,} tokens | {((b27_tot_toks - v3_tot_toks) / v3_tot_toks * 100.0 if v3_tot_toks else 0.0):+.1f}% tokens |" + ) report_text = "\n".join(lines) with open(report_file, "w") as f: @@ -811,23 +905,35 @@ def generate_report(v3_file: Path, b27_file: Path, report_file: Path): print(f"Report written to {report_file}") print("\n" + report_text) + # ----------------------------------------------------------------------------- # Main Entry Point # ----------------------------------------------------------------------------- + def main(): - parser = argparse.ArgumentParser(description="Swift 27B vs Swift V3 Quality & Speed Benchmark") - parser.add_argument("--target", choices=["v3", "27b", "report"], default="v3", - help="Target model to evaluate or 'report' to generate scorecard") - parser.add_argument("--limit", type=int, default=0, help="Optional limit on total items") - parser.add_argument("--seed", type=int, default=1234, help="Random seed for deterministic sampling") + parser = argparse.ArgumentParser( + description="Swift 27B vs Swift V3 Quality & Speed Benchmark" + ) + parser.add_argument( + "--target", + choices=["v3", "27b", "report"], + default="v3", + help="Target model to evaluate or 'report' to generate scorecard", + ) + parser.add_argument( + "--limit", type=int, default=0, help="Optional limit on total items" + ) + parser.add_argument( + "--seed", type=int, default=1234, help="Random seed for deterministic sampling" + ) args = parser.parse_args() RESULTS_DIR.mkdir(parents=True, exist_ok=True) items = prepare_dataset(seed=args.seed) if args.limit > 0: - items = items[:args.limit] + items = items[: args.limit] v3_file = RESULTS_DIR / "swift_flash_next_v3_results.jsonl" b27_file = RESULTS_DIR / "swift_27b_splash_hq_results.jsonl" @@ -846,7 +952,7 @@ def main(): base_url="http://127.0.0.1:8090/v1", model_id="local/swift-qwen38-flash-next-v3", items=items, - output_file=v3_file + output_file=v3_file, ) elif args.target == "27b": print(f"Loaded {len(items)} benchmark test items across 6 domains:") @@ -861,10 +967,11 @@ def main(): base_url="http://127.0.0.1:8000/v1", model_id="nitinpanj/Swift-Qwen3.8-27B-Splash-HQ", items=items, - output_file=b27_file + output_file=b27_file, ) elif args.target == "report": generate_report(v3_file, b27_file, report_file) + if __name__ == "__main__": main() diff --git a/dev/native.mk b/dev/native.mk index c022615..eba75de 100644 --- a/dev/native.mk +++ b/dev/native.mk @@ -28,6 +28,8 @@ MODEL_SOURCES := \ models/qwen4exp/Qwen4Exp.cpp \ runtime/model/QwenTarget.cpp \ models/qwen4exp/Qwen4ExpTarget.cpp \ + models/qwen38/Qwen3_8.cpp \ + models/qwen38/Qwen3_8Target.cpp \ runtime/model/ModelFactory.cpp \ runtime/model/ModelDescriptor.mm MODEL_OPERATOR_SOURCES := \ diff --git a/dev/tests/engine/kv_first_engine_test.cpp b/dev/tests/engine/kv_first_engine_test.cpp index b0c49f5..9f3195e 100644 --- a/dev/tests/engine/kv_first_engine_test.cpp +++ b/dev/tests/engine/kv_first_engine_test.cpp @@ -228,7 +228,10 @@ class Executor final : public model::Model { 0, 0}); } else { - ModelStepResult step{item.requestId, 0, {42}, decodeFinishes, + const uint32_t outToken = (poisonRequest && item.requestId == poisonRequest) + ? poisonToken + : 42; + ModelStepResult step{item.requestId, 0, {outToken}, decodeFinishes, DecodeStage::Regular, 0, 0}; step.outputTokensWithoutKv = decodeTokensWithoutKv; result.push_back(std::move(step)); @@ -327,6 +330,8 @@ class Executor final : public model::Model { std::shared_ptr holdDecodeUntil; std::shared_ptr holdPrefillUntil; std::shared_ptr overlap; + uint64_t poisonRequest = 0; + uint32_t poisonToken = 0; }; class Events final : public EngineEventSink { @@ -2740,6 +2745,37 @@ void testCheckpointIntervalValidationAndDisable() { "disabling checkpoints changed existing replay-state behavior"); } +void testOutOfVocabularyOutputFailsLaneOnly() { + Backing backing(64); + KvPool pool(backing); + engine::Cache cache(pool, CacheNamespace{}); + Executor model; + Events events; + EngineConfig config; + config.vocabularySize = 1000; + engine::Engine engine(config, cache, model, events); + // The sampling kernels leave 0xffffffff when a logit row is entirely + // non-finite; the engine must fail that lane before the sentinel reaches + // the token history while the peer request completes normally. + model.poisonRequest = 1; + model.poisonToken = 0xFFFFFFFFU; + engine.submit(request(1, {7, 7, 7})); + engine.submit(request(2, {7, 7, 7})); + runUntilIdle(engine); + require(events.failedCount == 1, + "out-of-vocabulary model output did not fail the lane"); + require(events.failures.size() == 1 && + events.failures[0] == "model_result_invalid", + "out-of-vocabulary failure carried the wrong code"); + require(events.completedCount == 1, + "poisoned lane took down the rest of the batch"); + require(events.outputs[1].empty() && + events.outputs[2] == std::vector{42}, + "out-of-vocabulary token reached the event sink"); + require(events.usage.count(2) == 1, + "clean peer request did not complete"); +} + } // namespace int main() { @@ -2808,6 +2844,7 @@ int main() { testStalledSuspensionFailsWithCapacity(); testTerminalAnchorWithoutKvIsNotCached(); testPrefillCanCompleteTheRequest(); + testOutOfVocabularyOutputFailsLaneOnly(); std::cout << "KV-first engine tests passed\n"; return EXIT_SUCCESS; } catch (const std::exception &error) { diff --git a/dev/tests/engine/model_execution_plan_test.cpp b/dev/tests/engine/model_execution_plan_test.cpp index 3fd788d..87d0538 100644 --- a/dev/tests/engine/model_execution_plan_test.cpp +++ b/dev/tests/engine/model_execution_plan_test.cpp @@ -115,6 +115,11 @@ int main() { for (uint32_t family : {9U, 10U}) checkPackage(qwen4exp, family); std::cout << "model execution plans: PASS (qwen4exp)\n"; + + const auto qwen38 = package(); + for (uint32_t family : {9U, 10U}) + checkPackage(qwen38, family); + std::cout << "model execution plans: PASS (qwen38)\n"; } catch (const std::exception &error) { std::cerr << error.what() << '\n'; return 1; diff --git a/dev/tests/engine/native_engine_loop_test.cpp b/dev/tests/engine/native_engine_loop_test.cpp index 615a1ff..2633cbb 100644 --- a/dev/tests/engine/native_engine_loop_test.cpp +++ b/dev/tests/engine/native_engine_loop_test.cpp @@ -755,6 +755,56 @@ void testStepTokensFitTheWire() { } } +// The loop reports that it holds requests from the first it takes to the end +// of its last, the span the process keeps the Mac from idle sleep for. +void testHoldingRequestsSpansFirstToLastRequest() { + std::vector reported; + Backing backing(512); + KvPool pool(backing); + engine::Cache resources(pool, CacheNamespace{}); + Executor executor; + std::vector output; + double monotonic = 100.0; + engine::NativeLoopConfig config; + config.engine.maxContext = 1024; + config.holdingRequests = [&](bool held) { reported.push_back(held); }; + engine::NativeRuntime loop( + config, resources, executor, + [&](std::span bytes) { + output.insert(output.end(), bytes.begin(), bytes.end()); + }, + [] { return std::string("{\"schema_version\":5,\"ready\":true}"); }, + {[] { return uint64_t{1'000'000}; }, [&] { return monotonic += 0.25; }}); + loop.announceReady(); + require(reported.empty(), "a loop without requests reported holding one"); + auto sendReq = [&](protocol::RequestFrame r) { + auto encoded = protocol::serializeMessage(protocol::Message{r}); + return encoded && loop.receive(*encoded.value); + }; + require(sendReq(request(1)) && sendReq(request(2)), "two requests failed"); + require(reported == std::vector{true}, "two requests did not share one span"); + runUntilIdle(loop); + require(reported == std::vector{true, false}, + "the span did not end with the last request"); + // A cancelled request completes; a request whose deadline passes fails. + require(sendReq(request(3)) && loop.tick(), "request 3 failed"); + auto cancelEncoded = protocol::serializeMessage(protocol::Message{protocol::CancelFrame{3}}); + require(cancelEncoded && loop.receive(*cancelEncoded.value), "cancel failed"); + runUntilIdle(loop); + require(reported == std::vector{true, false, true, false}, + "a cancelled request did not end its span"); + require(sendReq(request(4, 64)), "request 4 failed"); + monotonic += 5000.0; + runUntilIdle(loop); + require(reported == std::vector{true, false, true, false, true, false}, + "a request that failed did not end its span"); + // One refused on arrival is never held. + protocol::RequestFrame expired = request(5); + expired.absoluteDeadlineUnixMicros = 1'000'000; + require(sendReq(expired) && reported.size() == 6, + "a request refused on arrival was held"); +} + } // namespace int main() { @@ -769,6 +819,7 @@ int main() { testControlFailureUsesExecutionBoundary(); testInvalidPromptTokensStayRequestScoped(); testStepTokensFitTheWire(); + testHoldingRequestsSpansFirstToLastRequest(); std::cout << "native KV-first loop tests passed\n"; return EXIT_SUCCESS; } catch (const std::exception &error) { diff --git a/dev/tests/engine/test_build_identity.py b/dev/tests/engine/test_build_identity.py index b38dafe..c3bf815 100644 --- a/dev/tests/engine/test_build_identity.py +++ b/dev/tests/engine/test_build_identity.py @@ -262,7 +262,7 @@ def calls(): return log.read_text().splitlines() outputs = ( - "splash", + "slipstream", "engine-tests/qwen4exp-package", "engine-tests/attention-sweep", "engine-tests/metal-backend.metallib", @@ -300,10 +300,10 @@ def calls(): self.assertIn(linked, calls()[start:]) if linked == targets[0]: self.assertIn( - str(build / "engine/libsplash.a"), calls()[start:] + str(build / "engine/libslipstream.a"), calls()[start:] ) self.assertIn( - str(build / "splash.metallib"), calls()[start:] + str(build / "slipstream.metallib"), calls()[start:] ) if linked == targets[3]: self.assertIn( @@ -353,7 +353,7 @@ def test_metal_input_removal_and_restore_rebuild_only_affected_outputs(self): f"{name}={sys.executable} {compiler}" for name in ("CXX", "METAL", "METALLIB", "AR") ] - library = str(build / "splash.metallib") + library = str(build / "slipstream.metallib") attention = str(build / "engine-tests/q8-attention.metallib") native = str(build / "engine/engine/Status.o") unrelated = str(build / "engine-tests/metal-backend.metallib") diff --git a/dev/tests/engine/test_clients.py b/dev/tests/engine/test_clients.py index d3a4230..27e409b 100644 --- a/dev/tests/engine/test_clients.py +++ b/dev/tests/engine/test_clients.py @@ -536,7 +536,10 @@ def test_unready_server_never_launches_or_downloads(self): mock.patch("sys.stderr", io.StringIO()) as error, ): self.assertEqual(launcher.main(["claude", *payload]), 1) - self.assertIn("slipstream-v2 serve", error.getvalue()) + self.assertTrue( + "slipstream serve" in error.getvalue() + or "slipstream-v2 serve" in error.getvalue() + ) execute.assert_not_called() install.assert_not_called() diff --git a/dev/tests/engine/test_completion.py b/dev/tests/engine/test_completion.py index 45e229c..a020e28 100644 --- a/dev/tests/engine/test_completion.py +++ b/dev/tests/engine/test_completion.py @@ -77,9 +77,8 @@ def layout(self, name="source tree", *, release=False): (directory / "official-models.txt").write_text("\n".join(OFFICIAL) + "\n") if release: (root / "release.json").write_text("{}") - models = self.home / "Library/Application Support/Splash/models" - else: - models = root / "install/models" + # Source and release installations share one model store. + models = self.home / ".slipstream/models" for model in (*OFFICIAL, LOCAL[0]): model_root = models / model model_root.mkdir(parents=True, exist_ok=True) @@ -174,7 +173,7 @@ def test_cached_catalog_adds_valid_entries_in_source_and_release(self): with self.subTest(release=release): root, directory = self.layout(str(release), release=release) data = ( - self.home / "Library/Application Support/Splash" + self.home / "Library/Application Support/Slipstream-v2" if release else root / "build/runtime" ) diff --git a/dev/tests/engine/test_gguf_in_place.py b/dev/tests/engine/test_gguf_in_place.py new file mode 100644 index 0000000..ebae93c --- /dev/null +++ b/dev/tests/engine/test_gguf_in_place.py @@ -0,0 +1,239 @@ +"""Preparing a GGUF model in place: its source is freed as parts are written, and resumes.""" + +import concurrent.futures +import contextlib +import io +import json +import struct +import tempfile +import unittest +from pathlib import Path +from unittest import mock + +from dev.tools.sharded_gguf_reader import MultiShardGgufReader +from models.qwen4exp.tools import convert_qwen4exp_gguf as converter + +# Three file-system blocks per tensor, so freeing one always frees whole blocks. +ELEMENTS = 3 * 4096 // 4 + + +def write_gguf(path: Path, names: list[str]) -> None: + """A GGUF of float32 vectors, the n-th filled with n.""" + header = struct.pack("<4sIQQ", b"GGUF", 3, len(names), 0) + for index, name in enumerate(names): + encoded = name.encode() + header += struct.pack(" len(self.buf): raise EOFError(f"{self.path}: header truncated") - v = self.buf[self.o:self.o+n] + v = self.buf[self.o : self.o + n] self.o += n return v def _u32(self): - return struct.unpack('" f = SCALAR[t] - return struct.unpack('<' + f, self._raw(struct.calcsize(f)))[0] + return struct.unpack("<" + f, self._raw(struct.calcsize(f)))[0] def read_header(path, probe=1 << 20): size = os.path.getsize(path) while True: - with open(path, 'rb') as f: + with open(path, "rb") as f: buf = f.read(min(probe, size)) try: return Header(path, buf) @@ -162,7 +202,7 @@ def read_header(path, probe=1 << 20): def copy_range(src, src_off, n, dst, chunk=32 << 20): - with open(src, 'rb') as f: + with open(src, "rb") as f: f.seek(src_off) left = n while left: @@ -174,7 +214,9 @@ def copy_range(src, src_off, n, dst, chunk=32 << 20): def fetch_header_remote(url: str, probe_bytes: int = 30000000) -> Header: - req = urllib.request.Request(url, headers={'Range': f'bytes=0-{probe_bytes}', 'User-Agent': 'hf'}) + req = urllib.request.Request( + url, headers={"Range": f"bytes=0-{probe_bytes}", "User-Agent": "hf"} + ) with urllib.request.urlopen(req) as resp: buf = resp.read() return Header(url, buf) @@ -184,7 +226,9 @@ def download_tensor_range(url: str, offset: int, nbytes: int, dst_path: Path): if dst_path.exists() and dst_path.stat().st_size == nbytes: return end_byte = offset + nbytes - 1 - req = urllib.request.Request(url, headers={'Range': f'bytes={offset}-{end_byte}', 'User-Agent': 'hf'}) + req = urllib.request.Request( + url, headers={"Range": f"bytes={offset}-{end_byte}", "User-Agent": "hf"} + ) for attempt in range(5): try: with urllib.request.urlopen(req, timeout=60) as resp: @@ -192,15 +236,15 @@ def download_tensor_range(url: str, offset: int, nbytes: int, dst_path: Path): if len(data) != nbytes: raise IOError(f"Expected {nbytes} bytes but got {len(data)}") dst_path.parent.mkdir(parents=True, exist_ok=True) - tmp_path = dst_path.with_suffix('.tmp') - with open(tmp_path, 'wb') as f: + tmp_path = dst_path.with_suffix(".tmp") + with open(tmp_path, "wb") as f: f.write(data) tmp_path.rename(dst_path) return - except Exception as e: + except Exception: if attempt == 4: raise - time.sleep(2 ** attempt) + time.sleep(2**attempt) def build_donor_index() -> dict[str, dict]: @@ -210,18 +254,22 @@ def build_donor_index() -> dict[str, dict]: url = f"https://huggingface.co/{REPO_ID}/resolve/main/Q8_0/Swift-1.5-Qwen3.8-Flash-Next-Q8_0-0000{s_idx}-of-00005.gguf" h = fetch_header_remote(url) for t in h.tensors: - name = t['name'] - hit = next((g for g, pat in GROUPS.items() if re.fullmatch(pat, name)), None) + name = t["name"] + hit = next( + (g for g, pat in GROUPS.items() if re.fullmatch(pat, name)), None + ) if hit: donor_map[name] = { - 'url': url, - 'offset': t['file_offset'], - 'nbytes': t['nbytes'], - 'type': t['type'], - 'dims': t['dims'], - 'group': hit, + "url": url, + "offset": t["file_offset"], + "nbytes": t["nbytes"], + "type": t["type"], + "dims": t["dims"], + "group": hit, } - log(f" Indexed {len(donor_map)} resident donor tensors (~{sum(d['nbytes'] for d in donor_map.values()) / 1024**3:.2f} GiB)") + log( + f" Indexed {len(donor_map)} resident donor tensors (~{sum(d['nbytes'] for d in donor_map.values()) / 1024**3:.2f} GiB)" + ) return donor_map @@ -231,7 +279,9 @@ def process_shard(shard_num: int, total_shards: int, donor_map: dict[str, dict]) out_path = OUT_DIR / out_name if out_path.exists() and out_path.stat().st_size > 10 * 1024**3: - log(f"Shard {shard_num}/{total_shards} already completed at {out_path} ({out_path.stat().st_size / 1024**3:.2f} GiB). Skipping.") + log( + f"Shard {shard_num}/{total_shards} already completed at {out_path} ({out_path.stat().st_size / 1024**3:.2f} GiB). Skipping." + ) return base_fn = f"Q4_0/Swift-1.5-Qwen3.8-Flash-Next-Q4_0-{shard_str}.gguf" @@ -246,7 +296,9 @@ def process_shard(shard_num: int, total_shards: int, donor_map: dict[str, dict]) ) raw_path = Path(raw_path_str) dl_elapsed = time.time() - t0 - log(f" Downloaded base shard ({raw_path.stat().st_size / 1024**3:.2f} GiB in {dl_elapsed:.1f}s)") + log( + f" Downloaded base shard ({raw_path.stat().st_size / 1024**3:.2f} GiB in {dl_elapsed:.1f}s)" + ) # Read base header log(" Parsing base shard header...") @@ -259,68 +311,77 @@ def process_shard(shard_num: int, total_shards: int, donor_map: dict[str, dict]) tensor_staging.mkdir(parents=True, exist_ok=True) for t in h.tensors: - name = t['name'] + name = t["name"] if name in donor_map: d = donor_map[name] dst_t_path = tensor_staging / f"{name}.bin" subs[name] = { - 'src': dst_t_path, - 'off': 0, - 'type': d['type'], - 'nbytes': d['nbytes'], - 'url': d['url'], - 'donor_off': d['offset'], + "src": dst_t_path, + "off": 0, + "type": d["type"], + "nbytes": d["nbytes"], + "url": d["url"], + "donor_off": d["offset"], } - download_tasks.append((d['url'], d['offset'], d['nbytes'], dst_t_path)) + download_tasks.append((d["url"], d["offset"], d["nbytes"], dst_t_path)) - log(f" Found {len(subs)} tensors in this shard to upgrade to Q8_0 (~{sum(s['nbytes'] for s in subs.values()) / 1024**2:.1f} MB)") + log( + f" Found {len(subs)} tensors in this shard to upgrade to Q8_0 (~{sum(s['nbytes'] for s in subs.values()) / 1024**2:.1f} MB)" + ) # Download donor tensors concurrently if download_tasks: - log(f" Streaming {len(download_tasks)} Q8_0 donor tensors via HTTP range requests...") + log( + f" Streaming {len(download_tasks)} Q8_0 donor tensors via HTTP range requests..." + ) t_dl0 = time.time() with concurrent.futures.ThreadPoolExecutor(max_workers=8) as ex: - futures = [ex.submit(download_tensor_range, url, off, nb, p) for url, off, nb, p in download_tasks] + futures = [ + ex.submit(download_tensor_range, url, off, nb, p) + for url, off, nb, p in download_tasks + ] for f in concurrent.futures.as_completed(futures): f.result() log(f" All donor tensors downloaded in {time.time() - t_dl0:.1f}s") # Compute new layout & patch header - hdr = bytearray(h.buf[:h.data_start]) + hdr = bytearray(h.buf[: h.data_start]) rel = 0 layout = [] for t in h.tensors: - name = t['name'] + name = t["name"] s = subs.get(name) - new_type = s['type'] if s else t['type'] - new_nb = s['nbytes'] if s else t['nbytes'] + new_type = s["type"] if s else t["type"] + new_nb = s["nbytes"] if s else t["nbytes"] - struct.pack_into(' list[Path]: @@ -171,6 +177,10 @@ def check() -> list[str]: errors.append( f"{name}: production backend contains client-specific behavior" ) + # Every timeout and duration counts time the Mac is awake, as the + # server's time.monotonic() does. + if SLEEP_COUNTING_CLOCK.search(text): + errors.append(f"{name}: measures time on a clock that counts sleep") return errors diff --git a/dev/tools/compare_slipstream_vs_llamacpp.py b/dev/tools/compare_slipstream_vs_llamacpp.py index 13cf8b3..d2127be 100755 --- a/dev/tools/compare_slipstream_vs_llamacpp.py +++ b/dev/tools/compare_slipstream_vs_llamacpp.py @@ -38,7 +38,7 @@ "\\[\\sum_{j = 1}^\\infty \\sum_{k = 1}^\\infty \\frac{1}{(j + k)^3}\\]\n" "in terms of $p$ and $q.$\n" "Think step by step and conclude your response with: " - 'Therefore, the final answer is \\boxed{ANSWER}' + "Therefore, the final answer is \\boxed{ANSWER}" ), "expected": "p - q", "max_tokens": 1200, @@ -75,7 +75,7 @@ "prompt": ( "Write a Rust function `parse_csv_line(line: &str) -> Vec` that parses a single CSV line " "with quoted fields (commas inside double quotes are preserved) into a Vec. " - "Handle double-quote escaping (\"\") properly. Include two unit tests in a `#[cfg(test)]` module." + 'Handle double-quote escaping ("") properly. Include two unit tests in a `#[cfg(test)]` module.' ), "expected": None, "max_tokens": 1200, @@ -96,10 +96,14 @@ def check_port_free(port: int): try: - out = subprocess.check_output( - ["lsof", "-nP", f"-iTCP:{port}", "-sTCP:LISTEN", "-t"], - stderr=subprocess.DEVNULL, - ).decode().strip() + out = ( + subprocess.check_output( + ["lsof", "-nP", f"-iTCP:{port}", "-sTCP:LISTEN", "-t"], + stderr=subprocess.DEVNULL, + ) + .decode() + .strip() + ) return len(out) == 0 except subprocess.CalledProcessError: return True @@ -107,10 +111,14 @@ def check_port_free(port: int): def kill_on_port(port: int): try: - out = subprocess.check_output( - ["lsof", "-nP", f"-iTCP:{port}", "-sTCP:LISTEN", "-t"], - stderr=subprocess.DEVNULL, - ).decode().strip() + out = ( + subprocess.check_output( + ["lsof", "-nP", f"-iTCP:{port}", "-sTCP:LISTEN", "-t"], + stderr=subprocess.DEVNULL, + ) + .decode() + .strip() + ) if out: for pid in out.split(): try: @@ -141,7 +149,9 @@ def wait_for_ready(url: str, timeout: int = 180): return False -def stream_chat_completion(base_url: str, prompt: str, max_tokens: int, model: str = None): +def stream_chat_completion( + base_url: str, prompt: str, max_tokens: int, model: str = None +): url = f"{base_url}/chat/completions" payload = { "messages": [{"role": "user", "content": prompt}], @@ -195,7 +205,11 @@ def stream_chat_completion(base_url: str, prompt: str, max_tokens: int, model: s elapsed = t_end - t0 ttft_ms = ((first_token_time - t0) * 1000.0) if first_token_time else 0.0 decode_duration = (t_end - first_token_time) if first_token_time else 0.0 - decode_tok_s = ((token_count - 1) / decode_duration) if (decode_duration > 0 and token_count > 1) else 0.0 + decode_tok_s = ( + ((token_count - 1) / decode_duration) + if (decode_duration > 0 and token_count > 1) + else 0.0 + ) full_content = "".join(chunks_text) full_reasoning = "".join(reasoning_text) @@ -213,37 +227,65 @@ def stream_chat_completion(base_url: str, prompt: str, max_tokens: int, model: s def run_benchmark_on_engine(engine_name: str, base_url: str, model_id: str = None): - print(f"\n{'='*70}\nRunning Benchmark on: {engine_name} ({base_url})\n{'='*70}") + print(f"\n{'=' * 70}\nRunning Benchmark on: {engine_name} ({base_url})\n{'=' * 70}") results = [] for item in BENCH_PROMPTS: - print(f"\n--> [{item['id']}] {item['category']} (max {item['max_tokens']} tok)...", end="", flush=True) - res = stream_chat_completion(base_url, item["prompt"], item["max_tokens"], model=model_id) + print( + f"\n--> [{item['id']}] {item['category']} (max {item['max_tokens']} tok)...", + end="", + flush=True, + ) + res = stream_chat_completion( + base_url, item["prompt"], item["max_tokens"], model=model_id + ) if "error" in res: print(f" ERROR: {res['error']}") - results.append({"id": item["id"], "category": item["category"], "error": res["error"]}) + results.append( + {"id": item["id"], "category": item["category"], "error": res["error"]} + ) else: - print(f" Done in {res['elapsed_s']:.2f}s | TTFT: {res['ttft_ms']:.1f}ms | Decode: {res['decode_tok_s']:.2f} tok/s | Tokens: {res['token_count']}") - ans_display = res["content"].strip() if res["content"].strip() else res["reasoning"].strip() - snippet = ans_display[-120:].replace("\n", " ") if len(ans_display) > 120 else ans_display.replace("\n", " ") + print( + f" Done in {res['elapsed_s']:.2f}s | TTFT: {res['ttft_ms']:.1f}ms | Decode: {res['decode_tok_s']:.2f} tok/s | Tokens: {res['token_count']}" + ) + ans_display = ( + res["content"].strip() + if res["content"].strip() + else res["reasoning"].strip() + ) + snippet = ( + ans_display[-120:].replace("\n", " ") + if len(ans_display) > 120 + else ans_display.replace("\n", " ") + ) print(f" Tail snippet: {snippet}") - results.append({ - "id": item["id"], - "category": item["category"], - "expected": item.get("expected"), - "token_count": res["token_count"], - "elapsed_s": res["elapsed_s"], - "ttft_ms": res["ttft_ms"], - "decode_tok_s": res["decode_tok_s"], - "content": res["content"], - "reasoning": res["reasoning"], - }) + results.append( + { + "id": item["id"], + "category": item["category"], + "expected": item.get("expected"), + "token_count": res["token_count"], + "elapsed_s": res["elapsed_s"], + "ttft_ms": res["ttft_ms"], + "decode_tok_s": res["decode_tok_s"], + "content": res["content"], + "reasoning": res["reasoning"], + } + ) return results def main(): - parser = argparse.ArgumentParser(description="A/B Benchmark: Slipstream-GGUF vs llama.cpp on V3 GGUF") - parser.add_argument("--model-dir", default=str(Path.home() / "models/qwen38-flash-next-v3"), help="Model directory for Slipstream") - parser.add_argument("--llama-model", default=None, help="GGUF shard 1 file for llama.cpp") + parser = argparse.ArgumentParser( + description="A/B Benchmark: Slipstream-GGUF vs llama.cpp on V3 GGUF" + ) + parser.add_argument( + "--model-dir", + default=str(Path.home() / "models/qwen38-flash-next-v3"), + help="Model directory for Slipstream", + ) + parser.add_argument( + "--llama-model", default=None, help="GGUF shard 1 file for llama.cpp" + ) parser.add_argument("--only-slipstream", action="store_true") parser.add_argument("--only-llamacpp", action="store_true") parser.add_argument("--out", default=None, help="Output JSON path") @@ -256,11 +298,16 @@ def main(): if shards: llama_model = str(shards[0]) else: - llama_model = str(Path.home() / "models/qwen38-flash-next-v3/Qwen3.8-Flash-Next-Q4_0-Q8out-v3-00001-of-00003.gguf") + llama_model = str( + Path.home() + / "models/qwen38-flash-next-v3/Qwen3.8-Flash-Next-Q4_0-Q8out-v3-00001-of-00003.gguf" + ) out_path_str = args.out if not out_path_str: - out_path_str = str(ROOT / f"dev/benchmarks/comparison_{model_dir_path.name}_results.json") + out_path_str = str( + ROOT / f"dev/benchmarks/comparison_{model_dir_path.name}_results.json" + ) out_file = Path(out_path_str) out_file.parent.mkdir(parents=True, exist_ok=True) all_data = {} @@ -280,9 +327,9 @@ def main(): # 1. RUN SLIPSTREAM-GGUF if not args.only_llamacpp: - print("\n" + "="*70) + print("\n" + "=" * 70) print("STEP 1: Starting Slipstream-GGUF on port 8090...") - print("="*70) + print("=" * 70) slip_env = os.environ.copy() slip_env["REPO"] = str(ROOT) slip_env["PKG"] = str(model_dir_path / "prepared") @@ -292,8 +339,10 @@ def main(): cmd = [ str(ROOT / "dev/benchmarks/guarded.py"), - "--floor-gib", "4", - "--max-seconds", "1800", + "--floor-gib", + "4", + "--max-seconds", + "1800", "--", str(ROOT / "splash"), "serve", @@ -303,16 +352,24 @@ def main(): "8090", ] log_file = open("/tmp/slipstream_bench_server.log", "w") - proc_slip = subprocess.Popen(cmd, env=slip_env, stdout=log_file, stderr=subprocess.STDOUT) + proc_slip = subprocess.Popen( + cmd, env=slip_env, stdout=log_file, stderr=subprocess.STDOUT + ) print("Waiting for Slipstream-GGUF on http://127.0.0.1:8090/v1/models...") if not wait_for_ready("http://127.0.0.1:8090/v1/models", timeout=120): - print("ERROR: Slipstream-GGUF failed to start! Check /tmp/slipstream_bench_server.log") + print( + "ERROR: Slipstream-GGUF failed to start! Check /tmp/slipstream_bench_server.log" + ) proc_slip.kill() return 1 print("Slipstream-GGUF is live!") - slip_results = run_benchmark_on_engine("Slipstream-GGUF", "http://127.0.0.1:8090/v1", model_id=f"local/{model_dir_path.name}") + slip_results = run_benchmark_on_engine( + "Slipstream-GGUF", + "http://127.0.0.1:8090/v1", + model_id=f"local/{model_dir_path.name}", + ) all_data["slipstream"] = slip_results print("\nStopping Slipstream-GGUF cleanly...") @@ -329,9 +386,11 @@ def main(): # 2. RUN LLAMA.CPP if not args.only_slipstream: - print("\n" + "="*70) - print(f"STEP 2: Starting llama.cpp (llama-server) on port 8080 with {Path(llama_model).name}...") - print("="*70) + print("\n" + "=" * 70) + print( + f"STEP 2: Starting llama.cpp (llama-server) on port 8080 with {Path(llama_model).name}..." + ) + print("=" * 70) llama_env = os.environ.copy() llama_env["MODEL"] = str(llama_model) llama_env["PORT"] = "8080" @@ -342,22 +401,30 @@ def main(): cmd = [ str(ROOT / "dev/benchmarks/guarded.py"), - "--floor-gib", "4", - "--max-seconds", "1800", + "--floor-gib", + "4", + "--max-seconds", + "1800", "--", - str(Path.home() / "models/bin/qwen-q40-server.sh") + str(Path.home() / "models/bin/qwen-q40-server.sh"), ] log_file_llama = open("/tmp/llamacpp_bench_server.log", "w") - proc_llama = subprocess.Popen(cmd, env=llama_env, stdout=log_file_llama, stderr=subprocess.STDOUT) + proc_llama = subprocess.Popen( + cmd, env=llama_env, stdout=log_file_llama, stderr=subprocess.STDOUT + ) print("Waiting for llama.cpp on http://127.0.0.1:8080/health...") if not wait_for_ready("http://127.0.0.1:8080/health", timeout=180): - print("ERROR: llama.cpp failed to start! Check /tmp/llamacpp_bench_server.log") + print( + "ERROR: llama.cpp failed to start! Check /tmp/llamacpp_bench_server.log" + ) proc_llama.kill() return 1 print("llama.cpp is live!") - llama_results = run_benchmark_on_engine("llama.cpp", "http://127.0.0.1:8080/v1", model_id="qwen3.8-flash-next-q40") + llama_results = run_benchmark_on_engine( + "llama.cpp", "http://127.0.0.1:8080/v1", model_id="qwen3.8-flash-next-q40" + ) all_data["llamacpp"] = llama_results print("\nStopping llama.cpp cleanly...") @@ -376,10 +443,12 @@ def main(): print(f"\nSaved raw benchmark data to {out_file}") if "slipstream" in all_data and "llamacpp" in all_data: - print("\n" + "="*80) + print("\n" + "=" * 80) print("HEAD-TO-HEAD SPEED & QUALITY COMPARISON (V3 GGUF Model)") - print("="*80) - print(f"{'Prompt ID':<20} | {'Slipstream (tok/s)':<18} | {'llama.cpp (tok/s)':<18} | {'Speedup':<8} | {'Quality Match'}") + print("=" * 80) + print( + f"{'Prompt ID':<20} | {'Slipstream (tok/s)':<18} | {'llama.cpp (tok/s)':<18} | {'Speedup':<8} | {'Quality Match'}" + ) print("-" * 80) slip_map = {r["id"]: r for r in all_data["slipstream"] if "decode_tok_s" in r} @@ -416,15 +485,19 @@ def main(): else: q_status = "Both completed" - print(f"{pid:<20} | {s_tok:>14.2f} t/s | {l_tok:>14.2f} t/s | {ratio:>6.2f}x | {q_status}") + print( + f"{pid:<20} | {s_tok:>14.2f} t/s | {l_tok:>14.2f} t/s | {ratio:>6.2f}x | {q_status}" + ) if slip_speeds and llama_speeds: avg_s = sum(slip_speeds) / len(slip_speeds) avg_l = sum(llama_speeds) / len(llama_speeds) overall_ratio = avg_s / avg_l if avg_l > 0 else 0.0 print("-" * 80) - print(f"{'AVERAGE':<20} | {avg_s:>14.2f} t/s | {avg_l:>14.2f} t/s | {overall_ratio:>6.2f}x |") - print("="*80) + print( + f"{'AVERAGE':<20} | {avg_s:>14.2f} t/s | {avg_l:>14.2f} t/s | {overall_ratio:>6.2f}x |" + ) + print("=" * 80) if __name__ == "__main__": diff --git a/dev/tools/fast_dequant_ext.c b/dev/tools/fast_dequant_ext.c new file mode 100644 index 0000000..80f2e4f --- /dev/null +++ b/dev/tools/fast_dequant_ext.c @@ -0,0 +1,988 @@ +/* Extended GGUF dequantization kernels for the sharded reader. + * + * Adds the quant types that fast_dequant.c does not cover: + * Q2_0 (42), Q5_K (13), IQ2_XXS (16), IQ2_XS (17), IQ2_S (22), + * IQ3_XXS (18), IQ3_S (21), IQ4_NL (20), IQ4_XS (23) + * + * The kernel bodies, block layouts and lookup tables are vendored from + * llama.cpp (ggml-quants.c, ggml-common.h), MIT licensed: + * https://github.com/ggml-org/llama.cpp/blob/master/LICENSE + * They are kept verbatim apart from removing the GGML_RESTRICT / + * GGML_FP16_TO_FP32 indirection. + * + * Exported symbol names follow the fast_dequant.c convention + * (lowercase type names, e.g. dequant_q5_k) so sharded_gguf_reader.py + * can look them up uniformly. + */ +#include +#include +#include +#include + +typedef uint16_t ggml_fp16_t; +typedef ggml_fp16_t ggml_half; + +static inline float fp16_to_fp32(ggml_fp16_t h) { + uint32_t sign = ((uint32_t)h & 0x8000) << 16; + int32_t exp = (h >> 10) & 0x1F; + uint32_t mant = h & 0x03FF; + + if (exp == 0) { + if (mant == 0) { + float f; + uint32_t u = sign; + memcpy(&f, &u, 4); + return f; + } + // Subnormal: normalize so the implicit leading bit is set. + exp = 1; + while (!(mant & 0x0400)) { + mant <<= 1; + exp--; + } + mant &= 0x03FF; + } else if (exp == 31) { + float f; + uint32_t u = sign | 0x7F800000 | (mant << 13); + memcpy(&f, &u, 4); + return f; + } + exp = exp + (127 - 15); + uint32_t u = sign | ((uint32_t)exp << 23) | (mant << 13); + float f; + memcpy(&f, &u, 4); + return f; +} + + +#define QK_K 256 +#define QK2_0 64 +#define QK4_NL 32 +#define K_SCALE_SIZE 12 +#define IQ3S_N_SCALE QK_K/64 + +/* block layouts (ggml-common.h) */ + +typedef struct { + ggml_half d; // delta (scale) + uint8_t qs[QK2_0 / 4]; // 2 bits per element +} block_q2_0; +static_assert(sizeof(block_q2_0) == sizeof(ggml_half) + QK2_0 / 4, "wrong q2_0 block size"); + +typedef struct { + ggml_half d; // super-block scale for quantized scales + ggml_half dmin; // super-block scale for quantized mins + uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits + uint8_t qh[QK_K/8]; // quants, high bit + uint8_t qs[QK_K/2]; // quants, low 4 bits +} block_q5_K; +static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_half) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size"); + +typedef struct { + ggml_half d; + uint16_t qs[QK_K/8]; +} block_iq2_xxs; +static_assert(sizeof(block_iq2_xxs) == sizeof(ggml_half) + QK_K/8*sizeof(uint16_t), "wrong iq2_xxs block size"); + +typedef struct { + ggml_half d; + uint16_t qs[QK_K/8]; + uint8_t scales[QK_K/32]; +} block_iq2_xs; +static_assert(sizeof(block_iq2_xs) == sizeof(ggml_half) + QK_K/8*sizeof(uint16_t) + QK_K/32, "wrong iq2_xs block size"); + +typedef struct { + ggml_half d; + uint8_t qs[QK_K/4]; + uint8_t qh[QK_K/32]; + uint8_t scales[QK_K/32]; +} block_iq2_s; +static_assert(sizeof(block_iq2_s) == sizeof(ggml_half) + QK_K/4 + QK_K/16, "wrong iq2_s block size"); + +typedef struct { + ggml_half d; + uint8_t qs[3*QK_K/8]; +} block_iq3_xxs; +static_assert(sizeof(block_iq3_xxs) == sizeof(ggml_half) + 3*(QK_K/8), "wrong iq3_xxs block size"); + +typedef struct { + ggml_half d; + uint8_t qs[QK_K/4]; + uint8_t qh[QK_K/32]; + uint8_t signs[QK_K/8]; + uint8_t scales[IQ3S_N_SCALE]; +} block_iq3_s; +static_assert(sizeof(block_iq3_s) == sizeof(ggml_half) + 13*(QK_K/32) + IQ3S_N_SCALE, "wrong iq3_s block size"); + +typedef struct { + ggml_half d; + uint8_t qs[QK4_NL/2]; +} block_iq4_nl; +static_assert(sizeof(block_iq4_nl) == sizeof(ggml_half) + QK4_NL/2, "wrong iq4_nl block size"); + +typedef struct { + ggml_half d; + uint16_t scales_h; + uint8_t scales_l[QK_K/64]; + uint8_t qs[QK_K/2]; +} block_iq4_xs; +static_assert(sizeof(block_iq4_xs) == sizeof(ggml_half) + sizeof(uint16_t) + QK_K/64 + QK_K/2, "wrong iq4_xs block size"); + + +/* lookup tables (ggml-common.h) */ + +static const uint8_t kmask_iq2xs[8] = { + 1, 2, 4, 8, 16, 32, 64, 128 +}; +static const uint8_t ksigns_iq2xs[128] = { + 0, 129, 130, 3, 132, 5, 6, 135, 136, 9, 10, 139, 12, 141, 142, 15, + 144, 17, 18, 147, 20, 149, 150, 23, 24, 153, 154, 27, 156, 29, 30, 159, + 160, 33, 34, 163, 36, 165, 166, 39, 40, 169, 170, 43, 172, 45, 46, 175, + 48, 177, 178, 51, 180, 53, 54, 183, 184, 57, 58, 187, 60, 189, 190, 63, + 192, 65, 66, 195, 68, 197, 198, 71, 72, 201, 202, 75, 204, 77, 78, 207, + 80, 209, 210, 83, 212, 85, 86, 215, 216, 89, 90, 219, 92, 221, 222, 95, + 96, 225, 226, 99, 228, 101, 102, 231, 232, 105, 106, 235, 108, 237, 238, 111, + 240, 113, 114, 243, 116, 245, 246, 119, 120, 249, 250, 123, 252, 125, 126, 255, +}; +static const uint64_t iq2xxs_grid[256] = { + 0x0808080808080808, 0x080808080808082b, 0x0808080808081919, 0x0808080808082b08, + 0x0808080808082b2b, 0x0808080808190819, 0x0808080808191908, 0x08080808082b0808, + 0x08080808082b082b, 0x08080808082b2b08, 0x08080808082b2b2b, 0x0808080819080819, + 0x0808080819081908, 0x0808080819190808, 0x0808080819192b08, 0x08080808192b0819, + 0x08080808192b1908, 0x080808082b080808, 0x080808082b08082b, 0x080808082b082b2b, + 0x080808082b2b082b, 0x0808081908080819, 0x0808081908081908, 0x0808081908190808, + 0x0808081908191919, 0x0808081919080808, 0x080808192b081908, 0x080808192b192b08, + 0x0808082b08080808, 0x0808082b0808082b, 0x0808082b082b082b, 0x0808082b2b08082b, + 0x0808190808080819, 0x0808190808081908, 0x0808190808190808, 0x08081908082b0819, + 0x08081908082b1908, 0x0808190819080808, 0x080819081908082b, 0x0808190819082b08, + 0x08081908192b0808, 0x080819082b080819, 0x080819082b081908, 0x080819082b190808, + 0x080819082b2b1908, 0x0808191908080808, 0x080819190808082b, 0x0808191908082b08, + 0x08081919082b0808, 0x080819191908192b, 0x08081919192b2b19, 0x080819192b080808, + 0x080819192b190819, 0x0808192b08082b19, 0x0808192b08190808, 0x0808192b19080808, + 0x0808192b2b081908, 0x0808192b2b2b1908, 0x08082b0808080808, 0x08082b0808081919, + 0x08082b0808082b08, 0x08082b0808191908, 0x08082b08082b2b08, 0x08082b0819080819, + 0x08082b0819081908, 0x08082b0819190808, 0x08082b081919082b, 0x08082b082b082b08, + 0x08082b1908081908, 0x08082b1919080808, 0x08082b2b0808082b, 0x08082b2b08191908, + 0x0819080808080819, 0x0819080808081908, 0x0819080808190808, 0x08190808082b0819, + 0x0819080819080808, 0x08190808192b0808, 0x081908082b081908, 0x081908082b190808, + 0x081908082b191919, 0x0819081908080808, 0x0819081908082b08, 0x08190819082b0808, + 0x0819081919190808, 0x0819081919192b2b, 0x081908192b080808, 0x0819082b082b1908, + 0x0819082b19081919, 0x0819190808080808, 0x0819190808082b08, 0x08191908082b0808, + 0x08191908082b1919, 0x0819190819082b19, 0x081919082b080808, 0x0819191908192b08, + 0x08191919192b082b, 0x0819192b08080808, 0x0819192b0819192b, 0x08192b0808080819, + 0x08192b0808081908, 0x08192b0808190808, 0x08192b0819080808, 0x08192b082b080819, + 0x08192b1908080808, 0x08192b1908081919, 0x08192b192b2b0808, 0x08192b2b19190819, + 0x082b080808080808, 0x082b08080808082b, 0x082b080808082b2b, 0x082b080819081908, + 0x082b0808192b0819, 0x082b08082b080808, 0x082b08082b08082b, 0x082b0819082b2b19, + 0x082b081919082b08, 0x082b082b08080808, 0x082b082b0808082b, 0x082b190808080819, + 0x082b190808081908, 0x082b190808190808, 0x082b190819080808, 0x082b19081919192b, + 0x082b191908080808, 0x082b191919080819, 0x082b1919192b1908, 0x082b192b2b190808, + 0x082b2b0808082b08, 0x082b2b08082b0808, 0x082b2b082b191908, 0x082b2b2b19081908, + 0x1908080808080819, 0x1908080808081908, 0x1908080808190808, 0x1908080808192b08, + 0x19080808082b0819, 0x19080808082b1908, 0x1908080819080808, 0x1908080819082b08, + 0x190808081919192b, 0x19080808192b0808, 0x190808082b080819, 0x190808082b081908, + 0x190808082b190808, 0x1908081908080808, 0x19080819082b0808, 0x19080819192b0819, + 0x190808192b080808, 0x190808192b081919, 0x1908082b08080819, 0x1908082b08190808, + 0x1908082b19082b08, 0x1908082b1919192b, 0x1908082b192b2b08, 0x1908190808080808, + 0x1908190808082b08, 0x19081908082b0808, 0x190819082b080808, 0x190819082b192b19, + 0x190819190819082b, 0x19081919082b1908, 0x1908192b08080808, 0x19082b0808080819, + 0x19082b0808081908, 0x19082b0808190808, 0x19082b0819080808, 0x19082b0819081919, + 0x19082b1908080808, 0x19082b1919192b08, 0x19082b19192b0819, 0x19082b192b08082b, + 0x19082b2b19081919, 0x19082b2b2b190808, 0x1919080808080808, 0x1919080808082b08, + 0x1919080808190819, 0x1919080808192b19, 0x19190808082b0808, 0x191908082b080808, + 0x191908082b082b08, 0x1919081908081908, 0x191908191908082b, 0x191908192b2b1908, + 0x1919082b2b190819, 0x191919082b190808, 0x191919082b19082b, 0x1919191908082b2b, + 0x1919192b08080819, 0x1919192b19191908, 0x19192b0808080808, 0x19192b0808190819, + 0x19192b0808192b19, 0x19192b08192b1908, 0x19192b1919080808, 0x19192b2b08082b08, + 0x192b080808081908, 0x192b080808190808, 0x192b080819080808, 0x192b0808192b2b08, + 0x192b081908080808, 0x192b081919191919, 0x192b082b08192b08, 0x192b082b192b0808, + 0x192b190808080808, 0x192b190808081919, 0x192b191908190808, 0x192b19190819082b, + 0x192b19192b081908, 0x192b2b081908082b, 0x2b08080808080808, 0x2b0808080808082b, + 0x2b08080808082b2b, 0x2b08080819080819, 0x2b0808082b08082b, 0x2b08081908081908, + 0x2b08081908192b08, 0x2b08081919080808, 0x2b08082b08190819, 0x2b08190808080819, + 0x2b08190808081908, 0x2b08190808190808, 0x2b08190808191919, 0x2b08190819080808, + 0x2b081908192b0808, 0x2b08191908080808, 0x2b0819191908192b, 0x2b0819192b191908, + 0x2b08192b08082b19, 0x2b08192b19080808, 0x2b08192b192b0808, 0x2b082b080808082b, + 0x2b082b1908081908, 0x2b082b2b08190819, 0x2b19080808081908, 0x2b19080808190808, + 0x2b190808082b1908, 0x2b19080819080808, 0x2b1908082b2b0819, 0x2b1908190819192b, + 0x2b1908192b080808, 0x2b19082b19081919, 0x2b19190808080808, 0x2b191908082b082b, + 0x2b19190819081908, 0x2b19191919190819, 0x2b192b082b080819, 0x2b192b19082b0808, + 0x2b2b08080808082b, 0x2b2b080819190808, 0x2b2b08082b081919, 0x2b2b081908082b19, + 0x2b2b082b08080808, 0x2b2b190808192b08, 0x2b2b2b0819190808, 0x2b2b2b1908081908, +}; +static const uint64_t iq2xs_grid[512] = { + 0x0808080808080808, 0x080808080808082b, 0x0808080808081919, 0x0808080808082b08, + 0x0808080808082b2b, 0x0808080808190819, 0x0808080808191908, 0x080808080819192b, + 0x0808080808192b19, 0x08080808082b0808, 0x08080808082b082b, 0x08080808082b1919, + 0x08080808082b2b08, 0x0808080819080819, 0x0808080819081908, 0x080808081908192b, + 0x0808080819082b19, 0x0808080819190808, 0x080808081919082b, 0x0808080819191919, + 0x0808080819192b08, 0x08080808192b0819, 0x08080808192b1908, 0x080808082b080808, + 0x080808082b08082b, 0x080808082b081919, 0x080808082b082b08, 0x080808082b190819, + 0x080808082b191908, 0x080808082b192b19, 0x080808082b2b0808, 0x0808081908080819, + 0x0808081908081908, 0x080808190808192b, 0x0808081908082b19, 0x0808081908190808, + 0x080808190819082b, 0x0808081908191919, 0x0808081908192b08, 0x0808081908192b2b, + 0x08080819082b0819, 0x08080819082b1908, 0x0808081919080808, 0x080808191908082b, + 0x0808081919081919, 0x0808081919082b08, 0x0808081919190819, 0x0808081919191908, + 0x08080819192b0808, 0x08080819192b2b08, 0x080808192b080819, 0x080808192b081908, + 0x080808192b190808, 0x0808082b08080808, 0x0808082b0808082b, 0x0808082b08081919, + 0x0808082b08082b08, 0x0808082b08190819, 0x0808082b08191908, 0x0808082b082b0808, + 0x0808082b19080819, 0x0808082b19081908, 0x0808082b19190808, 0x0808082b19191919, + 0x0808082b2b080808, 0x0808082b2b082b2b, 0x0808190808080819, 0x0808190808081908, + 0x080819080808192b, 0x0808190808082b19, 0x0808190808190808, 0x080819080819082b, + 0x0808190808191919, 0x0808190808192b08, 0x08081908082b0819, 0x08081908082b1908, + 0x0808190819080808, 0x080819081908082b, 0x0808190819081919, 0x0808190819082b08, + 0x0808190819190819, 0x0808190819191908, 0x080819081919192b, 0x08081908192b0808, + 0x080819082b080819, 0x080819082b081908, 0x080819082b190808, 0x0808191908080808, + 0x080819190808082b, 0x0808191908081919, 0x0808191908082b08, 0x0808191908190819, + 0x0808191908191908, 0x08081919082b0808, 0x0808191919080819, 0x0808191919081908, + 0x0808191919190808, 0x08081919192b0819, 0x080819192b080808, 0x0808192b08080819, + 0x0808192b08081908, 0x0808192b08190808, 0x0808192b082b192b, 0x0808192b19080808, + 0x0808192b1908082b, 0x0808192b2b081908, 0x08082b0808080808, 0x08082b080808082b, + 0x08082b0808081919, 0x08082b0808082b08, 0x08082b0808082b2b, 0x08082b0808190819, + 0x08082b0808191908, 0x08082b08082b0808, 0x08082b08082b1919, 0x08082b0819080819, + 0x08082b0819081908, 0x08082b0819190808, 0x08082b0819192b08, 0x08082b082b080808, + 0x08082b082b2b0808, 0x08082b082b2b2b2b, 0x08082b1908080819, 0x08082b1908081908, + 0x08082b1908190808, 0x08082b1919080808, 0x08082b192b080819, 0x08082b192b082b19, + 0x08082b2b08080808, 0x08082b2b082b0808, 0x08082b2b082b2b08, 0x08082b2b2b19192b, + 0x08082b2b2b2b0808, 0x0819080808080819, 0x0819080808081908, 0x081908080808192b, + 0x0819080808082b19, 0x0819080808190808, 0x081908080819082b, 0x0819080808191919, + 0x0819080808192b08, 0x08190808082b0819, 0x08190808082b1908, 0x0819080819080808, + 0x081908081908082b, 0x0819080819081919, 0x0819080819082b08, 0x0819080819190819, + 0x0819080819191908, 0x08190808192b0808, 0x08190808192b2b2b, 0x081908082b080819, + 0x081908082b081908, 0x081908082b190808, 0x0819081908080808, 0x081908190808082b, + 0x0819081908081919, 0x0819081908082b08, 0x0819081908190819, 0x0819081908191908, + 0x08190819082b0808, 0x0819081919080819, 0x0819081919081908, 0x0819081919190808, + 0x081908192b080808, 0x081908192b191908, 0x081908192b19192b, 0x0819082b08080819, + 0x0819082b08081908, 0x0819082b0808192b, 0x0819082b08190808, 0x0819082b19080808, + 0x0819082b192b0808, 0x0819190808080808, 0x081919080808082b, 0x0819190808081919, + 0x0819190808082b08, 0x0819190808190819, 0x0819190808191908, 0x08191908082b0808, + 0x0819190819080819, 0x0819190819081908, 0x0819190819082b19, 0x0819190819190808, + 0x08191908192b1908, 0x081919082b080808, 0x0819191908080819, 0x0819191908081908, + 0x0819191908190808, 0x0819191919080808, 0x0819192b08080808, 0x0819192b08191908, + 0x0819192b19082b19, 0x08192b0808080819, 0x08192b0808081908, 0x08192b0808190808, + 0x08192b080819082b, 0x08192b0819080808, 0x08192b0819191908, 0x08192b082b08192b, + 0x08192b1908080808, 0x08192b1908081919, 0x08192b19192b192b, 0x08192b2b19190819, + 0x08192b2b2b2b2b19, 0x082b080808080808, 0x082b08080808082b, 0x082b080808081919, + 0x082b080808082b08, 0x082b080808082b2b, 0x082b080808190819, 0x082b080808191908, + 0x082b0808082b0808, 0x082b080819080819, 0x082b080819081908, 0x082b080819190808, + 0x082b08082b080808, 0x082b08082b2b0808, 0x082b081908080819, 0x082b081908081908, + 0x082b081908190808, 0x082b081919080808, 0x082b081919082b08, 0x082b0819192b1919, + 0x082b082b08080808, 0x082b082b082b082b, 0x082b082b2b080808, 0x082b082b2b2b2b08, + 0x082b190808080819, 0x082b190808081908, 0x082b190808190808, 0x082b1908082b2b19, + 0x082b190819080808, 0x082b191908080808, 0x082b191919080819, 0x082b19191919082b, + 0x082b19192b192b19, 0x082b192b08080819, 0x082b192b08192b2b, 0x082b192b2b2b192b, + 0x082b2b0808080808, 0x082b2b0808082b08, 0x082b2b0808082b2b, 0x082b2b08082b0808, + 0x082b2b0819191919, 0x082b2b082b082b08, 0x082b2b082b2b082b, 0x082b2b19192b2b08, + 0x082b2b192b190808, 0x082b2b2b08082b08, 0x082b2b2b082b0808, 0x082b2b2b2b08082b, + 0x082b2b2b2b082b08, 0x082b2b2b2b082b2b, 0x1908080808080819, 0x1908080808081908, + 0x190808080808192b, 0x1908080808082b19, 0x1908080808190808, 0x190808080819082b, + 0x1908080808191919, 0x1908080808192b08, 0x19080808082b0819, 0x19080808082b1908, + 0x1908080819080808, 0x190808081908082b, 0x1908080819081919, 0x1908080819082b08, + 0x1908080819082b2b, 0x1908080819190819, 0x1908080819191908, 0x19080808192b0808, + 0x19080808192b1919, 0x190808082b080819, 0x190808082b081908, 0x190808082b190808, + 0x1908081908080808, 0x190808190808082b, 0x1908081908081919, 0x1908081908082b08, + 0x1908081908190819, 0x1908081908191908, 0x19080819082b0808, 0x1908081919080819, + 0x1908081919081908, 0x1908081919190808, 0x190808192b080808, 0x190808192b081919, + 0x190808192b2b082b, 0x1908082b08080819, 0x1908082b08081908, 0x1908082b08190808, + 0x1908082b0819082b, 0x1908082b082b2b19, 0x1908082b19080808, 0x1908190808080808, + 0x190819080808082b, 0x1908190808081919, 0x1908190808082b08, 0x1908190808190819, + 0x1908190808191908, 0x1908190808192b19, 0x19081908082b0808, 0x1908190819080819, + 0x1908190819081908, 0x1908190819190808, 0x190819082b080808, 0x190819082b191908, + 0x1908191908080819, 0x1908191908081908, 0x1908191908190808, 0x19081919082b1908, + 0x1908191919080808, 0x190819192b192b2b, 0x1908192b08080808, 0x1908192b08082b2b, + 0x1908192b19081908, 0x1908192b19190808, 0x19082b0808080819, 0x19082b0808081908, + 0x19082b0808190808, 0x19082b0819080808, 0x19082b0819081919, 0x19082b0819191908, + 0x19082b08192b082b, 0x19082b1908080808, 0x19082b1908190819, 0x19082b1919081908, + 0x19082b1919190808, 0x19082b19192b2b19, 0x19082b2b08081908, 0x1919080808080808, + 0x191908080808082b, 0x1919080808081919, 0x1919080808082b08, 0x1919080808190819, + 0x1919080808191908, 0x19190808082b0808, 0x19190808082b2b08, 0x1919080819080819, + 0x1919080819081908, 0x1919080819190808, 0x191908082b080808, 0x1919081908080819, + 0x1919081908081908, 0x1919081908190808, 0x1919081908191919, 0x1919081919080808, + 0x191908191908082b, 0x1919082b08080808, 0x1919082b19081908, 0x1919082b2b2b2b2b, + 0x1919190808080819, 0x1919190808081908, 0x1919190808190808, 0x19191908082b0819, + 0x1919190819080808, 0x19191908192b0808, 0x191919082b080819, 0x191919082b2b0819, + 0x1919191908080808, 0x1919191908082b08, 0x191919192b080808, 0x191919192b082b08, + 0x1919192b082b0819, 0x1919192b192b2b08, 0x1919192b2b2b0819, 0x19192b0808080808, + 0x19192b0808191908, 0x19192b0819080819, 0x19192b0819190808, 0x19192b082b192b19, + 0x19192b1908192b2b, 0x19192b1919080808, 0x19192b191908082b, 0x19192b2b2b081919, + 0x192b080808080819, 0x192b080808081908, 0x192b080808190808, 0x192b080819080808, + 0x192b080819191908, 0x192b0808192b082b, 0x192b08082b08192b, 0x192b08082b2b2b19, + 0x192b081908080808, 0x192b082b082b1908, 0x192b082b19082b2b, 0x192b082b2b19082b, + 0x192b190808080808, 0x192b19080819192b, 0x192b191908190808, 0x192b191919080808, + 0x192b191919081919, 0x192b19192b2b1908, 0x192b2b0808080819, 0x192b2b08192b2b2b, + 0x192b2b19082b1919, 0x192b2b2b0808192b, 0x192b2b2b19191908, 0x192b2b2b192b082b, + 0x2b08080808080808, 0x2b0808080808082b, 0x2b08080808081919, 0x2b08080808082b08, + 0x2b08080808190819, 0x2b08080808191908, 0x2b080808082b0808, 0x2b080808082b2b2b, + 0x2b08080819080819, 0x2b08080819081908, 0x2b08080819190808, 0x2b0808082b080808, + 0x2b0808082b08082b, 0x2b0808082b2b2b08, 0x2b0808082b2b2b2b, 0x2b08081908080819, + 0x2b08081908081908, 0x2b0808190808192b, 0x2b08081908190808, 0x2b08081919080808, + 0x2b08081919190819, 0x2b08081919192b19, 0x2b08082b08080808, 0x2b08082b082b0808, + 0x2b08082b2b080808, 0x2b08082b2b08082b, 0x2b08082b2b2b0808, 0x2b08082b2b2b2b08, + 0x2b08190808080819, 0x2b08190808081908, 0x2b08190808190808, 0x2b0819080819082b, + 0x2b08190808191919, 0x2b08190819080808, 0x2b081908192b0808, 0x2b0819082b082b19, + 0x2b08191908080808, 0x2b08191919081908, 0x2b0819192b2b1919, 0x2b08192b08192b08, + 0x2b08192b192b2b2b, 0x2b082b0808080808, 0x2b082b0808082b08, 0x2b082b08082b1919, + 0x2b082b0819192b2b, 0x2b082b082b080808, 0x2b082b082b08082b, 0x2b082b082b2b2b08, + 0x2b082b190808192b, 0x2b082b2b082b082b, 0x2b082b2b2b080808, 0x2b082b2b2b082b08, + 0x2b082b2b2b19192b, 0x2b082b2b2b2b2b08, 0x2b19080808080819, 0x2b19080808081908, + 0x2b19080808190808, 0x2b19080819080808, 0x2b1908081919192b, 0x2b1908082b081908, + 0x2b19081908080808, 0x2b190819082b082b, 0x2b190819192b1908, 0x2b19082b1919192b, + 0x2b19082b2b082b19, 0x2b19190808080808, 0x2b19190808081919, 0x2b19190819081908, + 0x2b19190819190808, 0x2b19190819192b08, 0x2b191919082b2b19, 0x2b1919192b190808, + 0x2b1919192b19082b, 0x2b19192b19080819, 0x2b192b0819190819, 0x2b192b082b2b192b, + 0x2b192b1919082b19, 0x2b192b2b08191919, 0x2b192b2b192b0808, 0x2b2b080808080808, + 0x2b2b08080808082b, 0x2b2b080808082b08, 0x2b2b080808082b2b, 0x2b2b0808082b0808, + 0x2b2b0808082b2b2b, 0x2b2b08082b2b0808, 0x2b2b081919190819, 0x2b2b081919192b19, + 0x2b2b08192b2b192b, 0x2b2b082b08080808, 0x2b2b082b0808082b, 0x2b2b082b08082b08, + 0x2b2b082b082b2b2b, 0x2b2b082b2b080808, 0x2b2b082b2b2b0808, 0x2b2b190819080808, + 0x2b2b19082b191919, 0x2b2b192b192b1919, 0x2b2b192b2b192b08, 0x2b2b2b0808082b2b, + 0x2b2b2b08082b0808, 0x2b2b2b08082b082b, 0x2b2b2b08082b2b08, 0x2b2b2b082b2b0808, + 0x2b2b2b082b2b2b08, 0x2b2b2b1908081908, 0x2b2b2b192b081908, 0x2b2b2b192b08192b, + 0x2b2b2b2b082b2b08, 0x2b2b2b2b082b2b2b, 0x2b2b2b2b2b190819, 0x2b2b2b2b2b2b2b2b, +}; +static const uint64_t iq2s_grid[1024] = { + 0x0808080808080808, 0x080808080808082b, 0x0808080808081919, 0x0808080808082b08, + 0x0808080808082b2b, 0x0808080808190819, 0x0808080808191908, 0x080808080819192b, + 0x0808080808192b19, 0x08080808082b0808, 0x08080808082b082b, 0x08080808082b1919, + 0x08080808082b2b08, 0x0808080819080819, 0x0808080819081908, 0x080808081908192b, + 0x0808080819082b19, 0x0808080819190808, 0x080808081919082b, 0x0808080819191919, + 0x0808080819192b08, 0x08080808192b0819, 0x08080808192b1908, 0x08080808192b192b, + 0x08080808192b2b19, 0x080808082b080808, 0x080808082b08082b, 0x080808082b081919, + 0x080808082b082b08, 0x080808082b190819, 0x080808082b191908, 0x080808082b2b0808, + 0x080808082b2b1919, 0x080808082b2b2b2b, 0x0808081908080819, 0x0808081908081908, + 0x080808190808192b, 0x0808081908082b19, 0x0808081908190808, 0x080808190819082b, + 0x0808081908191919, 0x0808081908192b08, 0x08080819082b0819, 0x08080819082b1908, + 0x0808081919080808, 0x080808191908082b, 0x0808081919081919, 0x0808081919082b08, + 0x0808081919190819, 0x0808081919191908, 0x080808191919192b, 0x0808081919192b19, + 0x08080819192b0808, 0x08080819192b1919, 0x08080819192b2b08, 0x080808192b080819, + 0x080808192b081908, 0x080808192b190808, 0x080808192b19082b, 0x080808192b191919, + 0x080808192b2b0819, 0x080808192b2b1908, 0x0808082b08080808, 0x0808082b0808082b, + 0x0808082b08081919, 0x0808082b08082b08, 0x0808082b08190819, 0x0808082b08191908, + 0x0808082b082b0808, 0x0808082b082b2b2b, 0x0808082b19080819, 0x0808082b19081908, + 0x0808082b1908192b, 0x0808082b19082b19, 0x0808082b19190808, 0x0808082b19191919, + 0x0808082b2b080808, 0x0808082b2b081919, 0x0808082b2b082b2b, 0x0808082b2b191908, + 0x0808082b2b2b082b, 0x0808190808080819, 0x0808190808081908, 0x080819080808192b, + 0x0808190808082b19, 0x0808190808190808, 0x080819080819082b, 0x0808190808191919, + 0x0808190808192b08, 0x08081908082b0819, 0x08081908082b1908, 0x08081908082b192b, + 0x08081908082b2b19, 0x0808190819080808, 0x080819081908082b, 0x0808190819081919, + 0x0808190819082b08, 0x0808190819082b2b, 0x0808190819190819, 0x0808190819191908, + 0x080819081919192b, 0x0808190819192b19, 0x08081908192b0808, 0x08081908192b082b, + 0x08081908192b1919, 0x080819082b080819, 0x080819082b081908, 0x080819082b08192b, + 0x080819082b082b19, 0x080819082b190808, 0x080819082b191919, 0x080819082b192b08, + 0x080819082b2b0819, 0x080819082b2b1908, 0x0808191908080808, 0x080819190808082b, + 0x0808191908081919, 0x0808191908082b08, 0x0808191908082b2b, 0x0808191908190819, + 0x0808191908191908, 0x080819190819192b, 0x0808191908192b19, 0x08081919082b0808, + 0x08081919082b1919, 0x08081919082b2b08, 0x0808191919080819, 0x0808191919081908, + 0x080819191908192b, 0x0808191919082b19, 0x0808191919190808, 0x080819191919082b, + 0x0808191919191919, 0x0808191919192b08, 0x08081919192b0819, 0x08081919192b1908, + 0x080819192b080808, 0x080819192b08082b, 0x080819192b081919, 0x080819192b082b08, + 0x080819192b190819, 0x080819192b191908, 0x080819192b2b0808, 0x0808192b08080819, + 0x0808192b08081908, 0x0808192b0808192b, 0x0808192b08082b19, 0x0808192b08190808, + 0x0808192b08191919, 0x0808192b19080808, 0x0808192b19081919, 0x0808192b19082b08, + 0x0808192b19190819, 0x0808192b19191908, 0x0808192b192b0808, 0x0808192b2b080819, + 0x0808192b2b081908, 0x0808192b2b190808, 0x08082b0808080808, 0x08082b080808082b, + 0x08082b0808081919, 0x08082b0808082b08, 0x08082b0808190819, 0x08082b0808191908, + 0x08082b080819192b, 0x08082b0808192b19, 0x08082b08082b0808, 0x08082b08082b1919, + 0x08082b08082b2b2b, 0x08082b0819080819, 0x08082b0819081908, 0x08082b081908192b, + 0x08082b0819082b19, 0x08082b0819190808, 0x08082b081919082b, 0x08082b0819191919, + 0x08082b0819192b08, 0x08082b08192b0819, 0x08082b08192b1908, 0x08082b082b080808, + 0x08082b082b081919, 0x08082b082b191908, 0x08082b082b2b2b2b, 0x08082b1908080819, + 0x08082b1908081908, 0x08082b1908190808, 0x08082b190819082b, 0x08082b1908191919, + 0x08082b1908192b08, 0x08082b19082b0819, 0x08082b1919080808, 0x08082b1919081919, + 0x08082b1919082b08, 0x08082b1919190819, 0x08082b1919191908, 0x08082b19192b0808, + 0x08082b192b080819, 0x08082b192b190808, 0x08082b2b08080808, 0x08082b2b08190819, + 0x08082b2b08191908, 0x08082b2b082b082b, 0x08082b2b082b2b08, 0x08082b2b082b2b2b, + 0x08082b2b19190808, 0x08082b2b2b192b19, 0x0819080808080819, 0x0819080808081908, + 0x081908080808192b, 0x0819080808082b19, 0x0819080808190808, 0x081908080819082b, + 0x0819080808191919, 0x0819080808192b08, 0x08190808082b0819, 0x08190808082b1908, + 0x08190808082b192b, 0x0819080819080808, 0x081908081908082b, 0x0819080819081919, + 0x0819080819082b08, 0x0819080819190819, 0x0819080819191908, 0x081908081919192b, + 0x0819080819192b19, 0x08190808192b0808, 0x08190808192b082b, 0x08190808192b1919, + 0x08190808192b2b08, 0x081908082b080819, 0x081908082b081908, 0x081908082b08192b, + 0x081908082b190808, 0x081908082b191919, 0x081908082b192b08, 0x081908082b2b0819, + 0x081908082b2b1908, 0x0819081908080808, 0x081908190808082b, 0x0819081908081919, + 0x0819081908082b08, 0x0819081908082b2b, 0x0819081908190819, 0x0819081908191908, + 0x081908190819192b, 0x0819081908192b19, 0x08190819082b0808, 0x08190819082b082b, + 0x08190819082b1919, 0x08190819082b2b08, 0x0819081919080819, 0x0819081919081908, + 0x081908191908192b, 0x0819081919082b19, 0x0819081919190808, 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0x2b0808081919082b, + 0x2b08080819191919, 0x2b08080819192b08, 0x2b080808192b0819, 0x2b0808082b080808, + 0x2b0808082b081919, 0x2b0808082b190819, 0x2b0808082b191908, 0x2b08081908080819, + 0x2b08081908081908, 0x2b08081908082b19, 0x2b08081908190808, 0x2b0808190819082b, + 0x2b08081908191919, 0x2b08081908192b08, 0x2b080819082b0819, 0x2b080819082b1908, + 0x2b08081919080808, 0x2b0808191908082b, 0x2b08081919081919, 0x2b08081919082b08, + 0x2b08081919190819, 0x2b08081919191908, 0x2b0808192b080819, 0x2b0808192b081908, + 0x2b0808192b190808, 0x2b0808192b2b2b19, 0x2b08082b08080808, 0x2b08082b08081919, + 0x2b08082b08082b2b, 0x2b08082b08190819, 0x2b08082b08191908, 0x2b08082b19080819, + 0x2b08082b19081908, 0x2b08082b19190808, 0x2b08190808080819, 0x2b08190808081908, + 0x2b0819080808192b, 0x2b08190808082b19, 0x2b08190808190808, 0x2b0819080819082b, + 0x2b08190808191919, 0x2b08190808192b08, 0x2b081908082b0819, 0x2b08190819080808, + 0x2b0819081908082b, 0x2b08190819081919, 0x2b08190819082b08, 0x2b08190819190819, + 0x2b08190819191908, 0x2b081908192b0808, 0x2b0819082b080819, 0x2b0819082b081908, + 0x2b0819082b190808, 0x2b08191908080808, 0x2b0819190808082b, 0x2b08191908081919, + 0x2b08191908082b08, 0x2b08191908190819, 0x2b08191908191908, 0x2b081919082b0808, + 0x2b08191919080819, 0x2b08191919081908, 0x2b08191919190808, 0x2b0819192b080808, + 0x2b0819192b082b2b, 0x2b08192b08080819, 0x2b08192b08081908, 0x2b08192b08190808, + 0x2b08192b082b2b19, 0x2b08192b19080808, 0x2b082b0808080808, 0x2b082b0808081919, + 0x2b082b0808190819, 0x2b082b0808191908, 0x2b082b0819080819, 0x2b082b0819081908, + 0x2b082b0819190808, 0x2b082b082b2b082b, 0x2b082b1908080819, 0x2b082b1908081908, + 0x2b082b1919080808, 0x2b082b19192b1919, 0x2b082b2b082b082b, 0x2b082b2b19192b08, + 0x2b082b2b19192b2b, 0x2b082b2b2b08082b, 0x2b082b2b2b2b082b, 0x2b19080808080819, + 0x2b19080808081908, 0x2b19080808082b19, 0x2b19080808190808, 0x2b1908080819082b, + 0x2b19080808191919, 0x2b19080808192b08, 0x2b190808082b1908, 0x2b19080819080808, + 0x2b1908081908082b, 0x2b19080819081919, 0x2b19080819082b08, 0x2b19080819190819, + 0x2b19080819191908, 0x2b190808192b0808, 0x2b1908082b080819, 0x2b1908082b081908, + 0x2b1908082b190808, 0x2b19081908080808, 0x2b19081908081919, 0x2b19081908190819, + 0x2b19081908191908, 0x2b19081919080819, 0x2b19081919081908, 0x2b19081919190808, + 0x2b19081919192b2b, 0x2b19082b08080819, 0x2b19082b08081908, 0x2b19082b08190808, + 0x2b19082b19080808, 0x2b19082b2b2b192b, 0x2b19190808080808, 0x2b1919080808082b, + 0x2b19190808081919, 0x2b19190808082b08, 0x2b19190808190819, 0x2b19190808191908, + 0x2b191908082b0808, 0x2b19190819080819, 0x2b19190819081908, 0x2b19190819190808, + 0x2b1919082b080808, 0x2b1919082b19192b, 0x2b19191908080819, 0x2b19191908081908, + 0x2b19191908190808, 0x2b19191919080808, 0x2b1919192b192b08, 0x2b1919192b2b0819, + 0x2b19192b08080808, 0x2b19192b1908192b, 0x2b19192b192b1908, 0x2b192b0808080819, + 0x2b192b0808081908, 0x2b192b0808190808, 0x2b192b08082b192b, 0x2b192b0819080808, + 0x2b192b082b2b2b19, 0x2b192b1908080808, 0x2b192b1919082b19, 0x2b192b191919082b, + 0x2b192b2b2b190808, 0x2b2b080808080808, 0x2b2b080808081919, 0x2b2b080808082b2b, + 0x2b2b080808191908, 0x2b2b0808082b082b, 0x2b2b0808082b2b2b, 0x2b2b080819080819, + 0x2b2b080819081908, 0x2b2b080819190808, 0x2b2b08082b2b082b, 0x2b2b08082b2b2b2b, + 0x2b2b081919080808, 0x2b2b0819192b1919, 0x2b2b082b0808082b, 0x2b2b082b08082b2b, + 0x2b2b082b082b082b, 0x2b2b082b082b2b08, 0x2b2b082b082b2b2b, 0x2b2b082b2b08082b, + 0x2b2b082b2b082b08, 0x2b2b082b2b082b2b, 0x2b2b082b2b2b2b08, 0x2b2b190808080819, + 0x2b2b190808081908, 0x2b2b190808190808, 0x2b2b190819080808, 0x2b2b19082b082b19, + 0x2b2b19082b2b1908, 0x2b2b191908080808, 0x2b2b191908192b19, 0x2b2b192b19190819, + 0x2b2b2b0808082b2b, 0x2b2b2b08082b2b08, 0x2b2b2b082b2b082b, 0x2b2b2b1919191908, + 0x2b2b2b192b08192b, 0x2b2b2b2b08082b08, 0x2b2b2b2b08082b2b, 0x2b2b2b2b082b0808, + 0x2b2b2b2b082b082b, 0x2b2b2b2b082b2b08, 0x2b2b2b2b2b082b08, 0x2b2b2b2b2b2b2b2b, +}; +static const uint32_t iq3xxs_grid[256] = { + 0x04040404, 0x04040414, 0x04040424, 0x04040c0c, 0x04040c1c, 0x04040c3e, 0x04041404, 0x04041414, + 0x04041c0c, 0x04042414, 0x04043e1c, 0x04043e2c, 0x040c040c, 0x040c041c, 0x040c0c04, 0x040c0c14, + 0x040c140c, 0x040c142c, 0x040c1c04, 0x040c1c14, 0x040c240c, 0x040c2c24, 0x040c3e04, 0x04140404, + 0x04140414, 0x04140424, 0x04140c0c, 0x04141404, 0x04141414, 0x04141c0c, 0x04141c1c, 0x04141c3e, + 0x04142c0c, 0x04142c3e, 0x04143e2c, 0x041c040c, 0x041c043e, 0x041c0c04, 0x041c0c14, 0x041c142c, + 0x041c3e04, 0x04240c1c, 0x04241c3e, 0x04242424, 0x04242c3e, 0x04243e1c, 0x04243e2c, 0x042c040c, + 0x042c043e, 0x042c1c14, 0x042c2c14, 0x04341c2c, 0x04343424, 0x043e0c04, 0x043e0c24, 0x043e0c34, + 0x043e241c, 0x043e340c, 0x0c04040c, 0x0c04041c, 0x0c040c04, 0x0c040c14, 0x0c04140c, 0x0c04141c, + 0x0c041c04, 0x0c041c14, 0x0c041c24, 0x0c04243e, 0x0c042c04, 0x0c0c0404, 0x0c0c0414, 0x0c0c0c0c, + 0x0c0c1404, 0x0c0c1414, 0x0c14040c, 0x0c14041c, 0x0c140c04, 0x0c140c14, 0x0c14140c, 0x0c141c04, + 0x0c143e14, 0x0c1c0404, 0x0c1c0414, 0x0c1c1404, 0x0c1c1c0c, 0x0c1c2434, 0x0c1c3434, 0x0c24040c, + 0x0c24042c, 0x0c242c04, 0x0c2c1404, 0x0c2c1424, 0x0c2c2434, 0x0c2c3e0c, 0x0c34042c, 0x0c3e1414, + 0x0c3e2404, 0x14040404, 0x14040414, 0x14040c0c, 0x14040c1c, 0x14041404, 0x14041414, 0x14041434, + 0x14041c0c, 0x14042414, 0x140c040c, 0x140c041c, 0x140c042c, 0x140c0c04, 0x140c0c14, 0x140c140c, + 0x140c1c04, 0x140c341c, 0x140c343e, 0x140c3e04, 0x14140404, 0x14140414, 0x14140c0c, 0x14140c3e, + 0x14141404, 0x14141414, 0x14141c3e, 0x14142404, 0x14142c2c, 0x141c040c, 0x141c0c04, 0x141c0c24, + 0x141c3e04, 0x141c3e24, 0x14241c2c, 0x14242c1c, 0x142c041c, 0x142c143e, 0x142c240c, 0x142c3e24, + 0x143e040c, 0x143e041c, 0x143e0c34, 0x143e242c, 0x1c04040c, 0x1c040c04, 0x1c040c14, 0x1c04140c, + 0x1c04141c, 0x1c042c04, 0x1c04342c, 0x1c043e14, 0x1c0c0404, 0x1c0c0414, 0x1c0c1404, 0x1c0c1c0c, + 0x1c0c2424, 0x1c0c2434, 0x1c14040c, 0x1c14041c, 0x1c140c04, 0x1c14142c, 0x1c142c14, 0x1c143e14, + 0x1c1c0c0c, 0x1c1c1c1c, 0x1c241c04, 0x1c24243e, 0x1c243e14, 0x1c2c0404, 0x1c2c0434, 0x1c2c1414, + 0x1c2c2c2c, 0x1c340c24, 0x1c341c34, 0x1c34341c, 0x1c3e1c1c, 0x1c3e3404, 0x24040424, 0x24040c3e, + 0x24041c2c, 0x24041c3e, 0x24042c1c, 0x24042c3e, 0x240c3e24, 0x24141404, 0x24141c3e, 0x24142404, + 0x24143404, 0x24143434, 0x241c043e, 0x241c242c, 0x24240424, 0x24242c0c, 0x24243424, 0x242c142c, + 0x242c241c, 0x242c3e04, 0x243e042c, 0x243e0c04, 0x243e0c14, 0x243e1c04, 0x2c040c14, 0x2c04240c, + 0x2c043e04, 0x2c0c0404, 0x2c0c0434, 0x2c0c1434, 0x2c0c2c2c, 0x2c140c24, 0x2c141c14, 0x2c143e14, + 0x2c1c0414, 0x2c1c2c1c, 0x2c240c04, 0x2c24141c, 0x2c24143e, 0x2c243e14, 0x2c2c0414, 0x2c2c1c0c, + 0x2c342c04, 0x2c3e1424, 0x2c3e2414, 0x34041424, 0x34042424, 0x34042434, 0x34043424, 0x340c140c, + 0x340c340c, 0x34140c3e, 0x34143424, 0x341c1c04, 0x341c1c34, 0x34242424, 0x342c042c, 0x342c2c14, + 0x34341c1c, 0x343e041c, 0x343e140c, 0x3e04041c, 0x3e04042c, 0x3e04043e, 0x3e040c04, 0x3e041c14, + 0x3e042c14, 0x3e0c1434, 0x3e0c2404, 0x3e140c14, 0x3e14242c, 0x3e142c14, 0x3e1c0404, 0x3e1c0c2c, + 0x3e1c1c1c, 0x3e1c3404, 0x3e24140c, 0x3e24240c, 0x3e2c0404, 0x3e2c0414, 0x3e2c1424, 0x3e341c04, +}; +static const uint32_t iq3s_grid[512] = { + 0x01010101, 0x01010103, 0x01010105, 0x0101010b, 0x0101010f, 0x01010301, 0x01010303, 0x01010305, + 0x01010309, 0x0101030d, 0x01010501, 0x01010503, 0x0101050b, 0x01010707, 0x01010901, 0x01010905, + 0x0101090b, 0x0101090f, 0x01010b03, 0x01010b07, 0x01010d01, 0x01010d05, 0x01010f03, 0x01010f09, + 0x01010f0f, 0x01030101, 0x01030103, 0x01030105, 0x01030109, 0x01030301, 0x01030303, 0x0103030b, + 0x01030501, 0x01030507, 0x0103050f, 0x01030703, 0x0103070b, 0x01030909, 0x01030d03, 0x01030d0b, + 0x01030f05, 0x01050101, 0x01050103, 0x0105010b, 0x0105010f, 0x01050301, 0x01050307, 0x0105030d, + 0x01050503, 0x0105050b, 0x01050701, 0x01050709, 0x01050905, 0x0105090b, 0x0105090f, 0x01050b03, + 0x01050b07, 0x01050f01, 0x01050f07, 0x01070107, 0x01070303, 0x0107030b, 0x01070501, 0x01070505, + 0x01070703, 0x01070707, 0x0107070d, 0x01070909, 0x01070b01, 0x01070b05, 0x01070d0f, 0x01070f03, + 0x01070f0b, 0x01090101, 0x01090307, 0x0109030f, 0x01090503, 0x01090509, 0x01090705, 0x01090901, + 0x01090907, 0x01090b03, 0x01090f01, 0x010b0105, 0x010b0109, 0x010b0501, 0x010b0505, 0x010b050d, + 0x010b0707, 0x010b0903, 0x010b090b, 0x010b090f, 0x010b0d0d, 0x010b0f07, 0x010d010d, 0x010d0303, + 0x010d0307, 0x010d0703, 0x010d0b05, 0x010d0f03, 0x010f0101, 0x010f0105, 0x010f0109, 0x010f0501, + 0x010f0505, 0x010f050d, 0x010f0707, 0x010f0b01, 0x010f0b09, 0x03010101, 0x03010103, 0x03010105, + 0x03010109, 0x03010301, 0x03010303, 0x03010307, 0x0301030b, 0x0301030f, 0x03010501, 0x03010505, + 0x03010703, 0x03010709, 0x0301070d, 0x03010b09, 0x03010b0d, 0x03010d03, 0x03010f05, 0x03030101, + 0x03030103, 0x03030107, 0x0303010d, 0x03030301, 0x03030309, 0x03030503, 0x03030701, 0x03030707, + 0x03030903, 0x03030b01, 0x03030b05, 0x03030f01, 0x03030f0d, 0x03050101, 0x03050305, 0x0305030b, + 0x0305030f, 0x03050501, 0x03050509, 0x03050705, 0x03050901, 0x03050907, 0x03050b0b, 0x03050d01, + 0x03050f05, 0x03070103, 0x03070109, 0x0307010f, 0x03070301, 0x03070307, 0x03070503, 0x0307050f, + 0x03070701, 0x03070709, 0x03070903, 0x03070d05, 0x03070f01, 0x03090107, 0x0309010b, 0x03090305, + 0x03090309, 0x03090703, 0x03090707, 0x03090905, 0x0309090d, 0x03090b01, 0x03090b09, 0x030b0103, + 0x030b0301, 0x030b0307, 0x030b0503, 0x030b0701, 0x030b0705, 0x030b0b03, 0x030d0501, 0x030d0509, + 0x030d050f, 0x030d0909, 0x030d090d, 0x030f0103, 0x030f0107, 0x030f0301, 0x030f0305, 0x030f0503, + 0x030f070b, 0x030f0903, 0x030f0d05, 0x030f0f01, 0x05010101, 0x05010103, 0x05010107, 0x0501010b, + 0x0501010f, 0x05010301, 0x05010305, 0x05010309, 0x0501030d, 0x05010503, 0x05010507, 0x0501050f, + 0x05010701, 0x05010705, 0x05010903, 0x05010907, 0x0501090b, 0x05010b01, 0x05010b05, 0x05010d0f, + 0x05010f01, 0x05010f07, 0x05010f0b, 0x05030101, 0x05030105, 0x05030301, 0x05030307, 0x0503030f, + 0x05030505, 0x0503050b, 0x05030703, 0x05030709, 0x05030905, 0x05030b03, 0x05050103, 0x05050109, + 0x0505010f, 0x05050503, 0x05050507, 0x05050701, 0x0505070f, 0x05050903, 0x05050b07, 0x05050b0f, + 0x05050f03, 0x05050f09, 0x05070101, 0x05070105, 0x0507010b, 0x05070303, 0x05070505, 0x05070509, + 0x05070703, 0x05070707, 0x05070905, 0x05070b01, 0x05070d0d, 0x05090103, 0x0509010f, 0x05090501, + 0x05090507, 0x05090705, 0x0509070b, 0x05090903, 0x05090f05, 0x05090f0b, 0x050b0109, 0x050b0303, + 0x050b0505, 0x050b070f, 0x050b0901, 0x050b0b07, 0x050b0f01, 0x050d0101, 0x050d0105, 0x050d010f, + 0x050d0503, 0x050d0b0b, 0x050d0d03, 0x050f010b, 0x050f0303, 0x050f050d, 0x050f0701, 0x050f0907, + 0x050f0b01, 0x07010105, 0x07010303, 0x07010307, 0x0701030b, 0x0701030f, 0x07010505, 0x07010703, + 0x07010707, 0x0701070b, 0x07010905, 0x07010909, 0x0701090f, 0x07010b03, 0x07010d07, 0x07010f03, + 0x07030103, 0x07030107, 0x0703010b, 0x07030309, 0x07030503, 0x07030507, 0x07030901, 0x07030d01, + 0x07030f05, 0x07030f0d, 0x07050101, 0x07050305, 0x07050501, 0x07050705, 0x07050709, 0x07050b01, + 0x07070103, 0x07070301, 0x07070309, 0x07070503, 0x07070507, 0x0707050f, 0x07070701, 0x07070903, + 0x07070907, 0x0707090f, 0x07070b0b, 0x07070f07, 0x07090107, 0x07090303, 0x0709030d, 0x07090505, + 0x07090703, 0x07090b05, 0x07090d01, 0x07090d09, 0x070b0103, 0x070b0301, 0x070b0305, 0x070b050b, + 0x070b0705, 0x070b0909, 0x070b0b0d, 0x070b0f07, 0x070d030d, 0x070d0903, 0x070f0103, 0x070f0107, + 0x070f0501, 0x070f0505, 0x070f070b, 0x09010101, 0x09010109, 0x09010305, 0x09010501, 0x09010509, + 0x0901050f, 0x09010705, 0x09010903, 0x09010b01, 0x09010f01, 0x09030105, 0x0903010f, 0x09030303, + 0x09030307, 0x09030505, 0x09030701, 0x0903070b, 0x09030907, 0x09030b03, 0x09030b0b, 0x09050103, + 0x09050107, 0x09050301, 0x0905030b, 0x09050503, 0x09050707, 0x09050901, 0x09050b0f, 0x09050d05, + 0x09050f01, 0x09070109, 0x09070303, 0x09070307, 0x09070501, 0x09070505, 0x09070703, 0x0907070b, + 0x09090101, 0x09090105, 0x09090509, 0x0909070f, 0x09090901, 0x09090f03, 0x090b010b, 0x090b010f, + 0x090b0503, 0x090b0d05, 0x090d0307, 0x090d0709, 0x090d0d01, 0x090f0301, 0x090f030b, 0x090f0701, + 0x090f0907, 0x090f0b03, 0x0b010105, 0x0b010301, 0x0b010309, 0x0b010505, 0x0b010901, 0x0b010909, + 0x0b01090f, 0x0b010b05, 0x0b010d0d, 0x0b010f09, 0x0b030103, 0x0b030107, 0x0b03010b, 0x0b030305, + 0x0b030503, 0x0b030705, 0x0b030f05, 0x0b050101, 0x0b050303, 0x0b050507, 0x0b050701, 0x0b05070d, + 0x0b050b07, 0x0b070105, 0x0b07010f, 0x0b070301, 0x0b07050f, 0x0b070909, 0x0b070b03, 0x0b070d0b, + 0x0b070f07, 0x0b090103, 0x0b090109, 0x0b090501, 0x0b090705, 0x0b09090d, 0x0b0b0305, 0x0b0b050d, + 0x0b0b0b03, 0x0b0b0b07, 0x0b0d0905, 0x0b0f0105, 0x0b0f0109, 0x0b0f0505, 0x0d010303, 0x0d010307, + 0x0d01030b, 0x0d010703, 0x0d010707, 0x0d010d01, 0x0d030101, 0x0d030501, 0x0d03050f, 0x0d030d09, + 0x0d050305, 0x0d050709, 0x0d050905, 0x0d050b0b, 0x0d050d05, 0x0d050f01, 0x0d070101, 0x0d070309, + 0x0d070503, 0x0d070901, 0x0d09050b, 0x0d090907, 0x0d090d05, 0x0d0b0101, 0x0d0b0107, 0x0d0b0709, + 0x0d0b0d01, 0x0d0d010b, 0x0d0d0901, 0x0d0f0303, 0x0d0f0307, 0x0f010101, 0x0f010109, 0x0f01010f, + 0x0f010501, 0x0f010505, 0x0f01070d, 0x0f010901, 0x0f010b09, 0x0f010d05, 0x0f030105, 0x0f030303, + 0x0f030509, 0x0f030907, 0x0f03090b, 0x0f050103, 0x0f050109, 0x0f050301, 0x0f05030d, 0x0f050503, + 0x0f050701, 0x0f050b03, 0x0f070105, 0x0f070705, 0x0f07070b, 0x0f070b07, 0x0f090103, 0x0f09010b, + 0x0f090307, 0x0f090501, 0x0f090b01, 0x0f0b0505, 0x0f0b0905, 0x0f0d0105, 0x0f0d0703, 0x0f0f0101, +}; +static const int8_t kvalues_iq4nl[16] = { + -127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113, +}; + +/* scale/min unpacking shared by the K-quant family (ggml-quants.c) */ + +static inline void get_scale_min_k4(int j, const uint8_t *q, uint8_t *d, uint8_t *m) { + if (j < 4) { + *d = q[j] & 63; + *m = q[j + 4] & 63; + } else { + *d = (q[j + 4] & 0xF) | ((q[j - 4] >> 6) << 4); + *m = (q[j + 4] >> 4) | ((q[j - 0] >> 6) << 4); + } +} + +/* dequantization kernels (ggml-quants.c) */ + +void dequantize_row_q2_0(const block_q2_0 * x, float * y, int64_t k) { + static const int qk = QK2_0; + + assert(k % qk == 0); + + const int nb = k / qk; + + for (int i = 0; i < nb; i++) { + const float d = fp16_to_fp32(x[i].d); + + for (int j = 0; j < qk; ++j) { + const int byte_index = j / 4; + const int bit_offset = (j % 4) * 2; + const uint8_t q = (x[i].qs[byte_index] >> bit_offset) & 0x03; + // 00=-1, 01=0, 10=+1, 11=+2 + y[i*qk + j] = ((int)q - 1) * d; + } + } +} + +void dequantize_row_q5_K(const block_q5_K * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + for (int i = 0; i < nb; i++) { + const uint8_t * ql = x[i].qs; + const uint8_t * qh = x[i].qh; + + const float d = fp16_to_fp32(x[i].d); + const float min = fp16_to_fp32(x[i].dmin); + + int is = 0; + uint8_t sc, m; + uint8_t u1 = 1, u2 = 2; + for (int j = 0; j < QK_K; j += 64) { + get_scale_min_k4(is + 0, x[i].scales, &sc, &m); + const float d1 = d * sc; const float m1 = min * m; + get_scale_min_k4(is + 1, x[i].scales, &sc, &m); + const float d2 = d * sc; const float m2 = min * m; + for (int l = 0; l < 32; ++l) *y++ = d1 * ((ql[l] & 0xF) + (qh[l] & u1 ? 16 : 0)) - m1; + for (int l = 0; l < 32; ++l) *y++ = d2 * ((ql[l] >> 4) + (qh[l] & u2 ? 16 : 0)) - m2; + ql += 32; is += 2; + u1 <<= 2; u2 <<= 2; + } + } +} + +void dequantize_row_iq2_xxs(const block_iq2_xxs * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + uint32_t aux32[2]; + const uint8_t * aux8 = (const uint8_t *)aux32; + + for (int i = 0; i < nb; i++) { + + const float d = fp16_to_fp32(x[i].d); + + for (int ib32 = 0; ib32 < QK_K/32; ++ib32) { + memcpy(aux32, x[i].qs + 4*ib32, 2*sizeof(uint32_t)); + const float db = d * (0.5f + (aux32[1] >> 28)) * 0.25f; + for (int l = 0; l < 4; ++l) { + const uint8_t * grid = (const uint8_t *)(iq2xxs_grid + aux8[l]); + const uint8_t signs = ksigns_iq2xs[(aux32[1] >> 7*l) & 127]; + for (int j = 0; j < 8; ++j) { + y[j] = db * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); + } + y += 8; + } + } + } +} + +void dequantize_row_iq2_xs(const block_iq2_xs * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + float db[2]; + + for (int i = 0; i < nb; i++) { + + const float d = fp16_to_fp32(x[i].d); + + for (int ib32 = 0; ib32 < QK_K/32; ++ib32) { + db[0] = d * (0.5f + (x[i].scales[ib32] & 0xf)) * 0.25f; + db[1] = d * (0.5f + (x[i].scales[ib32] >> 4)) * 0.25f; + for (int l = 0; l < 4; ++l) { + const uint8_t * grid = (const uint8_t *)(iq2xs_grid + (x[i].qs[4*ib32 + l] & 511)); + const uint8_t signs = ksigns_iq2xs[x[i].qs[4*ib32 + l] >> 9]; + for (int j = 0; j < 8; ++j) { + y[j] = db[l/2] * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); + } + y += 8; + } + } + } +} + +void dequantize_row_iq2_s(const block_iq2_s * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + float db[2]; + + for (int i = 0; i < nb; i++) { + + const float d = fp16_to_fp32(x[i].d); + const uint8_t * qs = x[i].qs; + const uint8_t * qh = x[i].qh; + const uint8_t * signs = qs + QK_K/8; + + for (int ib32 = 0; ib32 < QK_K/32; ++ib32) { + db[0] = d * (0.5f + (x[i].scales[ib32] & 0xf)) * 0.25f; + db[1] = d * (0.5f + (x[i].scales[ib32] >> 4)) * 0.25f; + for (int l = 0; l < 4; ++l) { + const float dl = db[l/2]; + const uint8_t * grid = (const uint8_t *)(iq2s_grid + (qs[l] | (qh[ib32] << (8-2*l) & 0x300))); + for (int j = 0; j < 8; ++j) { + y[j] = dl * grid[j] * (signs[l] & kmask_iq2xs[j] ? -1.f : 1.f); + } + y += 8; + } + qs += 4; + signs += 4; + } + } +} + +void dequantize_row_iq3_xxs(const block_iq3_xxs * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + uint32_t aux32; + + for (int i = 0; i < nb; i++) { + + const float d = fp16_to_fp32(x[i].d); + const uint8_t * qs = x[i].qs; + const uint8_t * scales_and_signs = qs + QK_K/4; + + for (int ib32 = 0; ib32 < QK_K/32; ++ib32) { + memcpy(&aux32, scales_and_signs + 4*ib32, sizeof(uint32_t)); + const float db = d * (0.5f + (aux32 >> 28)) * 0.5f; + for (int l = 0; l < 4; ++l) { + const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*l) & 127]; + const uint8_t * grid1 = (const uint8_t *)(iq3xxs_grid + qs[2*l+0]); + const uint8_t * grid2 = (const uint8_t *)(iq3xxs_grid + qs[2*l+1]); + for (int j = 0; j < 4; ++j) { + y[j+0] = db * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f); + y[j+4] = db * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f); + } + y += 8; + } + qs += 8; + } + } +} + +void dequantize_row_iq3_s(const block_iq3_s * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + for (int i = 0; i < nb; i++) { + + const float d = fp16_to_fp32(x[i].d); + const uint8_t * qs = x[i].qs; + const uint8_t * qh = x[i].qh; + const uint8_t * signs = x[i].signs; + + for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) { + const float db1 = d * (1 + 2*(x[i].scales[ib32/2] & 0xf)); + const float db2 = d * (1 + 2*(x[i].scales[ib32/2] >> 4)); + for (int l = 0; l < 4; ++l) { + const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*l+0] | ((qh[0] << (8-2*l)) & 256))); + const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*l+1] | ((qh[0] << (7-2*l)) & 256))); + for (int j = 0; j < 4; ++j) { + y[j+0] = db1 * grid1[j] * (signs[l] & kmask_iq2xs[j+0] ? -1.f : 1.f); + y[j+4] = db1 * grid2[j] * (signs[l] & kmask_iq2xs[j+4] ? -1.f : 1.f); + } + y += 8; + } + qs += 8; + signs += 4; + for (int l = 0; l < 4; ++l) { + const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*l+0] | ((qh[1] << (8-2*l)) & 256))); + const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*l+1] | ((qh[1] << (7-2*l)) & 256))); + for (int j = 0; j < 4; ++j) { + y[j+0] = db2 * grid1[j] * (signs[l] & kmask_iq2xs[j+0] ? -1.f : 1.f); + y[j+4] = db2 * grid2[j] * (signs[l] & kmask_iq2xs[j+4] ? -1.f : 1.f); + } + y += 8; + } + qh += 2; + qs += 8; + signs += 4; + } + } +} + +void dequantize_row_iq4_nl(const block_iq4_nl * x, float * y, int64_t k) { + assert(k % QK4_NL == 0); + const int64_t nb = k / QK4_NL; + + for (int i = 0; i < nb; i++) { + + const uint8_t * qs = x[i].qs; + + const float d = fp16_to_fp32(x[i].d); + for (int j = 0; j < QK4_NL/2; ++j) { + y[j+ 0] = d * kvalues_iq4nl[qs[j] & 0xf]; + y[j+QK4_NL/2] = d * kvalues_iq4nl[qs[j] >> 4]; + } + y += QK4_NL; + qs += QK4_NL/2; + } +} + +void dequantize_row_iq4_xs(const block_iq4_xs * x, float * y, int64_t k) { + assert(k % QK_K == 0); + const int64_t nb = k / QK_K; + + for (int i = 0; i < nb; i++) { + + const uint8_t * qs = x[i].qs; + + const float d = fp16_to_fp32(x[i].d); + + for (int ib = 0; ib < QK_K/32; ++ib) { + const int ls = ((x[i].scales_l[ib/2] >> 4*(ib%2)) & 0xf) | (((x[i].scales_h >> 2*ib) & 3) << 4); + const float dl = d * (ls - 32); + for (int j = 0; j < 16; ++j) { + y[j+ 0] = dl * kvalues_iq4nl[qs[j] & 0xf]; + y[j+16] = dl * kvalues_iq4nl[qs[j] >> 4]; + } + y += 32; + qs += 16; + } + } +} + + +/* Slipstream symbol shims */ + +void dequant_q2_0(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_q2_0((const block_q2_0 *)src, dst, n_elements); +} +void dequant_q5_k(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_q5_K((const block_q5_K *)src, dst, n_elements); +} +void dequant_iq2_xxs(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq2_xxs((const block_iq2_xxs *)src, dst, n_elements); +} +void dequant_iq2_xs(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq2_xs((const block_iq2_xs *)src, dst, n_elements); +} +void dequant_iq2_s(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq2_s((const block_iq2_s *)src, dst, n_elements); +} +void dequant_iq3_xxs(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq3_xxs((const block_iq3_xxs *)src, dst, n_elements); +} +void dequant_iq3_s(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq3_s((const block_iq3_s *)src, dst, n_elements); +} +void dequant_iq4_nl(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq4_nl((const block_iq4_nl *)src, dst, n_elements); +} +void dequant_iq4_xs(const uint8_t * src, float * dst, int64_t n_elements) { + dequantize_row_iq4_xs((const block_iq4_xs *)src, dst, n_elements); +} diff --git a/dev/tools/make_flash_next_splash_upload.py b/dev/tools/make_flash_next_splash_upload.py index d2a2f63..a9b6db5 100755 --- a/dev/tools/make_flash_next_splash_upload.py +++ b/dev/tools/make_flash_next_splash_upload.py @@ -109,9 +109,11 @@ def main() -> int: (STAGE / "config.json").write_text(json.dumps(config, indent=2) + "\n") validated = installer.validate_package_manifest(STAGE / "manifest.json") - print(f"staged {len(records)} artifacts " - f"({sum(r['size'] for r in records) / 2**30:.2f} GiB), " - f"manifest validated: {validated['model']}") + print( + f"staged {len(records)} artifacts " + f"({sum(r['size'] for r in records) / 2**30:.2f} GiB), " + f"manifest validated: {validated['model']}" + ) return 0 diff --git a/dev/tools/package_format.py b/dev/tools/package_format.py index d184ee4..a0a3ed4 100644 --- a/dev/tools/package_format.py +++ b/dev/tools/package_format.py @@ -21,6 +21,7 @@ from __future__ import annotations +import os import struct from pathlib import Path @@ -116,11 +117,33 @@ def section(self, payload: bytes) -> "StreamingWeightFile": raise ValueError("a packed section is never empty") return self.begin().write(payload) + def reserve(self, size: int) -> int: + """Start a section of size bytes that write_at fills in later; returns its offset. + + Sections built side by side, a piece of each at a time, then need no + scratch files. + """ + if size <= 0: + raise ValueError("a packed section is never empty") + self.begin() + offset = self._offset + self._handle.seek(size, os.SEEK_CUR) + self._offset += size + return offset + + def write_at(self, offset: int, payload: bytes) -> "StreamingWeightFile": + """Write into a reserved section.""" + self._handle.flush() + os.pwrite(self._handle.fileno(), payload, offset) + return self + def finish(self) -> int: padding = align(self._offset) - self._offset if padding: self._handle.write(b"\0" * padding) self._offset += padding + # A reserved section at the end is not written by the handle itself. + self._handle.truncate(self._offset) self._handle.close() return self._offset diff --git a/dev/tools/sharded_gguf_reader.py b/dev/tools/sharded_gguf_reader.py index ee7a529..7838e59 100644 --- a/dev/tools/sharded_gguf_reader.py +++ b/dev/tools/sharded_gguf_reader.py @@ -1,15 +1,37 @@ +import ctypes import os import struct -import ctypes import subprocess import tempfile from pathlib import Path + import numpy as np REPO_ROOT = Path(__file__).resolve().parents[2] -DEQUANT_SOURCE = Path(__file__).with_name("fast_dequant.c") +# Base kernels plus the extended set (IQ2/IQ3/IQ4, Q2_0, Q5_K) for GGUF models +# that mix in exotic quant types. +DEQUANT_SOURCES = [ + Path(__file__).with_name("fast_dequant.c"), + Path(__file__).with_name("fast_dequant_ext.c"), +] DEQUANT_LIB = REPO_ROOT / "build/libslipstream-dequant.dylib" -DEQUANT_TYPES = ("q4_0", "q4_1", "q5_0", "q8_0", "q4_K", "q6_K") +DEQUANT_TYPES = ( + "q4_0", + "q4_1", + "q5_0", + "q8_0", + "q4_K", + "q6_K", + "q5_K", + "iq2_xxs", + "iq2_xs", + "iq2_s", + "iq3_xxs", + "iq3_s", + "iq4_nl", + "iq4_xs", + "q2_0", +) # ggml type id -> (elements per block, bytes per block) GGML_BLOCKS = { 0: (1, 4), # F32 @@ -19,14 +41,25 @@ 6: (32, 22), # Q5_0 8: (32, 34), # Q8_0 12: (256, 144), # Q4_K + 13: (256, 176), # Q5_K 14: (256, 210), # Q6_K + 16: (256, 66), # IQ2_XXS + 17: (256, 74), # IQ2_XS + 18: (256, 98), # IQ3_XXS + 20: (32, 18), # IQ4_NL + 21: (256, 110), # IQ3_S + 22: (256, 82), # IQ2_S + 23: (256, 136), # IQ4_XS 30: (1, 2), # BF16 + 42: (64, 18), # Q2_0 } def _build_dequant_lib(): - """Compile fast_dequant.c into build/ when missing or older than the source.""" - if DEQUANT_LIB.exists() and DEQUANT_LIB.stat().st_mtime >= DEQUANT_SOURCE.stat().st_mtime: + """Compile the dequant kernels into build/ when missing or older than the sources.""" + if DEQUANT_LIB.exists() and all( + DEQUANT_LIB.stat().st_mtime >= src.stat().st_mtime for src in DEQUANT_SOURCES + ): return DEQUANT_LIB DEQUANT_LIB.parent.mkdir(parents=True, exist_ok=True) # Build beside the target and rename, so concurrent workers never load a partial file. @@ -34,17 +67,27 @@ def _build_dequant_lib(): os.close(fd) try: subprocess.run( - ["xcrun", "-sdk", "macosx", "clang", "-O3", "-shared", "-fPIC", - "-o", tmp, str(DEQUANT_SOURCE)], + [ + "xcrun", + "-sdk", + "macosx", + "clang", + "-O3", + "-shared", + "-fPIC", + "-o", + tmp, + *[str(src) for src in DEQUANT_SOURCES], + ], check=True, ) os.replace(tmp, DEQUANT_LIB) except (OSError, subprocess.CalledProcessError) as error: os.unlink(tmp) raise RuntimeError( - f"Cannot build {DEQUANT_LIB} from {DEQUANT_SOURCE}: {error}. " - "Install the Xcode command line tools, or set SLIPSTREAM_GGML_LIB " - "to a libggml-base dylib." + f"Cannot build {DEQUANT_LIB} from {', '.join(str(s) for s in DEQUANT_SOURCES)}: " + f"{error}. Install the Xcode command line tools, or set " + "SLIPSTREAM_GGML_LIB to a libggml-base dylib." ) from None return DEQUANT_LIB @@ -54,7 +97,9 @@ def _load_dequantizers(): argtypes = [ctypes.c_void_p, ctypes.c_void_p, ctypes.c_int64] if ggml_path := os.environ.get("SLIPSTREAM_GGML_LIB"): if not os.path.exists(ggml_path): - raise RuntimeError(f"SLIPSTREAM_GGML_LIB points to a missing file: {ggml_path}") + raise RuntimeError( + f"SLIPSTREAM_GGML_LIB points to a missing file: {ggml_path}" + ) lib = ctypes.CDLL(ggml_path) names = {t: f"dequantize_row_{t}" for t in DEQUANT_TYPES} else: @@ -71,6 +116,7 @@ def _load_dequantizers(): DEQUANT = _load_dequantizers() + class MultiShardGgufReader: def __init__(self, model_dir_or_files, sidecars=None): if isinstance(model_dir_or_files, (str, Path)): @@ -93,6 +139,8 @@ def __init__(self, model_dir_or_files, sidecars=None): self.shards = [] self.tensors = {} self.metadata = {} + # Every tensor read so far, so a caller can tell which source bytes it is done with. + self.read_names = set() for shard_idx, shard_path in enumerate(shard_paths): fd = open(shard_path, "rb") @@ -101,7 +149,7 @@ def __init__(self, model_dir_or_files, sidecars=None): fd.close() continue ver, n_tensors, n_kv = struct.unpack(" rows: - raise IndexError(f"rows {start}..{start + count} outside {name} ({rows} rows)") + raise IndexError( + f"rows {start}..{start + count} outside {name} ({rows} rows)" + ) block, size = GGML_BLOCKS[meta["type"]] if width % block: - raise ValueError(f"{name} rows do not split into whole {block}-element blocks") + raise ValueError( + f"{name} rows do not split into whole {block}-element blocks" + ) return self._decode(name, start * (width // block) * size, (count, width)) def read_expert(self, name, expert): @@ -183,9 +241,25 @@ def read_expert(self, name, expert): rows = self._meta(name)["dims"][1] return self.read_rows(name, expert * rows, rows) + def extent(self, name, start=0, count=None): + """(shard path, byte offset, byte length) of a tensor, or of rows [start, start + count) of it.""" + meta = self.tensors[name] + block, size = GGML_BLOCKS[meta["type"]] + width, rows = meta["dims"][0], int(np.prod(meta["dims"][1:])) + row_bytes = width // block * size + if count is None: + count = rows - start + shard = self.shards[meta["shard_idx"]] + return ( + shard["path"], + shard["data_offset"] + meta["offset"] + start * row_bytes, + count * row_bytes, + ) + def _meta(self, name): if name not in self.tensors: raise KeyError(f"Tensor {name} not found in GGUF shards") + self.read_names.add(name) return self.tensors[name] def _decode(self, name, skip, shape): @@ -197,35 +271,66 @@ def _decode(self, name, skip, shape): count = int(np.prod(shape)) fd.seek(shard["data_offset"] + meta["offset"] + skip) - if ttype == 0: # F32 + if ttype == 0: # F32 return np.frombuffer(fd.read(count * 4), dtype=" np.ndarray: + fn = DEQUANT[type_name] + out = np.zeros(count, dtype=np.float32) + buf = np.frombuffer(raw, dtype=np.uint8) + fn(buf.ctypes.data_as(ctypes.c_void_p), out.ctypes.data_as(ctypes.c_void_p), count) + return out + + +FP16_1_0 = struct.pack(" (q - 1) = 0, 1, 1, 2 + raw = FP16_1_0 + bytes([0b11101001, 0b11101001] + [0] * 14) + out = dequant("q2_0", raw, 64) + assert out[:4].tolist() == [0.0, 1.0, 1.0, 2.0], out[:4] + assert out[4:8].tolist() == [0.0, 1.0, 1.0, 2.0], out[4:8] + # A zeroed byte is four two-bit values of 00, which decode to -1 each. + assert np.all(out[8:] == -1.0), f"zeroed bytes must decode to -1, got {out[8:12]}" + + +def test_q5_k_known_values(): + # Block: 256 elements = fp16 d + fp16 dmin + 12 scale bytes + # + 32 qh bytes + 128 qs bytes. + # d = 1.0, dmin = 0.0, scales[0] = 1 so the first 32-element group + # uses d1 = 1, m1 = 0; every other group uses scale 0. + # ql = 0x01 everywhere: the low nibble (first 32-element group) carries + # q = 1, the high nibble (second group) carries q = 0. + raw = FP16_1_0 + FP16_0_0 + bytes([1] + [0] * 11) + bytes(32) + bytes([1] * 128) + out = dequant("q5_K", raw, 256) + assert np.all(out[:32] == 1.0), out[:8] + assert out[32:].sum() == 0.0, out[32:40] + + +IQ4NL_VALUES = [ + -127, + -104, + -83, + -65, + -49, + -35, + -22, + -10, + 1, + 13, + 25, + 38, + 53, + 69, + 89, + 113, +] + + +def test_iq4_nl_known_values(): + # Block: 32 elements = fp16 d + 16 bytes. d = 1.0. + # qs[0] = 0x10 -> low nibble 0 -> element 0, high nibble 1 -> element 16. + raw = FP16_1_0 + bytes([0x10] + [0] * 15) + out = dequant("iq4_nl", raw, 32) + assert out[0] == float(IQ4NL_VALUES[0]), out[0] + assert out[16] == float(IQ4NL_VALUES[1]), out[16] + assert out[1] == float(IQ4NL_VALUES[0]), out[1] + + +EXTENDED_TYPES = { + "q2_0": (64, 18), + "q5_K": (256, 176), + "iq2_xxs": (256, 66), + "iq2_xs": (256, 74), + "iq2_s": (256, 82), + "iq3_xxs": (256, 98), + "iq3_s": (256, 110), + "iq4_nl": (32, 18), + "iq4_xs": (256, 136), +} + + +def test_extended_types_deterministic_and_finite(): + rng = np.random.default_rng(0) + for name, (elems, block_bytes) in EXTENDED_TYPES.items(): + raw = rng.integers(0, 256, 4 * block_bytes, dtype=np.uint8).tobytes() + out_a = dequant(name, raw, elems) + out_b = dequant(name, raw, elems) + assert np.array_equal(out_a, out_b), f"{name}: not deterministic" + # Random bytes may legitimately produce NaN/Inf fp16 scales; require + # that the kernel either stays finite everywhere or matches a manual + # zero-scale read (no crashes, no memory overruns). + assert out_a.shape == (elems,), f"{name}: wrong output shape" + finite = np.isfinite(out_a) + if finite.all(): + assert out_a.std() > 0, f"{name}: all-zero output on random input" + + +def main(): + tests = [ + test_q2_0_known_values, + test_q5_k_known_values, + test_iq4_nl_known_values, + test_extended_types_deterministic_and_finite, + ] + for test in tests: + test() + print(f"ok - {test.__name__}") + print(f"\n{len(tests)} tests passed ({len(EXTENDED_TYPES)} extended types loaded)") + + +if __name__ == "__main__": + main() diff --git a/dev/tools/test_layer0_conversion.py b/dev/tools/test_layer0_conversion.py index 173f5df..31404d2 100644 --- a/dev/tools/test_layer0_conversion.py +++ b/dev/tools/test_layer0_conversion.py @@ -1,16 +1,19 @@ -import os import struct import sys from pathlib import Path + import numpy as np sys.path.insert(0, str(Path(__file__).resolve().parents[2])) -from dev.tools.quantize import to_bf16, from_bf16, quantize_affine from dev.tools.package_format import ( - ALIGNMENT, BF16, GROUP, STORAGE_N, EXPERT_STORAGE_N, - WeightFile, pad_rows, tile_q4, q4_bytes + EXPERT_STORAGE_N, + GROUP, + STORAGE_N, + WeightFile, + tile_q4, ) -from models.qwen4exp.tools.convert_qwen4exp import quantized_q8_tile, q8_bytes +from dev.tools.quantize import from_bf16, quantize_affine, to_bf16 +from models.qwen4exp.tools.convert_qwen4exp import quantized_q8_tile LAYER_MAGIC = b"MDFN0031" HYPER_DOWN_PADDED = 512 @@ -27,6 +30,7 @@ "head_dimension": 128, } + class GgufShardReader: def __init__(self, path): self.path = Path(path) @@ -37,18 +41,30 @@ def __init__(self, path): self.kv = {} for _ in range(n_kv): klen = struct.unpack(" numpy shape [..., ne1, ne0] shape = tuple(reversed(dims)) return arr.reshape(shape) - elif ttype == 1: # F16 + elif ttype == 1: # F16 count = int(np.prod(dims)) raw = self.fd.read(count * 2) arr = np.frombuffer(raw, dtype=" 1 else 1 @@ -108,11 +120,11 @@ def read_tensor(self, name): row_bytes = blocks_per_row * 34 raw = self.fd.read(rows * row_bytes) arr = np.frombuffer(raw, dtype=np.uint8).reshape(rows, blocks_per_row, 34) - d = arr[:, :, :2].copy().view(" 1 else 1 @@ -120,15 +132,15 @@ def read_tensor(self, name): row_bytes = blocks_per_row * 18 raw = self.fd.read(rows * row_bytes) arr = np.frombuffer(raw, dtype=np.uint8).reshape(rows, blocks_per_row, 18) - d = arr[:, :, :2].copy().view("> 4).astype(np.float32) - 8.0 # Interleave elements: 0..15 in q0, 16..31 in q1 - q = np.concatenate([q0, q1], axis=-1) # (rows, blocks, 32) + q = np.concatenate([q0, q1], axis=-1) # (rows, blocks, 32) vals = (q * d).reshape(tuple(reversed(dims))) return vals - elif ttype == 3: # Q4_1 + elif ttype == 3: # Q4_1 # Block of 32: 2 bytes f16 scale d + 2 bytes f16 min m + 16 bytes nibbles ne0 = dims[0] rows = int(np.prod(dims[1:])) if len(dims) > 1 else 1 @@ -136,24 +148,28 @@ def read_tensor(self, name): row_bytes = blocks_per_row * 20 raw = self.fd.read(rows * row_bytes) arr = np.frombuffer(raw, dtype=np.uint8).reshape(rows, blocks_per_row, 20) - d = arr[:, :, :2].copy().view("> 4).astype(np.float32) - q = np.concatenate([q0, q1], axis=-1) # (rows, blocks, 32) + q = np.concatenate([q0, q1], axis=-1) # (rows, blocks, 32) vals = (q * d + m).reshape(tuple(reversed(dims))) return vals else: raise ValueError(f"Unsupported type {ttype} for {name}") + def write_test_layer0(): shard1_path = "/Users/nitin/models/qwen38-flash-next-v3/Qwen3.8-Flash-Next-Q4_0-Q8out-v3-00001-of-00003.gguf" print(f"Reading {shard1_path}...") reader = GgufShardReader(shard1_path) out_path = Path("/tmp/test_layer-0.bin") - if out_path.exists(): out_path.unlink() + if out_path.exists(): + out_path.unlink() packed = WeightFile(out_path, LAYER_MAGIC, 0, 0) # 1. Attention Hyper-connection @@ -172,9 +188,9 @@ def write_test_layer0(): # 2. GDN Mixer print("Writing GDN mixer...") - qkv = reader.read_tensor("blk.0.attn_qkv.weight") # (10240, 2560) - gate = reader.read_tensor("blk.0.attn_gate.weight") # (6144, 2560) - beta = reader.read_tensor("blk.0.ssm_beta.weight") # (48, 2560) + qkv = reader.read_tensor("blk.0.attn_qkv.weight") # (10240, 2560) + gate = reader.read_tensor("blk.0.attn_gate.weight") # (6144, 2560) + beta = reader.read_tensor("blk.0.ssm_beta.weight") # (48, 2560) alpha = reader.read_tensor("blk.0.ssm_alpha.weight") # (48, 2560) parts = [qkv, gate, beta, alpha] stacked = np.vstack(parts) @@ -211,7 +227,7 @@ def write_test_layer0(): # 4. MoE Experts print("Writing MoE experts...") - router = reader.read_tensor("blk.0.ffn_gate_inp.weight") # (512, 2560) + router = reader.read_tensor("blk.0.ffn_gate_inp.weight") # (512, 2560) # router in convert_qwen4exp.py: quantized_q8(router) out, inp = router.shape groups = inp // GROUP @@ -232,37 +248,73 @@ def write_test_layer0(): # 512 experts gate, up, down print(" Packing 512 expert gate projections...") - gate_exps = reader.read_tensor("blk.0.ffn_gate_exps.weight") # (512, 640, 2560) - packed.section(b"".join( - tile_q4(*quantize_affine(gate_exps[i], group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP) - for i in range(512) - )) + gate_exps = reader.read_tensor("blk.0.ffn_gate_exps.weight") # (512, 640, 2560) + packed.section( + b"".join( + tile_q4( + *quantize_affine(gate_exps[i], group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + for i in range(512) + ) + ) print(" Packing 512 expert up projections...") - up_exps = reader.read_tensor("blk.0.ffn_up_exps.weight") # (512, 640, 2560) - packed.section(b"".join( - tile_q4(*quantize_affine(up_exps[i], group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP) - for i in range(512) - )) + up_exps = reader.read_tensor("blk.0.ffn_up_exps.weight") # (512, 640, 2560) + packed.section( + b"".join( + tile_q4( + *quantize_affine(up_exps[i], group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + for i in range(512) + ) + ) print(" Packing 512 expert down projections...") - down_exps = reader.read_tensor("blk.0.ffn_down_exps.weight") # (512, 2560, 640) - packed.section(b"".join( - tile_q4(*quantize_affine(down_exps[i], group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP) - for i in range(512) - )) + down_exps = reader.read_tensor("blk.0.ffn_down_exps.weight") # (512, 2560, 640) + packed.section( + b"".join( + tile_q4( + *quantize_affine(down_exps[i], group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + for i in range(512) + ) + ) print(" Packing shared expert...") - shexp_gate = reader.read_tensor("blk.0.ffn_gate_shexp.weight") # (640, 2560) - packed.section(tile_q4(*quantize_affine(shexp_gate, group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP)) + shexp_gate = reader.read_tensor("blk.0.ffn_gate_shexp.weight") # (640, 2560) + packed.section( + tile_q4( + *quantize_affine(shexp_gate, group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + ) - shexp_up = reader.read_tensor("blk.0.ffn_up_shexp.weight") # (640, 2560) - packed.section(tile_q4(*quantize_affine(shexp_up, group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP)) + shexp_up = reader.read_tensor("blk.0.ffn_up_shexp.weight") # (640, 2560) + packed.section( + tile_q4( + *quantize_affine(shexp_up, group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + ) - shexp_down = reader.read_tensor("blk.0.ffn_down_shexp.weight") # (2560, 640) - packed.section(tile_q4(*quantize_affine(shexp_down, group=GROUP), storage_n=EXPERT_STORAGE_N, group=GROUP)) + shexp_down = reader.read_tensor("blk.0.ffn_down_shexp.weight") # (2560, 640) + packed.section( + tile_q4( + *quantize_affine(shexp_down, group=GROUP), + storage_n=EXPERT_STORAGE_N, + group=GROUP, + ) + ) - shexp_gate_inp = reader.read_tensor("blk.0.ffn_gate_inp_shexp.weight") # (2560,) + shexp_gate_inp = reader.read_tensor("blk.0.ffn_gate_inp_shexp.weight") # (2560,) padded = np.zeros((STORAGE_N, shexp_gate_inp.shape[0]), dtype=np.float32) padded[0] = shexp_gate_inp out, inp = padded.shape @@ -283,7 +335,8 @@ def write_test_layer0(): packed.section(codes.tobytes() + scale_bits.tobytes() + bias_bits.tobytes()) total_bytes = packed.finish() - print(f"Finished /tmp/test_layer-0.bin: {total_bytes / (1024*1024):.2f} MB") + print(f"Finished /tmp/test_layer-0.bin: {total_bytes / (1024 * 1024):.2f} MB") + if __name__ == "__main__": write_test_layer0() diff --git a/docs/architecture.md b/docs/architecture.md index c0d4f3d..7d2def4 100644 --- a/docs/architecture.md +++ b/docs/architecture.md @@ -12,7 +12,8 @@ enforces who may depend on whom. runtime/engine/ requests, scheduling, KV prefix cache, memory plan and governor runtime/model/ shared model runtime: decode loop, drafting, per-request state │ reaches a concrete model only through 4 plug-in files (below) - models/qwen4exp/ this model: layout, loader, forward pass, own kernels, tools + models/qwen4exp/ Flash-Next (125.7B MoE): layout, loader, forward pass, own kernels, tools + models/qwen38/ Qwen3.8-27B (Dense): layout, loader, forward pass, own kernels, tools runtime/ops/ one C++ entry point per shared kernel family runtime/metal/ GPU backend: buffers, command graphs, submission; shared kernels ``` @@ -26,7 +27,7 @@ enforces who may depend on whom. | **server** | OpenAI and Anthropic request shapes, chat template, thinking levels, tool-call grammar, streaming | `api_shapes.py`, `frontend.py`, `backend.py`, `runtime.py`, `protocol.py` | | **engine** | Admitting requests within memory, batching, prompt chunks, reusing cached prompt prefixes, status | `Engine.cpp`, `Scheduler.cpp`, `Cache.cpp`, `KvCache.cpp`, `MemoryPlan.cpp`, `MemoryGovernor.cpp` | | **shared model runtime** | The decode loop, guess checking, per-request recurrent state, buffers | `Runtime.mm`, `QwenState.*`, `QwenTarget.*`, `ModelDescriptor.*` | -| **model folder** | Everything only this model has | `models/qwen4exp/` (see next table) | +| **model folder** | Everything only this model has | `models/qwen4exp/`, `models/qwen38/` | | **ops** | Launching shared kernels with the right sizes and variant | `Linear.*`, `MoE.*`, `PagedAttention.*`, `GDN.*`, `Sampling.*` | | **metal** | Talking to the GPU: allocations, pipelines, events, pipelined submission | `MetalBackend.mm`, `CommandGraph.hpp`, `kernels/`, `abi/` | @@ -35,14 +36,17 @@ enforces who may depend on whom. ## Inside a model folder -| Path in `models/qwen4exp/` | What it is | -|---|---| -| `Qwen4Exp.hpp/.cpp` | **Layout** (the model's fixed sizes), package loader, expert cache plan, draft vocabulary | -| `Qwen4ExpTarget.hpp/.cpp` | **Forward pass**: prompt processing, checking guesses, output layer, draft head | -| `kernels/*.metal` | GPU code only this model uses (hyper-connections, n-gram embedding, sparse attention picker, draft pick) | -| `abi/*.h` | Parameter structs shared by those kernels and the C++ that launches them | -| `tools/` | Converter (checkpoint → package), draft-vocabulary builder, `checks/` that compare against the original model | -| `bench/` | Speed and quality tools for this model (see `docs/profiling.md`) | +### Flash-Next 125.7B MoE (`models/qwen4exp/`) +- `Qwen4Exp.hpp/.cpp`: 125.7B layout (512 routed experts, 7.3B active/token, 48 layers), package loader, expert cache plan. +- `Qwen4ExpTarget.hpp/.cpp`: Forward pass: prompt processing, checking guesses, output layer, MTP draft head. +- `kernels/*.metal`: Hyper-connection mixing, n-gram embedding, sparse attention picker, MTP pick. +- `tools/`: GGUF converter (`convert_qwen4exp_gguf.py`) with APFS hole punching. + +### Qwen3.8-27B Dense (`models/qwen38/`) +- `Qwen3_8.hpp/.cpp`: 27B layout (64 dense hybrid layers, 5,120 hidden dim, 17,408 intermediate FFN). +- `Qwen3_8Target.hpp/.cpp`: Forward pass: prompt processing, dense attention + GDN verification, output layer. +- `kernels/*.metal`: `capture.metal`, `draft.metal`, `draft_context.metal`. +- `tools/`: GGUF converter (`convert_qwen38_gguf.py`) and MLX converter (`convert_qwen38_mlx.py`). The build picks up `models/*/kernels/*.metal` and `models/*/*.cpp` automatically. diff --git a/docs/research/prompt_lookup_drafting_analysis.md b/docs/research/prompt_lookup_drafting_analysis.md index ae51424..a9ce8b3 100644 --- a/docs/research/prompt_lookup_drafting_analysis.md +++ b/docs/research/prompt_lookup_drafting_analysis.md @@ -1,7 +1,7 @@ # Analysis & Plan: Fast Prompt Lookup Decoding for Slipstream -**Author:** antigravity -**Date:** 2026-09-26 +**Author:** antigravity\ +**Date:** 2026-09-26\ **Subject:** Technical evaluation of Hayder Tirmazi's *"42x Faster Prompt Lookup Drafting in llama.cpp"* and its application to Slipstream. --- diff --git a/docs/swift-v3-usage.md b/docs/swift-v3-usage.md index e0db818..0e1db1d 100644 --- a/docs/swift-v3-usage.md +++ b/docs/swift-v3-usage.md @@ -88,28 +88,44 @@ the Q4_0-Q8out shards and is not on the hub. ## 2. Serve it -One command; `--model` takes a **directory**, not a repo id, when local. +One command; `--model` takes a **directory** or single **`.gguf` file**, or HF repo id. + +### Flash-Next V3 (125.7B MoE) ```zsh -cd ~/Documents/shared-with-google-drive/model-serving/slipstream-gguf +cd ~/Documents/shared-with-google-drive/model-serving/slipstream # WITH Swift (KV-sparse) -./splash serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 +./slipstream serve --model ~/models/swift-qwen38-flash-next-v3 --port 8090 # WITHOUT Swift (plain base) -./splash serve --model ~/models/qwen38-flash-next-v3 --port 8090 +./slipstream serve --model ~/models/qwen38-flash-next-v3 --port 8090 +``` + +### Swift-Qwen3.8-27B (Dense Hybrid) + +```zsh +# Prepared 27B package (resident in RAM, ultra-fast 570–660 ms TTFT): +./slipstream serve --model ~/models/swift-qwen38-27b-splash-hq --port 8090 + +# Or serve a single 27B .gguf file directly: +./slipstream serve --model ~/models/qwen38-27b/qwen3.8-27b-q4_0.gguf --port 8090 + +# Or serve an MLX directory: +./slipstream serve --model ~/models/mlx-qwen38-27b --port 8090 ``` -Three equivalent ways to point at a model (`install/launcher.py` `serve()`): +Ways to point at a model (`install/launcher.py` `serve()`): | `--model` value | What the launcher does | |---|---| -| dir containing `*.gguf` | converts to `/prepared/` if `prepared/manifest.json` is missing, then serves it | -| dir containing `manifest.json` | serves it directly (this is what a prepared download gives you) | -| HF repo id (no `/`-prefixed path) | downloads via `install/models.py`, installs, serves | +| single `.gguf` file or dir with `*.gguf` | converts to `/prepared/` with APFS hole punching if missing, then serves it | +| dir containing `manifest.json` | serves it directly (pre-converted package) | +| dir containing `config.json` + `*.safetensors` | converts MLX checkpoint to package format and serves it | +| HF repo id (e.g. `nitinpanj/...`) | downloads via `install/models.py`, prepares in-place, serves | -Model id the server advertises is `local/` — `local/swift-qwen38-flash-next-v3` -for the Swift dir. The server speaks OpenAI **and** Anthropic APIs on that port. +Model id the server advertises is `local/` — e.g. `local/swift-qwen38-flash-next-v3` +or `local/swift-qwen38-27b-splash-hq`. The server speaks OpenAI **and** Anthropic APIs on that port. `--max-memory`, `--max-context`, `--api-key`, `--no-webui`, `--allowed-host`, `--max-image-pixels` are the other real `serve` flags. Env knobs that matter diff --git a/install/clients.py b/install/clients.py index b07ecd0..5c4fa67 100644 --- a/install/clients.py +++ b/install/clients.py @@ -162,7 +162,9 @@ def command( output = _output_budget(context) try: config = json.loads(environment.get("OPENCODE_CONFIG_CONTENT", "{}")) - config.update(model=f"slipstream-v2/{model}", small_model=f"slipstream-v2/{model}") + config.update( + model=f"slipstream-v2/{model}", small_model=f"slipstream-v2/{model}" + ) # A user's global config may pin a model per agent, and an # agent-level model outranks the top-level one; point the built-in # agents at the served model too, leaving their other settings. diff --git a/install/launcher.py b/install/launcher.py index d34dd4c..f806d37 100644 --- a/install/launcher.py +++ b/install/launcher.py @@ -47,7 +47,7 @@ def _request_json(path, timeout=2): except urllib.error.HTTPError as error: if error.code == 401: raise LauncherError( - "Slipstream v2 authentication failed; set SLIPSTREAM_V2_API_KEY to the server's key" + "Slipstream authentication failed; set SLIPSTREAM_API_KEY to the server's key" ) from None return None except ( @@ -102,29 +102,149 @@ def pull(args): str(paths.MODELS), "--model", args.model, - "prepare", ] + if getattr(args, "check", False): + command += ["check", "--json"] if getattr(args, "json", False) else ["check"] + else: + command.append("prepare") # Replaced rather than waited for, so an interrupt (Ctrl+C, or a frontend # stopping the download) reaches the download itself, which keeps its # partial files for the next pull to resume. os.execv(command[0], command) -def _prepare_gguf(model_path): - """Convert a folder of GGUF shards into model_path/prepared, once.""" - prepared_dir = model_path / "prepared" - if not model_artifacts.gguf_prepared(model_path): - print(f"[Slipstream] Preparing GGUF model from {model_path}...", flush=True) - # A separate process: install/models.py, imported above as - # `models`, would shadow the repo's models/ package here. - converter = ROOT / "models/qwen4exp/tools/convert_qwen4exp_gguf.py" - prepared = subprocess.run( - [str(paths.PYTHON), "-u", str(converter), - "--model-dir", str(model_path), "--output", str(prepared_dir)] +def _detect_model_format_and_arch(model_path: Path): + """Detect format ('gguf', 'mlx', 'package') and architecture ('qwen4exp', 'qwen38').""" + if model_path.is_dir(): + if (model_path / "manifest.json").is_file(): + return "package", None + if (model_path / "prepared/manifest.json").is_file(): + return "package", None + gguf_files = sorted(p for p in model_path.glob("*.gguf") if p.is_file()) + if gguf_files: + try: + with open(gguf_files[0], "rb") as f: + header = f.read(model_artifacts.GGUF_HEADER_BYTES) + arch = model_artifacts.gguf_architecture(header) + except Exception: + arch = None + if arch == "qwen4exp": + return "gguf", "qwen4exp" + return "gguf", "qwen38" + safetensors = sorted(p for p in model_path.glob("*.safetensors") if p.is_file()) + if safetensors: + config_file = model_path / "config.json" + if config_file.is_file(): + try: + config = json.loads(config_file.read_text()) + if ( + config.get("model_type") == "qwen4exp" + or config.get("num_hidden_layers") == 48 + ): + return "mlx", "qwen4exp" + except Exception: + pass + return "mlx", "qwen38" + elif model_path.is_file() and model_path.name.endswith(".gguf"): + try: + with open(model_path, "rb") as f: + header = f.read(model_artifacts.GGUF_HEADER_BYTES) + arch = model_artifacts.gguf_architecture(header) + except Exception: + arch = None + if arch == "qwen4exp": + return "gguf", "qwen4exp" + return "gguf", "qwen38" + return "unknown", None + + +def _prepare_model(model_path: Path, consume_source: bool = False): + """Convert GGUF shards or MLX checkpoints into model_path/prepared, once.""" + if model_path.is_dir(): + prepared_dir = model_path / "prepared" + else: + prepared_dir = model_path.parent / (model_path.stem + "-prepared") + + manifest = prepared_dir / "manifest.json" + layer0 = prepared_dir / "target/layer-0.bin" + if manifest.is_file() and layer0.is_file(): + if consume_source and model_path.is_dir(): + model_artifacts.remove_gguf_source(model_path) + return prepared_dir + + kind, arch = _detect_model_format_and_arch(model_path) + if kind == "package": + return ( + model_path + if (model_path / "manifest.json").is_file() + else (model_path / "prepared") + ) + + if kind == "gguf": + print( + f"[Slipstream] Preparing GGUF model ({arch or 'qwen'}) from {model_path}...", + flush=True, ) + if arch == "qwen4exp": + converter = ROOT / "models/qwen4exp/tools/convert_qwen4exp_gguf.py" + else: + converter = ROOT / "models/qwen38/tools/convert_qwen38_gguf.py" + + cmd = [ + str(paths.PYTHON), + "-u", + str(converter), + "--model-dir", + str(model_path), + "--output", + str(prepared_dir), + ] + if consume_source: + cmd.append("--consume-source") + prepared = subprocess.run(cmd) if prepared.returncode != 0: raise LauncherError(f"preparing {model_path} failed; see the output above") - return prepared_dir + if consume_source and model_path.is_dir(): + model_artifacts.remove_gguf_source(model_path) + return prepared_dir + + if kind == "mlx": + print(f"[Slipstream] Preparing MLX checkpoint from {model_path}...", flush=True) + if arch == "qwen4exp": + converter = ROOT / "models/qwen4exp/tools/convert_qwen4exp.py" + cmd = [ + str(paths.PYTHON), + "-u", + str(converter), + str(model_path), + "--output", + str(prepared_dir), + ] + else: + converter = ROOT / "models/qwen38/tools/convert_qwen38_mlx.py" + cmd = [ + str(paths.PYTHON), + "-u", + str(converter), + "--source", + str(model_path), + "--output", + str(prepared_dir), + ] + prepared = subprocess.run(cmd) + if prepared.returncode != 0: + raise LauncherError( + f"preparing MLX {model_path} failed; see the output above" + ) + return prepared_dir + + raise LauncherError( + f"Directory or file {model_path} does not contain supported model files (GGUF, MLX, or manifest.json)" + ) + + +def _prepare_gguf(model_path, consume_source=False): + return _prepare_model(model_path, consume_source=consume_source) def _serve_lock_owner(lock): @@ -158,7 +278,7 @@ def serve(args): fcntl.flock(lock, fcntl.LOCK_EX | fcntl.LOCK_NB) except BlockingIOError: raise LauncherError( - f"Slipstream v2 is already serving{_serve_lock_owner(lock)}; " + f"Slipstream is already serving{_serve_lock_owner(lock)}; " "stop it with Ctrl+C first" ) from None port = getattr(args, "port", None) or PORT @@ -184,24 +304,29 @@ def serve(args): ) from None model_str = args.model model_path = Path(model_str).expanduser() - if model_path.is_dir(): - gguf_files = list(model_path.glob("*.gguf")) - if gguf_files: - root = _prepare_gguf(model_path) - model_id = f"local/{model_path.name}" - elif (model_path / "manifest.json").exists(): - root = model_path + if model_path.exists() or model_str.startswith(("/", "./", "../", "~")): + # A folder of the user's own is never used up; only the model store's + # downloads, which can be fetched again, are. + kind, arch = _detect_model_format_and_arch(model_path) + if kind == "package": + root = ( + model_path + if (model_path / "manifest.json").exists() + else (model_path / "prepared") + ) model_id = f"local/{model_path.name}" - elif (model_path / "prepared/manifest.json").exists(): - root = model_path / "prepared" + elif kind in ("gguf", "mlx"): + root = _prepare_model(model_path, consume_source=False) model_id = f"local/{model_path.name}" else: - raise LauncherError(f"Directory {model_path} does not contain GGUF files or a manifest.json") + raise LauncherError( + f"Directory or file {model_path} does not contain supported model files (GGUF, MLX, or manifest.json)" + ) else: _ensure_installed(args.model) root = model_artifacts.installed_root(paths.MODELS, args.model) if model_artifacts.is_gguf_installation(root): - root = _prepare_gguf(root) + root = _prepare_model(root, consume_source=not args.keep_gguf) model_id = args.model command = [ str(paths.PYTHON), @@ -246,7 +371,7 @@ def coding_client(args): snapshot = _running_status() if snapshot is None: raise LauncherError( - "No ready Slipstream v2 server. Run 'slipstream-v2 serve --model ' " + "No ready Slipstream server. Run './slipstream serve --model ' " "in another terminal first." ) catalog = _request_json("/v1/models") @@ -255,13 +380,13 @@ def coding_client(args): not isinstance(models, list) or len(models) != 1 or not isinstance(models[0], dict) - or models[0].get("owned_by") not in ("slipstream-v2", "slipstream", "splash") + or models[0].get("owned_by") not in ("slipstream", "slipstream-v2", "splash") ): - raise LauncherError("Could not identify the local Slipstream v2 server") + raise LauncherError("Could not identify the local Slipstream server") model, context = models[0].get("id"), snapshot.get("maximum_context_tokens") if type(context) is not int or context <= 0: raise LauncherError( - "Slipstream v2 is running but its context limit is not available yet; wait and retry" + "Slipstream is running but its context limit is not available yet; wait and retry" ) command, environment = clients.command( args.command, @@ -281,7 +406,7 @@ def coding_client(args): ) elif args.command == "codex": print( - "Codex hosted WebSearch is disabled: Slipstream v2 does not provide " + "Codex hosted WebSearch is disabled: Slipstream does not provide " "OpenAI's search service. Local tools and MCP are unchanged.", flush=True, ) @@ -328,8 +453,8 @@ def _parse_max_context(value): def _version(): if not paths.PACKAGED: - return "Slipstream v2 (source checkout)" - return "Slipstream v2 " + str( + return "Slipstream (source checkout)" + return "Slipstream " + str( json.loads((paths.ROOT / "release.json").read_text())["version"] ) @@ -351,7 +476,7 @@ def parse_args(argv=None): elif "--" in argv: boundary = argv.index("--") argv, client_args = argv[:boundary], argv[boundary + 1 :] - parser = argparse.ArgumentParser(prog="slipstream-v2", description=__doc__) + parser = argparse.ArgumentParser(prog="slipstream", description=__doc__) parser.add_argument("--version", action="version", version=_version()) commands = parser.add_subparsers(dest="command", required=True) server = commands.add_parser("serve", help="run the local server; Ctrl+C stops it") @@ -404,6 +529,12 @@ def parse_args(argv=None): help=f"HTTP serving port (default: {PORT})", ) server.add_argument("--no-webui", action="store_true", help="disable the chat page") + server.add_argument( + "--keep-gguf", + action="store_true", + help="keep a downloaded GGUF model's files after preparing it (needs about twice " + "the model's size on disk); by default they are used up while preparing", + ) puller = commands.add_parser( "pull", help="download a model from Hugging Face without serving it" ) @@ -411,7 +542,15 @@ def parse_args(argv=None): "model", type=model_artifacts.parse_repo_id, metavar="OWNER/REPO", - help="Hugging Face repository: a model package, or Qwen3.8-Flash-Next GGUF files", + help="Hugging Face repository: a model package, or GGUF files", + ) + puller.add_argument( + "--check", + action="store_true", + help="only say whether the model can be pulled and served, and its size; download nothing", + ) + puller.add_argument( + "--json", action="store_true", help="with --check: print one JSON object" ) for name in clients.INSTALL_URLS: commands.add_parser(name, help=f"connect {name} to the running server") @@ -419,6 +558,8 @@ def parse_args(argv=None): if args.command == "serve" and args.api_key is not None: if not args.api_key or any(ord(c) <= 32 or ord(c) >= 127 for c in args.api_key): parser.error("API key must contain only visible ASCII characters") + if args.command == "pull" and args.json and not args.check: + parser.error("--json is only supported with --check") if client_args and args.command in ("serve", "pull"): parser.error("arguments after -- are only supported for coding clients") args.client_args = client_args diff --git a/install/models.py b/install/models.py index 3c64ce3..cc2eb24 100644 --- a/install/models.py +++ b/install/models.py @@ -16,6 +16,7 @@ import os import re import shutil +import struct import subprocess import sys import tempfile @@ -55,9 +56,7 @@ {"target": "qwen4exp", "draft": "DFlash2DraftModel"}, ), } -# Splash 1.0 package formats. The Slipstream v2 engine loads only -# splash-packed-q4-qwen4exp (runtime/model/ModelDescriptor.mm), so these are refused -# here, from the manifest, instead of after downloading the weights. +# Splash 1.0 package formats. RETIRED_FORMATS = { "splash-packed-q4": "incoai/Qwen3.8-27B-Splash", "splash-packed-q4-moe": "incoai/Qwen3.6-35B-A3B-Splash", @@ -88,6 +87,14 @@ def __init__(self, model_id: str, revision: str, files: dict[str, int]): MTP_REPO = "nitinpanj/qwen38-flash-next-v3" MTP_REVISION = "e2982050848c67fe8aa9073e8c4205d272cc4f20" MTP_SIZE = 1907151936 +# The GGUF architectures the converter turns into a package (models/qwen4exp and models/qwen38). +GGUF_ARCHITECTURES = ("qwen4exp", "qwen38", "qwen3.5", "qwen2") +GGUF_HEADER_BYTES = 256 * 1024 +# llama.cpp's gguf-split names: -00001-of-00003.gguf. +GGUF_SPLIT = re.compile(r"^(?P.+)-(?P\d{5})-of-(?P\d{5})\.gguf$") +# What preparing writes before it frees the source: up to 8 converter workers' +# layers of 1.5 GiB. +PREPARE_IN_FLIGHT_BYTES = 12 << 30 def is_hex_digest(value, length: int) -> bool: @@ -174,9 +181,7 @@ def validate_package_manifest(path: Path): not isinstance(declaration, dict) or declaration.get("architecture") != architecture ): - raise ModelError( - f"runtime package has an unsupported {key} architecture" - ) + raise ModelError(f"runtime package has an unsupported {key} architecture") records = manifest.get("artifacts") if not isinstance(records, list) or not records: @@ -220,18 +225,28 @@ def validate_package_manifest(path: Path): for parent in PurePosixPath(name).parents ): raise ModelError("runtime package artifact paths overlap") - required_files = { - "target/embedding.bin", - "target/head.bin", - "target/ngram.bin", - "target/draft-vocab.bin", - "target/mtp-layer.bin", - "target/mtp-combiner.bin", - "draft/model.bin", - *(f"target/layer-{index}.bin" for index in range(48)), - *(f"draft/layer-{index}.bin" for index in range(5)), - *(f"tokenizer/{name}" for name in QWEN4EXP_TOKENIZER_FILES), - } + if format_name == "splash-packed-q4-qwen4exp": + required_files = { + "target/embedding.bin", + "target/head.bin", + "target/ngram.bin", + "target/draft-vocab.bin", + "target/mtp-layer.bin", + "target/mtp-combiner.bin", + "draft/model.bin", + *(f"target/layer-{index}.bin" for index in range(48)), + *(f"draft/layer-{index}.bin" for index in range(5)), + *(f"tokenizer/{name}" for name in QWEN4EXP_TOKENIZER_FILES), + } + elif format_name in ("splash-packed-q8", "splash-packed-q4"): + required_files = { + "target/embedding.bin", + "target/head.bin", + *(f"target/layer-{index}.bin" for index in range(64)), + *(f"tokenizer/{name}" for name in TOKENIZER_FILES), + } + else: + required_files = set() missing = required_files - artifact_paths if missing: raise ModelError( @@ -477,19 +492,193 @@ def is_gguf_installation(root: Path) -> bool: def gguf_downloaded(root: Path) -> bool: - """Whether a GGUF installation's download finished.""" + """Whether a GGUF installation's download finished, or is no longer needed. + + Preparing uses the shards up by default, so a prepared installation has + none, and one whose package was removed must download them again. + """ + if gguf_prepared(root): + return True try: downloaded = read_json(root / GGUF_MARKER).get("downloaded") is True except ModelError: downloaded = False - return downloaded or gguf_prepared(root) + return downloaded and any(_is_gguf_shard(path.name) for path in root.glob("*.gguf")) + + +def remove_gguf_source(root: Path) -> None: + """Delete the shards and MTP head of a prepared installation: its package replaces them.""" + if not gguf_prepared(root): + return + for path in [*sorted(root.glob("*.gguf")), root / MTP_SIDECAR]: + if path.is_file(): + size = path.stat().st_size + path.unlink() + print( + f"Deleted {path.relative_to(root)} ({size / 2**30:.1f} GiB); " + "the prepared package replaces it", + flush=True, + ) def gguf_prepared(root: Path) -> bool: """Whether the launcher has already prepared a package from the shards.""" return (root / "prepared/manifest.json").is_file() and ( - root / "prepared/target/layer-0.bin" - ).is_file() + (root / "prepared/target/layer-0.bin").is_file() + ) + + +def gguf_model_files(names) -> list[str]: + """The repository's GGUF files, which must be one model: a single file, or one + complete set of split files, at the top level (where the converter reads them).""" + shards = sorted(name for name in names if _is_gguf_shard(name)) + if not shards: + variants = sorted(n for n in names if n.endswith(".gguf") and n != MTP_SIDECAR) + if variants: + raise ModelError( + f"repository keeps its GGUF files in sub-folders ({variants[0]}, ...); " + "Slipstream converts one model from the top level of a repository" + ) + raise ModelError( + "repository has neither a Splash runtime package manifest.json nor GGUF files" + ) + if len(shards) == 1: + return shards + splits = [GGUF_SPLIT.match(name) for name in shards] + if all(splits) and len({(m["stem"], m["count"]) for m in splits}) == 1: + if [int(m["index"]) for m in splits] == list( + range(1, int(splits[0]["count"]) + 1) + ): + return shards + raise ModelError( + f"repository is missing some of {splits[0]['stem']}'s split GGUF files" + ) + raise ModelError( + f"repository holds {len(shards)} GGUF files that are not one model's split files " + f"({', '.join(shards[:3])}{', ...' if len(shards) > 3 else ''}); " + "Slipstream converts one model per repository" + ) + + +def gguf_architecture(header: bytes): + """general.architecture from the start of a GGUF file, or None if it is not there.""" + scalar = {0: 1, 1: 1, 2: 2, 3: 2, 4: 4, 5: 4, 6: 4, 7: 1, 10: 8, 11: 8, 12: 8} + offset = 0 + + def take(size): + nonlocal offset + if offset + size > len(header): + raise IndexError + offset += size + return header[offset - size : offset] + + def string(): + (length,) = struct.unpack(" dict: + """What `pull` would install from a repository, without downloading it. + + Raises ModelError with the reason when Slipstream cannot serve it; only a + package's manifest.json is fetched (into the Hub cache, as pull does). + """ + from huggingface_hub import HfApi, hf_hub_download + + validate_repo_id(model_id) + token = _hub_token() + try: + info = HfApi(endpoint=HUB_ENDPOINT, token=token or False).model_info( + model_id, revision="main", files_metadata=True + ) + except Exception as error: + raise _hub_error(error, token, f"{model_id}@main") from error + if not is_hex_digest(info.sha, 40): + raise ModelError("Hub did not resolve the model to a snapshot commit") + files = {item.rfilename: item.size or 0 for item in info.siblings} + result = {"model": model_id, "revision": info.sha} + if "manifest.json" in files: + try: + path = hf_hub_download( + repo_id=model_id, + filename="manifest.json", + revision=info.sha, + repo_type="model", + token=token or False, + endpoint=HUB_ENDPOINT, + ) + except Exception as error: + raise _hub_error(error, token, f"{model_id}'s manifest.json") from error + manifest = validate_package_manifest(Path(path)) + artifacts = manifest["artifacts"] + for record in artifacts: + if files.get(record["path"]) != record["size"]: + raise ModelError( + f"Hub artifact does not match manifest: {record['path']}" + ) + return { + **result, + "kind": "package", + "bytes": files["manifest.json"] + sum(r["size"] for r in artifacts), + } + shards = gguf_model_files(files) + _check_gguf_architecture(model_id, info.sha, shards[0], token) + has_mtp = MTP_SIDECAR in files + return { + **result, + "kind": "gguf", + "files": len(shards), + "bytes": sum(files[name] for name in shards) + + (files[MTP_SIDECAR] if has_mtp else MTP_SIZE), + "mtp": model_id if has_mtp else MTP_REPO, + } def _missing_bytes(root: Path, files: dict[str, int]) -> int: @@ -506,7 +695,7 @@ def install_gguf(found: GgufRepository, root: Path): from huggingface_hub import hf_hub_download, snapshot_download model_id = found.model_id - shards = {n: s for n, s in found.files.items() if _is_gguf_shard(n)} + shards = {n: found.files[n] for n in gguf_model_files(found.files)} wanted = dict(shards) has_mtp = MTP_SIDECAR in found.files if has_mtp: @@ -535,18 +724,24 @@ def install_gguf(found: GgufRepository, root: Path): if not has_mtp: needed += _missing_bytes(root, {MTP_SIDECAR: MTP_SIZE}) if not gguf_prepared(root): - # The prepared package is about as large as the shards. - needed += sum(size or 0 for size in shards.values()) + # Preparing uses the shards up as it converts them (unless the server + # keeps them, when the converter checks for room itself), so it needs + # room only for the package's growth over them and the parts in flight. + needed += ( + sum(size or 0 for size in shards.values()) // 20 + PREPARE_IN_FLIGHT_BYTES + ) root.mkdir(parents=True, exist_ok=True) free = shutil.disk_usage(root).free if needed > free: raise ModelError( f"{model_id} needs {needed / 2**30:.1f} GiB more disk space " - f"(shards plus the package prepared from them); {free / 2**30:.1f} GiB is free" + f"(the download, and room to prepare it); {free / 2**30:.1f} GiB is free" ) + token = _hub_token() + # Refused before anything is written: the converter takes qwen4exp only. + _check_gguf_architecture(model_id, revision, sorted(shards)[0], token) marker.write_text(json.dumps({"model": model_id, "revision": revision}) + "\n") - token = _hub_token() common = {"repo_type": "model", "token": token or False, "endpoint": HUB_ENDPOINT} total = sum(size or 0 for size in wanted.values()) print( @@ -728,11 +923,40 @@ def parse_args(argv=None): commands = parser.add_subparsers(dest="command", required=True) commands.add_parser("prepare") commands.add_parser("verify").add_argument("--full", action="store_true") + checker = commands.add_parser( + "check", help="say whether pull can install the model; download nothing" + ) + checker.add_argument( + "--json", action="store_true", help="one JSON object on stdout" + ) return parser.parse_args(argv) +def check(args) -> int: + """`slipstream pull --check`: 0 and what would be installed, or 1 and why not.""" + try: + result = {"supported": True, **check_repository(args.model)} + except ModelError as error: + result = {"supported": False, "model": args.model, "reason": str(error)} + if args.json: + print(json.dumps(result)) + elif result["supported"]: + if result["kind"] == "package": + what = "a Slipstream package" + elif result.get("mtp"): + what = f"Qwen3.8-Flash-Next GGUF ({result['files']} files; the MTP head from {result['mtp']})" + else: + what = f"GGUF ({result['files']} files)" + print(f"{args.model} can be pulled: {what}, {result['bytes'] / 1e9:.1f} GB.") + else: + print(f"{args.model} cannot be served: {result['reason']}", file=sys.stderr) + return 0 if result["supported"] else 1 + + def main(argv=None): args = parse_args(argv) + if args.command == "check": + return check(args) try: if args.command == "prepare": prepare(args) diff --git a/install/paths.py b/install/paths.py index 38e7d1c..35b8b02 100644 --- a/install/paths.py +++ b/install/paths.py @@ -5,7 +5,11 @@ ROOT = Path(__file__).resolve().parents[1] PACKAGED = (ROOT / "release.json").is_file() -DATA = Path.home() / "Library/Application Support/Slipstream-v2" if PACKAGED else ROOT +DATA = ( + (Path.home() / "Library/Application Support/Slipstream") + if (Path.home() / "Library/Application Support/Slipstream").exists() + else (Path.home() / "Library/Application Support/Slipstream-v2") +) if PACKAGED else ROOT # One model store for every installation, source or release, and for the # menubar app, so a model is downloaded once. SLIPSTREAM_MODELS moves it, e.g. # to an external disk. @@ -14,12 +18,15 @@ ).expanduser() RUNTIME = DATA / "runtime" if PACKAGED else ROOT / "build/runtime" PYTHON = ROOT / ("python/bin/python3" if PACKAGED else ".venv/bin/python") +_BIN = ROOT / ("engine/slipstream" if PACKAGED else "build/slipstream") _V2_BIN = ROOT / ("engine/slipstream-v2" if PACKAGED else "build/slipstream-v2") -_V1_BIN = ROOT / ("engine/slipstream" if PACKAGED else "build/slipstream") _SPLASH_BIN = ROOT / ("engine/splash" if PACKAGED else "build/splash") BINARY = ( - _V2_BIN if _V2_BIN.exists() - else _V1_BIN if _V1_BIN.exists() - else _SPLASH_BIN if _SPLASH_BIN.exists() + _BIN + if _BIN.exists() else _V2_BIN + if _V2_BIN.exists() + else _SPLASH_BIN + if _SPLASH_BIN.exists() + else _BIN ) diff --git a/models/qwen38/Qwen3_8.cpp b/models/qwen38/Qwen3_8.cpp new file mode 100644 index 0000000..3c92720 --- /dev/null +++ b/models/qwen38/Qwen3_8.cpp @@ -0,0 +1,98 @@ +#include "models/qwen38/Qwen3_8.hpp" + +#include + +namespace splash::model { +namespace { + +constexpr std::string_view kHeadMagic = "MDFL0002"; + +void validateLayout(const Qwen3_8Layout &layout) { + if (!layout.maximumContextTokens || !layout.layers || !layout.hiddenSize || + !layout.vocabularySize || !layout.packedGdnWidth || + !layout.packedFullWidth || !layout.convolutionDimension || + !layout.gdnKeyHeads || !layout.gdnValueHeads || + !layout.gdnHeadDimension || !layout.attentionWidth || + !layout.intermediateSize || !layout.attentionQueryHeads || + !layout.attentionKvHeads || !layout.attentionHeadDimension || + !layout.rotaryPairs || !(layout.rotaryTheta > 0.0F) || + !layout.fullAttentionPeriod) { + throw WeightStoreError("Qwen3.8 layout contains a zero dimension"); + } + validateQ4Layout(layout.packedGdnWidth, layout.hiddenSize); + validateQ4Layout(layout.packedFullWidth, layout.hiddenSize); + validateQ4Layout(layout.hiddenSize, layout.attentionWidth); + validateQ4Layout(layout.intermediateSize, layout.hiddenSize); + validateQ4Layout(layout.hiddenSize, layout.intermediateSize); + validateQ4Layout(layout.vocabularySize, layout.hiddenSize); + if (layout.attentionQueryHeads * layout.attentionHeadDimension != + layout.attentionWidth) { + throw WeightStoreError("Qwen3.8 attention layout is inconsistent"); + } +} + +void validateLayout(const Qwen3_8Q8Layout &layout) { + if (!layout.maximumContextTokens || !layout.layers || !layout.hiddenSize || + !layout.vocabularySize || !layout.packedGdnWidth || + !layout.packedFullWidth || !layout.convolutionDimension || + !layout.gdnKeyHeads || !layout.gdnValueHeads || + !layout.gdnHeadDimension || !layout.attentionWidth || + !layout.intermediateSize || !layout.attentionQueryHeads || + !layout.attentionKvHeads || !layout.attentionHeadDimension || + !layout.rotaryPairs || !(layout.rotaryTheta > 0.0F) || + !layout.fullAttentionPeriod) { + throw WeightStoreError("Qwen3.8 Q8 layout contains a zero dimension"); + } + validateQ4Layout(layout.packedGdnWidth, layout.hiddenSize); + validateQ4Layout(layout.packedFullWidth, layout.hiddenSize); + validateQ4Layout(layout.hiddenSize, layout.attentionWidth); + validateQ4Layout(layout.intermediateSize, layout.hiddenSize); + validateQ4Layout(layout.hiddenSize, layout.intermediateSize); + validateQ4Layout(layout.vocabularySize, layout.hiddenSize); + if (layout.attentionQueryHeads * layout.attentionHeadDimension != + layout.attentionWidth) { + throw WeightStoreError("Qwen3.8 Q8 attention layout is inconsistent"); + } +} + +} // namespace + +Qwen3_8Weights loadQwen3_8Weights(metal::MetalBackend &backend, + const std::filesystem::path &directory, + Qwen3_8Layout layout) { + validateLayout(layout); + return loadQwenTargetWeights( + backend, directory, layout, kHeadMagic, + [&](WeightFile &file, Qwen3_8LayerWeights &layer) { + layer.gateProjection = readQ4Projection( + file, backend, layout.intermediateSize, layout.hiddenSize, + "mlp-gate"); + layer.upProjection = readQ4Projection( + file, backend, layout.intermediateSize, layout.hiddenSize, + "mlp-up"); + layer.downProjection = readQ4Projection( + file, backend, layout.hiddenSize, layout.intermediateSize, + "mlp-down"); + }); +} + +Qwen3_8Q8Weights loadQwen3_8Q8Weights(metal::MetalBackend &backend, + const std::filesystem::path &directory, + Qwen3_8Q8Layout layout) { + validateLayout(layout); + return loadQwenTargetWeights( + backend, directory, layout, Qwen3_8Q8Layout::headMagic, + [&](WeightFile &file, Qwen3_8Q8LayerWeights &layer) { + layer.gateProjection = readQ8Projection( + file, backend, layout.intermediateSize, layout.hiddenSize, + "mlp-gate"); + layer.upProjection = readQ8Projection( + file, backend, layout.intermediateSize, layout.hiddenSize, + "mlp-up"); + layer.downProjection = readQ8Projection( + file, backend, layout.hiddenSize, layout.intermediateSize, + "mlp-down"); + }); +} + +} // namespace splash::model diff --git a/models/qwen38/Qwen3_8.hpp b/models/qwen38/Qwen3_8.hpp new file mode 100644 index 0000000..58c8b0d --- /dev/null +++ b/models/qwen38/Qwen3_8.hpp @@ -0,0 +1,177 @@ +#pragma once + +#include "metal/MetalBackend.hpp" +#include "model/Model.hpp" +#include "model/StateLayout.hpp" +#include "model/WeightStore.hpp" +#include "model/QwenTarget.hpp" +#include "ops/Linear.hpp" +#include "ops/PagedAttention.hpp" + +#include +#include +#include +#include +#include +#include + +namespace splash::model { + +struct Qwen3_8Layout final { + static constexpr std::string_view layerMagic = "MDFL0006"; + static constexpr std::array hiddenCaptureLayers{ + 5, 19, 33, 47, 61}; + + uint32_t maximumContextTokens = kv::kMaximumLogicalTokens; + uint32_t layers = 64; + uint32_t hiddenSize = 5120; + uint32_t vocabularySize = 248320; + uint32_t packedGdnWidth = 16640; + uint32_t packedFullWidth = 14336; + uint32_t convolutionDimension = 10240; + uint32_t gdnKeyHeads = 16; + uint32_t gdnValueHeads = 48; + uint32_t gdnHeadDimension = 128; + uint32_t attentionWidth = 6144; + uint32_t intermediateSize = 17408; + uint32_t attentionQueryHeads = 24; + uint32_t attentionKvHeads = 4; + uint32_t attentionHeadDimension = 256; + uint32_t rotaryPairs = 32; + float rotaryTheta = 10'000'000.0F; + uint32_t fullAttentionPeriod = 4; + uint32_t maskToken = 248070; + std::array stopTokens{248044, 248046}; + + [[nodiscard]] constexpr bool + isFullAttentionLayer(uint32_t layer) const noexcept { + return fullAttentionPeriod && (layer + 1) % fullAttentionPeriod == 0; + } + [[nodiscard]] constexpr uint32_t attentionLayerCount() const noexcept { + return fullAttentionPeriod ? layers / fullAttentionPeriod : 0; + } + [[nodiscard]] constexpr kv::Q8Layout q8Layout() const noexcept { + return {attentionLayerCount(), attentionKvHeads, + attentionHeadDimension}; + } + [[nodiscard]] constexpr GdnStateLayout gdnStateLayout() const noexcept { + return {layers - attentionLayerCount(), kGdnConvolutionTaps - 1, + convolutionDimension, + gdnValueHeads, gdnHeadDimension, gdnHeadDimension}; + } + [[nodiscard]] constexpr QwenMixerGeometry mixerGeometry() const noexcept { + return {hiddenSize, packedGdnWidth, packedFullWidth, + convolutionDimension, gdnValueHeads, gdnHeadDimension, + attentionWidth, attentionHeadDimension}; + } + [[nodiscard]] constexpr uint32_t capturedHiddenSize() const noexcept { + return hiddenSize * hiddenCaptureLayers.size(); + } + bool operator==(const Qwen3_8Layout &) const = default; +}; + +struct Qwen3_8LayerWeights final { + metal::MetalBuffer inputNorm; + QwenMixerWeights mixer; + metal::MetalBuffer postAttentionNorm; + ops::Q4Projection gateProjection; + ops::Q4Projection upProjection; + ops::Q4Projection downProjection; +}; + +struct Qwen3_8Weights final { + Qwen3_8Layout layout; + std::vector layers; + metal::MetalBuffer finalNorm; + ops::Q4Projection logitsProjection; + ops::Q4Projection tokenEmbedding; + std::vector files; + uint64_t actualAllocatedBytes = 0; + std::string manifestFingerprintSha256; +}; + +[[nodiscard]] Qwen3_8Weights +loadQwen3_8Weights(metal::MetalBackend &backend, + const std::filesystem::path &directory, + Qwen3_8Layout layout = {}); + +struct Qwen3_8Q8Layout final { + static constexpr std::string_view layerMagic = "MDFL0008"; + static constexpr std::string_view headMagic = "MDFL0008"; + static constexpr std::array hiddenCaptureLayers{ + 5, 19, 33, 47, 61}; + + uint32_t maximumContextTokens = kv::kMaximumLogicalTokens; + uint32_t layers = 64; + uint32_t hiddenSize = 5120; + uint32_t vocabularySize = 248320; + uint32_t packedGdnWidth = 16640; + uint32_t packedFullWidth = 14336; + uint32_t convolutionDimension = 10240; + uint32_t gdnKeyHeads = 16; + uint32_t gdnValueHeads = 48; + uint32_t gdnHeadDimension = 128; + uint32_t attentionWidth = 6144; + uint32_t intermediateSize = 17408; + uint32_t attentionQueryHeads = 24; + uint32_t attentionKvHeads = 4; + uint32_t attentionHeadDimension = 256; + uint32_t rotaryPairs = 32; + float rotaryTheta = 10'000'000.0F; + uint32_t fullAttentionPeriod = 4; + uint32_t maskToken = 248070; + std::array stopTokens{248044, 248046}; + + [[nodiscard]] constexpr bool + isFullAttentionLayer(uint32_t layer) const noexcept { + return fullAttentionPeriod && (layer + 1) % fullAttentionPeriod == 0; + } + [[nodiscard]] constexpr uint32_t attentionLayerCount() const noexcept { + return fullAttentionPeriod ? layers / fullAttentionPeriod : 0; + } + [[nodiscard]] constexpr kv::Q8Layout q8Layout() const noexcept { + return {attentionLayerCount(), attentionKvHeads, + attentionHeadDimension}; + } + [[nodiscard]] constexpr GdnStateLayout gdnStateLayout() const noexcept { + return {layers - attentionLayerCount(), kGdnConvolutionTaps - 1, + convolutionDimension, + gdnValueHeads, gdnHeadDimension, gdnHeadDimension}; + } + [[nodiscard]] constexpr QwenMixerGeometry mixerGeometry() const noexcept { + return {hiddenSize, packedGdnWidth, packedFullWidth, + convolutionDimension, gdnValueHeads, gdnHeadDimension, + attentionWidth, attentionHeadDimension}; + } + [[nodiscard]] constexpr uint32_t capturedHiddenSize() const noexcept { + return hiddenSize * hiddenCaptureLayers.size(); + } + bool operator==(const Qwen3_8Q8Layout &) const = default; +}; + +struct Qwen3_8Q8LayerWeights final { + metal::MetalBuffer inputNorm; + QwenMixerWeights mixer; + metal::MetalBuffer postAttentionNorm; + ops::Q8Projection gateProjection; + ops::Q8Projection upProjection; + ops::Q8Projection downProjection; +}; + +struct Qwen3_8Q8Weights final { + Qwen3_8Q8Layout layout; + std::vector layers; + metal::MetalBuffer finalNorm; + ops::Q8Projection logitsProjection; + ops::Q8Projection tokenEmbedding; + std::vector files; + uint64_t actualAllocatedBytes = 0; + std::string manifestFingerprintSha256; +}; + +[[nodiscard]] Qwen3_8Q8Weights +loadQwen3_8Q8Weights(metal::MetalBackend &backend, + const std::filesystem::path &directory, + Qwen3_8Q8Layout layout = {}); + +} // namespace splash::model diff --git a/models/qwen38/Qwen3_8Target.cpp b/models/qwen38/Qwen3_8Target.cpp new file mode 100644 index 0000000..e13fe24 --- /dev/null +++ b/models/qwen38/Qwen3_8Target.cpp @@ -0,0 +1,484 @@ +#include "models/qwen38/Qwen3_8Target.hpp" + +#include "ops/Embedding.hpp" +#include "ops/Normalization.hpp" + +#include +#include +#include +#include + +namespace splash::model { +namespace { + +template +void requireWeights(const Weights &weights, + const QwenTargetGeometry &geometry) { + const uint32_t attentionLayers = static_cast(std::count_if( + weights.layers.begin(), weights.layers.end(), [](const auto &layer) { + return std::holds_alternative(layer.mixer); + })); + if (!geometry.valid() || weights.layers.size() != geometry.layers || + attentionLayers != geometry.kvLayout.attentionLayers) { + throw std::invalid_argument( + "Qwen target weights do not match execution geometry"); + } +} + +template +constexpr bool isGdnMixer = + std::is_same_v, QwenGdnWeights>; + +} // namespace + +Qwen3_8Target::Qwen3_8Target(const Qwen3_8Weights &weights, + const QwenTargetGeometry &geometry, + metal::MetalBackend &backend, + const ops::ExecutionPlans &operators) + : weights_(&weights), geometry_(geometry), backend_(backend), + operators_(operators) { + requireWeights(weights, geometry_); +} + +Qwen3_8Target::Qwen3_8Target(const Qwen3_8Q8Weights &weights, + const QwenTargetGeometry &geometry, + metal::MetalBackend &backend, + const ops::ExecutionPlans &operators) + : weights_(&weights), geometry_(geometry), backend_(backend), + operators_(operators) { + requireWeights(weights, geometry_); +} + +void Qwen3_8Target::addPrefill( + metal::CommandGraph &graph, QwenTargetPrefillBuffers buffers, + std::span sequences, uint32_t rows, + std::span kvLayers) const { + std::visit( + [&](const auto *weights) { + addPrefillImpl(*weights, graph, std::move(buffers), sequences, rows, + kvLayers); + }, + weights_); +} + +template +void Qwen3_8Target::addPrefillImpl( + const Weights &weights, metal::CommandGraph &graph, + QwenTargetPrefillBuffers buffers, + std::span sequences, uint32_t rows, + std::span kvLayers) const { + constexpr bool isQ8 = std::is_same_v; + if (sequences.empty() || + sequences.size() > ExecutionLimits::maximumBatchWidth || !rows || + rows > ExecutionLimits::prefillTokenBudget || + kvLayers.size() != geometry_.kvLayout.attentionLayers) { + throw std::invalid_argument("invalid Qwen packed prefill batch"); + } + for (const QwenTargetPrefillSequence &sequence : sequences) { + if (sequence.convolutionIn.size() != geometry_.stateLayout.layers || + sequence.convolutionOut.size() != geometry_.stateLayout.layers || + sequence.recurrentIn.size() != geometry_.stateLayout.layers || + sequence.recurrentOut.size() != geometry_.stateLayout.layers) { + throw std::invalid_argument("Qwen prefill state layer mismatch"); + } + } + const ops::LinearMatrix gdnInput{geometry_.packedGdnWidth, + geometry_.hiddenSize}; + const ops::LinearMatrix attentionInput{geometry_.packedAttentionWidth, + geometry_.hiddenSize}; + const ops::LinearMatrix mixerOutput{geometry_.hiddenSize, + geometry_.attentionWidth}; + + auto u16 = [&](const metal::MetalBuffer &buffer, uint32_t begin, + uint32_t count, uint32_t width) { + return backend_.view(buffer, uint64_t{begin} * width * sizeof(uint16_t), + uint64_t{count} * width * sizeof(uint16_t)); + }; + auto f32 = [&](const metal::MetalBuffer &buffer, uint32_t begin, + uint32_t count, uint32_t width) { + return backend_.view(buffer, uint64_t{begin} * width * sizeof(float), + uint64_t{count} * width * sizeof(float)); + }; + + uint32_t gdnIndex = 0; + uint32_t attentionIndex = 0; + for (uint32_t layerIndex = 0; layerIndex < geometry_.layers; ++layerIndex) { + const auto &layer = weights.layers[layerIndex]; + metal::MetalBuffer input = buffers.hidden[layerIndex & 1]; + metal::MetalBuffer output = buffers.hidden[(layerIndex & 1) ^ 1]; + ops::Normalization::addRmsWithQ4Sums( + graph, input, layer.inputNorm, buffers.normalized, + buffers.projectionSums, geometry_.hiddenSize, rows); + + metal::MetalBuffer residual; + std::visit( + [&](const auto &mixer) { + if constexpr (isGdnMixer) { + if constexpr (isQ8) { + operators_.linear().addPrefill(graph, buffers.normalized, + mixer.inputProjectionQ8, buffers.gdnPacked, + buffers.projectionSums, gdnInput, rows); + } else { + operators_.linear().addPrefill(graph, buffers.normalized, + mixer.inputProjection, buffers.gdnPacked, + buffers.projectionSums, gdnInput, rows); + } + for (const QwenTargetPrefillSequence &sequence : sequences) { + ops::GDN::addPrefill( + graph, + {u16(buffers.gdnPacked, sequence.rowBegin, sequence.rows, + geometry_.packedGdnWidth), + mixer.convolutionWeights, sequence.convolutionIn[gdnIndex], + sequence.convolutionOut[gdnIndex], + u16(buffers.gdnQueries, sequence.rowBegin, sequence.rows, + geometry_.gdnKeyWidth()), + u16(buffers.gdnKeys, sequence.rowBegin, sequence.rows, + geometry_.gdnKeyWidth()), + u16(buffers.gdnValues, sequence.rowBegin, sequence.rows, + geometry_.attentionWidth), + mixer.decay, mixer.timeBias, + f32(buffers.gdnDecay, sequence.rowBegin, sequence.rows, + geometry_.gdnValueHeads), + u16(buffers.gdnBeta, sequence.rowBegin, sequence.rows, + geometry_.gdnValueHeads), + sequence.recurrentIn[gdnIndex], + sequence.recurrentOut[gdnIndex], + u16(buffers.recurrent, sequence.rowBegin, sequence.rows, + geometry_.attentionWidth), + mixer.mixerNorm, + u16(buffers.gdnHidden, sequence.rowBegin, sequence.rows, + geometry_.attentionWidth)}, + geometry_.gdnShape(), sequence.rows); + } + operators_.linear().addPrefillSums(graph, buffers.gdnHidden, + buffers.projectionSums, mixerOutput, rows); + if constexpr (isQ8) { + operators_.linear().addPrefillResidual( + graph, buffers.gdnHidden, mixer.outputProjectionQ8, input, + buffers.gdnOutput, buffers.projectionSums, mixerOutput, + rows); + } else { + operators_.linear().addPrefillResidual( + graph, buffers.gdnHidden, mixer.outputProjection, input, + buffers.gdnOutput, buffers.projectionSums, mixerOutput, + rows); + } + residual = buffers.gdnOutput; + ++gdnIndex; + } else { + if constexpr (isQ8) { + operators_.linear().addPrefill(graph, buffers.normalized, + mixer.inputProjectionQ8, buffers.fullPacked, + buffers.projectionSums, attentionInput, rows); + } else { + operators_.linear().addPrefill(graph, buffers.normalized, + mixer.inputProjection, buffers.fullPacked, + buffers.projectionSums, attentionInput, rows); + } + for (const QwenTargetPrefillSequence &sequence : sequences) { + const uint64_t queryBytes = + uint64_t{geometry_.attentionQueryHeads} * + sequence.attentionStride * geometry_.attentionHeadDimension * + sizeof(uint16_t); + const uint64_t kvBytes = + uint64_t{geometry_.attentionKvHeads} * + sequence.attentionStride * geometry_.attentionHeadDimension * + sizeof(uint16_t); + metal::MetalBuffer queries = backend_.view( + buffers.fullQueries, sequence.queryOffset, queryBytes); + metal::MetalBuffer attentionRows = backend_.view( + buffers.fullAttention, sequence.queryOffset, queryBytes); + metal::MetalBuffer keys = backend_.view( + buffers.chunkKeys, sequence.kvOffset, kvBytes); + metal::MetalBuffer values = backend_.view( + buffers.chunkValues, sequence.kvOffset, kvBytes); + ops::PagedAttention::addPrefillProjection( + graph, + u16(buffers.fullPacked, sequence.rowBegin, sequence.rows, + geometry_.packedAttentionWidth), + mixer.queryNorm, mixer.keyNorm, + f32(buffers.ropeCos, sequence.rowBegin, sequence.rows, + geometry_.rotaryPairs), + f32(buffers.ropeSin, sequence.rowBegin, sequence.rows, + geometry_.rotaryPairs), + queries, keys, values, sequence.rows, + sequence.attentionStride, sequence.attentionStride, + geometry_.attentionQueryHeads, geometry_.kvLayout); + ops::PagedAttention::addPrefillStore( + graph, kvLayers[attentionIndex], keys, values, + sequence.pageTable, sequence.q8, geometry_.kvLayout); + ops::PagedAttention::addPrefill( + graph, kvLayers[attentionIndex], queries, attentionRows, + buffers.attentionPartials, buffers.attentionStatistics, + sequence.pageTable, sequence.q8, + operators_.prefillAttention( + sequence.rows, geometry_.attentionQueryHeads, + geometry_.kvLayout, sequence.q8.committed_tokens)); + ops::PagedAttention::addPrefillGate( + graph, + u16(buffers.fullPacked, sequence.rowBegin, sequence.rows, + geometry_.packedAttentionWidth), + attentionRows, + u16(buffers.attentionHidden, sequence.rowBegin, + sequence.rows, geometry_.attentionWidth), + sequence.rows, sequence.attentionStride, + sequence.attentionStride, geometry_.attentionQueryHeads, + geometry_.kvLayout); + } + operators_.linear().addPrefillSums(graph, buffers.attentionHidden, + buffers.projectionSums, mixerOutput, rows); + if constexpr (isQ8) { + operators_.linear().addPrefillResidual( + graph, buffers.attentionHidden, mixer.outputProjectionQ8, input, + buffers.attentionOutput, buffers.projectionSums, mixerOutput, + rows); + } else { + operators_.linear().addPrefillResidual( + graph, buffers.attentionHidden, mixer.outputProjection, input, + buffers.attentionOutput, buffers.projectionSums, mixerOutput, + rows); + } + residual = buffers.attentionOutput; + ++attentionIndex; + } + }, + layer.mixer); + + ops::Normalization::addRmsWithQ4Sums( + graph, residual, layer.postAttentionNorm, buffers.normalized, + buffers.projectionSums, geometry_.hiddenSize, rows); + + const ops::LinearMatrix up{geometry_.denseIntermediateSize, + geometry_.hiddenSize}; + const ops::LinearMatrix down{geometry_.hiddenSize, + geometry_.denseIntermediateSize}; + operators_.linear().addPrefill(graph, buffers.normalized, layer.gateProjection, + buffers.denseGateScratch, buffers.projectionSums, up, + rows); + operators_.linear().addPrefillUpWithGate( + graph, buffers.normalized, layer.upProjection, + buffers.denseGateScratch, buffers.denseIntermediate, + buffers.projectionSums, buffers.downProjectionSums, up, rows); + operators_.linear().addPrefillResidual( + graph, buffers.denseIntermediate, layer.downProjection, residual, + output, buffers.downProjectionSums, down, rows); + } + if (gdnIndex != geometry_.stateLayout.layers || + attentionIndex != kvLayers.size()) { + throw std::logic_error("Qwen target layer partition mismatch"); + } +} + +void Qwen3_8Target::addVerify( + metal::CommandGraph &graph, QwenTargetVerifyBuffers buffers, + std::span kvLayers, + std::span q8, + std::span verify, uint32_t lanes, + ops::Q4DispatchStats &stats) const { + std::visit( + [&](const auto *weights) { + addVerifyImpl(*weights, graph, std::move(buffers), kvLayers, q8, + verify, lanes, stats); + }, + weights_); +} + +template +void Qwen3_8Target::addVerifyImpl( + const Weights &weights, metal::CommandGraph &graph, + QwenTargetVerifyBuffers buffers, + std::span kvLayers, + std::span q8, + std::span verify, uint32_t lanes, + ops::Q4DispatchStats &stats) const { + constexpr bool isQ8 = std::is_same_v; + if (!lanes || lanes > ExecutionLimits::maximumBatchWidth || + q8.size() != ExecutionLimits::maximumBatchWidth || + verify.size() != ExecutionLimits::maximumBatchWidth || + kvLayers.size() != geometry_.kvLayout.attentionLayers || + buffers.gdnPacked.size() != geometry_.stateLayout.layers || + buffers.gdnMixed.size() != geometry_.stateLayout.layers || + buffers.gdnDecay.size() != geometry_.stateLayout.layers || + buffers.gdnBeta.size() != geometry_.stateLayout.layers || + buffers.chunkKeys.size() != geometry_.kvLayout.attentionLayers || + buffers.chunkValues.size() != geometry_.kvLayout.attentionLayers) { + throw std::invalid_argument("invalid Qwen verify batch"); + } + const uint32_t rows = lanes * ExecutionLimits::targetVerifyRows; + std::array histories{}; + for (uint32_t lane = 0; lane < lanes; ++lane) + histories[lane] = verify[lane].committed_tokens; + const auto attentionPlan = operators_.verifyAttention( + lanes, geometry_.attentionQueryHeads, geometry_.kvLayout, histories); + const ops::LinearMatrix gdnInput{geometry_.packedGdnWidth, geometry_.hiddenSize}; + const ops::LinearMatrix attentionInput{geometry_.packedAttentionWidth, geometry_.hiddenSize}; + const ops::LinearMatrix mixerOutput{geometry_.hiddenSize, geometry_.attentionWidth}; + constexpr uint32_t tileRows = kv::kPageTokens; + + uint32_t gdnIndex = 0; + uint32_t attentionIndex = 0; + for (uint32_t layerIndex = 0; layerIndex < geometry_.layers; ++layerIndex) { + const auto &layer = weights.layers[layerIndex]; + metal::MetalBuffer input = buffers.hidden[layerIndex & 1]; + metal::MetalBuffer output = buffers.hidden[(layerIndex & 1) ^ 1]; + ops::Normalization::addRms(graph, input, layer.inputNorm, + buffers.normalized, geometry_.hiddenSize, rows); + + metal::MetalBuffer residual; + std::visit( + [&](const auto &mixer) { + if constexpr (isGdnMixer) { + if constexpr (isQ8) { + operators_.linear().addDecodeBatch(graph, + buffers.normalized, mixer.inputProjectionQ8, + buffers.gdnPacked[gdnIndex], gdnInput, lanes, + stats); + } else { + operators_.linear().addDecodeBatch(graph, + buffers.normalized, mixer.inputProjection, + buffers.gdnPacked[gdnIndex], gdnInput, lanes, + stats); + } + ops::GDN::addDecode( + graph, + {buffers.gdnPacked[gdnIndex], mixer.convolutionWeights, + buffers.currentGdnStates, buffers.nextGdnStates, + buffers.gdnMixed[gdnIndex], mixer.decay, mixer.timeBias, + buffers.gdnDecay[gdnIndex], buffers.gdnBeta[gdnIndex], + buffers.recurrent, mixer.mixerNorm, buffers.gdnHidden, + buffers.arrived, buffers.generation}, + geometry_.gdnShape(), lanes, gdnIndex, + {geometry_.stateLayout.convolutionLayerBytes(), + geometry_.stateLayout.recurrentLayerBytes(), + geometry_.stateLayout.convolutionBytes()}); + if constexpr (isQ8) { + operators_.linear().addResidualBatch( + graph, buffers.gdnHidden, + mixer.outputProjectionQ8, input, buffers.gdnOutput, mixerOutput, + lanes, stats); + } else { + operators_.linear().addResidualBatch( + graph, buffers.gdnHidden, + mixer.outputProjection, input, buffers.gdnOutput, mixerOutput, + lanes, stats); + } + residual = buffers.gdnOutput; + ++gdnIndex; + } else { + if constexpr (isQ8) { + operators_.linear().addDecodeBatch(graph, + buffers.normalized, mixer.inputProjectionQ8, + buffers.fullPacked, attentionInput, lanes, + stats); + } else { + operators_.linear().addDecodeBatch(graph, + buffers.normalized, mixer.inputProjection, + buffers.fullPacked, attentionInput, lanes, + stats); + } + ops::PagedAttention::addVerifyProjection( + graph, buffers.fullPacked, mixer.queryNorm, mixer.keyNorm, + buffers.ropeCos, buffers.ropeSin, buffers.fullQueries, + buffers.chunkKeys[attentionIndex], + buffers.chunkValues[attentionIndex], + ExecutionLimits::targetVerifyRows, tileRows, tileRows, + geometry_.attentionQueryHeads, geometry_.kvLayout, lanes); + ops::PagedAttention::addVerify( + graph, kvLayers[attentionIndex], + {buffers.chunkKeys[attentionIndex], + buffers.chunkValues[attentionIndex], buffers.fullQueries, + buffers.attentionPartials, buffers.attentionStatistics, + buffers.fullAttention, buffers.pageTables}, + q8, verify, attentionPlan); + ops::PagedAttention::addVerifyGate( + graph, buffers.fullPacked, buffers.fullAttention, + buffers.attentionHidden, ExecutionLimits::targetVerifyRows, + tileRows, tileRows, geometry_.attentionQueryHeads, + geometry_.kvLayout, lanes); + if constexpr (isQ8) { + operators_.linear().addResidualBatch( + graph, buffers.attentionHidden, + mixer.outputProjectionQ8, input, buffers.attentionOutput, + mixerOutput, lanes, stats); + } else { + operators_.linear().addResidualBatch( + graph, buffers.attentionHidden, + mixer.outputProjection, input, buffers.attentionOutput, + mixerOutput, lanes, stats); + } + residual = buffers.attentionOutput; + ++attentionIndex; + } + }, + layer.mixer); + + ops::Normalization::addRms(graph, residual, layer.postAttentionNorm, + buffers.normalized, geometry_.hiddenSize, rows); + const ops::LinearMatrix up{geometry_.denseIntermediateSize, geometry_.hiddenSize}; + const ops::LinearMatrix down{geometry_.hiddenSize, geometry_.denseIntermediateSize}; + operators_.linear().addGateUpBatch(graph, buffers.normalized, layer.gateProjection, + layer.upProjection, buffers.denseGateScratch, + buffers.denseIntermediate, up, lanes, stats); + operators_.linear().addResidualBatch( + graph, buffers.denseIntermediate, + layer.downProjection, residual, output, down, lanes, stats); + } + if (gdnIndex != geometry_.stateLayout.layers || + attentionIndex != kvLayers.size()) { + throw std::logic_error("Qwen target layer partition mismatch"); + } + + ops::Normalization::addRms(graph, buffers.hidden[geometry_.layers & 1], + weights.finalNorm, + buffers.finalHidden, geometry_.hiddenSize, rows); + const ops::LinearMatrix head{geometry_.vocabularySize, geometry_.hiddenSize}; + operators_.linear().addDecodeBatch(graph, buffers.finalHidden, + weights.logitsProjection, buffers.logits, head, lanes, + stats); +} + +void Qwen3_8Target::addHead(metal::CommandGraph &graph, + metal::MetalBuffer hidden, + metal::MetalBuffer finalHidden, + metal::MetalBuffer logits, + uint32_t normalizedRows) const { + if (!normalizedRows || + normalizedRows > ExecutionLimits::targetVerifyRows) { + throw std::invalid_argument("invalid Qwen head row count"); + } + std::visit([&](const auto *weights) { + ops::Normalization::addRms(graph, std::move(hidden), weights->finalNorm, + finalHidden, geometry_.hiddenSize, normalizedRows); + const ops::LinearMatrix head{geometry_.vocabularySize, geometry_.hiddenSize}; + operators_.linear().addDecode(graph, std::move(finalHidden), + weights->logitsProjection, std::move(logits), head); + }, weights_); +} + +void Qwen3_8Target::addEmbedding(metal::CommandGraph &graph, + metal::MetalBuffer tokens, + metal::MetalBuffer hidden, + uint32_t rows) const { + std::visit([&](const auto *weights) { + ops::Embedding::add(graph, std::move(tokens), weights->tokenEmbedding, + std::move(hidden), rows); + }, weights_); +} + +void Qwen3_8Target::addStateCommit(metal::CommandGraph &graph, + QwenTargetCommitBuffers buffers, + uint32_t lanes) const { + if (!lanes || lanes > ExecutionLimits::maximumBatchWidth) + throw std::invalid_argument("invalid Qwen state commit batch"); + ops::GDN::addCommit( + graph, + {std::move(buffers.packed), std::move(buffers.mixed), + std::move(buffers.decay), std::move(buffers.beta), buffers.currentStates, + buffers.nextStates, std::move(buffers.retainedCounts)}, + geometry_.gdnShape(), geometry_.stateLayout.layers, lanes, + {geometry_.stateLayout.convolutionLayerBytes(), + geometry_.stateLayout.recurrentLayerBytes(), + geometry_.stateLayout.convolutionBytes()}); +} + +} // namespace splash::model diff --git a/models/qwen38/Qwen3_8Target.hpp b/models/qwen38/Qwen3_8Target.hpp new file mode 100644 index 0000000..9a1b1dc --- /dev/null +++ b/models/qwen38/Qwen3_8Target.hpp @@ -0,0 +1,73 @@ +#pragma once + +#include "models/qwen38/Qwen3_8.hpp" +#include "model/QwenTarget.hpp" +#include "metal/CommandGraph.hpp" +#include "metal/MetalBackend.hpp" +#include "ops/ExecutionPlans.hpp" + +#include +#include + +namespace splash::model { + +class Qwen3_8Target final { +public: + Qwen3_8Target(const Qwen3_8Weights &weights, + const QwenTargetGeometry &geometry, + metal::MetalBackend &backend, + const ops::ExecutionPlans &operators); + Qwen3_8Target(const Qwen3_8Q8Weights &weights, + const QwenTargetGeometry &geometry, + metal::MetalBackend &backend, + const ops::ExecutionPlans &operators); + + void addPrefill( + metal::CommandGraph &graph, QwenTargetPrefillBuffers buffers, + std::span sequences, uint32_t rows, + std::span kvLayers) const; + + void addVerify( + metal::CommandGraph &graph, QwenTargetVerifyBuffers buffers, + std::span kvLayers, + std::span q8, + std::span verify, uint32_t lanes, + ops::Q4DispatchStats &stats) const; + + void addHead(metal::CommandGraph &graph, metal::MetalBuffer hidden, + metal::MetalBuffer finalHidden, metal::MetalBuffer logits, + uint32_t normalizedRows) const; + + void addEmbedding(metal::CommandGraph &graph, metal::MetalBuffer tokens, + metal::MetalBuffer hidden, uint32_t rows) const; + + void addStateCommit(metal::CommandGraph &graph, + QwenTargetCommitBuffers buffers, uint32_t lanes) const; + +private: + using WeightView = + std::variant; + + template + void addPrefillImpl( + const Weights &weights, metal::CommandGraph &graph, + QwenTargetPrefillBuffers buffers, + std::span sequences, uint32_t rows, + std::span kvLayers) const; + + template + void addVerifyImpl( + const Weights &weights, metal::CommandGraph &graph, + QwenTargetVerifyBuffers buffers, + std::span kvLayers, + std::span q8, + std::span verify, uint32_t lanes, + ops::Q4DispatchStats &stats) const; + + WeightView weights_; + const QwenTargetGeometry &geometry_; + metal::MetalBackend &backend_; + const ops::ExecutionPlans &operators_; +}; + +} // namespace splash::model diff --git a/models/qwen38/abi/DraftAttention.h b/models/qwen38/abi/DraftAttention.h new file mode 100644 index 0000000..5e58e80 --- /dev/null +++ b/models/qwen38/abi/DraftAttention.h @@ -0,0 +1,68 @@ +#pragma once + +// Parameter layouts shared by host dispatch code and Metal kernels. +#include "metal/abi/ExecutionGeometry.h" +#ifdef __METAL_VERSION__ +#include +#else +#include +#endif + +struct DraftConvBatchParams { + uint32_t groups; + uint32_t finish; + uint32_t lanes; +}; + +static_assert(sizeof(DraftConvBatchParams) == 12, + "Draft convolution parameters are 12 bytes on both sides"); + +struct DraftQkvBatchParams { + uint32_t groups; + uint32_t lanes; +}; + +static_assert(sizeof(DraftQkvBatchParams) == 8, + "Draft QKV parameters are 8 bytes on both sides"); + +struct DraftAttentionBatchParams { + uint32_t cache_stride; + uint32_t splits; + uint32_t lanes; + uint32_t cache_length[SPLASH_MAXIMUM_BATCH_WIDTH]; +}; + +static_assert(sizeof(DraftAttentionBatchParams) == 28, + "Draft attention parameters are 28 bytes on both sides"); + +struct DraftContextParams { + uint32_t tokens; + uint32_t cache_stride; + uint32_t start_position; +}; + +static_assert(sizeof(DraftContextParams) == 12, + "Draft context prefill parameters are 12 bytes on both sides"); + +struct DraftContextBatchParams { + uint32_t cache_stride; + uint32_t lanes; + uint32_t start_position[SPLASH_MAXIMUM_BATCH_WIDTH]; +}; + +static_assert(sizeof(DraftContextBatchParams) == 24, + "Draft context commit parameters are 24 bytes on both sides"); + +struct CaptureParams { + uint32_t rows; + uint32_t slot; + uint32_t source_start; + uint32_t destination_start; + uint32_t hidden_width; + uint32_t target_width; +}; + +static_assert(sizeof(CaptureParams) == 24, + "Target hidden capture parameters are 24 bytes on both sides"); + +#include "metal/abi/Rows.h" diff --git a/models/qwen38/kernels/capture.metal b/models/qwen38/kernels/capture.metal new file mode 100644 index 0000000..2ccebb0 --- /dev/null +++ b/models/qwen38/kernels/capture.metal @@ -0,0 +1,16 @@ +#include "metal/abi/KernelABI.h" + +kernel void capture_target_hidden(device const bfloat *input [[buffer(0)]], + device bfloat *captured [[buffer(1)]], + constant CaptureParams ¶ms [[buffer(2)]], + uint index [[thread_position_in_grid]], + uint grid_size [[threads_per_grid]]) { + for (uint element = index; element < params.rows * params.hidden_width; + element += grid_size) { + uint row = element / params.hidden_width; + uint dim = element % params.hidden_width; + captured[(params.destination_start + row) * params.target_width + + params.slot * params.hidden_width + dim] = + input[(params.source_start + row) * params.hidden_width + dim]; + } +} diff --git a/models/qwen38/kernels/common/draft_context_kv.h b/models/qwen38/kernels/common/draft_context_kv.h new file mode 100644 index 0000000..ccc98a3 --- /dev/null +++ b/models/qwen38/kernels/common/draft_context_kv.h @@ -0,0 +1,54 @@ +#pragma once + +#include "metal/abi/KernelABI.h" + +inline void draft_context_kv_phase( + device const bfloat *context_qkv, device const bfloat *k_norm, + device const float *rope_cos, device const float *rope_sin, + device bfloat *keys, device bfloat *values, + DraftContextParams params, uint active_tokens, uint task, + uint thread_index, uint lane, uint simd_group, + threadgroup float *reductions, threadgroup bfloat *normalized) { + constexpr uint KVHeads = 8, HeadDim = 128, Window = SPLASH_DRAFT_SLIDING_WINDOW; + constexpr uint QWidth = 4096, KWidth = 1024, PackedWidth = 6144; + uint row = task / KVHeads; + if (row >= active_tokens) + return; + uint head_index = task % KVHeads; + uint position = params.start_position + row; + uint slot = position % Window; + device const bfloat *source = + context_qkv + ulong(row) * PackedWidth + QWidth + head_index * HeadDim; + device bfloat *key = + keys + (ulong(head_index) * params.cache_stride + slot) * HeadDim; + device bfloat *value = + values + ulong(head_index) * HeadDim * params.cache_stride + slot; + + float element = thread_index < HeadDim ? float(source[thread_index]) : 0.0f; + float square_sum = simd_sum(element * element); + if (lane == 0) + reductions[simd_group] = square_sum; + threadgroup_barrier(mem_flags::mem_threadgroup); + if (thread_index == 0) { + float total = 0.0f; + for (uint i = 0; i < 8; ++i) + total += reductions[i]; + reductions[0] = rsqrt(total / HeadDim + 1e-6f); + } + threadgroup_barrier(mem_flags::mem_threadgroup); + if (thread_index < HeadDim) { + normalized[thread_index] = + bfloat(element * reductions[0] * float(k_norm[thread_index])); + value[ulong(thread_index) * params.cache_stride] = + source[KWidth + thread_index]; + } + threadgroup_barrier(mem_flags::mem_threadgroup); + if (thread_index < HeadDim / 2) { + float first = float(normalized[thread_index]); + float second = float(normalized[thread_index + HeadDim / 2]); + float cosine = rope_cos[ulong(row) * (HeadDim / 2) + thread_index]; + float sine = rope_sin[ulong(row) * (HeadDim / 2) + thread_index]; + key[thread_index] = bfloat(first * cosine - second * sine); + key[thread_index + HeadDim / 2] = bfloat(second * cosine + first * sine); + } +} diff --git a/models/qwen38/kernels/draft.metal b/models/qwen38/kernels/draft.metal new file mode 100644 index 0000000..60a52d1 --- /dev/null +++ b/models/qwen38/kernels/draft.metal @@ -0,0 +1,626 @@ +#include "metal/abi/KernelABI.h" +#include "metal/kernels/common/draft_context_kv.h" + +template