rlx_ir/quant.rs
1// RLX — versatile ML compiler + runtime.
2// Copyright (C) 2026 Eugene Hauptmann, Nataliya Kosmyna.
3// SPDX-License-Identifier: MIT OR Apache-2.0
4
5//! Quantization metadata as graph annotations (plan #57).
6//!
7//! Schemes attach per-tensor via [`QuantMap`] on [`crate::Graph`], not inside
8//! [`crate::Node`], so the common case stays lean.
9//!
10//! # GGUF schemes and backends
11//!
12//! All `Gguf*` variants use two-input `Op::DequantMatMul` (`x`, packed weights).
13//! GPU backends share integer **scheme ids** (0–23) in `dequant_gguf` kernels;
14//! legacy tail: Q4_0 = 19, Q8_0 = 20, Q4_1 = 21, Q5_0 = 22, Q5_1 = 23.
15//!
16//! Per-backend dispatch (GPU dequant, fused GEMV, ANE constexpr, TPU compile-time
17//! bake, env toggles): [`docs/gguf-backend-paths.md`](../../docs/gguf-backend-paths.md).
18
19use crate::NodeId;
20use std::collections::HashMap;
21
22/// How a tensor is quantized. Mirrors the schemes RLX needs for LLM
23/// inference on Apple Silicon: blockwise int8 (GPTQ-style),
24/// blockwise int4 (Q4_K), and per-tensor fp8 (e4m3 / e5m2).
25///
26/// Each variant carries the parameters the dequantizer needs to read
27/// at runtime — scale, zero-point, block size. Where these live in
28/// the actual weight tensor is up to the loader (#56).
29#[cfg_attr(feature = "serialize", derive(serde::Serialize, serde::Deserialize))]
30#[derive(Debug, Clone, Copy, PartialEq)]
31pub enum QuantScheme {
32 /// Symmetric int8 with one scale per `block_size` elements.
33 Int8Block { block_size: u32 },
34 /// Asymmetric int8 with scale + zero-point per `block_size` elements.
35 Int8BlockAsym { block_size: u32 },
36 /// Int4 packed two-per-byte, scale per `block_size` elements
37 /// (Q4_K-ish; matches GGUF block layout).
38 Int4Block { block_size: u32 },
39 /// FP8 e4m3 (no scale; same domain as half).
40 Fp8E4m3,
41 /// FP8 e5m2 (no scale; wider range than e4m3).
42 Fp8E5m2,
43 /// GGUF / llama.cpp Q4_K super-block (256 elements / 144 bytes).
44 /// Packs an f16 super-scale + f16 super-min + 8 sub-block 6-bit
45 /// scales + 8 sub-block 6-bit mins + 128 nibbles. Block layout is
46 /// fixed by the format — there's no `block_size` knob.
47 GgufQ4K,
48 /// GGUF Q5_K (256 / 176 bytes). Adds a 32-byte high-bit plane on
49 /// top of Q4_K.
50 GgufQ5K,
51 /// GGUF Q6_K (256 / 210 bytes). Per-sub-block signed scales,
52 /// no min term.
53 GgufQ6K,
54 /// GGUF Q8_K (256 / 276 bytes). Per-super-block f32 scale plus
55 /// i8 quants and a 32-byte sum-of-blocks table that's only used
56 /// by Q8_K × Q8_K matmul accumulation paths.
57 GgufQ8K,
58 /// GGUF Q2_K (256 / 84 bytes). 2-bit quants with per-sub-block scale/min.
59 GgufQ2K,
60 /// GGUF Q3_K (256 / 110 bytes). 3-bit quants with hmask high bit plane.
61 GgufQ3K,
62 /// GGUF Q4_0 (32 / 18 bytes). Legacy llama.cpp block: f16 scale + signed nibbles (−8..7).
63 GgufQ4_0,
64 /// GGUF Q4_1 (32 / 20 bytes). Legacy block: f16 scale + f16 min + unsigned nibbles (0..15).
65 /// GPU kernel scheme id **21** (shared with Metal/CUDA/ROCm/WGPU).
66 GgufQ4_1,
67 /// GGUF Q5_0 (32 / 22 bytes). Legacy block: f16 scale + 32-bit high plane + signed 5-bit quants.
68 /// GPU kernel scheme id **22**.
69 GgufQ5_0,
70 /// GGUF Q5_1 (32 / 24 bytes). Legacy block: f16 scale + f16 min + high plane + unsigned 5-bit quants.
71 /// GPU kernel scheme id **23**.
72 GgufQ5_1,
73 /// GGUF Q8_0 (32 / 34 bytes). Legacy block: f16 scale + 32×i8 quants.
74 GgufQ8_0,
75 /// NVIDIA FP4 (E2M1) block — fixed 16-element groups, FP8 E4M3 block
76 /// scales, optional f32 global scale on input 3 (legacy `zp` slot).
77 /// Used by FLUX.2 / MLX `nvfp4` checkpoints.
78 Nvfp4Block,
79 /// MLX affine quantization (`nn.quantize` / mlx-lm default): packed
80 /// uint codes + per-group f32 scale and bias. Inputs to
81 /// `DequantMatMul`: `x`, `w_q`, `scales`, `biases` (biases in the
82 /// legacy `zp` slot). Typical `bits=4`, `group_size=64`.
83 MlxAffine { bits: u8, group_size: u32 },
84 /// MLX `mxfp4` mode — E2M1 nibbles × per-group scale (E8M0 or FP8).
85 /// Inputs: `x`, `w_q`, `scales`, unused `zp` (pass ones).
86 MlxMxfp4 { group_size: u32 },
87 /// MLX `mxfp8` mode — FP8 E4M3 codes × per-group scale.
88 MlxMxfp8 { group_size: u32 },
89 /// **MxFp4x2** — two-level residual FP4 (E2M1): `value ≈ s0·q0 + s1·q1`,
90 /// each level an E2M1 nibble plane with its own per-group scale. Roughly
91 /// doubles the effective mantissa of MXFP4 (~3.3 → ~6.7 bits) at 2× storage.
92 /// The low-precision analog of double-word; see [`crate::residual`].
93 MxFp4x2Block { group_size: u32 },
94 // ── GGUF IQ-family (sub-byte LUT-coded) ─────────────────────
95 /// IQ4_NL: 4.5 bpw non-linear. 32-element block (18 bytes).
96 GgufIQ4NL,
97 /// IQ4_XS: 4.25 bpw. 256-element super-block (136 bytes).
98 GgufIQ4XS,
99 /// IQ2_XXS: 2.0625 bpw. 256 / 66.
100 GgufIQ2XXS,
101 /// IQ2_XS: 2.3125 bpw. 256 / 74.
102 GgufIQ2XS,
103 /// IQ2_S: 2.5625 bpw. 256 / 82.
104 GgufIQ2S,
105 /// IQ3_XXS: 3.0625 bpw. 256 / 98.
106 GgufIQ3XXS,
107 /// IQ3_S: 3.4375 bpw. 256 / 110.
108 GgufIQ3S,
109 /// IQ1_S: 1.5625 bpw. 256 / 50.
110 GgufIQ1S,
111 /// IQ1_M: 1.75 bpw. 256 / 56.
112 GgufIQ1M,
113 /// TQ1_0: 1.6875 bpw ternary. 256 / 54.
114 GgufTQ1_0,
115 /// TQ2_0: 2.0625 bpw ternary. 256 / 66.
116 GgufTQ2_0,
117 /// MXFP4: OCP microscaling FP4 with E8M0 scale. 32 / 17.
118 GgufMXFP4,
119 /// NVFP4 GGUF variant: E4M3 scale + E2M1 nibbles. 16 / 9.
120 GgufNVFP4,
121 /// Custom 1-bit format (PrismML `Bonsai-27B`, ggml type 41): one
122 /// f16 group scale + 128 sign bits selecting `±d`. 128 / 18 bytes
123 /// (1.125 bpw). See [`crate`] consumers `rlx_gguf::q1_dequant`.
124 GgufQ1_0,
125 /// PrismML / upstream `Q2_0` (ggml type 42): f16 group scale + 128×2-bit
126 /// codes → `(q−1)·d`. 128 / 34 bytes (2.125 bpw). Used by Ternary Bonsai
127 /// (`prism-ml/Ternary-Bonsai-*-gguf`). See `rlx_gguf::q2_dequant`.
128 GgufQ2_0,
129 /// Fermion five-value ternary (`fermion-fv5` fork, ggml type 43): two f32
130 /// per-row scales `s_lo`/`s_hi` + three 256-bit planes (`bp`,`bn`,`br`)
131 /// → `w = (bp−bn)·(br ? s_hi : s_lo)`, five values `{0, ±s_lo, ±s_hi}`.
132 /// 256 / 104 bytes (3.25 bpw). All Neutrino transformer linears.
133 /// See `rlx_gguf::fv5_dequant`. CPU-only (no GPU kernel — matches the fork).
134 GgufFV5,
135 /// Fermion int8 companion (`fermion-fv5` fork, ggml type 44): one f32
136 /// per-row scale + 256 int8 codes → `w = s·q`. 256 / 260 bytes (8.125 bpw).
137 /// Neutrino's untied int8 `token_embd` / `output` (lm_head).
138 /// See `rlx_gguf::fv5_dequant`.
139 GgufFV5B,
140}
141
142/// Single source of truth for GGUF → GPU `dequant_gguf` scheme ids.
143///
144/// Expanding this macro inside `impl QuantScheme` defines:
145/// - [`QuantScheme::gpu_dequant_scheme_id`]
146/// - [`QuantScheme::from_gpu_dequant_scheme_id`]
147/// - test helper [`QuantScheme::GPU_DEQUANT_SCHEME_ID_PAIRS`]
148///
149/// GPU backends (`gguf_host::gguf_scheme_id` / `scheme_from_id`) must
150/// delegate here — do not re-list variants by hand.
151macro_rules! define_gguf_gpu_dequant_ids {
152 ($(($variant:ident, $id:literal)),+ $(,)?) => {
153 /// Canonical numeric id for the shared on-device GGUF dequant kernel
154 /// (`dequant_gguf` in MSL / CU / WGSL / GLSL).
155 ///
156 /// Generated by `define_gguf_gpu_dequant_ids!` so encode and
157 /// [`Self::from_gpu_dequant_scheme_id`] share one table — backends
158 /// must only call these helpers (no hand-rolled `match` in
159 /// `gguf_host`). Adding a scheme is one macro row + the matching
160 /// kernel branch. Guarded by `gpu_dequant_scheme_id_is_stable`.
161 pub const fn gpu_dequant_scheme_id(self) -> Option<u32> {
162 match self {
163 $(Self::$variant => Some($id),)+
164 _ => None,
165 }
166 }
167
168 /// Inverse of [`Self::gpu_dequant_scheme_id`].
169 pub const fn from_gpu_dequant_scheme_id(id: u32) -> Option<Self> {
170 match id {
171 $($id => Some(Self::$variant),)+
172 _ => None,
173 }
174 }
175
176 /// `(scheme, id)` pairs for tests / docs — keep in sync via the macro.
177 #[cfg(test)]
178 pub(crate) const GPU_DEQUANT_SCHEME_ID_PAIRS: &'static [(Self, u32)] = &[
179 $((Self::$variant, $id),)+
180 ];
181 };
182}
183
184impl QuantScheme {
185 /// Bits per element after packing (×10 for K-quants since they
186 /// have fractional bit budgets — divide by 10 when comparing).
187 pub const fn bits_per_element_x10(self) -> u32 {
188 match self {
189 Self::Int8Block { .. } | Self::Int8BlockAsym { .. } => 80,
190 Self::Int4Block { .. } => 40,
191 Self::Fp8E4m3 | Self::Fp8E5m2 => 80,
192 // GGUF K-quants: header + per-element bits over a 256-element block.
193 Self::GgufQ4K => 45, // 144 bytes / 256 elems × 8 = 4.5 bpe
194 Self::GgufQ5K => 55, // 176 / 256 × 8 ≈ 5.5
195 Self::GgufQ6K => 66, // 210 / 256 × 8 ≈ 6.5625 → 66 (rounded)
196 Self::GgufQ8K => 91, // 292 / 256 × 8 ≈ 9.125 → 91
197 Self::GgufQ2K => 26, // 84 / 256 × 8 ≈ 2.625 → 26
198 Self::GgufQ3K => 34, // 110 / 256 × 8 ≈ 3.4375 → 34
199 Self::GgufQ4_0 => 45, // 18 / 32 × 8 = 4.5 bpe
200 Self::GgufQ4_1 => 50, // 20 / 32 × 8 = 5.0 bpe
201 Self::GgufQ5_0 => 55, // 22 / 32 × 8 = 5.5 bpe
202 Self::GgufQ5_1 => 60, // 24 / 32 × 8 = 6.0 bpe
203 Self::GgufQ8_0 => 85, // 34 / 32 × 8 = 8.5 bpe
204 Self::Nvfp4Block => 40,
205 Self::MlxAffine { bits, .. } => (bits as u32) * 10,
206 Self::MlxMxfp4 { .. } => 40,
207 Self::MlxMxfp8 { .. } => 80,
208 Self::MxFp4x2Block { .. } => 84, // 2× E2M1 nibbles + 2 group scales
209
210 Self::GgufIQ4NL => 45,
211 Self::GgufIQ4XS => 42, // 136/256 × 8 = 4.25
212 Self::GgufIQ2XXS => 20,
213 Self::GgufIQ2XS => 23,
214 Self::GgufIQ2S => 25,
215 Self::GgufIQ3XXS => 30,
216 Self::GgufIQ3S => 34,
217 Self::GgufIQ1S => 15,
218 Self::GgufIQ1M => 17,
219 Self::GgufTQ1_0 => 16, // 54/256 × 8 = 1.6875 → 16
220 Self::GgufTQ2_0 => 20,
221 Self::GgufMXFP4 => 42,
222 Self::GgufNVFP4 => 45,
223 Self::GgufQ1_0 => 11, // 18 bytes / 128 elems × 8 = 1.125 bpe
224 Self::GgufQ2_0 => 21, // 34 bytes / 128 elems × 8 = 2.125 bpe
225 Self::GgufFV5 => 32, // 104 bytes / 256 elems × 8 = 3.25 bpe
226 Self::GgufFV5B => 81, // 260 bytes / 256 elems × 8 = 8.125 bpe
227 }
228 }
229
230 /// Bits per element after packing (rounded down). Use
231 /// `bits_per_element_x10` for the K-quant fractional values.
232 pub const fn bits_per_element(self) -> u32 {
233 self.bits_per_element_x10() / 10
234 }
235
236 // Table defined once via `define_gguf_gpu_dequant_ids!` above.
237 define_gguf_gpu_dequant_ids! {
238 (GgufQ4K, 0),
239 (GgufQ5K, 1),
240 (GgufQ6K, 2),
241 (GgufQ8K, 3),
242 (GgufQ2K, 4),
243 (GgufQ3K, 5),
244 (GgufIQ4NL, 6),
245 (GgufIQ4XS, 7),
246 (GgufTQ1_0, 8),
247 (GgufTQ2_0, 9),
248 (GgufMXFP4, 10),
249 (GgufNVFP4, 11),
250 (GgufIQ2XXS, 12),
251 (GgufIQ2XS, 13),
252 (GgufIQ2S, 14),
253 (GgufIQ3XXS, 15),
254 (GgufIQ3S, 16),
255 (GgufIQ1S, 17),
256 (GgufIQ1M, 18),
257 (GgufQ4_0, 19),
258 (GgufQ8_0, 20),
259 (GgufQ4_1, 21),
260 (GgufQ5_0, 22),
261 (GgufQ5_1, 23),
262 (GgufQ1_0, 24),
263 (GgufQ2_0, 25),
264 (GgufFV5, 26),
265 (GgufFV5B, 27),
266 }
267
268 /// True if this scheme requires a per-block scale tensor on the side.
269 pub const fn has_scale(self) -> bool {
270 matches!(
271 self,
272 Self::Int8Block { .. }
273 | Self::Int8BlockAsym { .. }
274 | Self::Int4Block { .. }
275 | Self::Nvfp4Block
276 | Self::MlxAffine { .. }
277 | Self::MlxMxfp4 { .. }
278 | Self::MlxMxfp8 { .. }
279 | Self::MxFp4x2Block { .. }
280 )
281 }
282
283 /// True for NVFP4 / MLX mxfp block scales stored as FP8 / E8M0 bytes (not f32).
284 pub const fn scale_is_fp8(self) -> bool {
285 matches!(
286 self,
287 Self::Nvfp4Block | Self::MlxMxfp4 { .. } | Self::MlxMxfp8 { .. }
288 )
289 }
290
291 /// Fixed NVFP4 group size along K (0 for other schemes).
292 pub const fn nvfp4_group_size(self) -> u32 {
293 match self {
294 Self::Nvfp4Block => crate::nvfp4::NVFP4_GROUP_SIZE as u32,
295 _ => 0,
296 }
297 }
298
299 /// For [`Self::MxFp4x2Block`]: `(per-element format, residual levels, group
300 /// size)`; `None` for every other scheme. Ties the scheme to the shared
301 /// residual codec in [`crate::residual`].
302 pub const fn mxfp4x2_config(self) -> Option<(ScaledFormat, u32, u32)> {
303 match self {
304 Self::MxFp4x2Block { group_size } => Some((ScaledFormat::F4E2M1, 2, group_size)),
305 _ => None,
306 }
307 }
308
309 /// True if this scheme requires a per-block zero-point / bias tensor.
310 pub const fn has_zero_point(self) -> bool {
311 matches!(self, Self::Int8BlockAsym { .. } | Self::MlxAffine { .. })
312 }
313
314 /// True for MLX-native affine / mxfp schemes (not GGUF, not legacy int blocks).
315 pub const fn is_mlx(self) -> bool {
316 matches!(
317 self,
318 Self::MlxAffine { .. } | Self::MlxMxfp4 { .. } | Self::MlxMxfp8 { .. }
319 )
320 }
321
322 /// MLX group size along K (0 when not an MLX scheme).
323 pub const fn mlx_group_size(self) -> u32 {
324 match self {
325 Self::MlxAffine { group_size, .. }
326 | Self::MlxMxfp4 { group_size }
327 | Self::MlxMxfp8 { group_size } => group_size,
328 _ => 0,
329 }
330 }
331
332 /// GPU launch args for MLX dequant-matmul kernels: `(kind, bits, group_size)`.
333 ///
334 /// `kind`: 0 = [`Self::MlxAffine`], 1 = [`Self::MlxMxfp4`], 2 = [`Self::MlxMxfp8`].
335 /// `bits` is 0 for mxfp schemes. Returns `None` for non-MLX schemes.
336 pub const fn mlx_gpu_launch(self) -> Option<(u32, u32, u32)> {
337 match self {
338 Self::MlxAffine { bits, group_size } => Some((0, bits as u32, group_size)),
339 Self::MlxMxfp4 { group_size } => Some((1, 0, group_size)),
340 Self::MlxMxfp8 { group_size } => Some((2, 0, group_size)),
341 _ => None,
342 }
343 }
344
345 /// GGUF K-quant block size (256 elements) — meaningless for the
346 /// non-GGUF schemes (returns 0).
347 pub const fn gguf_block_size(self) -> u32 {
348 match self {
349 Self::GgufQ4K
350 | Self::GgufQ5K
351 | Self::GgufQ6K
352 | Self::GgufQ8K
353 | Self::GgufQ2K
354 | Self::GgufQ3K
355 | Self::GgufIQ4XS
356 | Self::GgufIQ2XXS
357 | Self::GgufIQ2XS
358 | Self::GgufIQ2S
359 | Self::GgufIQ3XXS
360 | Self::GgufIQ3S
361 | Self::GgufIQ1S
362 | Self::GgufIQ1M
363 | Self::GgufTQ1_0
364 | Self::GgufTQ2_0
365 | Self::GgufFV5
366 | Self::GgufFV5B => 256,
367 Self::GgufQ4_0
368 | Self::GgufQ4_1
369 | Self::GgufQ5_0
370 | Self::GgufQ5_1
371 | Self::GgufQ8_0
372 | Self::GgufIQ4NL
373 | Self::GgufMXFP4 => 32,
374 Self::GgufNVFP4 => 16,
375 Self::GgufQ1_0 => 128,
376 Self::GgufQ2_0 => 128,
377 _ => 0,
378 }
379 }
380
381 /// Bytes per GGUF super-block. 0 for non-GGUF schemes.
382 pub const fn gguf_block_bytes(self) -> u32 {
383 match self {
384 Self::GgufQ4K => 144, // f16 d + f16 dmin + 12 packed scales + 128 nibbles
385 Self::GgufQ5K => 176, // + 32-byte high-bit plane
386 Self::GgufQ6K => 210, // 128 ql + 64 qh + 16 i8 scales + f16 d
387 Self::GgufQ8K => 292, // f32 d + 256 i8 + 16 i16 bsums = 4 + 256 + 32
388 Self::GgufQ2K => 84, // f16 d + f16 dmin + 16 scales + 64 qs
389 Self::GgufQ3K => 110, // f16 d + 12 scales + 32 hmask + 64 qs
390 Self::GgufQ4_0 => 18, // f16 d + 16 packed nibbles
391 Self::GgufQ4_1 => 20, // f16 d + f16 min + 16 packed nibbles
392 Self::GgufQ5_0 => 22, // f16 d + 32-bit qh + 16 packed nibbles
393 Self::GgufQ5_1 => 24, // f16 d + f16 min + 32-bit qh + 16 packed nibbles
394 Self::GgufQ8_0 => 34, // f16 d + 32 i8 quants
395 Self::GgufIQ4NL => 18,
396 Self::GgufIQ4XS => 136,
397 Self::GgufIQ2XXS => 66,
398 Self::GgufIQ2XS => 74,
399 Self::GgufIQ2S => 82,
400 Self::GgufIQ3XXS => 98,
401 Self::GgufIQ3S => 110,
402 Self::GgufIQ1S => 50,
403 Self::GgufIQ1M => 56,
404 Self::GgufTQ1_0 => 54,
405 Self::GgufTQ2_0 => 66,
406 Self::GgufMXFP4 => 17,
407 Self::GgufNVFP4 => 9,
408 Self::GgufQ1_0 => 18, // f16 scale + 128 sign bits
409 Self::GgufQ2_0 => 34, // Metal fused Q2_0 block (128 elems)
410 Self::GgufFV5 => 104, // f32 s_lo + f32 s_hi + 3×32B planes (256 elems)
411 Self::GgufFV5B => 260, // f32 s + 256 int8 (256 elems)
412 _ => 0,
413 }
414 }
415
416 /// True for any GGUF-format block scheme. GGUF schemes carry
417 /// their scales / mins / sub-block metadata *inside* the packed
418 /// weight bytes — they don't need separate `scale` / `zp`
419 /// tensors fed alongside as the legacy `Int8Block` paths do.
420 pub const fn is_gguf(self) -> bool {
421 matches!(
422 self,
423 Self::GgufQ4K
424 | Self::GgufQ5K
425 | Self::GgufQ6K
426 | Self::GgufQ8K
427 | Self::GgufQ2K
428 | Self::GgufQ3K
429 | Self::GgufQ4_0
430 | Self::GgufQ4_1
431 | Self::GgufQ5_0
432 | Self::GgufQ5_1
433 | Self::GgufQ8_0
434 | Self::GgufIQ4NL
435 | Self::GgufIQ4XS
436 | Self::GgufIQ2XXS
437 | Self::GgufIQ2XS
438 | Self::GgufIQ2S
439 | Self::GgufIQ3XXS
440 | Self::GgufIQ3S
441 | Self::GgufIQ1S
442 | Self::GgufIQ1M
443 | Self::GgufTQ1_0
444 | Self::GgufTQ2_0
445 | Self::GgufMXFP4
446 | Self::GgufNVFP4
447 | Self::GgufQ1_0
448 | Self::GgufQ2_0
449 | Self::GgufFV5
450 | Self::GgufFV5B
451 )
452 }
453}
454
455impl std::fmt::Display for QuantScheme {
456 fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
457 match self {
458 Self::Int8Block { block_size } => write!(f, "int8/{block_size}"),
459 Self::Int8BlockAsym { block_size } => write!(f, "int8a/{block_size}"),
460 Self::Int4Block { block_size } => write!(f, "int4/{block_size}"),
461 Self::Fp8E4m3 => write!(f, "fp8e4m3"),
462 Self::Fp8E5m2 => write!(f, "fp8e5m2"),
463 Self::GgufQ4K => write!(f, "gguf_q4k"),
464 Self::GgufQ5K => write!(f, "gguf_q5k"),
465 Self::GgufQ6K => write!(f, "gguf_q6k"),
466 Self::GgufQ8K => write!(f, "gguf_q8k"),
467 Self::GgufQ2K => write!(f, "gguf_q2k"),
468 Self::GgufQ3K => write!(f, "gguf_q3k"),
469 Self::GgufQ4_0 => write!(f, "gguf_q4_0"),
470 Self::GgufQ4_1 => write!(f, "gguf_q4_1"),
471 Self::GgufQ5_0 => write!(f, "gguf_q5_0"),
472 Self::GgufQ5_1 => write!(f, "gguf_q5_1"),
473 Self::GgufQ8_0 => write!(f, "gguf_q8_0"),
474 Self::Nvfp4Block => write!(f, "nvfp4/16"),
475 Self::MlxAffine { bits, group_size } => {
476 write!(f, "mlx_affine/{bits}/{group_size}")
477 }
478 Self::MlxMxfp4 { group_size } => write!(f, "mlx_mxfp4/{group_size}"),
479 Self::MxFp4x2Block { group_size } => write!(f, "mxfp4x2/{group_size}"),
480 Self::MlxMxfp8 { group_size } => write!(f, "mlx_mxfp8/{group_size}"),
481 Self::GgufIQ4NL => write!(f, "gguf_iq4_nl"),
482 Self::GgufIQ4XS => write!(f, "gguf_iq4_xs"),
483 Self::GgufIQ2XXS => write!(f, "gguf_iq2_xxs"),
484 Self::GgufIQ2XS => write!(f, "gguf_iq2_xs"),
485 Self::GgufIQ2S => write!(f, "gguf_iq2_s"),
486 Self::GgufIQ3XXS => write!(f, "gguf_iq3_xxs"),
487 Self::GgufIQ3S => write!(f, "gguf_iq3_s"),
488 Self::GgufIQ1S => write!(f, "gguf_iq1_s"),
489 Self::GgufIQ1M => write!(f, "gguf_iq1_m"),
490 Self::GgufTQ1_0 => write!(f, "gguf_tq1_0"),
491 Self::GgufTQ2_0 => write!(f, "gguf_tq2_0"),
492 Self::GgufMXFP4 => write!(f, "gguf_mxfp4"),
493 Self::GgufNVFP4 => write!(f, "gguf_nvfp4"),
494 Self::GgufQ1_0 => write!(f, "gguf_q1_0"),
495 Self::GgufQ2_0 => write!(f, "gguf_q2_0"),
496 Self::GgufFV5 => write!(f, "gguf_fv5"),
497 Self::GgufFV5B => write!(f, "gguf_fv5b"),
498 }
499 }
500}
501
502/// Element format for a **native low-precision tensor-core GEMM** operand
503/// (see [`crate::op::Op::ScaledMatMul`]).
504///
505/// Distinct from [`QuantScheme`]: a `QuantScheme` is block-scaled *storage*
506/// that the CPU/GPU decodes to f32 *before* a normal sgemm. A `ScaledFormat`
507/// is the raw element encoding hardware tensor cores consume **directly**, with
508/// f32 accumulation — the whole point of FP8/FP6/FP4 on Hopper / Ada /
509/// Blackwell / CDNA3 / CDNA4. The per-block/per-tensor scale layout is
510/// orthogonal and lives in [`ScaleLayout`].
511///
512/// Operands flow through the graph as `DType::U8` byte buffers (one code per
513/// byte on the CPU oracle; packed on GPU); the format is carried on the op,
514/// not the dtype, so no `DType` variant is needed.
515#[cfg_attr(feature = "serialize", derive(serde::Serialize, serde::Deserialize))]
516#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
517pub enum ScaledFormat {
518 /// OCP FP8 E4M3 — bias 7, no infinities, only `S.1111.111` is NaN.
519 /// Max ±448. Hopper / Ada / Blackwell; weights + forward activations.
520 F8E4M3,
521 /// OCP FP8 E5M2 — bias 15, IEEE-like inf/NaN at max exponent.
522 /// Max ±57344. Wider range — the gradient format.
523 F8E5M2,
524 /// AMD "FNUZ" FP8 E4M3 — bias 8, single NaN at `0x80`, no inf, no −0.
525 /// Max ±240. CDNA3 / MI300.
526 F8E4M3Fnuz,
527 /// AMD "FNUZ" FP8 E5M2 — bias 16, single NaN at `0x80`, no inf, no −0.
528 /// Max ±57344. CDNA3 / MI300.
529 F8E5M2Fnuz,
530 /// MX FP6 E2M3 — bias 1, all 64 codes finite. Max ±7.5. Blackwell / CDNA4.
531 F6E2M3,
532 /// MX FP6 E3M2 — bias 3, all 64 codes finite. Max ±28. Blackwell / CDNA4.
533 F6E3M2,
534 /// FP4 E2M1 — all 16 codes finite. Max ±6. Blackwell / CDNA4.
535 /// Shared by NVFP4 and MXFP4 — the [`ScaleLayout`] tells them apart.
536 F4E2M1,
537 /// Arbitrary sub-byte minifloat parameterized by exponent / mantissa width
538 /// — the `fNeXmY` family (`N = 1 + exp_bits + mant_bits` total bits).
539 ///
540 /// All-finite (no infinities, no NaN, no AMD FNUZ), IEEE-style gradual
541 /// underflow (subnormals when `exp == 0`), sign in bit `exp_bits +
542 /// mant_bits`, one code per byte. The whole code must fit in a byte, so
543 /// `1 + exp_bits + mant_bits <= 8` and `exp_bits >= 1`.
544 ///
545 /// This is a *research / experimental* encoding: it has no hardware
546 /// tensor-core GEMM, so it always runs the decode-and-accumulate path (CPU
547 /// oracle + generic GPU kernel). Build one with [`ScaledFormat::custom`]
548 /// (IEEE bias `2^(exp_bits-1) - 1`) or [`ScaledFormat::custom_with_bias`],
549 /// or parse a name via `"f4e3m0".parse()`.
550 ///
551 /// Example — `f4e3m0` (`exp_bits: 3, mant_bits: 0, bias: 3`): the 16 codes
552 /// are `±0` and `±{0.25, 0.5, 1, 2, 4, 8, 16}` — a signed power-of-two
553 /// (near-logarithmic) 4-bit format.
554 Custom {
555 exp_bits: u8,
556 mant_bits: u8,
557 bias: i8,
558 },
559}
560
561impl ScaledFormat {
562 /// Total bit width of one element code (4, 6, or 8).
563 pub const fn bit_width(self) -> u32 {
564 match self {
565 Self::F8E4M3 | Self::F8E5M2 | Self::F8E4M3Fnuz | Self::F8E5M2Fnuz => 8,
566 Self::F6E2M3 | Self::F6E3M2 => 6,
567 Self::F4E2M1 => 4,
568 Self::Custom {
569 exp_bits,
570 mant_bits,
571 ..
572 } => 1 + exp_bits as u32 + mant_bits as u32,
573 }
574 }
575
576 /// `(exponent_bits, mantissa_bits, exponent_bias)`.
577 pub const fn fields(self) -> (u32, u32, i32) {
578 match self {
579 Self::F8E4M3 => (4, 3, 7),
580 Self::F8E5M2 => (5, 2, 15),
581 Self::F8E4M3Fnuz => (4, 3, 8),
582 Self::F8E5M2Fnuz => (5, 2, 16),
583 Self::F6E2M3 => (2, 3, 1),
584 Self::F6E3M2 => (3, 2, 3),
585 Self::F4E2M1 => (2, 1, 1),
586 Self::Custom {
587 exp_bits,
588 mant_bits,
589 bias,
590 } => (exp_bits as u32, mant_bits as u32, bias as i32),
591 }
592 }
593
594 /// Build an arbitrary all-finite minifloat with `exp_bits` exponent and
595 /// `mant_bits` mantissa bits, using the IEEE-style bias `2^(exp_bits-1) - 1`
596 /// — the convention every named rlx format follows (E4M3 → 7, E5M2 → 15,
597 /// E2M1 → 1, …). The whole code must fit in a byte. `const` — usable in
598 /// `const` contexts and pattern-free construction.
599 ///
600 /// Panics if `exp_bits == 0` or `1 + exp_bits + mant_bits > 8`.
601 ///
602 /// ```
603 /// use rlx_ir::ScaledFormat;
604 /// const F4E3M0: ScaledFormat = ScaledFormat::custom(3, 0);
605 /// assert_eq!(F4E3M0.to_string(), "f4e3m0");
606 /// assert_eq!(F4E3M0.exp_bits(), 3);
607 /// assert_eq!(F4E3M0.mant_bits(), 0);
608 /// // Nearest representable value ("quantize" a single f32):
609 /// assert_eq!(F4E3M0.quantize(1.4), 1.0);
610 /// assert_eq!(F4E3M0.max_finite(), 16.0);
611 /// ```
612 pub const fn custom(exp_bits: u8, mant_bits: u8) -> Self {
613 assert!(exp_bits >= 1, "minifloat needs at least one exponent bit");
614 assert!(
615 1 + exp_bits + mant_bits <= 8,
616 "minifloat code must fit in a byte (1 + exp + mant <= 8)"
617 );
618 let bias = (1i32 << (exp_bits - 1)) - 1;
619 Self::Custom {
620 exp_bits,
621 mant_bits,
622 bias: bias as i8,
623 }
624 }
625
626 /// Like [`custom`](Self::custom) but with an explicit exponent bias
627 /// (for formats that don't use the IEEE `2^(e-1)-1` convention). `const`.
628 pub const fn custom_with_bias(exp_bits: u8, mant_bits: u8, bias: i8) -> Self {
629 assert!(exp_bits >= 1, "minifloat needs at least one exponent bit");
630 assert!(
631 1 + exp_bits + mant_bits <= 8,
632 "minifloat code must fit in a byte (1 + exp + mant <= 8)"
633 );
634 Self::Custom {
635 exp_bits,
636 mant_bits,
637 bias,
638 }
639 }
640
641 /// The seven named hardware element formats, for enumeration / format sweeps.
642 pub const NAMED: [ScaledFormat; 7] = [
643 Self::F8E4M3,
644 Self::F8E5M2,
645 Self::F8E4M3Fnuz,
646 Self::F8E5M2Fnuz,
647 Self::F6E2M3,
648 Self::F6E3M2,
649 Self::F4E2M1,
650 ];
651
652 /// Exponent-field bit count (`X` in `fNeXmY`).
653 pub const fn exp_bits(self) -> u32 {
654 self.fields().0
655 }
656 /// Mantissa-field bit count (`Y` in `fNeXmY`; `0` for a pure power-of-two
657 /// format such as `f4e3m0`).
658 pub const fn mant_bits(self) -> u32 {
659 self.fields().1
660 }
661 /// Exponent bias.
662 pub const fn bias(self) -> i32 {
663 self.fields().2
664 }
665 /// True for a parameterized [`Custom`](Self::Custom) format (no hardware
666 /// tensor core — always runs the decode path).
667 pub const fn is_custom(self) -> bool {
668 matches!(self, Self::Custom { .. })
669 }
670 /// True for one of the seven [`NAMED`](Self::NAMED) hardware formats.
671 pub const fn is_named(self) -> bool {
672 !self.is_custom()
673 }
674
675 /// AMD OCP-FNUZ encoding (single NaN at `0x80`, no inf, no −0).
676 pub const fn is_fnuz(self) -> bool {
677 matches!(self, Self::F8E4M3Fnuz | Self::F8E5M2Fnuz)
678 }
679
680 /// True for IEEE-like formats carrying inf / NaN at the max exponent
681 /// (OCP E5M2 only — E4M3 is finite-with-one-NaN, FP6/FP4 are all-finite).
682 pub const fn has_inf(self) -> bool {
683 matches!(self, Self::F8E5M2)
684 }
685
686 /// Largest finite magnitude representable (used as the amax divisor when
687 /// computing a per-tensor / per-block scale).
688 pub fn max_finite(self) -> f32 {
689 crate::lowp_codec::max_finite(self)
690 }
691
692 /// Decode one packed code to f32 (bit-exact; `±inf` / `NaN` for the formats
693 /// that encode them). Method form of [`crate::lowp_codec::decode`].
694 pub fn decode(self, code: u8) -> f32 {
695 crate::lowp_codec::decode(self, code)
696 }
697
698 /// Encode an f32 to its nearest representable code (round-half-to-even,
699 /// saturating overflow / `±inf` to `±max_finite`, `NaN → 0`). Method form of
700 /// [`crate::lowp_codec::encode`].
701 pub fn encode(self, x: f32) -> u8 {
702 crate::lowp_codec::encode(self, x)
703 }
704
705 /// Round-trip `x` through the format — the nearest value it can represent.
706 /// Handy for eyeballing a format's resolution without building a graph
707 /// (e.g. `ScaledFormat::custom(3, 0).quantize(1.4) == 1.0`).
708 pub fn quantize(self, x: f32) -> f32 {
709 self.decode(self.encode(x))
710 }
711
712 /// Every finite value the format represents, ascending and deduplicated —
713 /// the format's grid. Useful for inspecting a research minifloat, e.g.
714 /// `ScaledFormat::custom(3, 0).representable_values()` yields
715 /// `[-16, -8, -4, -2, -1, -0.5, -0.25, 0, 0.25, 0.5, 1, 2, 4, 8, 16]`.
716 pub fn representable_values(self) -> Vec<f32> {
717 let n = 1u16 << self.bit_width();
718 let mut v: Vec<f32> = (0..n)
719 .map(|c| self.decode(c as u8))
720 .filter(|x| x.is_finite())
721 .collect();
722 v.sort_by(|a, b| a.partial_cmp(b).unwrap());
723 v.dedup();
724 v
725 }
726
727 /// The GPU dispatch word passed to `scaled_lowp_general.cu` (`rlx_decode_lowp`).
728 ///
729 /// For the seven named formats this is a small stable id matching the
730 /// kernel's `switch`: e4m3=0, e5m2=1, e4m3fnuz=2, e5m2fnuz=3, e2m3=4,
731 /// e3m2=5, e2m1=6.
732 ///
733 /// For a [`Custom`](Self::Custom) format there is no fixed id, so this
734 /// returns a **packed field descriptor** with the top bit set as a
735 /// sentinel: `0x8000_0000 | exp_bits | mant_bits<<4 | (bias as u8)<<8`.
736 /// The kernel detects the sentinel bit and decodes generically from the
737 /// unpacked `(exp_bits, mant_bits, bias)` — so a new format needs no kernel
738 /// edit. The named ids stay in `0..=6` (top bit clear), so the existing
739 /// hardware `switch` path is unchanged.
740 pub const fn kernel_id(self) -> u32 {
741 match self {
742 Self::F8E4M3 => 0,
743 Self::F8E5M2 => 1,
744 Self::F8E4M3Fnuz => 2,
745 Self::F8E5M2Fnuz => 3,
746 Self::F6E2M3 => 4,
747 Self::F6E3M2 => 5,
748 Self::F4E2M1 => 6,
749 Self::Custom {
750 exp_bits,
751 mant_bits,
752 bias,
753 } => {
754 0x8000_0000
755 | (exp_bits as u32 & 0xF)
756 | ((mant_bits as u32 & 0xF) << 4)
757 | (((bias as u8) as u32) << 8)
758 }
759 }
760 }
761
762 /// True for the OCP FP8 variants that the native cublasLt / hipBLASLt FP8
763 /// GEMM accepts (per-tensor only). Other formats use the decode fallback.
764 pub const fn is_native_fp8(self) -> bool {
765 matches!(self, Self::F8E4M3 | Self::F8E5M2)
766 }
767}
768
769impl std::fmt::Display for ScaledFormat {
770 fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
771 let s = match self {
772 Self::F8E4M3 => "f8e4m3",
773 Self::F8E5M2 => "f8e5m2",
774 Self::F8E4M3Fnuz => "f8e4m3fnuz",
775 Self::F8E5M2Fnuz => "f8e5m2fnuz",
776 Self::F6E2M3 => "f6e2m3",
777 Self::F6E3M2 => "f6e3m2",
778 Self::F4E2M1 => "f4e2m1",
779 // `fNeXmY`, N = 1 + exp + mant. The bias is implied by the width
780 // (IEEE convention) and not rendered; round-trips through `FromStr`.
781 Self::Custom {
782 exp_bits,
783 mant_bits,
784 ..
785 } => {
786 return write!(
787 f,
788 "f{}e{}m{}",
789 1 + exp_bits + mant_bits,
790 exp_bits,
791 mant_bits
792 );
793 }
794 };
795 f.write_str(s)
796 }
797}
798
799impl std::str::FromStr for ScaledFormat {
800 type Err = String;
801
802 /// Parse a format name. The seven named formats (`"f8e4m3"`, `"f4e2m1"`,
803 /// the `…fnuz` variants, …) keep their exact hardware semantics (FNUZ,
804 /// inf/NaN); any other `fNeXmY` string becomes an all-finite
805 /// [`Custom`](Self::Custom) with the IEEE bias. `N` must equal `1 + X + Y`
806 /// and the code must fit in a byte (`N <= 8`, `X >= 1`).
807 fn from_str(s: &str) -> Result<Self, Self::Err> {
808 match s {
809 "f8e4m3" => return Ok(Self::F8E4M3),
810 "f8e5m2" => return Ok(Self::F8E5M2),
811 "f8e4m3fnuz" => return Ok(Self::F8E4M3Fnuz),
812 "f8e5m2fnuz" => return Ok(Self::F8E5M2Fnuz),
813 "f6e2m3" => return Ok(Self::F6E2M3),
814 "f6e3m2" => return Ok(Self::F6E3M2),
815 "f4e2m1" => return Ok(Self::F4E2M1),
816 _ => {}
817 }
818 let err = || format!("invalid minifloat format {s:?} (expected e.g. \"f4e3m0\")");
819 let rest = s.strip_prefix('f').ok_or_else(err)?;
820 let (total, rest) = take_leading_u32(rest).ok_or_else(err)?;
821 let rest = rest.strip_prefix('e').ok_or_else(err)?;
822 let (exp, rest) = take_leading_u32(rest).ok_or_else(err)?;
823 let rest = rest.strip_prefix('m').ok_or_else(err)?;
824 let (mant, rest) = take_leading_u32(rest).ok_or_else(err)?;
825 if !rest.is_empty() || exp == 0 || total != 1 + exp + mant || 1 + exp + mant > 8 {
826 return Err(err());
827 }
828 Ok(Self::custom(exp as u8, mant as u8))
829 }
830}
831
832/// Split the leading run of ASCII digits off `s`, returning `(value, tail)`.
833/// `None` if `s` doesn't start with a digit.
834fn take_leading_u32(s: &str) -> Option<(u32, &str)> {
835 let end = s.find(|c: char| !c.is_ascii_digit()).unwrap_or(s.len());
836 if end == 0 {
837 return None;
838 }
839 Some((s[..end].parse().ok()?, &s[end..]))
840}
841
842/// How scale factors are laid out for an [`crate::op::Op::ScaledMatMul`]
843/// operand. The reconstructed value of element `i` is
844/// `decode(code[i]) * scale(block_of(i))`.
845#[cfg_attr(feature = "serialize", derive(serde::Serialize, serde::Deserialize))]
846#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
847pub enum ScaleLayout {
848 /// One f32 amax scale for the whole operand (classic per-tensor FP8 GEMM).
849 PerTensor,
850 /// OCP microscaling: one power-of-two **E8M0** scale per `block`
851 /// consecutive elements along K (MXFP8 / MXFP6 / MXFP4). Scale tensor
852 /// is `DType::U8` (E8M0 bytes).
853 BlockMxE8M0 { block: u32 },
854 /// NVFP4: one FP8 **E4M3** scale per `group` (16) elements along K, plus
855 /// an optional per-tensor f32 global. Scale tensor is `DType::U8`.
856 Nvfp4 { group: u32 },
857}
858
859impl ScaleLayout {
860 /// OCP microscaling default (32-element blocks).
861 pub const fn mx() -> Self {
862 Self::BlockMxE8M0 { block: 32 }
863 }
864 /// NVFP4 default (16-element groups).
865 pub fn nvfp4() -> Self {
866 Self::Nvfp4 {
867 group: crate::nvfp4::NVFP4_GROUP_SIZE as u32,
868 }
869 }
870 /// Element dtype of the scale tensor for this layout.
871 pub const fn scale_dtype(self) -> crate::DType {
872 match self {
873 Self::PerTensor => crate::DType::F32,
874 Self::BlockMxE8M0 { .. } | Self::Nvfp4 { .. } => crate::DType::U8,
875 }
876 }
877 /// Number of consecutive elements sharing one scale (1 for per-tensor).
878 pub const fn block(self) -> u32 {
879 match self {
880 Self::PerTensor => 1,
881 Self::BlockMxE8M0 { block } => block,
882 Self::Nvfp4 { group } => group,
883 }
884 }
885
886 /// `(scale_mode, block)` for GPU kernels (`scaled_lowp_general.cu`):
887 /// per-tensor=0, block-E8M0=1, NVFP4-E4M3=2.
888 pub const fn mode_block(self) -> (u32, u32) {
889 match self {
890 Self::PerTensor => (0, 1),
891 Self::BlockMxE8M0 { block } => (1, block),
892 Self::Nvfp4 { group } => (2, group),
893 }
894 }
895}
896
897impl std::fmt::Display for ScaleLayout {
898 fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
899 match self {
900 Self::PerTensor => write!(f, "per_tensor"),
901 Self::BlockMxE8M0 { block } => write!(f, "mx_e8m0/{block}"),
902 Self::Nvfp4 { group } => write!(f, "nvfp4/{group}"),
903 }
904 }
905}
906
907impl std::str::FromStr for ScaleLayout {
908 type Err = String;
909
910 /// Parse a scale-layout name: `"per_tensor"`, `"mx"` (32-element E8M0
911 /// microscaling), `"nvfp4"` (16-element E4M3), or an explicit block size
912 /// `"mx/<block>"` / `"nvfp4/<group>"`. Mirrors [`Display`](Self) round-trip.
913 fn from_str(s: &str) -> Result<Self, Self::Err> {
914 match s {
915 "per_tensor" | "pertensor" => return Ok(Self::PerTensor),
916 "mx" | "mxfp8" | "block" => return Ok(Self::mx()),
917 "nvfp4" => return Ok(Self::nvfp4()),
918 _ => {}
919 }
920 if let Some(rest) = s.strip_prefix("mx/").or_else(|| s.strip_prefix("mx_e8m0/")) {
921 if let Ok(block) = rest.parse::<u32>() {
922 return Ok(Self::BlockMxE8M0 { block });
923 }
924 }
925 if let Some(rest) = s.strip_prefix("nvfp4/") {
926 if let Ok(group) = rest.parse::<u32>() {
927 return Ok(Self::Nvfp4 { group });
928 }
929 }
930 Err(format!(
931 "unknown scale layout {s:?} (expected \"per_tensor\", \"mx\", \"nvfp4\", or \"mx/<block>\")"
932 ))
933 }
934}
935
936/// Per-graph map of quantized tensors. Lookup is O(1).
937#[derive(Debug, Clone, Default)]
938pub struct QuantMap {
939 map: HashMap<NodeId, QuantScheme>,
940}
941
942impl QuantMap {
943 pub fn new() -> Self {
944 Self::default()
945 }
946 pub fn get(&self, id: NodeId) -> Option<QuantScheme> {
947 self.map.get(&id).copied()
948 }
949 pub fn insert(&mut self, id: NodeId, scheme: QuantScheme) -> Option<QuantScheme> {
950 self.map.insert(id, scheme)
951 }
952 pub fn is_empty(&self) -> bool {
953 self.map.is_empty()
954 }
955 pub fn len(&self) -> usize {
956 self.map.len()
957 }
958 pub fn iter(&self) -> impl Iterator<Item = (&NodeId, &QuantScheme)> {
959 self.map.iter()
960 }
961}
962
963#[cfg(test)]
964mod tests {
965 use super::*;
966
967 #[test]
968 fn scheme_traits() {
969 assert_eq!(
970 QuantScheme::Int4Block { block_size: 32 }.bits_per_element(),
971 4
972 );
973 assert!(QuantScheme::Int8BlockAsym { block_size: 64 }.has_zero_point());
974 assert!(!QuantScheme::Fp8E4m3.has_scale());
975 }
976
977 /// Pins the shared GGUF dequant-kernel ids so they can NEVER drift out
978 /// from under the compiled MSL/CU/WGSL/GLSL `switch (scheme_id)` in any
979 /// backend. Every GPU backend delegates to `gpu_dequant_scheme_id`; if
980 /// someone reorders a variant here this test fails before a mis-decode
981 /// ships. Non-GGUF schemes must report `None`.
982 #[test]
983 fn gpu_dequant_scheme_id_is_stable() {
984 use QuantScheme::*;
985 assert_eq!(QuantScheme::GPU_DEQUANT_SCHEME_ID_PAIRS.len(), 28);
986 for &(scheme, id) in QuantScheme::GPU_DEQUANT_SCHEME_ID_PAIRS {
987 assert_eq!(scheme.gpu_dequant_scheme_id(), Some(id), "{scheme:?}");
988 assert_eq!(
989 QuantScheme::from_gpu_dequant_scheme_id(id),
990 Some(scheme),
991 "id {id}"
992 );
993 }
994 for scheme in [
995 Int8Block { block_size: 32 },
996 Int8BlockAsym { block_size: 32 },
997 Int4Block { block_size: 32 },
998 Fp8E4m3,
999 Fp8E5m2,
1000 Nvfp4Block,
1001 MlxAffine {
1002 bits: 4,
1003 group_size: 64,
1004 },
1005 MlxMxfp4 { group_size: 32 },
1006 MlxMxfp8 { group_size: 32 },
1007 ] {
1008 assert_eq!(scheme.gpu_dequant_scheme_id(), None, "{scheme:?}");
1009 }
1010 assert_eq!(QuantScheme::from_gpu_dequant_scheme_id(999), None);
1011 }
1012
1013 #[test]
1014 fn quant_map_lookup() {
1015 let mut q = QuantMap::new();
1016 let id = NodeId(7);
1017 q.insert(id, QuantScheme::Int8Block { block_size: 32 });
1018 assert_eq!(q.get(id), Some(QuantScheme::Int8Block { block_size: 32 }));
1019 assert_eq!(q.get(NodeId(99)), None);
1020 }
1021
1022 #[test]
1023 fn custom_format_ieee_bias_and_width() {
1024 // IEEE bias 2^(e-1)-1, matching every named format.
1025 assert_eq!(ScaledFormat::custom(3, 0).fields(), (3, 0, 3)); // f4e3m0
1026 assert_eq!(ScaledFormat::custom(4, 3).fields(), (4, 3, 7)); // e4m3 bias
1027 assert_eq!(ScaledFormat::custom(5, 2).fields(), (5, 2, 15)); // e5m2 bias
1028 assert_eq!(ScaledFormat::custom(2, 1).fields(), (2, 1, 1)); // e2m1 bias
1029 assert_eq!(ScaledFormat::custom(3, 0).bit_width(), 4);
1030 assert_eq!(ScaledFormat::custom(3, 4).bit_width(), 8);
1031 }
1032
1033 #[test]
1034 fn custom_format_parse_display_round_trip() {
1035 let f: ScaledFormat = "f4e3m0".parse().unwrap();
1036 assert_eq!(f, ScaledFormat::custom(3, 0));
1037 assert_eq!(f.to_string(), "f4e3m0");
1038 // A few more splits.
1039 assert_eq!(
1040 "f5e2m2".parse::<ScaledFormat>().unwrap().to_string(),
1041 "f5e2m2"
1042 );
1043 assert_eq!(
1044 "f8e3m4".parse::<ScaledFormat>().unwrap().to_string(),
1045 "f8e3m4"
1046 );
1047 // Named formats parse to their exact hardware variants, not Custom.
1048 assert_eq!(
1049 "f8e4m3".parse::<ScaledFormat>().unwrap(),
1050 ScaledFormat::F8E4M3
1051 );
1052 assert_eq!(
1053 "f4e2m1".parse::<ScaledFormat>().unwrap(),
1054 ScaledFormat::F4E2M1
1055 );
1056 assert_eq!(
1057 "f8e5m2fnuz".parse::<ScaledFormat>().unwrap(),
1058 ScaledFormat::F8E5M2Fnuz
1059 );
1060 }
1061
1062 #[test]
1063 fn custom_format_parse_rejects_invalid() {
1064 assert!("f4e3m1".parse::<ScaledFormat>().is_err()); // 1+3+1 != 4
1065 assert!("f9e4m4".parse::<ScaledFormat>().is_err()); // 9 bits > byte
1066 assert!("f1e0m0".parse::<ScaledFormat>().is_err()); // 0 exponent bits
1067 assert!("e3m0".parse::<ScaledFormat>().is_err()); // missing 'f'
1068 assert!("f4e3m0x".parse::<ScaledFormat>().is_err()); // trailing junk
1069 assert!("garbage".parse::<ScaledFormat>().is_err());
1070 }
1071
1072 #[test]
1073 fn custom_gpu_word_is_packed_descriptor() {
1074 // Named formats keep their small ids (top bit clear).
1075 assert_eq!(ScaledFormat::F8E4M3.kernel_id(), 0);
1076 assert_eq!(ScaledFormat::F4E2M1.kernel_id(), 6);
1077 assert!(ScaledFormat::F4E2M1.kernel_id() & 0x8000_0000 == 0);
1078 // Custom packs (exp, mant, bias) with the sentinel bit set.
1079 let w = ScaledFormat::custom(3, 0).kernel_id(); // e=3, m=0, bias=3
1080 assert_eq!(w & 0x8000_0000, 0x8000_0000);
1081 assert_eq!(w & 0xF, 3); // exp_bits
1082 assert_eq!((w >> 4) & 0xF, 0); // mant_bits
1083 assert_eq!((w >> 8) & 0xFF, 3); // bias
1084 // Negative bias round-trips through the u8 reinterpretation.
1085 let wn = ScaledFormat::custom_with_bias(3, 0, -2).kernel_id();
1086 assert_eq!(((wn >> 8) & 0xFF) as u8 as i8, -2);
1087 }
1088
1089 #[test]
1090 fn format_is_const_and_introspectable() {
1091 // Usable in const context.
1092 const F: ScaledFormat = ScaledFormat::custom(3, 0);
1093 assert!(F.is_custom() && !F.is_named());
1094 assert_eq!((F.exp_bits(), F.mant_bits(), F.bias()), (3, 0, 3));
1095 assert!(ScaledFormat::F8E4M3.is_named() && !ScaledFormat::F8E4M3.is_custom());
1096 assert_eq!(ScaledFormat::NAMED.len(), 7);
1097 assert!(ScaledFormat::NAMED.iter().all(|f| f.is_named()));
1098 }
1099
1100 #[test]
1101 fn format_codec_methods_and_quantize() {
1102 // Method forms match the free functions for every named format.
1103 for f in ScaledFormat::NAMED {
1104 for c in 0..(1u16 << f.bit_width()) {
1105 assert_eq!(
1106 f.decode(c as u8).to_bits(),
1107 crate::lowp_codec::decode(f, c as u8).to_bits()
1108 );
1109 }
1110 }
1111 let cf = ScaledFormat::custom(3, 0); // f4e3m0 grid: ±{0.25,..,16}, ±0
1112 assert_eq!(cf.quantize(1.4), 1.0);
1113 assert_eq!(cf.quantize(1.6), 2.0);
1114 assert_eq!(cf.quantize(-3.0), -2.0); // nearer 2 than 4 in magnitude
1115 assert_eq!(cf.decode(cf.encode(100.0)), 16.0); // saturates
1116 assert_eq!(cf.decode(cf.encode(f32::INFINITY)), 16.0);
1117 }
1118
1119 #[test]
1120 fn representable_values_grid() {
1121 assert_eq!(
1122 ScaledFormat::custom(3, 0).representable_values(),
1123 vec![
1124 -16.0, -8.0, -4.0, -2.0, -1.0, -0.5, -0.25, 0.0, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0,
1125 16.0
1126 ]
1127 );
1128 // Named formats: the grid size never exceeds the finite code count.
1129 for f in ScaledFormat::NAMED {
1130 let g = f.representable_values();
1131 assert!(!g.is_empty() && g.windows(2).all(|w| w[0] < w[1]));
1132 }
1133 }
1134
1135 #[test]
1136 fn enumerate_all_fnexmy() {
1137 // Every valid fNeXmY: exp >= 1, mant >= 0, 1 + exp + mant <= 8.
1138 let mut all = vec![];
1139 for exp in 1u8..=7 {
1140 for mant in 0u8..=(7 - exp) {
1141 all.push(ScaledFormat::custom(exp, mant));
1142 }
1143 }
1144 assert_eq!(all.len(), 28, "there are exactly 28 fNeXmY formats");
1145 eprintln!(
1146 "{:<8} {:>4} {:>3} {:>3} {:>4} {:>12} {:>12} {:>5}",
1147 "name", "bits", "e", "m", "bias", "max_finite", "min_pos", "vals"
1148 );
1149 for f in &all {
1150 let vals = f.representable_values();
1151 let min_pos = vals.iter().copied().find(|&x| x > 0.0).unwrap();
1152 assert!(f.bit_width() <= 8 && f.exp_bits() >= 1 && !vals.is_empty());
1153 eprintln!(
1154 "{:<8} {:>4} {:>3} {:>3} {:>4} {:>12.3e} {:>12.3e} {:>5}",
1155 f.to_string(),
1156 f.bit_width(),
1157 f.exp_bits(),
1158 f.mant_bits(),
1159 f.bias(),
1160 f.max_finite(),
1161 min_pos,
1162 vals.len()
1163 );
1164 }
1165 }
1166
1167 #[test]
1168 fn scale_layout_parse_round_trip() {
1169 assert_eq!(
1170 "per_tensor".parse::<ScaleLayout>().unwrap(),
1171 ScaleLayout::PerTensor
1172 );
1173 assert_eq!("mx".parse::<ScaleLayout>().unwrap(), ScaleLayout::mx());
1174 assert_eq!(
1175 "nvfp4".parse::<ScaleLayout>().unwrap(),
1176 ScaleLayout::nvfp4()
1177 );
1178 assert_eq!(
1179 "mx/64".parse::<ScaleLayout>().unwrap(),
1180 ScaleLayout::BlockMxE8M0 { block: 64 }
1181 );
1182 assert!("bogus".parse::<ScaleLayout>().is_err());
1183 // Display round-trips through FromStr.
1184 let mx = ScaleLayout::mx();
1185 assert_eq!(mx.to_string().parse::<ScaleLayout>().unwrap(), mx);
1186 }
1187}