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chore: Check malformed jaccl hostfile that miss rdma in pairs - #4284
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Both the code comment and error message are hard to comprehend, so it checks connected nodes must have rdma set in hostfile?
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Yes, but it checks the pairs the chosen topology will actually use, not every connected pair. For jaccl-ring that is each rank's two neighbours; for the mesh it is every pair. So a hostfile can be a valid ring and an invalid mesh, which is one of the tests. |
…uses launch_jaccl checked the shape of the rdma matrix, its dimensions and its null diagonal, but never whether the pairs the backend is about to communicate over are actually in it. A hostfile whose rank order places unconnected nodes beside each other passes both checks. What follows is the worst failure available. The group does not fail to form and it does not run slowly: every rank ends up alone in a group of size one, reports success, and the job computes N separate wrong answers at full speed with nothing on stderr. Verified on four M4 Pro minis wired as a full mesh, where permuting two hosts in a working hostfile, rows and columns together so the file stays internally consistent, produced four independent groups of one and four 'membership OK' lines. This is the same class as ml-explore#4210, where a group of size 1 counted as a successful init. missing_jaccl_links reports the pairs that are used but absent: for a ring each rank's two neighbours, for a mesh every pair. With two ranks the previous and next neighbour are the same node, which is harmless because the pair is simply examined twice. The error names the hosts and says that for jaccl-ring the host order is the ring order, since that is the mistake that produces it. Checked against the live mesh: the misordered hostfile is now rejected, and valid mesh and valid ring hostfiles still run at 20.87 and 16.33 GB/s.
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* Return tuple in meshgrid (ml-explore#4229) * Add endpoint parameter to linspace (ml-explore#4184) Co-authored-by: Cheng <git@zcbenz.com> * Fix vmap of partition/argpartition dropping the kth argument (ml-explore#4116) * Fix nan_to_num replacing inf with 0 for float16 and bfloat16 (ml-explore#4222) Co-authored-by: codeAnqiang-ma <273298913+codeAnqiang-ma@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Fix einsum not broadcasting batch dimensions in batched tensordot (ml-explore#4125) Co-authored-by: Cheng <git@zcbenz.com> * Dequantize in float32 (ml-explore#4241) * chore: Reject complex in erf and erfinv (ml-explore#4243) * Fix cpu compilation failure of abs with uint (ml-explore#4240) Co-authored-by: Cheng <git@zcbenz.com> * Fix quantize matrix multiplication floor issue (ml-explore#4251) * Only use MPI backend for world size > 1 (ml-explore#4210) * chore: Reject complex in expm1, sigmoid and arctan2 (ml-explore#4257) * Decompose small kernel-depth 3D convs into 2D convs (ml-explore#3785) Co-authored-by: katlun-lgtm <264247399+katlun-lgtm@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Fix Metal sort of a view with a negative stride (ml-explore#4252) * Mirror the depth axis in the decomposed 3D conv when flipped (ml-explore#4277) * Fix Metal row reductions on negative-stride views (ml-explore#4267) Co-authored-by: Fu Xiaonan <214359569+FU-max-boop@users.noreply.github.com> * [CUDA] Fix custom kernel cache collision for same name, different source (ml-explore#4273) Co-authored-by: Cheng <git@zcbenz.com> * Fix ops rejecting integers larger than INT32_MAX (ml-explore#4255) Co-authored-by: Feli <feli@hnu.edu.cn> Co-authored-by: Cheng <git@zcbenz.com> * Fix var/std for complex numbers (ml-explore#4260) * Fix int32 overflow in conv padded input and pad shapes (ml-explore#4258) Co-authored-by: Cheng <git@zcbenz.com> * chore: Reject complex in remainder (ml-explore#4270) * chore: Compare the macOS SDK version as a version when gating JACCL (ml-explore#4286) * Clamp ring socket transfers so a payload of 2 GiB or more can be sent (ml-explore#4281) Co-authored-by: Cheng <git@zcbenz.com> * chore: Use normalize_axis_index in split/unstack/partition/topk (ml-explore#4288) * Remove grouped output in CI (ml-explore#4195) * [CUDA] Fix finding cuda 13 headers in JIT compilation (ml-explore#3995) * Refactor wheel building script (ml-explore#3818) * Make mx.compile cache erasing thread safe (ml-explore#4248) Co-authored-by: yentur <mr.yentur@gmail.com> * Add builds for free-threaded python (ml-explore#3812) * Fix int32 overflow in concatenate/repeat/kron (ml-explore#4303) * python: Widen list elements that do not fit in int32 to int64 (ml-explore#4305) * Propagate CPU errors to events (ml-explore#3742) Co-authored-by: Alessio Pollero <alessio.pollero@gmail.com> * Fix mx.arange dtype inference overflow regression (ml-explore#4324) * Add workflow to update pull request limit bypass list (ml-explore#4320) * Support head dimension 72 in Metal full attention (ml-explore#4330) * Patch bump to 0.32.2 (ml-explore#4333) * Preserve subnormal float values when casting to bool (ml-explore#4224) * python: Support assigning through a bare Ellipsis index (ml-explore#4314) * Fix divmod truncating the quotient for floats (ml-explore#4108) Co-authored-by: Cheng <git@zcbenz.com> * Add force_fused option to scaled_dot_product_attention (ml-explore#4185) * chore: Reject negative eps in the normalization layers (ml-explore#4312) * Bound GGUF metadata string/array values against the file mapping (ml-explore#4212) Co-authored-by: x14ngch3n <x14ngch3n@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Read each K/V byte once in gqa-8 decode attention (ml-explore#4077) * Fix fft vmap and jvp for transforms over a subset of axes (ml-explore#4138) * Fix median dropping NaN (ml-explore#4146) * Fix the CPU scan over a size one axis with a padded stride (ml-explore#4139) Co-authored-by: Cheng <git@zcbenz.com> * chore: Validate the optimizer betas at construction (ml-explore#4310) Co-authored-by: Cheng <git@zcbenz.com> * `RMSNormVJP` backward writes a full `{n_rows, D}` `gw_temp` intermediate (ml-explore#4293) * [Bug]: add default none value to axis parameter of the take_along_axis (ml-explore#4357) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * Add a fused full-attention path for head_dim 256 on NAX devices (ml-explore#3842) Co-authored-by: Cheng <git@zcbenz.com> * Update nanobind to 2.15.0 (ml-explore#4337) * Skip unnecessary simdgroup computations for quantised MOE matmuls on NAX (ml-explore#4352) * Add AI usage policy (ml-explore#4331) Co-authored-by: Jake Bowhay <60778417+j-bowhay@users.noreply.github.com> * Raise cpu stream errors from synchronize (ml-explore#4338) Co-authored-by: Cheng <git@zcbenz.com> * chore: Validate eps in Adam at construction (ml-explore#4361) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * Bound winograd conv2d working set by tiling the batch (ml-explore#4102) Co-authored-by: Cheng <git@zcbenz.com> * Use a 32-row block in qmm_t_nax when one block covers all of M (ml-explore#4171) * chore: Deduplicate fftshift and ifftshift (ml-explore#4318) * Fix Log and Equal is_equivalent ignoring primitive state (ml-explore#4266) Co-authored-by: Cheng <git@zcbenz.com> * Stabilize reduced-precision InstanceNorm (ml-explore#4230) * chore: Normalize negative axes in sort and argsort (ml-explore#4332) * Clean up main thread compile cache before python interpreter shuts down (ml-explore#4373) * chore: Check malformed jaccl hostfile that miss rdma in pairs (ml-explore#4284) Co-authored-by: Cheng <git@zcbenz.com> * Round mxfp8 block scales up to avoid saturation (ml-explore#4353) Co-authored-by: Daniel Hiltgen <daniel.hiltgen@ollama.com> Co-authored-by: Cheng <git@zcbenz.com> * Add support for the __array_namespace_info__ (ml-explore#4334) * Stop a failed CUDA graph commit from poisoning the encoder (ml-explore#4356) Co-authored-by: Cheng <git@zcbenz.com> * Fix quantized kernels in JIT build (ml-explore#4372) Co-authored-by: Cheng <git@zcbenz.com> * Avoid zero work in stride-2 ConvTranspose3d (ml-explore#4343) * [CUDA] Ce fused kernel (ml-explore#3947) * Fix cpu exclusive scan for complex numbers (ml-explore#4272) Co-authored-by: Cheng <git@zcbenz.com> * Support Relocatable CUDA DLLs on Windows (ml-explore#4382) * Use cast_to for fused AsType in compiled Metal kernels (ml-explore#4351) Co-authored-by: katlun-lgtm <katlun@windyviews.com> Co-authored-by: Cheng <zcbenz@gmail.com> * python: Declare DLPackCompatible protocol members as methods (ml-explore#4384) * Fix quantizing sliced arrays (ml-explore#4381) * Fix einsum dropping a trailing empty subscript (ml-explore#4299) Co-authored-by: Cheng <git@zcbenz.com> * Add script to run python tests (ml-explore#4393) * Hold GIL in AttachedData destructor (ml-explore#4391) * Bound Metal buffer COUNT, not just bytes, in MetalAllocator The Metal allocator throws `[metal::malloc] Resource limit (N) exceeded` when num_resources_ (the live+cached Metal buffer COUNT) reaches resource_limit_ (the iogpu.rsrc_limit sysctl, default ~499000). Freed buffers are recycled into a size-keyed cache whose only trim is by BYTES (release_cached_buffers takes a bytes-to-free target, max_pool_size_ ~= physical RAM). Under churn with many distinct buffer shapes (varied prompt lengths, growing KV caches, multiple co-resident models) the cache fills with entries never reused at that exact size, so the COUNT climbs to the limit while byte usage stays modest and the byte trim never fires — the process crashes mid-inference on a machine with most of its RAM free. malloc() now also reclaims by count: when num_resources_ crosses a 90% high-water mark of resource_limit_, it clears the (pure-reuse) buffer cache so the count drops back to the live working set. Clearing the cache only costs re-allocation, never correctness, so the count limit becomes unreachable by any request mix or batching method while the existing byte limits keep total memory bounded. Adds get_num_resources()/get_resource_limit() to the public memory API (metal + no_gpu + cuda backends) so the count and its ceiling are observable from callers. Adds an MLX_RESOURCE_LIMIT env override that can only LOWER the ceiling (clamped to the OS limit, strictly validated) to exercise the trim deterministically and as an operator safety valve. * perf(mlx): opt-in Gemma 4 expert-QMM tile kernel with parallel descriptor builder (#4) * perf(mlx): add opt-in Gemma 4 expert-QMM tile kernel with parallel descriptor builder Adds a distinctly-named expert QMM implementation for the Gemma 4 26B-A4B MoE production shapes, gated by MLX_GATHER_QMM_EXPERT_SLICES: - qmm_t_expert_impl: BM32 expert tile body (BM16 fallback rows) taking a private/by-value row count; the shared qmm_t_impl constant-address ABI and all ordinary gathered/batched/dense QMM routes are unchanged. - build_gemma4_sorted_expert_tiles_bm32: one 128-thread threadgroup replaces the reference design's single-GPU-thread serial builder; parallel expert-range binary search, Hillis-Steele scan, and strided upper-bound descriptor emission. - Selector runs after the NAX-first route and requires affine BF16 transposed inputs, 4-bit gs=64 weights, 128 experts, assignment counts of exactly 4096/8192/16384, and the exact gate/up or down rank-3 shapes; every miss keeps the legacy route. NAX engagement is non-engagement, never bypassed. - device.{h,cpp}: one-shot request resolution, nonthrowing dual-symbol AOT probe/prewarm, relaxed-atomic diagnostics (requested, aotAvailable, naxAvailable, hits, per-class fallbacks). - gpu_tests: exact-shape arithmetic parity, fallback, and counter invariant probes. Retention standing (2026-08-09 production matrix): opt-in experiment. Standalone profile dropped (prefill -10.2% vs bracket); paired weighted-unsort+R1 profile retained-final (prefill +1.8%, TTFT -7.5%, decode +3.3%, arrival E2E +12.0%). NOTE: this source post-dates the benchmarked binaries/metallib (post-measurement kernel-body edit); rebuild and re-verify before any performance claim. * fix(mlx): fail-safe sortedness check in gemma expert tile builder; counter/atomic hygiene Review-wave fixes for the R1 expert-QMM path: - N1 (sortedness trust): build_gemma4_sorted_expert_tiles_bm32 now verifies each thread's post-binary-search segment boundary against the generalized invariant indices[start - 1] < lid <= indices[start] (edge threads check their single neighbor), votes per simdgroup via simd_or, folds the votes through threadgroup memory, and on any violation retracts count[0] to 0 (tile kernel then early-returns) and records the violation in count[1]; the buffer ABI is unchanged (count index 1 was previously unused). try_gemma4_expert_qmm allocates the second count element, drains the encoder after the builder, and re-routes a retracted call to the order-agnostic legacy path instead of dispatching the tile kernel (zero count is unambiguous: the selector's assignment gate guarantees M is 4096/8192/16384). - N2 (route-condition duplication): the sorted-RHS gate literal that appeared (negated) in the diagnostics record and in the dispatch decision is now the shared static constexpr predicate takes_sorted_rhs_route, so future tuning of the 16/4 thresholds cannot desynchronize counter vs route. - N3 (per-call bias normalization): gather_qmm_rhs no longer spends ensure_row_contiguous on biases before classification reads the raw tensor's fields; normalization runs only inside the winning-route branch (hit semantics unchanged; the legacy block keeps its own normalization point and ordering). - N4 (armed_ data race): Gemma4ExpertQMMCounters::armed_ is now std::atomic<bool> with relaxed loads/stores in armed(), snapshot(), snapshot_and_disarm() (read-then-write order preserved) and clear_and_arm(); the class remains non-copyable, now enforced. * fix(mlx): make the R1 sortedness fail-safe sound; proper retract attribution F1: the per-expert boundary vote was a partial detector -- an inversion inside a segment used by no other expert's boundary could escape, so "re-route on any violation" overclaimed. build_gemma4_sorted_expert_tiles_bm32 now also runs a strided adjacent-pair scan: thread lid checks indices[i-1] <= indices[i] for i = lid+1; i < M; i += 128, covering every adjacent pair in [1, M) exactly once (1..128 iterations at the reachable M in {4096,8192,16384}). Adjacent-pair monotonicity is transitive, so a clean scan is a sound and complete sortedness oracle; it folds into the same simd_or/threadgroup vote and the same retract (count[0]=0, count[1]=1). The boundary checks stay as cheap, precise diagnostics. F2: retracts were write-only in count[1] and surfaced as fallback_metallib_unavailable -- misattribution in the only observable surface. A dedicated fallback_sortedness_retracted counter now rides the GemmA4 route counters and the C diagnostics ABI (sizeof 80 -> 88, new uint64 at offset 80; existing offsets unchanged). try_gemma4_expert_qmm returns the route class: count[0]==0 with count[1]==1 records fallback_sortedness_retracted, any other unusable build keeps fallback_metallib_unavailable, then re-routes to the legacy path as before. F4: new doctest drives the full armed() -> clear_and_arm() -> snapshot_and_disarm() cycle and the attempts == hits + fallbacks invariant including the new class; the route-table and counter-invariant tests now cover fallback_sortedness_retracted. Verified: cmake tests 262/262 + 3550 assertions pass; metal -Wall -Wextra -fno-fast-math compile of kernels/quantized.metal is warning-free. * perf(metal): E=256 expert-tile route + trust + gpu::eval UAF fix — darkbloom-base mirror (#7) * perf(metal): instantiate E=256 expert-tile route for Qwen 3.5/3.6 MoE prefill (mirror of Cmlx/mlx 58fab46) * fix(metal): use-after-free in gpu::eval for primitives that synchronize mid-eval (mirror) * perf(metal): trust mode skips retract readback (mirror) * fix(compile): preserve all-cache binding cleanup --------- Co-authored-by: JasonHonKL <148705846+JasonHonKL@users.noreply.github.com> Co-authored-by: AK <144495202+AKnassa@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> Co-authored-by: Adityaj0 <93090622+Adityaj0@users.noreply.github.com> Co-authored-by: anchor <codeanqiang@gmail.com> Co-authored-by: codeAnqiang-ma <273298913+codeAnqiang-ma@users.noreply.github.com> Co-authored-by: Rohan Gautam <rohan1gautam@gmail.com> Co-authored-by: Ayaan Gazali <ayaangazali.work@gmail.com> Co-authored-by: Erwin Zhang <59893706+erwinzhang7@users.noreply.github.com> Co-authored-by: katlun-lgtm <katlun@gmail.com> Co-authored-by: katlun-lgtm <264247399+katlun-lgtm@users.noreply.github.com> Co-authored-by: robertomeroni <150194833+robertomeroni@users.noreply.github.com> Co-authored-by: Fu Xiaonan <ht3fudatou@163.com> Co-authored-by: Fu Xiaonan <214359569+FU-max-boop@users.noreply.github.com> Co-authored-by: Hao Xu <hxu44@apple.com> Co-authored-by: Feli <89400571+FeliGame@users.noreply.github.com> Co-authored-by: Feli <feli@hnu.edu.cn> Co-authored-by: Eyüp Can Akman <eyupcanakman@gmail.com> Co-authored-by: Cheng <zcbenz@gmail.com> Co-authored-by: yentur <mr.yentur@gmail.com> Co-authored-by: Alessio Pollero <alessio.pollero@gmail.com> Co-authored-by: Zhiqi Zhang <zhiqizhangg@gmail.com> Co-authored-by: Daniel Hiltgen <dhiltgen@users.noreply.github.com> Co-authored-by: Tanish Jain <recklurker@gmail.com> Co-authored-by: hojin12312 <hojin12312@gmail.com> Co-authored-by: Xiang Chen <46052474+x14ngch3n@users.noreply.github.com> Co-authored-by: x14ngch3n <x14ngch3n@users.noreply.github.com> Co-authored-by: Duhyeon, Kim <49020301+dudududukim@users.noreply.github.com> Co-authored-by: rohith <kapellirohith@gmail.com> Co-authored-by: Ishaan Samantray <devteam.aegis@gmail.com> Co-authored-by: Aaishwarya Mishra <aaishwarymishra@gmail.com> Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> Co-authored-by: Yanzhao Wang <19340816+wyanzhao@users.noreply.github.com> Co-authored-by: XXXXRT666 <157766680+XXXXRT666@users.noreply.github.com> Co-authored-by: Jake Bowhay <60778417+j-bowhay@users.noreply.github.com> Co-authored-by: vraj patel <87225460+vraj00222@users.noreply.github.com> Co-authored-by: Gusanidas <33495733+Gusanidas@users.noreply.github.com> Co-authored-by: Dwijen Patel <dwijen@gmail.com> Co-authored-by: Vladimir Iglovikov <ternaus@users.noreply.github.com> Co-authored-by: Brian C. <94733710+deBrian07@users.noreply.github.com> Co-authored-by: Daniel Hiltgen <daniel.hiltgen@ollama.com> Co-authored-by: YH Yan <strayberry0w0@gmail.com> Co-authored-by: katlun-lgtm <katlun@windyviews.com> Co-authored-by: anupsv <6407789+anupsv@users.noreply.github.com> Co-authored-by: Gajesh Naik <26431906+Gajesh2007@users.noreply.github.com> Co-authored-by: David Tai <davidtai@Davids-MBP.lan>
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* Fix Log and Equal is_equivalent ignoring primitive state (ml-explore#4266) Co-authored-by: Cheng <git@zcbenz.com> * Stabilize reduced-precision InstanceNorm (ml-explore#4230) * chore: Normalize negative axes in sort and argsort (ml-explore#4332) * Clean up main thread compile cache before python interpreter shuts down (ml-explore#4373) * chore: Check malformed jaccl hostfile that miss rdma in pairs (ml-explore#4284) Co-authored-by: Cheng <git@zcbenz.com> * Round mxfp8 block scales up to avoid saturation (ml-explore#4353) Co-authored-by: Daniel Hiltgen <daniel.hiltgen@ollama.com> Co-authored-by: Cheng <git@zcbenz.com> * Add support for the __array_namespace_info__ (ml-explore#4334) * Stop a failed CUDA graph commit from poisoning the encoder (ml-explore#4356) Co-authored-by: Cheng <git@zcbenz.com> * Fix quantized kernels in JIT build (ml-explore#4372) Co-authored-by: Cheng <git@zcbenz.com> * Avoid zero work in stride-2 ConvTranspose3d (ml-explore#4343) * [CUDA] Ce fused kernel (ml-explore#3947) * Fix cpu exclusive scan for complex numbers (ml-explore#4272) Co-authored-by: Cheng <git@zcbenz.com> * Support Relocatable CUDA DLLs on Windows (ml-explore#4382) * Use cast_to for fused AsType in compiled Metal kernels (ml-explore#4351) Co-authored-by: katlun-lgtm <katlun@windyviews.com> Co-authored-by: Cheng <zcbenz@gmail.com> * python: Declare DLPackCompatible protocol members as methods (ml-explore#4384) * Fix quantizing sliced arrays (ml-explore#4381) * Fix einsum dropping a trailing empty subscript (ml-explore#4299) Co-authored-by: Cheng <git@zcbenz.com> * Add script to run python tests (ml-explore#4393) * Hold GIL in AttachedData destructor (ml-explore#4391) * Patch bump to 0.32.3 (ml-explore#4406) * Fix scan and sort for a zero-size axis (ml-explore#4340) * python: Add a correction parameter in std and var (ml-explore#4348) Signed-off-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com> Co-authored-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Fix tests/run.py stuck in macOS CI (ml-explore#4410) * chore: Update extension example (ml-explore#4412) * Fix sorted gather_qmm NAX row overflow above 32K (ml-explore#3922) Co-authored-by: Cheng <git@zcbenz.com> * Fix deadlock caused by mx.clear_streams() holding GIL (ml-explore#4413) * Fix integer pow zeroing a whole SIMD vector on a negative exponent (ml-explore#4354) * Make concurrency cap on load adaptative so that I/O scales with the machine (ml-explore#4408) * Fix pad with an axes subset and negative axes (ml-explore#4364) * Use sdpa_vector_2pass_1_gqa for GQA size 12 and 16 (ml-explore#4380) * python: Make axis of put_along_axis optional (ml-explore#4360) * python: Make axis default to -1 in take_along_axis (ml-explore#4368) * Propagate NaN in arg reductions (ml-explore#4291) Co-authored-by: Cheng <git@zcbenz.com> * Fix mx.from_fp8 E4M3FN NaN decode with branchless carry (ml-explore#4376) Co-authored-by: Saud <saudkamran@Sauds-MacBook-Pro.local> * Update rules for PR limitation bypass list (ml-explore#4415) * [CUDA] Use native events for GPU fence waits (ml-explore#4401) Co-authored-by: Cheng <git@zcbenz.com> * Validate GGUF tensor dimensions (ml-explore#4378) Co-authored-by: Cheng <git@zcbenz.com> * Fix crash on ellipsis indexing with too many trailing indices (ml-explore#4396) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * [CUDA] Cholesky via cuSOLVER (ml-explore#4208) Co-authored-by: Cheng <git@zcbenz.com> * python: Fix __setitem__ with negative index preceded by None (ml-explore#4414) * Update nanobind to 3.0.1 (ml-explore#4417) * chore: Use normalize_axis_index in scan ops (ml-explore#4383) * python: Add explicit index and bytes support (ml-explore#4388) * docs: fix typo recived -> received (ml-explore#4424) Signed-off-by: Vaibhav Srivastava <vaibhavsri1712@gmail.com> * Fix Metal grid sizing for strided scans (ml-explore#4420) Co-authored-by: Cheng <git@zcbenz.com> * Fix SGD and Adafactor weight decay mutating caller arrays (ml-explore#4426) * Widen float16/bfloat16 to float32 in cpu reduce (ml-explore#4387) * Fix sdpa_vector_2pass_1_gqa kernel batch offset for K/V in gqa decode (ml-explore#4431) * Make head-dim-256 prefill with array mask run fused NAX kernel (ml-explore#4416) * python: Make unstack return tuple instead of list (ml-explore#4448) * python: Make iter() throw TypeError for 0-dim array (ml-explore#4425) Co-authored-by: Cheng <git@zcbenz.com> * Fix save and save_safetensors corrupting a lazily loaded source file (ml-explore#4434) * [Metal] Use hypot for complex ops (ml-explore#4345) Co-authored-by: Cheng <git@zcbenz.com> * Add get_array_buffer_size to query buffer size for arrays (ml-explore#4436) * Add M5 ultra tunings for non-quantized matmuls (ml-explore#4447) * [CUDA] Fix completion worker busy loop (ml-explore#4452) * Fix non transposed affine qmm dispatch logic (ml-explore#4392) * Fix sorted gather_qmm on ragged K (ml-explore#4009) Co-authored-by: Cheng <git@zcbenz.com> * Don't restore a thread-affine stream when StreamContext dies on another thread (ml-explore#4462) * Fix Pad vjp with an axes subset and negative axes (ml-explore#4441) Co-authored-by: Cheng <git@zcbenz.com> * Fix integer div-by-zero crash in CPU backend (sort, scan, binary ops) (ml-explore#4442) Co-authored-by: Cheng <git@zcbenz.com> * Use 64-bit file seeks on Windows (ml-explore#4456) Co-authored-by: Cheng <git@zcbenz.com> * Use precise::exp in Sigmoid so compiled and eager sigmoid agree (ml-explore#4461) Co-authored-by: Pierre Lamy <pierrelamy427@gmail.com> * Use NAX attention for long unmasked D72/D80 inputs (ml-explore#4455) * Add D512 support to Metal vector attention (ml-explore#4459) Co-authored-by: Cheng <git@zcbenz.com> * Add a scoped_env utility for tests (ml-explore#4474) * [Metal] global scale for qmm (ml-explore#4458) * Fix re-entering the same stream context manager (ml-explore#4478) * Leak global CommandEncoder on exit (ml-explore#4480) * Update CONTRIBUTING.md (ml-explore#4469) * python: Fix bytes() on non-contiguous arrays (ml-explore#4449) * Break the sibling cycle when an array is released by assignment (ml-explore#4453) Co-authored-by: Cheng <git@zcbenz.com> * win: Use DXGI for accurate WDDM VRAM memory budget (ml-explore#4457) Co-authored-by: Cheng <git@zcbenz.com> * Add type hints and docstrings for ALiBi layer (ml-explore#4472) * Fix fp quantized matmul corruption when the quantized dim is not a multiple of 32 (ml-explore#3912) Co-authored-by: Rohan Gautam <rohan1gautam@gmail.com> * Fix CUDA test synchronization flake (ml-explore#4490) * ci: Skip bypass list updates in forks (ml-explore#4495) * Load global scales in qmm_t kernels (ml-explore#4483) * python: Release the GIL when copying Metal DLPack inputs (ml-explore#4497) Signed-off-by: Ranran Haoran Zhang <ranranhaoranzhang@gmail.com> * Use matrix kernels for global-scale gather_qqmm (ml-explore#4481) * Adding metal kernels for the gated delta nets. (ml-explore#4020) Co-authored-by: Yanzhao Wang <19340816+wyanzhao@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Fix jaccl ring all_gather: direction 1 slice was not mirrored (ml-explore#4443) Co-authored-by: Dave Hind <davehind42@gmail.com> Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * Skip Metal-only gated delta kernel tests on other backends(fix CI) (ml-explore#4522) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * [CUDA] Add global scale support to gather_qmm (ml-explore#4507) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * [BUG][Metal] Deadlock in fence (ml-explore#4552) Co-authored-by: Cheng <zcbenz@gmail.com> * Fix ordering of complex64 with NaNs (ml-explore#4519) * Improve metal memory usage for SDPA D256 (ml-explore#4505) Co-authored-by: Cheng <git@zcbenz.com> * Add support for matrix transpose (ml-explore#4402) Co-authored-by: Cheng <git@zcbenz.com> * Improve metal memory usage for SDPA D512 (ml-explore#4487) * Support shapeless compilation of scan operations (ml-explore#4510) * [Metal] Gather mm improvement (ml-explore#4567) * Fix perf regression for upsample `linear` mode align_corners=False (ml-explore#4500) * Add fused Metal kernels for fast.cross_entropy (ml-explore#4520) Co-authored-by: Anastasiia Filippova <a_filippova@apple.com> * python: Add missing defaults to tri, tril, triu, gather_mm signatures (ml-explore#4492) * Add Metal SDPA support for D96/V64 (ml-explore#4499) Co-authored-by: Cheng <git@zcbenz.com> * Raise IndexError for out of bounds axes (ml-explore#4484) * Fix floor_divide for integers (ml-explore#4515) Co-authored-by: Cheng <git@zcbenz.com> * Fix cpu binary ops on large data (ml-explore#4517) Co-authored-by: Cheng <git@zcbenz.com> * Do not throw from CUDA destructors and avoid implicit default streams in eval/compile (ml-explore#4514) Co-authored-by: Cheng <git@zcbenz.com> * [Metal] gather_qmm improvement (ml-explore#4572) * Fix floating-point constant precision in compiled kernels (ml-explore#4511) * chore: Fix assertion in ReduceScatter::eval_cpu (ml-explore#4557) * Leak thread local streams on exit in main thread (ml-explore#4576) * Adding VJP for the scaled dot product attention. (ml-explore#4563) * python: Add __pos__ support to array (ml-explore#4488) Co-authored-by: Cheng <zcbenz@gmail.com> * Add Python 3.15 and 3.15t support (ml-explore#4555) Co-authored-by: Cheng <git@zcbenz.com> * Add fixed size `unique` operation (ml-explore#4501) Co-authored-by: Cheng <zcbenz@gmail.com> * Fix normalizing single-element slice with negative stride (ml-explore#4446) Co-authored-by: Cheng <git@zcbenz.com> * Patch bump to 0.32.4 (ml-explore#4582) * Adding VJP for gated delta net. (ml-explore#4565) * Fix `col_reduce_longcolumn` for negative-stride views (ml-explore#4529) Co-authored-by: Cheng <zcbenz@gmail.com> * Clear CUDA errors once reported and raise eval errors in buffer protocol (ml-explore#4523) Co-authored-by: Cheng <zcbenz@gmail.com> * Improve pre-M5 metal memory usage for SDPA D512 (ml-explore#4518) * Fix split data size span (ml-explore#4540) * Re-introduce Array API Tests suite (ml-explore#4433) Signed-off-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com> Co-authored-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com> Co-authored-by: Cheng <zcbenz@gmail.com> * Fix view inside of a vmap (ml-explore#4586) * Fix cumsum of a non-contiguous bool (ml-explore#4590) * docs: contraction dtype requirements in matmul/einsum (ml-explore#4550) Co-authored-by: Cheng <zcbenz@gmail.com> * Fixing cooperative tensor build issues on Mac OS 27 (ml-explore#4594) * Handle EOF and EINTR in ParallelFileReader::read (ml-explore#4532) Co-authored-by: Cheng <git@zcbenz.com> * Clamp slice bounds when a slice is combined with an array index (ml-explore#4513) Co-authored-by: Cheng <zcbenz@gmail.com> * Fix grouped Conv1d/Conv2d init to use in_channels // groups (ml-explore#4544) Co-authored-by: Cheng <zcbenz@gmail.com> * Fix mx.view misaligned offset (ml-explore#4585) Co-authored-by: Cheng <git@zcbenz.com> * [CUDA] Add fp_gather_qmv to optimize gather_qmm (ml-explore#4508) * Fix eval cleanup deadlock by committing GPU streams before waiting (ml-explore#4556) * Fix shared_buffer_reshape contiguity flags (ml-explore#4589) * Fix view last axis stride (ml-explore#4587) Co-authored-by: Cheng <zcbenz@gmail.com> * Fix empty unsigned sum/prod failing on Metal (ml-explore#4546) Co-authored-by: Cheng <git@zcbenz.com> * [CUDA] Add gather_qmm_rhs_sm80 (ml-explore#4554) Co-authored-by: Cheng <git@zcbenz.com> * python: Fix bare ellipsis __setitem__ by squeezing leading singleton dimensions (ml-explore#4561) * Fix row/col contiguous flags in view (ml-explore#4588) * Do not cache failed distributed backend initialization (ml-explore#4558) * Fix reduction over large arrays (ml-explore#4549) Co-authored-by: Cheng <git@zcbenz.com> * docs: Correct the export callback type in the guide (ml-explore#4578) * Fix MultiOptimizer crash when an optimizer's group is empty (ml-explore#4570) * Fix fft size one (ml-explore#4591) * Sanitize '-' in make_template_hash for metal kernel (ml-explore#4584) Signed-off-by: GokayAI <60583610+gokay-ai@users.noreply.github.com> Co-authored-by: Cheng <git@zcbenz.com> * Fix as_strided contiguity (ml-explore#4575) * Reject non-aligned pointers when converting to mx.array (ml-explore#4592) * Fix conjugation in complex VJPs for inverse trig ops, cos, sqrt, and rsqrt (ml-explore#4606) * Fix complex to bool (ml-explore#4593) * [jaccl] second cable for the mesh (ml-explore#4607) * Fix vmap of scatter placing the batch axis wrongly in the updates (ml-explore#4322) Co-authored-by: Cheng <git@zcbenz.com> * Unroll TK=4 keys per iter in sdpa_vector_2pass_1 (ml-explore#4596) Co-authored-by: Cheng <git@zcbenz.com> * Fix CPU float16 SIMD comparison masks (ml-explore#4602) Co-authored-by: Cheng <git@zcbenz.com> * Add jvp support for logcumsumexp (ml-explore#4611) * [CUDA] Export CommandEncoder and Device (ml-explore#4619) * Use the fast qmv kernel for outputs not divisible by 8 (ml-explore#4516) Co-authored-by: Cheng <git@zcbenz.com> * Fix ResidencySets reading autoreleased error object (ml-explore#4623) * Use the small-channel implicit gemm loader for C_per_group = 8 (ml-explore#4617) * [CUDA] Reduce floor for fp_gather_qmv (ml-explore#4620) * Fix default.metallib lookup under swift test with Swift Build (ml-explore#4527) * Fix metal validation error when passing empty vector (ml-explore#4622) Co-authored-by: Cheng <git@zcbenz.com> * Replace Black formatter with ruff (ml-explore#4600) * Tune M1 quantized matmul dispatch for six-row large shapes (ml-explore#4629) Co-authored-by: deadbydawn <gothravenllm@gmail.com> Co-authored-by: Cheng <git@zcbenz.com> * [metal] Add env var based residency refresh interval (ml-explore#4633) * Promote integer inputs in logcumsumexp (ml-explore#4625) Co-authored-by: Cheng <git@zcbenz.com> * Fix slicing's non contiguous start (ml-explore#4599) * Fix float16 overflow in clip_grad_norm (ml-explore#4626) * Collapse the non sorted axes to pick the contiguous sort kernel (ml-explore#4366) Co-authored-by: Cheng <git@zcbenz.com> * Fix 32 bit dispatch grid overflow in Metal reductions (ml-explore#4437) Co-authored-by: Cheng <git@zcbenz.com> * Fix gpu boolean masking in 0 dim array (ml-explore#4635) Co-authored-by: Cheng <git@zcbenz.com> * Fix vmap of an inverse real FFT to an odd length (ml-explore#4637) * Fix cross-process race in CPU compile cache (ml-explore#4638) Co-authored-by: Cheng <git@zcbenz.com> * Update acknowledgments for past pinv contribution (ml-explore#4645) * Fix foreign buffer ownership (ml-explore#4634) * Add MLX_CONV_WINOGRAD switch to disable winograd for conv2d (ml-explore#4639) * Keep split-K quantized matmul partials in float32 (ml-explore#4641) * Thin N GEMM kernels (ml-explore#4640) Co-authored-by: Cheng <git@zcbenz.com> * Add 1-bit affine quantization support (Metal) (ml-explore#3161) Co-authored-by: Angelos Katharopoulos <a_katharopoulos@apple.com> Co-authored-by: bri-prism <288398250+bri-prism@users.noreply.github.com> * Update Metal Complex division in numpy style to avoid overflow condition (ml-explore#4644) * Fix pickle bfloat16 strides (ml-explore#4649) * Fix metal negative stride index in masked_scatter/scatter/SDPA mask/segmented_gemm (ml-explore#4650) * Fix missing break binary bool (ml-explore#4651) * Fix cpu binary_op_dispatch_dims on large data (ml-explore#4648) * Add FloorDivide primitive for integer floor division (ml-explore#4642) Co-authored-by: Cheng <git@zcbenz.com> * [Metal] Fix SDPA max threadgroup for M1/M2 generation (ml-explore#4643) Co-authored-by: Cheng <git@zcbenz.com> * Fix incorrect output mask computation in `mx.block_masked_mm` (ml-explore#4652) * Add thin M GEMM dispatch (ml-explore#4654) * Fix Python dtpye -> mlx conversion narrowing (ml-explore#4656) * Fix input/output scalar merging in compile (ml-explore#4658) Co-authored-by: Cheng <git@zcbenz.com> * Validate .npy shape in mlx/io/load.cpp (ml-explore#4657) Co-authored-by: Cheng <git@zcbenz.com> * Replace "pull_request_target" event with "pull_request" in update_bypass_list workflow (ml-explore#4667) * [CUDA] Only count consecutive misses in the LRUCache thrashing check (ml-explore#4661) Co-authored-by: Cheng <git@zcbenz.com> * Fix conv input gradient shape with uneven or large padding (ml-explore#4662) * Fix missing stream in layer_norm and sdpa fallbacks (ml-explore#4663) Co-authored-by: Cheng <git@zcbenz.com> * Fix direct CPU conv writing past output (ml-explore#4668) Co-authored-by: Cheng <git@zcbenz.com> * Add stft and istft to mlx.core.fft (ml-explore#3639) * Fix lost rank output in the distributed launcher (ml-explore#4615) Co-authored-by: Cheng <git@zcbenz.com> * Fix split-K test compatibility on M5, M6 (ml-explore#4677) * Fix signedness warning in quantized Metal tail bounds check (ml-explore#4675) * Fix batched row count mismatch in metal qvm_split_k (ml-explore#4673) Co-authored-by: Cheng <git@zcbenz.com> * Fix metal conv bounds checks and integer overflows (ml-explore#4672) Co-authored-by: Cheng <git@zcbenz.com> * python: Make arctan2/radians/degrees support scalar inputs (ml-explore#4679) Co-authored-by: Cheng <git@zcbenz.com> * Fix missing add_temporary in pad_gpu/fill_gpu (ml-explore#4660) Co-authored-by: “Ronald <“Ronaldmannak@me.com”> * Enable non-transposed NAX gather_qmm_rhs (ml-explore#4684) * Add Metal extension build support (ml-explore#4004) * Adding minmax method to MLX to follow Numpy/Jax API (ml-explore#4674) Co-authored-by: Cheng <git@zcbenz.com> * Fix missing stream in gather matmul indices cast (ml-explore#4687) * [BUG] Metal fence deadlock (ml-explore#4689) * Patch bump to 0.32.5 (ml-explore#4707) * docs: Publishing a New Release (ml-explore#4691) * ci: Run update_bypass_list on push instead of pull_request (ml-explore#4671) * [CUDA] Run the vector SDPA kernels at head_dim 256 (ml-explore#4698) Co-authored-by: yanghaojin <haojin.yang@greenbit.ai> * [CUDA] Fix grouped gemm with large data (ml-explore#4696) Co-authored-by: yanghaojin <haojin.yang@greenbit.ai> Co-authored-by: Cheng <git@zcbenz.com> * Fix conv2d OOB reads for partial output-channel tiles (ml-explore#4653) * docs: MetalLibrary in custom extension guide (ml-explore#4701) * [Metal] Fix SDPA f16/f32 d512 max threadgroup for M1/M2 generation (ml-explore#4708) * Add float16 head_dim 256 TK=1 SDPA vector kernel for M1/M2 (ml-explore#4719) Co-authored-by: Cheng <git@zcbenz.com> * Allow configuring the CPU JIT cache directory (ml-explore#4714) Co-authored-by: Cheng <git@zcbenz.com> * Make `broadcast_arrays` return a tuple (ml-explore#4713) Co-authored-by: Cheng <git@zcbenz.com> * Fix unaligned scalar reads and oversized contiguous buffer views (ml-explore#4721) Co-authored-by: Cheng <git@zcbenz.com> * [Metal] Add staged affine_qmm_t_nax kernels with split-k (ml-explore#4682) Signed-off-by: Yanzhao Wang <yzwang1996@gmail.com> Co-authored-by: Cheng <git@zcbenz.com> * [Metal] Add fast route for dequantizing fp4 to half in fp_qmm_t (ml-explore#4709) Co-authored-by: Cheng <git@zcbenz.com> * [Metal] Add qmv_mma/qmv_nax kernels for 6-16 rows with large N/K (ml-explore#4712) Co-authored-by: Cheng <git@zcbenz.com> * docs(forkdiff): move the base to upstream c6abf0d after the merge Set base.hash to the new merge-base. Remove the v0.32.2 sync section and the gather_mm row-tile backport section, because upstream now has those changes. Keep the revert of the ml-explore#4352 simdgroup skip in its own section. Reduce the floor_divide section to the tests the fork keeps. Add the re-deleted bypass-list workflow and scripts to Fork tooling. Keep the revert of the ml-explore#4352 simdgroup skip in fp_gather_qmm_rhs_nax and affine_gather_qmm_rhs_nax. The merge had taken upstream's sg_active guard there. State the new upstream sync policy in FORKDIFF.md: merge upstream when David directs it, and move base.hash at each merge. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix: repair the merge in the quantized kernels and the lint The merge put upstream's new "typename U = T" template parameter on the fork's qmm_t_expert_impl instead of qmm_t_impl. Move it back. fp_gather_qmv_fast_tail now calls adjust_matrix_offsets with the global scale, as upstream's fp_gather_qmv_fast does. Remove the extra closing brace that the previous commit put in affine_gather_qmm_rhs_nax. The kernel body is again the fork's body. Import numpy in test_fast_sdpa.py again. Upstream removed the import, and the fork's FP32-partials tests use it. Wrap the long lines in check_forkdiff.py for the ruff E501 rule that upstream turned on. Remove the PR #15 bias-sum sentence from fork.yaml: upstream now promotes the bias-sum operands itself (ml-explore#4516). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * test: follow the upstream allocator and gather_qmm APIs in fork tests Upstream allocator::malloc now returns an owning allocator::Data, and allocator::free is gone. The fork's snapshot and footprint tests need explicit release points, so they use allocator::allocator().malloc and free, as upstream's own allocator tests do. Upstream gather_qmm takes a global_scale argument before sorted_indices. Pass std::nullopt in the GPT-OSS MXFP4 tests. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(cpu): floor_divide of min by -1 must not trap Upstream's FloorDivide divides the minimum signed value by -1 on the CPU. The quotient overflows, and on x86 the division traps (SIGFPE). The fork test "test floor_divide integer edge cases on the CPU" crashed in the Fedora x86_64 job. Divide by 1 there instead, as the PR #32 functors did. The result wraps to min. Describe the guard in the floor_divide section of fork.yaml. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Compute the JACCL ring wire offsets in 64 bits CodeQL (cpp/integer-multiplication-cast-to-long) flagged the ring's wire offset expressions on PR 38: `lr * n_wires` is an `int` product that is widened to 64 bits only after the multiplication. The same pattern is in three ring_impl.h loops and in the two `size_ * 2 * n_conns_` thresholds in ring.cpp. Widen the first operand to int64_t so every product is computed in 64 bits. The operands are small, so results do not change. fork.yaml describes the new fork change. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * Compute the vector SDPA query layout check in 64 bits CodeQL (cpp/integer-multiplication-cast-to-long, alert 29) fails the PR 38 check on the vector SDPA query layout test: `shape[3] * shape[bidx]` is an `int` product compared with a 64-bit stride. Widen `shape[3]` to int64_t. The shapes are small, so the result does not change. The fork.yaml section for the JACCL ring fix now covers this file too. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * Fix `mx.take`'s negative indices (ml-explore#4729) * Fix normal loc scale shape (ml-explore#4730) * Fix zero-copy numpy arrays dtype mismatch (ml-explore#4731) * ci: skip the 4 GiB reduce test where the runner cannot hold it Upstream's test_init_reduce_large_output (ml-explore#4437) makes a 4 GiB boolean output. The fork CI runs on a GitHub-hosted macOS runner with a 3.5 GiB Metal buffer limit and 7 GB of memory. On the GPU the allocation fails; on the CPU it competes with the other test files for memory. Skip the test when the default device cannot hold the output. Machines with more memory still run it. When a CPU test file fails, print the end of its log at once. The job of the previous run was stopped before the full logs printed, so the cause of the test_eval failure on the CPU is not known. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Widen affine qmv_wide row tiles to 8 (ml-explore#4728) * Fix/padding jvp vjp (ml-explore#4736) * fix: qqmm refuses a global scale on the CPU; adapt GPU-path tests The CPU QQMatmul kernel has no global scale input and ignores the scales that qqmm passes to it. qqmm with global scales on a CPU stream returned a wrong result with no error: in the fork CPU test pass, test_fp_qmv_fast_unaligned_n_global_scale differed by about 1000. qqmm now raises "Global scale is only supported on the GPU" on a stream that is not a GPU stream, as gather_qmm already does. Upstream tests that check only GPU kernels failed in the CPU pass: test_sdpa_vector_2pass_threadgroup_limit (force_fused=True), test_fp_qmv_fast_unaligned_n_global_scale, test_qqmm_global_scale_matrix_kernels and test_gather_qmm_global_scale. When the default device is the CPU, they now check that the documented error is raised. The GPU pass runs them as before. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * ci: add a temporary diagnostic for the CPU NaN; reword the 4 GiB skip Add one temporary step after the build in metal-build-and-test. It runs the failing case of test_fp_gather_qmm_non_multiple_of_32 (K=512, N=1040, transpose=False, sorted, float32) on the CPU with a fresh allocator, after a warm-up that fills the allocator cache with NaN buffers, and with the buffer cache off, and on the GPU. It prints NaN counts per expert for w, w_hat, y_q and y_hat. The step has continue-on-error, so the full test suite still runs. The next push removes it. State in fork.yaml when test_init_reduce_large_output skips, why it cannot be smaller (ml-explore#4437), and that David ruled on 2026-10-23 to keep the skip. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * ci: move the CPU NaN diagnostic to its own short job Remove the temporary diagnostic step from metal-build-and-test. Its reimplementation found no NaN in any mode. Add a temporary job, diag-cpu-nan, that builds the wheel and runs only the diagnostic, so its log is ready after the build. It runs the real test_fp_gather_qmm_non_multiple_of_32 alone, then after the tests that come before it, and an instrumented copy of the test body (only the failing case, and all cases in the test order, each evaluated as one graph). The findings also go to ::notice annotations. The next push removes the job. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * ci: install numpy for the temporary NaN diagnostic job The tests import numpy through mlx_tests. The diagnostic job installed only the wheel, so every run stopped at the import. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Fix data race in distributed ring on pending send/recv lists (ml-explore#4737) Co-authored-by: Cheng <git@zcbenz.com> * Use data_size for gather/scatter large-offset checks (ml-explore#4724) Co-authored-by: Cheng <git@zcbenz.com> * fix(cpu): clear C before the BLAS matmul when beta is 0 test_fp_gather_qmm_non_multiple_of_32 (K=512, N=1040, sorted, float32) gave NaN on the CPU. The diagnostic job found the NaN only in the reference y_hat = x @ w_sel, a batched matmul with M = 1. Its inputs had no NaN. The test failed alone too, but only after the earlier subtests of the same test: y_hat is 266240 bytes, the same size as the packed fp4 weights of the previous subtest, so the output reused that buffer from the allocator cache. Accelerate read C even with beta = 0 and computed NaN * 0. Fill C with zeros before cblas_sgemm, cblas_dgemm and cblas_cgemm when beta is 0. MLX's own SIMD gemm already skips C when beta is 0. Remove the temporary diagnostic job. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(cpu): clear C at every BLAS gemm call with beta 0 The previous commit cleared C only in the gemms/cblas.cpp wrappers. Four more call sites call cblas_sgemm directly with beta 0: BlockMaskedMM and GatherMM (the CPU MoE gathered matmul) in masked_mm.cpp, and the two explicit-gemm convolutions in conv.cpp. They can give the same NaN * 0 from a reused output buffer. Add one helper, clear_gemm_output in gemm.h, that fills the exact C region of a call (rows by columns, with its ldc) with zeros. Use it at all five call sites, the wrappers included. No other BLAS gemm or gemv call exists in the CPU backend. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * ci: build once and run the Metal and CPU test passes in parallel Split the fork-tests job into parallel jobs. build-wheel and build-cpp build in parallel. build-cpp also runs the C++ tests on the GPU and on the CPU. python-gpu (3 shards) and python-cpu (4 shards) run the Python tests from the uploaded wheel. metal-build-and-test merges the coverage profiles of all jobs, writes the same coverage report, and fails when another job failed. python_shards.py checks the shard map: each python/tests/test*.py file must be in each pass exactly one time. Split files must partition their test IDs. The last job fails when a test ran in two shards. fork-build-cache restores and saves ccache on pull requests and on main, and keeps a cache of the compiled Metal kernels through an xcrun wrapper keyed on the preprocessed source, the arguments and the toolchain. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * [CUDA] Fix gather_qmm for experts past 2^32 weight elements (ml-explore#4738) Co-authored-by: Cheng <git@zcbenz.com> * ci: split the long CPU test files and skip cache saves with no misses Split test_fast_sdpa and test_quantized into named tests and rest entries in the CPU shards, so that no CPU shard has an entry longer than test_gated_delta_sequential. Put the entries in longest-first order. Save the ccache files and the Metal kernel cache only when the build had misses. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * ci: key the build caches on compiler versions, not the runner image The full --version text of clang and metal names the install folder and the OS, and it changed between three macos-26 runner images, so every job started from an empty cache. Key ccache on the clang major.minor version and fall back to a cache of another clang version; ccache keeps compiler_check=content. Key the Metal kernel cache on the metal compiler version and the kernels hash, and fall back only to a cache of the same metal compiler. Each Metal entry key holds the first line of the metal --version text and the SDK build. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * Add array::is_uniquely_referenced for the fork C API Upstream 5dbe999 (ml-explore#4634) makes is_donatable() also require that MLX owns the buffer, so the allocator never reuses a wrapped external buffer. The fork's mlx-c buffer-info API reported `unique` from is_donatable(), and mlx-swift-lm uses that as a "no other reference" proof for paged KV segments, checkpoint memory accounting and MTP state, including wrapped host pages, which now always read as not unique. Add is_uniquely_referenced(): the same reference-count test without the ownership test. is_donatable() and donation behavior do not change. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * fix: async_eval must not throw a stream task error test_eval.test_async_eval_error_in_synchronize (upstream ml-explore#4338) failed on some runs of the fork's CPU test pass: mx.async_eval raised the LU factorization error that the test expects only from mx.synchronize. Cause: StreamThread::enqueue throws the stream's stored error when it runs on the main thread (ml-explore#3742). async_eval enqueues several tasks. When the stream thread finishes the failing task before async_eval enqueues the next one, that enqueue throws. The order depends on thread timing, so the failure is intermittent. The fork does not change this path. async_eval now holds a scheduler::DeferStreamErrors guard. While it lives, enqueue on that thread does not throw the stored error, and synchronize throws it later. eval does not change. Add a C++ test that stores the error before async_eval, so it fails on every run without the fix. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * Fix GPU pad for outputs larger than 2^31 elements (ml-explore#4744) * ci: format python_shards.py with the pinned ruff Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * ci: run the Python tests in 2 GPU and 3 CPU shards The hosted macOS runners are a shared pool. Pack the GPU pass into 2 shards and the CPU pass into 3 shards, balanced by the durations that run 39902948153 measured. A run now uses 8 macOS jobs, and at most 6 run at the same time (before: 10 jobs, 8 at the same time). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * ci: give the NAX kernels Metal cache hits and lighten CPU shard 0 The preprocessed source of the NAX kernels names the Metal toolchain mount folder, which has a random suffix on each runner. The 10 NAX kernels missed the Metal cache in every warm build (41 of 51 hits). Remove the suffix from the text that the key hashes, and keep the toolchain version. CPU shard 0 was the slowest shard in the cold and warm runs of b72420d (651 s and 470 s of tests). Move test_quantized:rest to CPU shard 1 (221 s). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> * docs(forkdiff): move the base to upstream afc03c5 Set base.hash to the new merge-base after the merge of the 9 upstream commits. No fork section changes: the merge has no conflict, and each merged file gets exactly upstream's change. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> --------- Signed-off-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com> Signed-off-by: Vaibhav Srivastava <vaibhavsri1712@gmail.com> Signed-off-by: Ranran Haoran Zhang <ranranhaoranzhang@gmail.com> Signed-off-by: GokayAI <60583610+gokay-ai@users.noreply.github.com> Signed-off-by: Yanzhao Wang <yzwang1996@gmail.com> Co-authored-by: rohith <kapellirohith@gmail.com> Co-authored-by: Cheng <git@zcbenz.com> Co-authored-by: Vladimir Iglovikov <ternaus@users.noreply.github.com> Co-authored-by: Brian C. <94733710+deBrian07@users.noreply.github.com> Co-authored-by: Cheng <zcbenz@gmail.com> Co-authored-by: Erwin Zhang <59893706+erwinzhang7@users.noreply.github.com> Co-authored-by: Daniel Hiltgen <dhiltgen@users.noreply.github.com> Co-authored-by: Daniel Hiltgen <daniel.hiltgen@ollama.com> Co-authored-by: Aaishwarya Mishra <aaishwarymishra@gmail.com> Co-authored-by: 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Fixes #4283.
The existing checks cover the shape of the rdma matrix and its null diagonal, not
whether the pairs about to be used are present, so a hostfile whose rank order places
unconnected nodes beside each other passes and then leaves every rank alone in a
group of size one, reporting success. Same class as #4210.
missing_jaccl_linksreports the pairs that are used but absent: for a ring eachrank's two neighbours, for a mesh every pair. With two ranks the previous and next
neighbour are the same node, which is harmless because the pair is simply examined
twice. The error names the hosts and says that for jaccl-ring the host order is the
ring order, since that is the mistake that produces it.
Checked against a live four node mesh: the misordered hostfile is now rejected, a
ring hostfile used as a mesh is rejected, and valid mesh and valid ring hostfiles
still run at 20.87 and 16.33 GB/s respectively. Six unit tests cover mesh, ring, the two rank
edge case and a ring that is deliberately not a mesh.