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Fix crash on ellipsis indexing with too many trailing indices - #4396

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nastya236 merged 4 commits into
ml-explore:mainfrom
Adityaj0:pr-fix-ellipsis-indexing-crash
Aug 28, 2026
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Fix crash on ellipsis indexing with too many trailing indices#4396
nastya236 merged 4 commits into
ml-explore:mainfrom
Adityaj0:pr-fix-ellipsis-indexing-crash

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@Adityaj0

@Adityaj0 Adityaj0 commented Aug 25, 2026 •
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Fixes #4398

Indexing with an ellipsis followed by more non-None indices than the array has dimensions computed an unsigned (size_t) underflow in the ellipsis-expansion loop bound, causing an out-of-bounds read / crash instead of raising a ValueError. Adds a regression test covering getitem and setitem.

@Adityaj0
Fix crash on ellipsis indexing with too many trailing indices
7d1ca6d 
mlx_expand_ellipsis in python/src/indexing.cpp computed the ellipsis
expansion loop bound as `shape.size() - non_none_indices_after`, mixing
an unsigned size_t with a signed int. When an index expression has more
non-None indices after the ellipsis than the array has dimensions (e.g.
a[..., 0, 0] on a 1-D array), this subtraction underflows to a huge
unsigned value, so the loop reads far past the end of the shape vector
and pushes an unbounded number of slices, crashing the process (SIGSEGV)
instead of raising an error. The existing "too many indices" check in
mlx_get_item_nd ran only after this expansion, so it never caught this
case.

Move the bounds check before expansion and do the arithmetic in signed
int, so this now raises the same "Too many indices" ValueError that
already applies when the extra indices are before the ellipsis.

Adds a regression test in python/tests/test_array.py covering
getitem and setitem with an ellipsis followed by too many indices.
@Adityaj0 Adityaj0 mentioned this pull request Aug 25, 2026
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@nastya236
nastya236 self-requested a review August 25, 2026 11:22
nastya236
nastya236 approved these changes Aug 25, 2026
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thanks for the fix! I merged the test into indexing.

zcbenz
zcbenz requested changes Aug 26, 2026
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Running this locally crashes:

Exception Type:        EXC_BAD_ACCESS (SIGSEGV)
Exception Codes:       KERN_INVALID_ADDRESS at 0x0000000116f98000
Exception Codes:       0x0000000000000001, 0x0000000116f98000

Termination Reason:    Namespace SIGNAL, Code 11 Segmentation fault: 11
Terminating Process:   exc handler [57082]

VM Region Info: 0x116f98000 is not in any region.  Bytes after previous region: 344065  Bytes before following region: 425984
      REGION TYPE                    START - END         [ VSIZE] PRT/MAX SHRMOD  REGION DETAIL
      mapped file                 116f08000-116f44000    [  240K] r--/r-x SM=ALI  Object_id=32228d39
--->  GAP OF 0xbc000 BYTES
      MALLOC_SMALL                117000000-117800000    [ 8192K] rw-/rwx SM=PRV  

Thread 0 Crashed::  Dispatch queue: com.apple.main-thread
0   core.cpython-313-darwin.so    	       0x104e59390 0x104de0000 + 496528
1   core.cpython-313-darwin.so    	       0x104e59c34 0x104de0000 + 498740
2   core.cpython-313-darwin.so    	       0x104e5d31c 0x104de0000 + 512796
3   core.cpython-313-darwin.so    	       0x104e02540 0x104de0000 + 140608
4   core.cpython-313-darwin.so    	       0x104de88ac 0x104de0000 + 34988
5   libpython3.13.dylib           	       0x105a270dc vectorcall_method + 192
6   libpython3.13.dylib           	       0x105a26ff4 slot_mp_subscript + 52
7   libpython3.13.dylib           	       0x105a803c0 _PyEval_EvalFrameDefault + 24016
8   libpython3.13.dylib           	       0x105cf5f88 method_vectorcall.llvm.5380863741279050681 + 176
9   libpython3.13.dylib           	       0x105a88850 _PyEval_EvalFrameDefault + 57952
10  libpython3.13.dylib           	       0x105aeea6c _PyObject_Call_Prepend + 152
11  libpython3.13.dylib           	       0x105aee510 slot_tp_call + 216
12  libpython3.13.dylib           	       0x105a8cf40 _PyEval_EvalFrameDefault + 76112
13  libpython3.13.dylib           	       0x105cf5f88 method_vectorcall.llvm.5380863741279050681 + 176
14  libpython3.13.dylib           	       0x105a88850 _PyEval_EvalFrameDefault + 57952
15  libpython3.13.dylib           	       0x105aeea6c _PyObject_Call_Prepend + 152
16  libpython3.13.dylib           	       0x105aee510 slot_tp_call + 216
17  libpython3.13.dylib           	       0x105a8cf40 _PyEval_EvalFrameDefault + 76112
18  libpython3.13.dylib           	       0x105cf5f88 method_vectorcall.llvm.5380863741279050681 + 176
19  libpython3.13.dylib           	       0x105a88850 _PyEval_EvalFrameDefault + 57952
20  libpython3.13.dylib           	       0x105aeea6c _PyObject_Call_Prepend + 152
21  libpython3.13.dylib           	       0x105aee510 slot_tp_call + 216
22  libpython3.13.dylib           	       0x105a859ec _PyEval_EvalFrameDefault + 46076
23  libpython3.13.dylib           	       0x105cf5f88 method_vectorcall.llvm.5380863741279050681 + 176
24  libpython3.13.dylib           	       0x105a88850 _PyEval_EvalFrameDefault + 57952
25  libpython3.13.dylib           	       0x105aeea6c _PyObject_Call_Prepend + 152
26  libpython3.13.dylib           	       0x105aee510 slot_tp_call + 216
27  libpython3.13.dylib           	       0x105a859ec _PyEval_EvalFrameDefault + 46076
28  libpython3.13.dylib           	       0x105cf6004 method_vectorcall.llvm.5380863741279050681 + 300
29  libpython3.13.dylib           	       0x105a8ab9c _PyEval_EvalFrameDefault + 66988
30  libpython3.13.dylib           	       0x105d1c550 slot_tp_init + 512
31  libpython3.13.dylib           	       0x105d1a7e8 type_call + 148
32  libpython3.13.dylib           	       0x105a8b530 _PyEval_EvalFrameDefault + 69440
33  libpython3.13.dylib           	       0x105b6ba0c PyEval_EvalCode + 132
34  libpython3.13.dylib           	       0x105b6b904 run_eval_code_obj + 100
35  libpython3.13.dylib           	       0x105b6aea0 run_mod.llvm.13438019438753279242 + 148
36  libpython3.13.dylib           	       0x105c90b64 pyrun_file + 164
37  libpython3.13.dylib           	       0x105c906fc _PyRun_SimpleFileObject + 256
38  libpython3.13.dylib           	       0x105c904bc _PyRun_AnyFileObject + 80
39  libpython3.13.dylib           	       0x105c9039c pymain_run_file_obj + 164
40  libpython3.13.dylib           	       0x105c901dc pymain_run_file + 76
41  libpython3.13.dylib           	       0x105bf44e4 Py_RunMain + 1068
42  libpython3.13.dylib           	       0x105be9c74 pymain_main + 468
43  libpython3.13.dylib           	       0x105be9a94 Py_BytesMain + 36
44  dyld                          	       0x190ebab98 start + 6076

@nastya236

nastya236 commented Aug 26, 2026 •
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Interesting, why it was not caught on CI..

@nastya236 nastya236 added the await response This pull request is waiting for response from the author. label Aug 26, 2026
@Adityaj0

Adityaj0 commented Aug 27, 2026

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Thanks for flagging this. I checked out the latest commit on this branch and rebuilt locally, then ran a bunch of over-indexing cases through it: plain trailing indices, mixed slices, None/newaxis combos, scalar arrays, boolean indices, array indices, and both getitem and setitem. All of them raise ValueError like they should, I couldn't get a crash.

Would you mind sharing the exact snippet that segfaulted for you, plus your Python version and how you built the extension? Want to make sure I'm testing the same thing you hit.

zcbenz
zcbenz approved these changes Aug 27, 2026
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No longer able to reproduce crash after a clean build, seems to be bad local build.

@zcbenz zcbenz removed the await response This pull request is waiting for response from the author. label Aug 27, 2026
@nastya236
nastya236 merged commit 99e45f7 into ml-explore:main Aug 28, 2026
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aaishwarymishra pushed a commit to aaishwarymishra/mlx that referenced this pull request Sep 11, 2026
@Adityaj0 @nastya236 @aaishwarymishra
Fix crash on ellipsis indexing with too many trailing indices (ml-exp…
6f37462 
…lore#4396)

Co-authored-by: Anastasiia Filippova <a_filippova@apple.com>
Gajesh2007 pushed a commit to Layr-Labs/mlx that referenced this pull request Oct 23, 2026
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Merge upstream ml-explore/mlx main afc03c5 (2026-10-23) (#38)
7b0ebaf 
* 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: YH Yan <strayberry0w0@gmail.com>
Co-authored-by: Dwijen Patel <dwijen@gmail.com>
Co-authored-by: Anastasiia Filippova <a_filippova@apple.com>
Co-authored-by: Ayaan Gazali <ayaangazali.work@gmail.com>
Co-authored-by: katlun-lgtm <katlun@gmail.com>
Co-authored-by: katlun-lgtm <katlun@windyviews.com>
Co-authored-by: Adityaj0 <93090622+Adityaj0@users.noreply.github.com>
Co-authored-by: Eyüp Can Akman <eyupcanakman@gmail.com>
Co-authored-by: Pradyot Ranjan <99216956+prady0t@users.noreply.github.com>
Co-authored-by: Pradyot Ranjan <99216956+pradyotRanjan@users.noreply.github.com>
Co-authored-by: Jagrit Digani <digani@apple.com>
Co-authored-by: Philip John Basile <PBasile@Basilecom.com>
Co-authored-by: Alessio Pollero <alessio.pollero@ventureone.ae>
Co-authored-by: Duhyeon, Kim <49020301+dudududukim@users.noreply.github.com>
Co-authored-by: Atirna <noctiselara0@gmail.com>
Co-authored-by: Saud Kamran <32072820+saud5150@users.noreply.github.com>
Co-authored-by: Saud <saudkamran@Sauds-MacBook-Pro.local>
Co-authored-by: YH Yan <yh.yukiyan@gmail.com>
Co-authored-by: Roshan Sharma <rs127@fordham.edu>
Co-authored-by: sashko-zakharchuk <oleksandr.zakharchuk@gmail.com>
Co-authored-by: XXXXRT666 <157766680+XXXXRT666@users.noreply.github.com>
Co-authored-by: Vaibhav Srivastava <vaibhavsri1712@gmail.com>
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[BUG] Crash on ellipsis indexing with too many trailing indices

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