PyTorch GPU access and drivers are painful
14 posts from 14 people11d activeRising, +5 this week
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[DTensor] threshold() keeps Partial(max) / Partial(min) when value > threshold
...mirrored) | | input `Shard` / `Replicate` | correct (no partial rule involved) | ## Workaround Call `x.redistribute(placements=[Replicate()])` (or `.full_tensor()`) before `threshold` when the input may be `Partial(max/min)` and `value > threshold`. ## Fix direction Make the...
DISABLED test_short_json_timing_enabled_True_include_collectives_True (__main__.NCCLTraceTest)
Platforms: rocm This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_short_json_timing_enabled_True_include_collectives_True&suite=NCCLTraceTest&limit=100) and the most recent trunk [workflow...
[RISC-V] matrix_exp effectively hangs on a small batch containing NaN
### 🐛 Describe the bug On two RISC-V CPU systems, `torch.linalg.matrix_exp` did not return within 12 seconds for a batch of two 2×2 matrices containing one NaN. A full `test_linalg.py` process on SG2044 remained CPU-bound for roughly 28 hours, with sampled native stacks in...
TaskThreadPoolBase::defaultNumThreads() does not cache sched_getaffinity()
### 🐛 Describe the bug Since #194605, c10::TaskThreadPoolBase::defaultNumThreads() calls sched_getaffinity(0, ...) (instead of querying the # of processors/cores, which remains stable) without caching the result. In an environment that changes cpuset.cpus during the job's...
[Bug]: get_top_k_tokens applies scaling and soft capping in the wrong order
### Your current environment Collecting environment information... ============================== System Info ============================== OS : Ubuntu 22.04.5 LTS (x86_64) GCC version : (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0 Clang version : Could not collect CMake version :...
[LocalTensor] fully_shard under LocalTensorMode uses ProcessGroup.rank()==0, so every simulated rank keeps chunks[0]
### 🐛 Describe the bug fully_shard on a Linear under FakePG + LocalTensorMode returns the wrong values (full-shaped, no error). Real multi-process FSDP is unaffected. ### Observed eager [28.0, 92.0, 156.0, 220.0, 284.0, 348.0, 412.0, 476.0] fsdp [28.0, 92.0, 28.0, 92.0, 28.0,...
[c10d][nccl] test_init_with_idx flakes: NCCL watchdog + "driver shutting down" + SIGABRT at teardown (missing destroy_process_group)
...29, SHA 2e9b4aff, failed both attempts ~14.4s). - Test is byte-identical between the failing SHA and latest main; no upstream DISABLED/flaky-bot record exists for it. - Legacy backend has no watchdog, hence only the new path is exposed. Fix: add the same explicit...
[ROCm][Windows] Device-side assert prints no message: C10_USE_ROCM_KERNEL_ASSERT is off in the Windows ROCm wheel
...device-side assert triggered`. Only the missing message is PyTorch's. Expected: the failing assertion's message is printed, as it is on CUDA. ### Versions Windows 11 Pro 10.0.26100.9457; PyTorch 2.11.0+rocm7.13.0a20260416 (HIP 7.2.0, `amdhip64_7.dll` 10.0.3581.0); Python 3.14.6;...
[Inductor][PDL] triton.enable_pdl: a kernel loads a buffer written two kernels back before gdc_wait() when the kernel in between is store-only, giving wrong results
### 🐛 Describe the bug The analysis was done with assistance of AI and was reviewed by me. With `torch.compile(..., options={"triton.enable_pdl": True})`, a kernel's first load of a buffer written *two kernels back* is emitted before `tl.extra.cuda.gdc_wait()` when the kernel...
[Inductor] Compiled softshrink turns NaN into zero
### 🐛 Describe the bug F.softshrink(NaN) returns NaN in eager and aot_eager, but zero with the Inductor backend. This reproduces on CPU and CUDA. ### Error logs No exception. Eager and aot_eager return tensor([nan]); Inductor returns tensor([0.]). ### Versions PyTorch version:...
Tensor.requires_grad_ typing is incorrectly defined in __init__.pyi
### 🐛 Describe the bug `TensorBase.requires_grad_` is typed as `def requires_grad_(self, mode: _bool = True) -> Tensor:` however it actually accepts argument `requires_grad` rather than `mode`: To produce the error: ### Versions PyTorch version: 2.14.0 Is debug build: False...
[PT2] Device-TMA reduction stores lose tma_min_block_sizes
...the bug ## Describe the bug `store_reduction()` bypasses `codegen_block_ptr()` and fails to record an in-kernel device-TMA descriptor. The resulting kernel can select XBLOCK=1 for an fp32 descriptor store, which Triton rejects because 1 * 4 < 16 bytes. ## Minimal reproducer...
[FSDP2][NCCL] Large slowdown for non-16-byte-aligned per-rank collective payloads
### 🐛 Describe the bug ## Summary Using PyTorch's NCCL tensor collectives on a flat buffer with the same per-rank layout as FSDP2's default non-symmetric-memory communication path, a per-rank payload whose byte count is not a multiple of 16 causes a substantial latency...
[MPS] bmm/baddbmm/addbmm silently wrong on M1/M2 when K >= 32767 (2-D paths already routed by #183535)
### 🐛 Describe the bug > This report was prepared with the help of an AI assistant; everything in it was verified by me on an M2 Max running macOS 26.6.2. On Apple7/8 GPUs (M1/M2), MPSGraph matmuls with a reduction dimension K >= 32767 and both output dims >= 16 can sum memory...
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About this problem
Evidence
14 posts from 14 people in 2 places, about 1 a week over 72 days. Mostly on pytorch/pytorch, vllm-project/vllm. Tools named alongside: NVIDIA, GitHub, Inc., Red Hat.
Frustration Frustration 0 of 3· Seen on GitHub issues
How it was grouped
Posts that state a pain and match the "gpu-access" rule about PyTorch. First post Aug 28, 2026, latest Nov 7, 2026. Corroborated: 3 or more posts from 2 or more people or places. Method
The same problem elsewhere
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