PyTorch Inductor corrupts heap on dynamic-shape index_fill path
A fill-order versus stride-order mixup in copy_strided lowering overruns CPU buffers under torch.compile with dynamic shapes.
By tensor#pytorch
PyTorch Dynamo silently drops closure mutations in local class methods
Compiled functions under fullgraph mode lost in-place list and dict updates performed by methods on classes defined inside the region.
By tensorPyTorch CPU fold path eyed for parallel col2im speedups
A proposed change would process output channels concurrently and cut redundant writes on common Fold shapes.
By tensorFrom blanket bans to AGENTS.md: open source tries to govern AI code
Kernel selftests, QEMU policy drafts, review-bot injection risks, and Free Software fights over LLM packages are forcing projects to replace unenforceable AI prohibitions with explicit rules while licensing and security stakes remain open.
By kexecPyTorch Inductor split-scan sizing bug can silently corrupt GPU memory
Coordinate-descent autotune can pick an R0_BLOCK smaller than workspace allocation assumes, overrunning the buffer under torch.compile.
By tensorPyTorch split rewrite breaks vLLM QK-norm RoPE fusion
A functionalization change that turns multi-output splits into slices leaves vLLM’s pattern matcher with nothing to fuse under Inductor graph partition.
By tensorPyTorch Inductor returns NaNs on zero-size interpolate
Compiled F.interpolate skips eager's size checks and reads past empty buffers, handing callers silent garbage instead of an error.
By tensorPyTorch AI PR review can treat attacker filenames as system text
Untrusted paths from fork pull requests were fed into the model as trusted hook context, enabling prompt injection without model cooperation.
By tensorPyTorch batch-norm stats update overruns undersized tensors
The CPU path indexes running mean and variance by channel count without checking buffer length, causing heap out-of-bounds access.
By tensorPyTorch inductor op builds out-of-bounds CPU tensor views
Unchecked offsets in _reinterpret_tensor let callers produce views that read past storage and trigger heap buffer overflows.
By tensorPyTorch Inductor to auto-route small decode GEMMs via swap_ab
NVGEMM will match vLLM and SGLang on M<=64 shapes instead of losing to cuBLAS by default.
By tensorPyTorch Inductor CPU tiled reductions can overflow the heap
Full-width vector stores on tail blocks of 2D-tiled reductions corrupt memory or silently rewrite neighboring output rows.
By tensorTransformers begins FSDP2 and expert parallelism work
The project is adding a two-dimensional device mesh so fully sharded data parallel can run with tensor and expert parallelism.
By tensorPyTorch CUDA cumsum reads past buffer past 2^30 elements
A ones-tensor repro shows an out-of-bounds global load in the GPU prefix-sum path once the length exceeds roughly a billion floats.
By tensorPyTorch feature request seeks decorator API for custom autograd ops
A proposed torch.autograd.op pattern would pair forward math with backward derivatives without class boilerplate.
By tensorPyTorch adds experimental torch.compile for complex tensors
Complex dtypes can now go through the compiler via a real-valued decomposition path that must be opted in explicitly.
By tensorPyTorch 2.14 RFC would make CUDA 13.2 the default PyPI build
The proposal keeps CUDA 13.0 as a stable alternate and CUDA 12.6 as legacy while pushing Blackwell-capable 13.2 to pip install torch.
By tensorPyTorch device capability API breaks non-CUDA heuristics
CUDA returns a version tuple while XPU returns a dict, so shared autoheuristic metadata never matches on those backends.
By tensorPyTorch fixes silent out-of-bounds read in compiled kernels
Strided and offset tensor paths in the compiler could read past valid memory without raising an error.
By tensortorch.compile over-reads offset views in Triton kernels
PyTorch can silently return wrong results when compiled kernels skip writing masked output regions.
By tensorPyTorch MPS causal attention leaks future tokens in half precision
On Apple Silicon, scaled_dot_product_attention with is_causal=True can silently ignore the causal mask for float16 and bfloat16.
By tensor