VEDA PyTorch

VEDA PyTorch is a library to add device support for the NEC SX-Aurora TSUBASA into PyTorch.

Python Versions Maintenance

Release Notes

Version	Comment
v14.1.1	Bugfix to prevent endless loop in PyTorch dispatcher.
v14.1.0	Added support to allocate float16 and bfloat16 Removed named tensor APIs for PyTorch >= 2.13.0
v14.0.1	Increased c10d compatibility (tested on v2.5-2.9) Added better error handling when running on systems with missing VEOS installation.
v14	Starting with v14, VEDA PyTorch is no longer distributed as precompiled binary but gets compiled as PyTorch C++ extension on the target machine. So you don't need to install a matching binary package anymore! We further added a experimental implementation for using NEC MPI. You can create the process group as follows: `torch.distributed.init_process_group( backend = 'veda', world_size = os.environ['MPISIZE'], rank = os.environ['MPIRANK'], store = torch.distributed.Store() )` Further changes: Added support for PyTorch v2.9.0 Added `arange.start_out` Added function tracing. Activate using `TUNGL_LOG=TRACE` Bugfix for `aten::cat.out` Bugfix for `copy_` Bugfix for `torch.load(location='ve')` Removed unnecessary context sync
v13	Fixed `torch.ve.set_device` Fixed allocation on wrong VE in multi-process execution Improved error messages Upgraded build script for PyTorch >=2.7!
v12	Added auto plugin loading for Pytorch. `import veda.pytorch` is no longer required with PyTorch >=2.5!
v11	Fixed shutdown problem in mixed GPU/VE use cases.
v10	Support for PyTorch v2.3.1 Support for SX-Aurora VE3
v9	Support for PyTorch v2.3.0
v8	Added `torch.logical_not`
v7	Support for PyTorch v2.0.0 Support for PyTorch v1.13.0 Added `torch.log1p`
v6	Support for PyTorch v1.12.0 and v1.12.1
v5	Added `torch.clamp` `torch.clamp_max` `torch.clamp_min` `torch.exp` `torch.log` `torch.norm` `torch.pow` `torch.where` Fixed conversion from numeric value to bool Fixed calling `torch.ve.memory_allocated()` without device id Preventing 0-byte allocations from PyTorch to be passed on to VEDA
v4	fixed possible segfault in Tensor resize if no storage is initialized fixed dtype handling in Scalar to Tensor operations
v3	added squeeze and unsqueeze handlers
v2	Minor changes to enable PyTorch v1.11.0 Fixed vedaInit error checking to ignore if already initialized
v1	Initial Release

Metadata

Release files for veda-pytorch 14.1.1

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veda_pytorch-14.1.1-py3-none-any.whl 55.7 kB Oct 8, 2026 Without provenance	Python 3	none	any	Details

Release files / veda_pytorch-14.1.1-py3-none-any.whl

Download URL	veda_pytorch-14.1.1-py3-none-any.whl
Size	55.7 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`7ec547e53e556fa97dcadb771c8fc96466f907a1e268c9ff01b4b48e6b61fead`
BLAKE2b-256 checksum How to use checksums	`fce8d759b20cb167decad2e0bab1f3af69a2e5c084259e0636dfca5da7fac3a4`
Upload date	Oct 8, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.12.3`

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