TorchCurves adds differentiable B-spline and Legendre curves to PyTorch
Coefficients can train with a surrounding model, with timings against NumPy, SciPy and EfficientKAN.
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Stories tagged #pytorch
TensorBound study maps tensor binding failures in AI stacks
Of 149 reconstructed repaired causes in IREE, XLA, and PyTorch, 69.1% were missing checks, bad mappings, or lost relations.
Zero-valued PyTorch loss can run code in the backward pass
IEEE 754 rounding and autodiff disagree, so a loss logged as 0.0 can still set gradients that rewrite weights.
Google open-sources TorchTPU for running PyTorch on TPUs
TPU support also landed in vLLM, SGLang, TorchTitan, Ray, and Hugging Face libraries, with two pieces still in preview.
Google open-sources TorchTPU so PyTorch apps can run on TPUs
Amazon released TorchNeuron a day earlier to port PyTorch apps to Trainium without rewriting them.
Edge-aware attention cuts graph-generation GPU memory about 65%
A FlexAttention implementation kept generation quality near the baseline while improving training and sampling throughput.
Google open-sources TorchTPU, a native PyTorch back end for TPUs
The feed only shows a Hacker News thread with 42 points and 12 comments.
Google open-sources TorchTPU, a PyTorch backend for Cloud TPUs
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Hugging Face announces native TorchTPU support
The post title says Hugging Face now supports TPUs natively through TorchTPU; no further details were provided.
Hugging Face blog covers MPS in PyTorch 2.15
The title names Metal Performance Shaders support in PyTorch 2.15; the post body was not available.
AWS releases TorchNeuron so PyTorch apps can run on Trainium
Amazon says one configuration line moves PyTorch apps to Trainium and it will upstream changes to loosen Nvidia ties in PyTorch.
Peak-Memory Schedules You Can Trust: Exact Realization, Certified Optimality, and the Limits of Recomputation for Inference
Statement-level reordering certifies peak-memory-optimal inference schedules more reliably than regenerating compiler code.
AI Models Can Provably Hide Arbitrary Capabilities
A paper shows neural nets can cryptographically hide arbitrary capabilities that elicitation audits cannot reliably surface.
KGATE : a Knowledge Graph Embedding Training Environment
KGATE is a modular PyTorch library for training knowledge-graph autoencoders with leakage-controlled preprocessing and reproducible benchmarks.
End-to-End Multimodal Data Augmentation and Adversarial Robustness Benchmark with AugLy for Images, Text, Audio, and PyTorch
A tutorial shows AugLy augmentations and small robustness tests for image, text, and audio in PyTorch.
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OpenArch – PyTorch implementations of modern LLM architectures
OpenArch provides PyTorch reference implementations of modern LLM architectures for developers and researchers.
Robust Policy Optimization via Adversarial Importance Sampling
Adversarial Importance Sampling estimates worst-case RL returns without extra interactions; authors also release the advrl PyTorch library.