31 posts
sklears 0.2.0 ships sklears-core::gpu, a real oxicuda-backed CUDA foundation (GpuBackend, GpuArray, GpuMatrixOps) powering on-device GEMM, Cholesky/LU/QR/SVD solves, and HNSW k-NN across 9 downstream crates, plus a wide correctness sweep. 12,721 tests passing, 36 crates, >99% scikit-learn API coverage held.
TenfloweRS 0.2.0 rewires the Python-facing, PyTorch-style implicit autograd system for real: every layer type gets tape-backed .backward()/.grad(), all 9 optimizers perform genuine gradient updates, and a correctness sweep fixes wrong Softmax/BatchNorm/GroupNorm/LayerNorm gradients — 14,536+ tests passing.
TrustformeRS 0.2.0 gives CUDA the same device-resident attention pipeline Metal already had, adds batched CUDA matmul and refcounted GPU buffers, fixes a silent CUDA data race, and drops the torch/libtorch backend workspace-wide. The sovereign transformer layer for the COOLJAPAN ecosystem.
TenfloweRS 0.1.2 adds PyTorch-style implicit autograd for Python, real ONNX protobuf import/export, a pure-Rust Blosc codec for Zarr, and a wide honesty-hardening sweep that replaces fabricated results with real computation or honest errors across the framework.
TrustformeRS 0.1.4 migrates CUDA and Metal from cudarc/scirs2-MPS to the Pure-Rust oxicuda stack, passes 12/12 CPU↔CUDA parity tests on a real RTX A4000, ships real PyRwkvModel/PyMambaModel classes on PyO3 0.28, and goes unwrap()-free workspace-wide. The sovereign transformer layer for the COOLJAPAN ecosystem.
sklears 0.1.2 brings 12 real preprocessing implementations (no more stubs), SciRS2 0.5.1 upgrade, AVX2 quicksort in sklears-simd, advanced categorical imputers, and a full benchmarking regression-detection subsystem — 12,242 tests across 36 crates, >99% scikit-learn API coverage held.
TrustformeRS 0.1.3 patch — real SHAP/LIME/Integrated-Gradients interpretability, ZeroCopyTensorView + GlobalMemoryPool + GlobalProfiler, Miri-verified memory-pool fixes, real SHA-256 on the HuggingFace upload path, and real OOXML .xlsx export via oxiarc-archive.
The high-performance Pure Rust DataFrame library reaches 0.4.0 — a correctness landmark. PandRS replaces a large swath of fabricated and stubbed ML and statistical results with real algorithms: Jacobi-rotation PCA, t-SNE, DBSCAN, agglomerative clustering, IRLS logistic regression, isolation-forest/LOF/OneClassSVM anomaly detection, real silhouette and ROC-AUC, and genuine chi-square/t/F p-values. SciRS2-Core becomes a non-optional core dependency, and the SciRS2 stats/linalg integration deepens onto the 0.5 line. The DataFrame layer of the COOLJAPAN scientific stack — no pandas, no scikit-learn C-extensions, no GIL.
Pure-Rust replacement for the NVIDIA CUDA Toolkit. OxiCUDA 0.1.6 adds a Tensor Core fast path for SYRK in oxicuda-blas and sixteen new ML crates (adversarial, SSL, continual, multimodal, 3D geometry, PINN, ANN, anomaly, causal, meta, MoE, NeRF, quantum, recsys, RLHF, tabular). No CUDA SDK, no nvcc.
Pure Rust autonomous semantic federation engine: learned source selection for SPARQL federated queries — context-aware, ML/RL-driven, edge & WASM-ready. 501 tests, 23k LoC, no_std-capable. No JVM. No C. No server farm.
sklears 0.1.1 is a correctness patch for pure-Rust scikit-learn: HDBSCAN cluster-persistence fix, streaming scaler/imputer Default cleanups, a pipeline lifetime fix, and serialization fixes — 11,586+ tests across 36 crates, >99% scikit-learn API coverage held.
TrustformeRS 0.1.1 patch — 22 new transformer architectures (49+ total: Falcon2, Gemma2, Mamba2, Qwen2.5, Phi4, Whisper, StarCoder2, xLSTM, and more). ONNX Runtime replaced by Pure Rust oxionnx, tar replaced by oxiarc-archive, Kafka feature-gated. Load any architecture through one AutoModel call — no Python, no PyTorch, no C++ ONNX runtime.
TenfloweRS 0.1.1 is an ergonomics + compatibility patch for the pure-Rust TensorFlow alternative: a declarative tensor! macro, an expanded prelude (transformers and RNNs), ndarray interop, ONNX re-exports, wgpu v29 compatibility across 57 sites, and richer typed Python FFI errors.
Pure-Rust FFmpeg+OpenCV replacement: OxiMedia 0.1.5 adds the oximedia-ml crate — typed ML pipelines (SceneClassifier, ShotBoundaryDetector, and more) on the Pure-Rust OxiONNX runtime, with a Python oximedia.ml submodule and an opt-in, symbol-free-by-default design. Plus a codec-decoder honesty pass. 108 crates, ~2.68M SLoC, 81,383 tests.
SciRS2 0.4.2 — pure-Rust SciPy/NumPy/scikit-learn replacement, 2.94M SLoC, 27,632 tests, 29 crates. This release adds Neural Architecture Search, CMA-ES, Mamba SSM, async/unified GPU memory, H-matrix compression, streaming FFT, DLPack zero-copy, and Apache Iceberg/DataFusion IO. No C/Fortran.
SciRS2 0.4.1 is a pure-Rust SciPy/NumPy/scikit-learn replacement: 2.91M SLoC, 25,863 tests, 32 crates. This release improves JIT compilation in scirs2-core, ships a 76-test WebGPU/WASM backend for browser GPU compute, and validates 15+ distributions to numerical accuracy. No C. No Fortran.
OptiRS is the Pure Rust ML optimizer suite — 22 optimizers across 7 crates — built on SciRS2. 0.3.1 is a maintenance patch: version sync across every crate's doc comments, a new optirs-wasm README, and fixed stale version strings. Honest housekeeping on top of 0.3.0.
High-performance ONNX runtime written entirely in pure Rust. Zero C/C++ dependencies, 147 operators fully supported, wgpu GPU acceleration, SIMD (AVX2/NEON), WASM + no_std ready, graph optimizer, async execution, model encryption. 30k+ SLoC, 590+ tests. The sovereign ONNX inference layer for SciRS2 and the entire COOLJAPAN ecosystem (now 21M+ SLoC total).
SciPy-compatible scientific computing and AI framework in 100% Pure Rust. 2.91M SLoC, 29 crates, 25,800+ tests. Flash Attention 2, LoRA/DoRA/GPTQ, ONNX export, GPU PDE/FFT/SpMV, Temporal GNNs, NeRF/instant-NGP, WebGPU backend, Delta Lake / Kafka I/O and more. 10–100× faster, zero system deps. The sovereign scientific computing and AI foundation for the entire COOLJAPAN ecosystem (now 21M+ SLoC total).
Pure Rust Hugging Face Transformers — the first stable release. 27+ transformer architectures, 17x CPU BLAS acceleration, GGUF/AWQ/GPTQ quantization, and WASM + server + mobile deployment. No Python, no PyTorch.
The first stable release of sklears: a pure-Rust scikit-learn alternative spanning 36 crates with >99% API coverage, type-safe Untrained→Trained state machines, and a SciRS2 foundation. No Python runtime, no GIL, no C or Fortran.
TenfloweRS is a pure-Rust alternative to TensorFlow, and this is its first stable release. It ships dual eager + graph execution, reverse-mode autodiff, 150+ research domains, and WGPU GPU acceleration — built on the SciRS2 and NumRS2 ecosystem, with no C++, CUDA-C, or Python runtime.
ToRSh is a PyTorch-compatible deep-learning framework in pure Rust with native tensor sharding. The 0.1.1 release hardens the 33-crate workspace onto consistent, published crates.io dependencies and adds the new torsh-convert model-converter CLI.
Production-grade machine learning optimization library with 22 optimizers (SGD→K-FAC), SIMD 2–4×, parallel 4–8×, GPU 10–50× acceleration. 251K+ SLoC, 7 crates, 1,220+ tests. Full extension of SciRS2-Core — no external deps allowed. The sovereign optimizer layer for SciRS2 and the entire COOLJAPAN ecosystem (now 21M SLoC total).
2.59 million lines of pure Rust. SciPy-compatible APIs, 10-100× faster with SIMD, no C/Fortran deps, 29 crates, 19,700+ tests, Python + WASM + no_std. The sovereign scientific computing and AI foundation for the entire COOLJAPAN ecosystem.
SciRS2 is a pure-Rust SciPy/NumPy/scikit-learn replacement, and 0.3.0 is the biggest release yet — transformers, GNNs, diffusion, MoE/RLHF, Gaussian processes, MCMC, survival analysis, radar/compressed sensing, LOBPCG/AMG, plus new Julia and Python bindings. 19,644 tests, ~2.59M lines of Rust. No C, no Fortran.
OptiRS is the Pure Rust ML optimizer suite (19 optimizers) built exclusively on SciRS2-Core. The 0.2.0 release relicenses to Apache-2.0 only and upgrades to SciRS2 v0.2.0 across every crate — fully backward compatible, with no API changes and no breaking changes. A one-line dependency bump.
SciRS2 is the pure-Rust SciPy/NumPy replacement. 0.2.0 restores the entire workspace to zero compile errors, makes Pure Rust OxiFFT the default FFT backend (rustfft now optional), rebuilds the neural stack, and ships the first WebAssembly bindings. ~11,400 tests, zero warnings. No C. No Fortran.
Pure-Rust SciPy/NumPy replacement. This release: SIMD phase 60-69 (8 new AVX2/NEON modules), modular Bowyer-Watson Delaunay (2D/3D/ND + constrained), OxiFFT now the 100% Pure Rust FFT default, and autograd optimizer fixes. 11,400+ tests, 27 crates. No C, no Fortran.
OptiRS is the Pure Rust ML optimization layer for the COOLJAPAN stack — the torch.optim / optax replacement built exclusively on SciRS2-Core. The 0.1.0 first stable release ships 19 optimizers, SIMD acceleration (2-4x), parallel parameter groups (4-8x), 1,134 passing tests, and zero clippy warnings.
SciRS2 0.1.0, the first stable release — a 100% Pure Rust scientific computing & AI/ML stack with SciPy-compatible APIs, built on OxiBLAS, refactored into clean modules with zero warnings and 10,861 passing tests. No C, no Fortran.