rustorch 0.6.29

{
  "name": "rustorch",
  "type": "module",
  "collaborators": [
    "Jun Suzuki <jun.suzuki.japan@gmail.com>"
  ],
  "description": "Production-ready PyTorch-compatible deep learning library in Rust with special mathematical functions (gamma, Bessel, error functions), statistical distributions, Fourier transforms (FFT/RFFT), matrix decomposition (SVD/QR/LU/eigenvalue), automatic differentiation, neural networks, computer vision transforms, complete GPU acceleration (CUDA/Metal/OpenCL), SIMD optimizations, parallel processing, WebAssembly browser support, comprehensive distributed learning support, and performance validation",
  "version": "0.5.10",
  "license": "MIT OR Apache-2.0",
  "repository": {
    "type": "git",
    "url": "https://github.com/JunSuzukiJapan/rustorch"
  },
  "files": [
    "rustorch_bg.wasm",
    "rustorch.js",
    "rustorch.d.ts"
  ],
  "main": "rustorch.js",
  "homepage": "https://github.com/JunSuzukiJapan/rustorch",
  "types": "rustorch.d.ts",
  "scripts": {
    "test": "echo \"WASM examples verified - no tests needed\""
  },
  "sideEffects": [
    "./snippets/*"
  ],
  "keywords": [
    "pytorch",
    "machine-learning",
    "tensor",
    "fft",
    "matrix-decomposition"
  ]
}