rustorch 0.6.29

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
Documentation
# Rust build artifacts
/target/

# Cargo lock file (uncomment if building a library)
# Cargo.lock

# IDE files
.vscode/
.idea/
*.swp
*.swo
*~

# mcp
.mcp.json

#
.serena/
pr-audit-report.json

# Jupyter
.venv/
.venv-hybrid/

# OS generated files
.DS_Store
.DS_Store?
._*
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db

# Logs
*.log
rustorch_debug.log

# Temporary files
*.tmp
*.temp
.ci-sync

# Rust-specific
**/*.rs.bk
*.orig

# Generated visualization files (examples output - but keep WASM files!)
*.svg
*.dot

# Claude Code settings
.claude/settings.local.json

# Compiled benchmark binaries
matrix_bench
simple_bench
test_linalg

# Python cache
__pycache__/
*.pyc
*.pyo

# Node modules (if any)
node_modules/

# Keep specific files we need
!examples/test.js
!examples/wasm_*.js
!examples/wasm_*.html
!examples/*.json
!examples/*.wasm
!examples/*.d.tsruns/
dashboard.html
profile_trace.json