rustorch 0.6.26

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
# Docker Compose for RusTorch Development and Production

version: '3.8'

services:
  # Main RusTorch service
  rustorch:
    build:
      context: .
      dockerfile: Dockerfile
    container_name: rustorch-main
    volumes:
      - ./data:/app/data
      - ./models:/app/models  
      - ./output:/app/output
      - ./examples:/app/examples
    environment:
      - RUST_LOG=info
      - RUSTORCH_ENV=production
    networks:
      - rustorch-network
    restart: unless-stopped

  # Development environment
  rustorch-dev:
    build:
      context: .
      dockerfile: Dockerfile.dev
    container_name: rustorch-dev
    volumes:
      - .:/workspace
      - cargo-registry:/usr/local/cargo/registry
    environment:
      - RUST_LOG=debug
      - RUSTORCH_ENV=development
    networks:
      - rustorch-network
    ports:
      - "8080:8080"  # For web demos
    working_dir: /workspace
    command: bash
    profiles:
      - dev

  # GPU-enabled service (for CUDA support)
  rustorch-gpu:
    build:
      context: .
      dockerfile: Dockerfile.gpu
    container_name: rustorch-gpu
    volumes:
      - ./data:/app/data
      - ./models:/app/models
      - ./output:/app/output
    environment:
      - RUST_LOG=info
      - CUDA_VISIBLE_DEVICES=0
    runtime: nvidia
    networks:
      - rustorch-network
    profiles:
      - gpu

  # Jupyter notebook service for Python integration
  rustorch-notebook:
    build:
      context: ./python
      dockerfile: Dockerfile.jupyter
    container_name: rustorch-notebook
    ports:
      - "8888:8888"
    volumes:
      - ./python:/workspace
      - ./data:/workspace/data
      - ./models:/workspace/models
    environment:
      - JUPYTER_ENABLE_LAB=yes
    networks:
      - rustorch-network
    profiles:
      - python

volumes:
  cargo-registry:
    driver: local

networks:
  rustorch-network:
    driver: bridge