API Reference

This section provides detailed documentation for all public APIs in Tensor Frame.

Core Types

• Tensor - The main tensor type with all operations
• Backends - Backend trait and implementation details
• Operations - Detailed operation specifications

Key Traits and Enums

TensorOps Trait

The TensorOps trait defines all tensor manipulation and computation operations:

pub trait TensorOps {
    fn reshape(&self, new_shape: Vec<usize>) -> Result<Tensor>;
    fn transpose(&self) -> Result<Tensor>;
    fn squeeze(&self, dim: Option<usize>) -> Result<Tensor>;
    fn unsqueeze(&self, dim: usize) -> Result<Tensor>;
    // ... more methods
}

DType Enum

Supported data types:

pub enum DType {
    F32,    // 32-bit floating point (default)
    F64,    // 64-bit floating point  
    I32,    // 32-bit signed integer
    U32,    // 32-bit unsigned integer
}

BackendType Enum

Available computational backends:

pub enum BackendType {
    Cpu,    // CPU backend with Rayon
    Wgpu,   // Cross-platform GPU backend
    Cuda,   // NVIDIA CUDA backend
}

Error Handling

All operations return Result<T> with TensorError for comprehensive error handling:

pub enum TensorError {
    ShapeMismatch { expected: Vec<usize>, got: Vec<usize> },
    BackendError(String),
    InvalidOperation(String),
    DimensionError(String),
}

Memory Management

Tensor Frame uses smart pointers and reference counting for efficient memory management:

• Tensors are cheaply clonable (reference counted)
• Backend storage is automatically managed
• Cross-backend tensor conversion is supported
• Zero-copy operations where possible