mirror of
https://github.com/huggingface/candle.git
synced 2025-06-17 02:58:50 +00:00
6475bfadfe
* Simplify Tensor::randn. * Also switch Tensor::rand to use a generic dtype. * Support sampling for f16. * Cleanup.
83 lines
2.3 KiB
Rust
83 lines
2.3 KiB
Rust
//! ML framework for Rust
|
|
//!
|
|
//! ```rust
|
|
//! use candle::{Tensor, DType, Device};
|
|
//! # use candle::Error;
|
|
//! # fn main() -> Result<(), Error>{
|
|
//!
|
|
//! let a = Tensor::arange(0f32, 6f32, &Device::Cpu)?.reshape((2, 3))?;
|
|
//! let b = Tensor::arange(0f32, 12f32, &Device::Cpu)?.reshape((3, 4))?;
|
|
//!
|
|
//! let c = a.matmul(&b)?;
|
|
//! # Ok(())}
|
|
//! ```
|
|
//!
|
|
//! ## Features
|
|
//!
|
|
//! - Simple syntax (looks and like PyTorch)
|
|
//! - CPU and Cuda backends (and M1 support)
|
|
//! - Enable serverless (CPU) small and fast deployments
|
|
//! - Model training
|
|
//! - Distributed computing (NCCL).
|
|
//! - Models out of the box (Llama, Whisper, Falcon, ...)
|
|
//!
|
|
//! ## FAQ
|
|
//!
|
|
//! - Why Candle?
|
|
//!
|
|
//! Candle stems from the need to reduce binary size in order to *enable serverless*
|
|
//! possible by making the whole engine smaller than PyTorch very large library volume
|
|
//!
|
|
//! And simply *removing Python* from production workloads.
|
|
//! Python can really add overhead in more complex workflows and the [GIL](https://www.backblaze.com/blog/the-python-gil-past-present-and-future/) is a notorious source of headaches.
|
|
//!
|
|
//! Rust is cool, and a lot of the HF ecosystem already has Rust crates [safetensors](https://github.com/huggingface/safetensors) and [tokenizers](https://github.com/huggingface/tokenizers)
|
|
|
|
pub mod backend;
|
|
mod backprop;
|
|
mod conv;
|
|
mod convert;
|
|
pub mod cpu_backend;
|
|
#[cfg(feature = "cuda")]
|
|
pub mod cuda_backend;
|
|
mod device;
|
|
pub mod display;
|
|
mod dtype;
|
|
mod dummy_cuda_backend;
|
|
mod error;
|
|
mod indexer;
|
|
pub mod layout;
|
|
#[cfg(feature = "mkl")]
|
|
mod mkl;
|
|
pub mod npy;
|
|
mod op;
|
|
pub mod safetensors;
|
|
pub mod shape;
|
|
mod storage;
|
|
mod strided_index;
|
|
mod tensor;
|
|
pub mod utils;
|
|
mod variable;
|
|
|
|
pub use cpu_backend::CpuStorage;
|
|
pub use device::{Device, DeviceLocation};
|
|
pub use dtype::{DType, FloatDType, IntDType, WithDType};
|
|
pub use error::{Error, Result};
|
|
pub use indexer::IndexOp;
|
|
pub use layout::Layout;
|
|
pub use op::{CustomOp1, CustomOp2, CustomOp3};
|
|
pub use shape::{Shape, D};
|
|
pub use storage::Storage;
|
|
pub use strided_index::{StridedBlocks, StridedIndex};
|
|
pub use tensor::{Tensor, TensorId};
|
|
pub use variable::Var;
|
|
|
|
#[cfg(feature = "cuda")]
|
|
pub use cuda_backend::{CudaDevice, CudaStorage};
|
|
|
|
#[cfg(not(feature = "cuda"))]
|
|
pub use dummy_cuda_backend::{CudaDevice, CudaStorage};
|
|
|
|
#[cfg(feature = "mkl")]
|
|
extern crate intel_mkl_src;
|