safemlx

safemlx provides safe, low-level Rust bindings to MLX: arrays and native operations, devices and streams, lazy graph evaluation, function transforms, native serialization, and accelerator/runtime facilities. It deliberately contains no neural-network layers, models, optimizers, checkpoint policy, or other framework abstractions. Eredu's MLX-specific abstractions live in eredu-backend-mlx.

Most applications should use eredu. Depend on this crate directly only when building MLX-specific operations or backend components.

Features

• accelerate: Accelerate-backed operations on Apple platforms.
• metal: Metal execution on Apple platforms.
• cuda: CUDA execution on x86-64 Linux or Windows.
• nccl: CUDA plus MLX's optional Linux NCCL backend.
• safetensors: conversion between Array and safetensors::TensorView.

The default feature set enables Accelerate and Metal where those backends are available.

Operations are lazy and run on an explicit stream:

use safemlx::{array, Device, DeviceType, Stream};

let stream = Stream::new_with_device(&Device::new(DeviceType::Cpu, 0));
let values = array!([1.0, 2.0, 3.0]);
let squares = values.square(&stream)?.into_evaluated()?;

assert_eq!(squares.as_slice::<f32>(), &[1.0, 4.0, 9.0]);
# Ok::<(), safemlx::error::Exception>(())

Rustdoc contains the API guide and examples for arrays, indexing, lazy evaluation, graph transforms, and I/O.

Notable APIs

• Completion events submit selected lazy graphs and support host observation or same-device stream ordering without a whole-stream drain.
• Typed host-transfer buffers provide explicit CPU, Metal shared, CUDA pinned, or CUDA managed storage policies.
• The distributed module wraps MLX groups, collectives, point-to-point operations, and their native execution semantics.

See the safemlx implementation guides for completion events, asynchronous device timing, and host-transfer buffers.

Platforms

Eredu's MLX implementation supports Apple silicon on macOS and selected Apple device targets, x86-64 Linux with CPU or CUDA, and native x86-64 Windows with CPU or CUDA. Backend prerequisites and application-bundling requirements are documented in the MLX backend's platform setup guide.

The minimum supported Rust version is 1.89.

License

Licensed under either MIT or Apache-2.0.