axonml-tensor

N-dimensional tensor operations for the Axonml ML framework.

Overview

axonml-tensor provides efficient tensor operations including:

• N-dimensional Arrays - Arbitrary shapes and strides
• Broadcasting - NumPy-compatible broadcasting rules
• Arithmetic - Add, subtract, multiply, divide, matmul
• Reductions - Sum, mean, max, min along dimensions
• Activations - ReLU, Sigmoid, Tanh, Softmax, GELU

Usage

use axonml_tensor::{Tensor, zeros, ones, randn};

// Create tensors
let a = zeros::<f32>(&[2, 3]);
let b = ones::<f32>(&[2, 3]);
let c = randn::<f32>(&[2, 3]);

// Operations
let d = a.add(&b).unwrap();
let e = c.matmul(&b.t()).unwrap();
let f = e.relu();

Part of Axonml

This crate is part of the Axonml ML framework.

License

MIT OR Apache-2.0