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Purpose

NuMojo is a library for numerical computing in Mojo similar to numpy in Python

NuMojo extends (most of) the standard library math functions to work on tensor inputs

NuMojo intends to capture a wide swath of numerics capability present in the Python packages numpy,scipy and scikit such as

• Linear/Tensor Algebra
• Integration
• Derivatives
• Optimizers
• Function approximators

NuMojo intends to try and get the most out of the capabilities of Mojo including vectorization, parallelization, and GPU acceleration(once available).

NuMojo intends to be a building block for other Mojo packages that need fast math under the hood without the added weight of a ML back and forward propagation system

What NuMojo is not

NuMojo is not a machine learning library, it will never include back-propagation in the base library.

How to install

Clone the repository and build

Usage

For now

import numojo
from Tensor import Tensor
def main():
    var tens = Tensor[DType.float32](10,10)
    tens=tens+numojo.pi/2
    print(numojo.sin[DType.float32](tens))

Available functions include:

abs, floor, ceil, trunc, round, roundeven, round_half_down, round_half_up, rsqrt, exp2, exp, log, log2, tanh, reciprocal, acos, asin, atan, cos, sin, tan, acosh, asinh, atanh, cosh, sinh, expm1, log10, log1p, cbrt, pow, mod, mul, sub, add, div, copysign, atan2, hypot, nextafter, scalb, remainder

Warnings

This library is still very much a work in progress and may change at any time. Also, the standard tensor has many rough edges.