Python

Start the python terminal.

\$ python

Run a short MXNet python program to create a 2X3 matrix of ones, multiply each element in the matrix by 2 followed by adding 1. We expect the output to be a 2X3 matrix with all elements being 3.

>>> import mxnet as mx
>>> a = mx.nd.ones((2, 3))
>>> b = a * 2 + 1
>>> b.asnumpy()
array([[ 3.,  3.,  3.],
[ 3.,  3.,  3.]], dtype=float32)

Python with GPU

This is similar to the previous example, but this time we use mx.gpu(), to set MXNet context to be GPUs.

>>> import mxnet as mx
>>> a = mx.nd.ones((2, 3), mx.gpu())
>>> b = a * 2 + 1
>>> b.asnumpy()
array([[ 3.,  3.,  3.],
[ 3.,  3.,  3.]], dtype=float32)

Alternative Language Bindings

Perl

Start the pdl2 terminal.

\$ pdl2

Run a short MXNet Perl program to create a 2X3 matrix of ones, multiply each element in the matrix by 2 followed by adding 1. We expect the output to be a 2X3 matrix with all elements being 3.

pdl> use AI::MXNet qw(mx)
pdl> \$a = mx->nd->ones([2, 3])
pdl> \$b = \$a * 2 + 1
pdl> print \$b->aspdl

[
[3 3 3]
[3 3 3]
]

R

Run a short MXNet R program to create a 2X3 matrix of ones, multiply each element in the matrix by 2 followed by adding 1. We expect the output to be a 2X3 matrix with all elements being 3.

library(mxnet)
a <- mx.nd.ones(c(2,3), ctx = mx.cpu())
b <- a * 2 + 1
b

You should see the following output:

[,1] [,2] [,3]
[1,]    3    3    3
[2,]    3    3    3

R with GPU

This is similar to the previous example, but this time we use mx.gpu(), to set MXNet context to be GPUs.

library(mxnet)
a <- mx.nd.ones(c(2,3), ctx = mx.gpu())
b <- a * 2 + 1
b

You should see the following output:

[,1] [,2] [,3]
[1,]    3    3    3
[2,]    3    3    3

Scala

Run the MXNet-Scala demo project to validate your Maven package installation.