Table Of Contents
Table Of Contents

Validate Your MXNet Installation

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 MKL

Instructions for validating MKL or MKLDNN can be found in the MKLDNN_README.

Python with GPU

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

>>> 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)

Verify GPU Training

Clone the MXNet repository to download all of the MXNet examples.

git clone --recursive https://github.com/apache/incubator-mxnet.git mxnet

From the mxnet directory run the following:

python example/image-classification/train_mnist.py --network lenet --gpus 0