mxnet

Version:

1.8.0

Category:

ai

Cluster:

Loki

Author / Distributor

https://mxnet.apache.org/

Description

Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scalable to many GPUs and machines.

Documentation

$ python -c "import mxnet; print(mxnet.__version__)"

Common modules:
  mxnet.ndarray      - Tensor operations (imperative)
  mxnet.symbol       - Symbolic graph programming
  mxnet.gluon        - High-level neural network API
  mxnet.autograd     - Automatic differentiation

To check GPU support:
  >>> import mxnet as mx
  >>> mx.context.num_gpus()

Full documentation: https://mxnet.apache.org/versions/1.8.0/

Examples/Usage

• Load the MXNet module:

  $ module load ai/mxnet-py37-cuda10.2-gcc8/1.8.0
  

• Unload the module:

  $ module unload ai/mxnet-py37-cuda10.2-gcc8/1.8.0
  

• Example usage in Python:

  import mxnet as mx
  from mxnet import nd
  
  x = nd.array([1, 2, 3])
  print((x * 2).asnumpy())
  

• Train a neural network with Gluon:

  from mxnet.gluon import nn
  net = nn.Sequential()
  net.add(nn.Dense(64, activation='relu'))
  net.add(nn.Dense(10))
  net.initialize()
  print(net)
  

Installation

Source code and binaries are obtained from Apache MXNet