MXNet - Scala API

See the MXNet Scala API Documentation.

MXNet supports the Scala programming language. The MXNet Scala package brings flexible and efficient GPU computing and state-of-art deep learning to Scala. It enables you to write seamless tensor/matrix computation with multiple GPUs in Scala. It also lets you construct and customize the state-of-art deep learning models in Scala, and apply them to tasks, such as image classification and data science challenges.

You can perform tensor or matrix computation in pure Scala:

   scala> import ml.dmlc.mxnet._
   import ml.dmlc.mxnet._

   scala> val arr = NDArray.ones(2, 3)
   arr: ml.dmlc.mxnet.NDArray = ml.dmlc.mxnet.NDArray@f5e74790

   scala> arr.shape
   res0: ml.dmlc.mxnet.Shape = (2,3)

   scala> (arr * 2).toArray
   res2: Array[Float] = Array(2.0, 2.0, 2.0, 2.0, 2.0, 2.0)

   scala> (arr * 2).shape
   res3: ml.dmlc.mxnet.Shape = (2,3)

Scala API Reference

  • Model API is an alternate simple high-level interface for training neural networks.
  • Symbolic API performs operations on NDArrays to assemble neural networks from layers.
  • IO Data Loading API performs parsing and data loading.
  • NDArray API performs vector/matrix/tensor operations.
  • KVStore API performs multi-GPU and multi-host distributed training.