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¶
- Module API is a flexible high-level interface for training neural networks.
- 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.