Transform a data stream of type A to type B. It is usually used in data pre-process stage.
Different transformers can compose a pipeline. For example, if there're transformer1 from A to
B, transformer2 from B to C, and transformer3 from C to D, you can compose them into a bigger
transformer from A to D by transformer1 -> transformer2 -> transformer 3.
The purpose of transformer is for code reuse. Many deep learning share many common data
pre-process steps. User needn't write them every time, but can reuse others work.
Transformer can be used with RDD(rdd.mapPartition), iterator and DataSet.
Transform a data stream of type A to type B. It is usually used in data pre-process stage. Different transformers can compose a pipeline. For example, if there're transformer1 from A to B, transformer2 from B to C, and transformer3 from C to D, you can compose them into a bigger transformer from A to D by transformer1 -> transformer2 -> transformer 3.
The purpose of transformer is for code reuse. Many deep learning share many common data pre-process steps. User needn't write them every time, but can reuse others work.
Transformer can be used with RDD(rdd.mapPartition), iterator and DataSet.